UNIVERSIDAD COMPLUTENSE DE MADRID 
FACULTAD DE PSICOLOGÍA 

 
 

 
 
 

TESIS DOCTORAL 
 

Correlatos neuronales de las emociones sociales de culpa, 
vergüenza y orgullo 

 
 

MEMORIA PARA OPTAR AL GRADO DE DOCTOR 
 

PRESENTADA POR 
 

José Sánchez García 
 
 

Director 
 

Manuel Martín-Loeches Garrido 
 
 

Madrid 
 
 

© José Sánchez García, 2021 



UNIVERSIDAD COMPLUTENSE DE MADRID 
FACULTAD DE PSICOLOGÍA 

 

 

 

 

 

 

 

TESIS DOCTORAL 
 

 Correlatos neuronales de las emociones sociales de culpa, vergüenza y orgullo 

 

MEMORIA PARA OPTAR AL GRADO DE DOCTOR 

PRESENTADA POR 

 

Jose Sánchez García 

 

DIRECTOR 
 

Manuel Martín-Loeches Garrido 



	 II	

 

 

 

 

A mis padres, de donde venimos. 

A mi mujer, quienes somos. 

A mi hijo, a donde vamos. 

A Arutam, fuerza de vida que nos traspasa, tan inefable y esquiva para los necios. 

 

  



	 III	

 

AGRADECIMIENTOS 

 

Aunque en la cultura en la que habito, el éxito es una extraña entidad asociada a la 

actitud, las agallas y la voluntad de un Yo individual (o acaso a las oportunidades de un 

Yo con amigos), en el mundo que vivo dentro nada se hace solo, sino que la mayoría de 

las cosas suceden por sí mismas, lo cual relaja incluso en medio de la guerra y el resto, 

se hacen apoyándose unos a otros. No hay mucho más espacio para Narciso. 

En el caso de este texto, la emoción que surge es aún más extraña, porque resulta 

sospechoso reclamar autoría alguna sobre aquello que jamás hubiera surgido por talento 

especial o actitud encomiable, ambas tan individuales y cuestionables a mi entender.  

Es por tanto más importante en este viaje del héroe que parece una tesis doctoral, 

agradecer, sincerarse o enraizarse que elevarse o sentirse autor, por mucho que uno 

tenga que poner el nombre y defender estos estudios, más bien en representación de 

todos que no solo de sí mismo. Al fin y al cabo el viaje del héroe, suele ser el de alguien 

un poco bobo, que como Skywalker, tarda 6 películas en conocer a su padre.  

En los agradecimientos sucede algo parecido a lo anterior con los esfuerzos. Se 

pueden agradecer los niveles técnicos o centrarse en los más importantes: los humanos. 

Para éste, que está de vuelta de muchos viajes en torno a un centro ciertamente esquivo, 

solo me interesa a estas alturas comprobar cuán bueno es alguien y no tanto sus dotes de 

memoria aplicada a un software o tarea. Importa más si posee esa inteligencia social que 

nos trasciende y que brilla en capacidades para respetar o apoyar al otro, en sinceras 

ausencias de juicio sobre aquel a quien se dirige, en posibilidades de ponerte en la piel 

del de enfrente o en esa rara habilidad que pocos profesan de confiar tanto, tanto en el 

otro, que a ojos de Zeus, convierte a Galatea en mujer, ante la pasión de Pigmalión. 



	 IV	

Valoro esa humanidad mucho más que hacer de Sísifo cargando estúpidamente una y 

otra vez la piedra del esfuerzo montaña arriba para demostrar perfeccionismo y 

voluntad o quien sabe si destino, mientras me temo, creaba hernias discales. O peor aún, 

hacer de Milarepa subiendo las piedras desde la base para hacer una casa en la cima, 

que Marpa se encarga de destruir, para que el posterior tibetano más grande de su 

historia limpie karma y acumule mérito.  

Comienzo desde este lugar por tanto, agradeciendo a Manolo, mi director, por 

muchas características y detalles. Muchas de ellas probablemente escaparán a sus ojos y 

entendimiento. Sospecho, como ingeniero camuflado, que no soy aquel que esperaba, 

pero espero no haberle defraudado del todo, siendo quien soy o acaso en quien me estoy 

convirtiendo. El caso es que cuando uno espera, como dice la tradición, una fricción 

constante entre director y doctorando, junto con la clásica y advertida depresión a mitad 

de tesis y una relación típica con un catedrático petulante con corbata, se encuentra con 

Manolo, el cual escapa a toda clasificación vulgar, incluso al mismísimo Big Five. La 

realidad es que no recuerdo fricción alguna en estos años, acaso las mías propias con 

mis desatinos. La depresión no apareció a la mitad, sino en todo el recorrido, porque no 

hay cosa más inapropiada que hacer una tesis a estas alturas y circunstancias, si bien me 

motiva como decían de Drake en 100 años de soledad, vínculos más poderosos que el 

amor, o sea, el remordimiento. Los supuestos estereotipos de catedrático alfa fueron 

más bien paciencia, perspectiva, estilo directivo y foco: afortunado soy por tanto. Sobre 

todo ello Manolo destaca con otra virtud: su sentido del humor, incluyendo una parte 

para “meterse conmigo” y es que nadie se libra de su creatividad… pero que ha sido una 

gran enseñanza e incluso aunque él no lo sepa, motivo de práctica introspectiva. Gracias 

a Manolo, veo que la ciencia es algo más modesto de lo que había conocido e 

imaginado antes y eso no se enseña, sino que lo vive y te cala. Se realizan hipótesis 



	 V	

pequeñas, con diseños simples y conclusiones modestas en donde la estridencia se 

encuentra siempre ausente. Este camino que él marca tiene ese toque japonés que tanto 

venero: el placer de lo pequeño, Wabi Sabi, o el silencio, que siempre es más armónico 

que hablar siendo pensado por uno mismo en atención ausente. Hay otro regalo 

inesperado: como profuso lector que es, él me ha acercado a autores que por mí mismo 

hubiera tardado mucho en llegar a ellos o quién sabe si nunca. Cuanto valor tiene esto 

último. Al colarme en su biblioteca y su entendimiento, abrí huecos insospechados en 

mi cerebro. Por último, para quienes agradecemos la N400 de la verdad flagrante más 

que la comodidad del autoengaño, para los que nos resultan insoportables los rodeos, las 

esquivas extrañas, o el sexto nivel del “mentalizing” de “si me dice B porque le digo A, 

le contesto C”, el ir al grano de Manolo, es un Kyosaku en toda regla. No solo se 

agradece sino que como en el buen Dojo, el Kyosaku se pide y si no, Manolo 

igualmente te lo da. La vida tiene sus más y sus menos, pero lo cierto, es que al final 

acabo siempre a lomos de gigantes. En esta tesis con el director, sin duda también.  

Con Pili la cosa no empezó bien. El primer día, me senté en su silla y ocupé su 

mesa, con la lógica inocente de que estaba vacía y así me dispuse a arrancar con buen 

pie la tesis doctoral. A los 15 minutos llegó, menos mal que no tenía los pies encima y 

amablemente me ofreció sentarme enfrente. Claro que antes le expliqué infantilmente: 

“soy Jose, soy nuevo y vi una mesa vacía”. Pili ha sido siempre un punto de inflexión 

para mí, ella es como esa derivada igual a cero que te dice: ahora te toca subir. Como se 

puede deducir, al ser varias las ocasiones, la tesis es por tanto un viaje sinusoidal. Con 

Pili, he podido ver señal en vez de artefactos y sin ella estaría inmerso en un electrodo 

epiléptico, o como un gallo batiendo alas en un corral para impresionar a las gallinas… 

mientras pasa el halcón volando camino al bosque. Si Manolo ha aportado dirección, 

foco, guía, perspectiva y resolución, Pili me ha llenado de estructura, algo que necesito 



	 VI	

porque soy de los que ven bosque, o incluso selva, en vez de un árbol. Todo menos vivir 

en el corral de gallitos y gallinas: Pili me ha ayudado a no estar ahí. 

Además de su humanidad debo decir, que comprender sus tesis del embodied syntax, es 

una tarea que te hace sentir de nuevo, que no eres nadie, absolutamente nadie. Si la 

meditación sirve para que no te creas que eres un Yo, y que por fin descanses en la vida, 

las tesis de Pili te lo muestran desde otro lugar.  Destaco una paradoja más: es la 

psicóloga sin serlo a la que uno esperaría ir a terapia, por la sencilla razón de que 

cuando uno sufre de verdad, lo único que necesita alguien no es curación, sino no 

sentirse juzgado. Qué más decir de Pili… 

David, o Da-Big si se quiere utilizar un nombre más apropiado, es ese 

compañero que en medio del caos te mete a que le acompañes en un Master de 

Metodología porque así se (mal-) trata a los amigos. Tiene alma de Pascal, cuerpo de 

luz de Laplace y sin embargo permanece libre y anumérico. Cuando te habla entiendes 

porqué la criptografía y el mismo Turing, son ciencias non-natas. Más allá de los dones 

citados, siente la ciencia con mucho rigor. Es metódico, trabaja como un pro y de 

corazón espero que se cumpla un sueño, donde le veía como un Pope de la 

neurolingüística mundial. A lo largo de los años ha estado siempre cerca, disponible y 

valorando mis integrales como hazañas.  Lo más importante con Da-big ha sido que se 

convirtió en alguien en quien puedo confiar. ¿Qué precio tiene eso en esta vida de giros 

y surcos donde el prefrontal dice una cosa y el hipotálamo la contraria? Para mí 

muchísimo, porque lo que no suma, resta, y a cierta edad, no está uno para inocentadas 

y promesas vacuas personales o profesionales. Así que sí, disfruto de sus alegrías y lloro 

con sus penas, faltaría más. Pero con Da-Big me he sentido como Rinzai, aquel maestro 

que a la mañana reía a carcajada limpia al despertar y a la noche hacía lo propio, sin 

motivo aparente, para sorpresa de sus discípulos. Y es que han sido muchísimos los 



	 VII	

momentos donde nos hemos reído por reír, ni siquiera ya de nosotros mismos o las 

situaciones, sino quizá como una forma sabia y oculta de parodiar nuestras miserias, 

presiones y anhelos incumplidos.  

Sabela tiene la virtud de ver a los demás fuertes, bien preparados y ciertamente 

inteligentes. Dado que cualquier camino cuando se empieza te lleva irremediablemente 

a sentirte tonto, y yo me he sentido dispuesto a reconocerlo sin sufrimiento alguno, 

Sabela es una luz. No te adula ni te halaga sino que sientes que su mirada sincera está 

teñida de ver potenciales ocultos, incluso en las cuevas a las que uno mismo ha caído. 

Me recuerda el ejemplo de C.J. Skender, ese afamado profesor de Duke, citado en el 

bellísimo libro de Adam Grant, Give and Take, donde todos los alumnos alcanzan cotas 

indescriptibles por la sencilla razón de que Skender ve siempre talento, motivación y 

potenciales. Cuando Sabela corrige el paper, notas compañía, apoyo y la forma concreta 

en la que puedes hacerlo mejor. En medio de una maraña de erratas en las revisiones, 

técnicas y científicas, sus mensajes son neurociencia social pura. Con la misma 

naturalidad que te acoge, también se abre y comparte intereses, sueños o ideas lo cual de 

nuevo te ayuda a sentirte uno más. Para muchos el Openness suele ser motivo de mofa 

más que de capacidad: estoy acostumbrado. Pero Sabela no se asusta, ni se posiciona 

provinciana, más bien escucha, se interesa y participa. Y es que me temo que la 

curiosidad es una virtud fundamental suya, no solo en la ciencia lo cual es esperable, 

sino en la vida, rara avis, curiosidad que ella derrocha y contagia.  

Laura tiene loco a Alan Baddeley, porque su ancho de banda le permite llevar 

proyectos, artículos, clases y maratones, sí, sí, maratones como si tal cosa. Esto huele a 

que además del bucle fonológico y la agenda visoespacial, existe un módulo de tinte 

Chomskyano, llamado Jiménez-Ortega, encapsulado en ella misma y que desde luego 

explica FoxP2. Me ha resultado inspiradora su capacidad encomiable y me siento 



	 VIII	

agradecido por sus ánimos en este viaje. Sin duda es un ejemplo a lo Di Stefano: roba 

balones, lanza faltas, mete goles y da pases. Laura es así: dirige tesis, publica artículos, 

hace proyectos, da clases y habla con las palomas, o hasta según se mire, de ahí lo del 

FoxP2. Omnipotente no sé, pero multipresente sin duda. Tiene la virtud de los 

mecánicos de antes: chapa, motor o pintura y eso es una garantía en procesos de 

eslabones lineales donde más de uno dará error. ¡Mucho valor tiene todo eso! 

Paco, además de ser cliente asiduo de restaurantes Michelín, es otro fajador del 

laboratorio. Su nivel de entendimiento de bucles, algoritmos, triggers y clusters le hacen 

merecedor de un puesto de honor en Black Mirror Bandersnatch. Sería presuntuoso por 

mi parte intentar comprender todo eso, me conformo con observar y asentir. Sus 

esporádicos paseos hacia el WC cuando pasa por tu pantalla suelen ser apocalípticos: se 

queda mirando, sabe lo que estás haciendo y encima te lo puede explicar.  

Javi me sorprendió por su meticulosidad y paciencia, de ahí que le gustara y 

dominara la programación del lab. Ante él mis propios fallos me generaban menos 

stress de lo habitual, vete a saber porqué. Lo cierto es que en el primer experimento su 

ayuda fue muy importante para coger unas mínimas tablas y parecer que haces algo, 

hasta que Manolo de alguna manera te hacía la pregunta precisa para darte cuenta que 

no sabías qué estabas haciendo y, como en las pelis de espionaje, tienes unas horas de 

experiencia y escombros sobre los que rehacer una misión. Esto no es Stanford, pero 

tiene un valor incalculable. 

Susana fue muy buena ayudante y me sentí, aunque fuera por solo unos meses, 

muy correspondido con todo lo que humildemente pude explicarla y de ahí unas líneas 

aquí. Qué lindo recordar Wirikuta con una mexicana o cómo la amabilidad que viene 

del náhualt en la travesía desértica de una tesis que te permite hasta abrazar un cáctus, 

puede venir de quien te ayuda a colocar un simple electrodo.  



	 IX	

Clara ha sido la imagen del “easy going” que tanto aprecio en algunos amigos 

americanos. Inteligente y reservada, no ha escatimado ni esquivado nunca una buena 

conversación ni una visión amplia sobre todo aquello que estábamos haciendo, como si 

pudiera contextualizar en la vida una simple tarde de EEG. Es de esas personas que ha 

ido más allá de un papel X en un laboratorio Z y a día de hoy, disfruto de su amabilidad 

y escucho atento sus sueños e ideas para un mundo más sincero y sencillo. 

El resto de compañeros que estuvieron o están en el laboratorio como Miguel, 

Oscar, Esperanza, Alvaro, Rahele, Esther, Marta y otros también han sido parte de mi 

aprendizaje, reflejo de mis procesos (incluidas mis neurosis) e incluso objeto de mi 

admiración silenciosa. A algunos de ellos que les tocó recibir algo mío, os recuerdo que 

el “disclaimer” decía: “se asegura la empatía, no el conocimiento”. A tod@s también 

muchas gracias.  	

“Dice la razón: busquemos la verdad 

Y el corazón: Vanidad. 

La verdad ya la tenemos. 

La razón: ¡Ay, quien alcanza la verdad! 

El corazón: Vanidad. 

La verdad es la esperanza. 

Dice la razón: Tú mientes 

Y contesta el corazón: 

Quien miente eres tú, razón, 

Que dices lo que no sientes. 

La razón: Jamás podremos entendernos, corazón. 

El corazón: Lo veremos” 

Antonio Machado	



	 1	

INDEX  

Abstract / Resumen          4 

Preface / Prefacio          9 

1. Chapter 1. Introduction        18 

1.1. Emotional processing: Basic and Social emotions    18 

1.2. Overview of general theories of emotion     20 

1.2.1 The Theory of constructed emotions – Feldman Barret   23 

1.3. The social emotions        27 

1.3.1. The Self aspect         28 

1.3.2. The Moral side of social emotions      30 

1.3.3. The social aspect. Attributional theories and social valuation theories  31 

1.4. A social brain         33 

1.5. Electrophysiological correlates of emotions      35	

1.6. The neuroanatomical correlates of social emotions    39 

1.7. How to study social emotions in the lab?     42 

 

 Chapter 2. Objectives and hypothesis      42	

 

Chapter 3. Study One. Interpersonal guilt.     45 

3.1. Introduction         45 

3.2. Method          50 

3.2.1. Participants         50 

3.2.2. Procedure         51 

3.2.3.. Electrophysiological recording and analysis     56 

3.2.4. SCR recording and analyses       58 



	 2	

3.2.5. Source generator analyses       58 

3.3.. Results           59 

3.3.1. Performance         59 

3.3.2 SCR          59 

3.3.3. ERPs and LORETA analyses       59 

3.3.4. Correlations between frontal negativity and variables linked to emotions and 

social cognition          62 

3.4. Discussion         64 

3.5. Conclusion         68 

 

4. Chapter 4. Study Two. Shame.       69 

4.1. Introduction         69	

4.2. Material and methods         74 

4.2.1. Participants         74 

4.2.2. Procedure         75 

4.2.3. Electrophysiological recording and analysis      78 

4.2.4. Source generator analyses       80 

4.2.5. SCR recording and analyses        80 

4.3. Results           81 

4.3.1. Performance         81 

4.3.2. SCR          81 

4.3.3 ERP and LORETA analyses       82 

4.3.4. Correlations between ERP results and variables linked to emotions  85 

4.4. Discussion         86 

4.5. Conclusion         90 



	 3	

 

5. Chapter 5. Study Three. Pride and shame.     91 

5.1.  Introduction         91 

5.2. Materials and methods         95 

5.2.1. Participants         95 

5.2.2. Procedure         95 

5.2.3. Electrophysiological recording and analysis      99 

5.3. Results          101 

5.3.1. Self-reported emotions ratings       101 

5.3.2. Electrophysiological data: Pride       103 

5.3.3. Electrophysiological data: Shame       107 

5.4. Discussion         111 

5.4.1. Prompting pride and shame in experimental environments   111 

5.4.2. Neural Mechanisms involved in pride      112 

5.4.3. Neural mechanisms involved in shame     114 

5.4.4. Limitations of the present study      115 

 

6. Chapter 6. General discussion      117 

 

7. Chapter 7. Conclusions       124 

References          125	

  



	 4	

Neural correlates of the social emotions guilt, shame and pride  

 

ABSTRACT 

Brain research on emotions is generally  focused on basic emotions such as anger, fear, 

sadness, joy, contempt, surprise and disgust. These basic emotions, are by far, the most 

well understood. They are easy to approach, presumably universal and linked to other 

primates and non human animals. These characteristics have permitted a broader search. 

Social emotions as guilt, shame, embarrasment and pride, nevertheless, remain largely 

unexplored, although our life is tainted with them,. 

 Social emotions are different to basic ones. They require complex cognitive and 

evaluative aspects, and not only emotional. In experimental settings are usually studied 

stemming from imagining or remembering situations removed from social reality.  

Participants imagines him/herself acting in a precise situation, or tries to restore a 

memory, relatively recent, in which that emotion has been felt in a similar social 

context. This experimental setting is very different to social life, where social emotions 

emerge as a reaction to self predictions, precise contexts, standards and norms. 

 Through three studies, this PhD research shows that social emotions are, 

spatially and temporally, created in the brain. Previous studies do not generate social 

emotions in the lab. Our aim has looked for a more ecological setting to study the social 

emotions of guilt, shame and pride where their emergence is not related to memory or 

imagination. 

Participants performed several games in which the main task was to cooperate or 

compete with others while their brain activity was measured by electroencephalography 

(EEG). Event-related potentials were measured in the critical moments of guilt, shame, 

pride, joy or  absent of emotion, according to each experiment.  



	 5	

In Study 1, we manipulated a dot estimation task result with 24 pairs (participant 

and friend) in which the different results elicited our conditions of interest, guilt and 

shame. A frontal negativity, replicating and broadening the results of a previous study 

(Leng et al, 2016), explained the emergence of empathic processes linked to the 

emotion of guilt and with a presumably medial prefrontal cortex activation related to the 

frontal negativity.. 

In Study 2, we focused on shame, trying to separate it from it from guilt, with a 

similar paradigm (dot estimation task) but creating new roles (adviser and decisor), for 

every pair of participants.  Medial areas were again involved in shame, with an early 

centro parietal negativity and a lateralized posterior frontal positivity.  

In Study 3, we approached shame and pride simultaneously with the dot 

estimation task and a particular social exposure, different to previous studies. Other 

students from different universities participated in real time in the dot estimation task 

simultaneously with our participants. The different experimental design combinations 

allowed us to graduate the maximal and minimal degrees of pride and shame elicited. 

Results showed early negativites and late positivities, frontals and centrals, for both 

emotions. 

Results in the three studies performed, consistently show that social emotions 

can and must be researched in a social context in the lab through ecological settings 

more similar to daily situations and imply a two-step brain process, early and late, with 

brain activity linked mainly to medial areas. 

 

 

 

 



	 6	

Correlatos neuronales de las emociones sociales de culpa, vergüenza y orgullo 

	

RESUMEN 

La investigación cerebral tradicional sobre las emociones se centra en las 

llamadas emociones básicas, siendo ira, miedo, tristeza, alegría y asco las más 

estudiadas. Su facilidad de estudio, ubicuidad y posible vínculo con otros primates y 

animales no humanos, han posibilitado una extensa investigación. Las emociones 

sociales, entre las que destacan principalmente la culpa, la vergüenza, el orgullo y el 

bochorno, a pesar de que nuestra vida está teñida de ellas, permanecen aún con 

muchísimos aspectos por explorar.  

Estas emociones sociales a diferencia de las básicas, implican aspectos 

cognitivos y evaluativos complejos, no solo emocionales. En  el ámbito experimental se 

suelen elicitar  a partir de situaciones imaginadas o recordadas, en los que el sujeto se 

visualiza a sí mismo respondiendo en una situación precisa, o trata de rescatar de su 

memoria una experiencia relativamente reciente en la que haya sentido esa emoción en 

un contexto social similar. Evidentemente este modo experimental está muy lejos de 

nuestra realidad social cotidiana en la que se las emociones sociales, surgen in situ, 

como respuesta a predicciones propias, contextos precisos, normas y acuerdos comunes, 

que toda vida social requiere.  

A lo largo de tres estudios, esta tesis investiga cómo se forman en el cerebro, 

temporal y espacialmente, estas emociones sociales. A diferencia de la mayoría de los 

estudios hasta ahora realizados, nuestro interés ha sido generar la emoción social en el 

laboratorio, en lo que hemos considerado un escenario más ecológico que el recuerdo o 

la imaginación de las mismas. 



	 7	

Los participantes realizaron diversos juegos en los que la competición y 

cooperación con otros era la principal característica y al mismo tiempo se registró su 

actividad eléctrica cerebral mediante un electroencefalograma (EEG). Se calcularon 

potenciales evento–relacionados (PERs) en los momentos críticos, los cuales, 

dependiendo del experimento, implicaban una condición de culpa, vergüenza, orgullo, 

alegría o ausencia de emoción.  

En el Estudio 1, se manipuló el resultado de una estimación de puntos realizada 

por 24 parejas (participante y amiga) en la que los diferentes resultados elicitaban las 

condiciones de interés, siendo culpa y vergüenza las que fueron objeto de nuestro 

estudio. Una negatividad frontal, replicando y ampliando resultados de una 

investigación previa (Leng et al, 2016) explicaba la emergencia de procesos empáticos 

vinculados a la emoción de culpa y con la posible partipación de la corteza medial 

prefrontal en la negatividad citada. 

En el Estudio 2, nos centramos en el análisis de la vergüenza, intentando 

diferenciarla de la culpa, en un paradigma similar de estimación de puntos y 

manipulación de resultados pero cambiando los roles de la pareja participante (consejera 

y decisora. Áreas mediales estuvieron de nuevo implicadas en la emoción social 

buscada, con negatividad temprana centro parietal y positividad frontal posterior 

lateralizada a la derecha.  

En el Estudio 3, estudiamos la vergüenza y el orgullo simultáneamente, con la 

tarea de estimación de puntos y una exposición social diferente a los anteriores estudios, 

al realizar el experimento junto con otros participantes de otras universidades online in 

vivo, aumentando el carácter de exposición social como inductor de las emociones 

buscadas. Las diferentes combinaciones del diseño experimental permiten graduar el 

nivel máximo y mínimo de vergüenza/orgullo elicitados obteniendo negatividades 



	 8	

tempranas y positividades tardías, frontales y centrales para ambas emociones. Las áreas 

mediales del medial prefrontal, precuneus y cingulado posterior se vinculan como 

posibles fuentes de las negatividades y positividades obtenidas. 

Los resultados obtenidos en los tres estudios demuestran que las emociones 

sociales pueden y deben ser investigadas en un contexto social en el laboratorio a través 

de escenarios más ecológicos y cercanos a la vida real, e implican un procesamiento 

cerebral en 2 etapas, temprana y tardía, con actividad vinculada fundamentalmente a 

áreas mediales. 

  



	 9	

PREFACE 

Many years ago in a far, far away mexican desert a book called  “El cerebro nos 

engaña” was by chance with me. Although it was a popular book it lead to a realization 

in my head since I realized then something which is  very clear to me now: all human 

experiences are brain centered ones (but not brain-centric). And of course, those 

experiencies were indeed brain experiences, but not illusory. Years before, when my 

father lost his job, and somehow his health, he brought to me one only book book from 

the printing house where “Cuadernos para el diálogo” was published, specifically one 

called“Las enseñanzas de Don Juan”. The author was a naughty anthropologist, 

compulsive liar, handler lady´s man but nevertheless a genius novelist and stalking 

master called Carlos Castaneda. Between algebra and thermodynamics, the teachings of 

Don Carlos and Don Genaro spread in my mind at times and paved the way to a Viaje a 

Itxlán in my youth as a true seeker, yes, amidst a strange industrial engineering and a 

devoted martial arts practise. In that desert, I was incidentally learning with an autor 

who has Castaneda’s  direct and smart oustanding pupil. He rooted  these novels by 

applying a psychological and meaningfull approach, far away from an esoteric view. I 

searched and followed him for years after reading his book for him and followed years 

after reading his book. But, returning to the desert, all of this was clearly and without 

the shadow of a doubt, a brain experience. It was 2007 and a true interest in researching 

about where we  came from, who we are and where we go arose in me, not only from a 

first person view but also from a third person’s perspective, indeed a scientific one. It is 

clear that I never wanted to put out the fire of these kinds of answers with religious fire 

extinguishers. The path seemed exhausting and it truly has been this way, so why 

neglect it?: studying a second degree, three Masters and a PhD at an age where one 

perhaps should be doing other things. If the turns of the brain are complex, the turns of 



	 10	

life gyri are not under our control. Naive in  neuroscience, but I emailed Dr. Rubia, the 

autor of that desert book, when  studying a Biotechnology degree in 4th year. I was 

looking for a PhD director long before enrolling in the Neuroscience Master. I was very 

fortunate, because in the that Master, there seemed to me to be only one option that 

could establish a link between life, dayly matters and my ectelctic past.  That option 

turned to be the Center for Evolution and Human Behavior (neuroscience section) 

directed by Manuel Martín-Loeches. I am not trying to reorder the pieces of my life 

pieces from a retrospective view in order to highlight a serendipia, but rather, as we are 

the constructors of our own feelings and emotions, the meaning we believe can be the 

starting point and not the finish line.  

Therefore I choose one that respects randomness, that embraces what we do not 

know yet and, as all human experiences are brain centered and most of them are social, 

this includes me as a part of something truly human, here and now, together. 

So, since some years ago for a Master thesis dissertation and after that for a PhD, I 

started finally, jumping from one inspiring book to another one, in C.E.C.H for this new 

journey. 

I admit I am twice lucky as emotions are a highly relevant subject for me either 

both personal or profesionally, although it is hard to extract something applicable from 

a “frontal negativity”. For better or worse, my best and worst decissions in life have 

been tainted  by social emotions: an indescriptible shame for loosing, absolute 

desperation after a heartbreak or a planned revenge because of a sport match-fixing. 

Those with strange valence, being as ecological as well as social, have arosen my 

curiosity: unspeakable awe in nature, a strange serenity and calmness in the middle of 

the storm or a devotional feeling to people who live merging into an obliged present. 



	 11	

Social emotions dye life with colours and keep it far from the grays. They are so 

fast that they seem conductists but they truly tend to arise from our previous 

assumptions about what we must feel and how we have to respond to precise contexts in 

determined contexts/situations. 

Researching emotions in third person is paradoxical, as any subjective human 

experience far from the hard sciences, but when talking about social emotions, even 

more.  

We could somehow through this research come back to “Cuadernos para el 

diálogo”. I can not find a better example than remembering myself sitting down in a 

train station between a renowned psychologist in “emotional intelligence” and a 

medicine man without any academic credentials in third person, but with a conscious 

life in the first one. The train broke down and an announcement call told us to wait four 

hours more. The psychologist said: “Damn it! Four hours here waiting! Medicine man 

replied: “mmm, four hours to remain calm”. 

Despite the obvious difficulties, in the three studies that form this PhD thesis we, 

somehow, have tried to stablish those encounters between real life and the laboratory, 

thinking, designing and setting up scenarios where participants felt at that moment the 

social emotion. In the name of science, we had to dupe them, as it is usual in 

psychology experiments to reach the most objective standards and therefore collect and 

measure what we were prompting to feel. 

These experimental designs represent a way to study social emotions from an 

ecological view, a bridge between first and third person with the measure of a brain 

activity signal that lights up a step further in this complex affective neuroscience world, 

yet to be developed. 



	 12	

We have spared no efforts in this direction studying the neural correlates of 

social emotions in ecological lab settings. Guilt, shame and pride were the first chosen 

ones, and have been a central meeting point of thoughts, debates, analysis, discussions, 

corrections and publications. They surprisely elicited in us, hope, joy or frustration, and 

luckily less from themselves. There is still much to learn from them and other social 

emotions, but this PhD is a good summary of a teamwork and that took a significant 

number of years in this field that someone undoubtfully will follow latter taking the 

lead.  

In this journey of social emotions several people have been involved in the 

researchs and as coauthors of the scientific papers. They are:  

 

Study One*: Jose Sánchez-García, Javier Espuny, David Hernández-Gutiérrez, Pili 

Casado, Francisco Muñoz, Laura Jiménez-Ortega, Sabela Fondevila, Manuel Martín-

Loeches. 

 

Study Two: Jose Sánchez-García,  David Hernández-Gutiérrez, Pili Casado, Sabela 

Fondevila, Francisco Muñoz, Laura Jiménez-Ortega, Manuel Martín-Loeches. 

 

Study Three**: Jose Sánchez-García, Gema Esther Rodríguez, David Hernández-

Gutiérrez,  Pili Casado, Sabela Fondevila, ,  Laura Jiménez-Ortega, Francisco Muñoz 

Miguel Rubianes,  Manuel Martín-Loeches. 

 

Published: Sánchez-García, J., Espuny, J., Hernández-Gutiérrez, D., Casado, P., Muñoz, 

F., Jiménez-Ortega, L., ... & Martín-Loeches, M. (2019).Neurofunctional 



	 13	

characterization of early prefrontal processes contributing to interpersonal 

guilt. Cognitive, Affective, &BehavioralNeuroscience, 19(5), 1192-1202. 

 

** Published  in BrainStructure and Function. 

  



	 14	

PREFACIO 

Hace muchos años en un desierto mexicano muy muy lejano me acompañaba 

casualmente un libro llamado “El cerebro nos engaña”. Aunque de corte divulgativo, 

provocó un estallido en mi cabeza porque me permitió darme cuenta de algo evidente 

ahora, y es que toda experiencia humana es cerebral (que no cerebrocéntrica). Y vaya si 

eran cerebrales aquellas experiencias, que no ilusorias. Años antes, cuando mi padre 

perdió su trabajo y parte de su salud, rescató un único libro de aquella imprenta donde 

se publicaban “Cuadernos para el diálogo”, concretamente uno llamado “Las 

enseñanzas de Don Juan” cuyo autor era un pillo antropólogo, mentiroso compulsivo, 

mujeriego manipulador, pero genial novelista y maestro del acecho llamado Carlos 

Castaneda. Entre algebra y termodinámica se colaban a ratos esas enseñanzas de Don 

Juan y Don Genaro y fueron instalando un Viaje a Itxlán en mi juventud como buscador 

genuino, sí, en medio de una ingeniería extraña y una devoción a las artes marciales. En 

ese desierto, casualmente me encontraba aprendiendo con un autor, alumno aventajado 

de Castaneda que enraizaba esas novelas y les daba un sentido y dirección práctica 

psicológica muy concreta, lejos de una interpretación esotérica, y al que busqué y seguí 

durante años tras leer su libro. Pero volviendo al desierto, resulta que todo eso era, 

evidentemente, una experiencia cerebral. Estaba en el año 2007 y nació un interés muy 

fuerte por investigar no solo en primera, sino en tercera persona desde la ciencia, algo 

del quiénes somos, de dónde venimos y adónde vamos, respuestas que nunca quise 

apagar con extintores religiosos. El camino parecía agotador y así ha sido, para qué 

negarlo: estudiar una segunda carrera, 3 masters y una tesis doctoral a una edad en la 

que uno debería quizá estar haciendo otras cosas. Si los giros del cerebro son 

complicados los de la vida no son aptos para el control. Profano y ridículamente 

inocente en esto de la neurociencia, escribí al Dr. Rubia, el del libro del desierto, en 

cuarto de Biotecnología, buscando un director para una tesis cuando ni siquiera había 



	 15	

empezado aún el Master. Acabé siendo muy afortunado, porque de todas las opciones 

que vi posteriormente en el Master de Neurociencia, solo una me parecía que podría 

tener un vínculo aplicable con la vida, lo cotidiano y mi ecléctico pasado. Esa opción 

resultaba ser la del grupo del Centro de Evolución y Comportamiento Humanos dirigido 

por Manuel Martín-Loeches, donde se investigaba todo ello. No trato de ordenar las 

piezas de mi vida en retrospectiva para destacar la posible serendipia, sino que, como 

constructores de emociones y sentimientos que somos, el sentido puede ser el punto de 

partida y no la meta. Y elijo uno que respete el azar, abrace lo que no sabemos aún y 

dado que toda experiencia es cerebral y la mayoría son además sociales, me incluya 

como parte de algo humano, aquí y ahora, juntos. 

Así que desde hace unos años para un TFM y después para una tesis, empecé por 

fin, de libro inspirador en libro inspirador, en el C.E.C.H. para este nuevo viaje.  

Confieso que he sido doblemente afortunado porque las emociones es un tema 

que me resulta profesional y personalmente relevante, aunque cuesta sacarle jugo 

profesional a una “frontal negativity”. Al fin y al cabo, mis peores y mejores decisiones 

en la vida han estado teñidas de emociones sociales: que si una vergüenza indescriptible 

por una derrota, la desolación absoluta del desamor o la venganza planificada ante un 

amaño deportivo entre otras. Las de valencia rara, por ser tan ecológicas como sociales, 

han ocupado mi curiosidad: un sobrecogimiento inmensurable una y otra vez ante la 

naturaleza,  una extrañísima serenidad en medio de las peores tormentas o una devoción 

intensa por los que viven mimetizados con un presente obligado.  

Las emociones sociales tiñen la vida de colores y la alejan de los grises. Son tan 

rápidas que parecen conductistas y sin embargo suelen nacer de interpretaciones previas 

de qué debemos sentir y cómo debemos responder ante determinados contextos.  



	 16	

Investigar las emociones en tercera persona resulta paradójico, como toda experiencia 

subjetiva humana lejana a las ciencias duras, pero en el caso de las emociones aún más. 

Quizá podamos aquí con estas investigaciones retomar de alguna manera esos 

Cuadernos para el diálogo y para ello no encuentro mejor ejemplo que uno de hace 

años en una estación de tren, sentado entre un reputado psicólogo experto en 

“inteligencia emocional” y un hombre medicina sin estudios en tercera persona pero 

toda una vida consciente en la primera. El tren se averió y por megafonía nos 

anunciaron un retraso de 4 horas. El psicólogo dijo: “Joder, cuatro horas aquí 

esperando”. El hombre medicina replicó: “Mmm, cuatro horas para estar serenos”. 

De alguna manera, a pesar de las evidentes dificultades, en los tres estudios que 

conforman esta tesis hemos intentado establecer esos encuentros entre el laboratorio y la 

vida real, reflexionando, diseñando y poniendo a prueba escenarios en los que los 

participantes sintieran allí mismo in situ, ante el contexto creado, nada más y nada 

menos, que una emoción social. En nombre de la ciencia hemos tenido que engañarles, 

como es habitual en los experimentos de psicología para ser lo más objetivos posibles, y 

de este modo, medir objetivamente lo que inducíamos a sentir.  

Estos diseños experimentales representan una vía para el estudio de las 

emociones sociales de forma ecológica y cercana, un intento de puente entre esa 

primera y tercera persona con una medida de la actividad cerebral que nos ilumine un 

poquito más en este complejísimo mundo de la neurociencia afectiva, aún en ciernes. 

No hemos escatimado esfuerzos en esta dirección en el estudio de correlatos 

neurales de emociones sociales en entornos ecológicos de laboratorios. Culpa, 

vergüenza y orgullo han sido las primeras elegidas y fueron objeto de lecturas, 

reflexiones, debates, análisis, discusiones, correcciones y publicaciones. Nos elicitaron 

curiosamente esperanza, alegría o frustración y afortunadamente menos de ellas 



	 17	

mismas. Seguimos aún con mucho por aprender de ellas y otras emociones sociales, 

pero esta tesis es un buen resumen de un trabajo común y colectivo en esta dirección 

que ya implica un considerable número de años y que sin duda alguien se encargará de 

ampliar y profundizar. 

En este viaje de experimentos en emociones sociales varias personas han 

formado parte. Las que han participando en la realización de los experimentos que 

forman la tesis y son coautores de las publicaciones científicas correspondientes son: 

 

Estudio Uno*: Jose Sánchez-García, Javier Espuny, David Hernández-Gutiérrez, Pili 

Casado, Francisco Muñoz, Laura Jiménez-Ortega, Sabela Fondevila, Manuel Martín-

Loeches. 

	

Estudio Dos: Jose Sánchez-García,  David Hernández-Gutiérrez, Pili Casado, Sabela 

Fondevila, Francisco Muñoz, Laura Jiménez-Ortega, Manuel Martín-Loeches. 

	

Estudio Tres**: Jose Sánchez-García, Gema Esther Rodríguez, David Hernández-

Gutiérrez,  Pili Casado, Sabela Fondevila, ,  Laura Jiménez-Ortega, Francisco Muñoz 

Miguel Rubianes,  Manuel Martín-Loeches. 

	

* Publicado: Sánchez-García, J., Espuny, J., Hernández-Gutiérrez, D., Casado, P., 

Muñoz, F., Jiménez-Ortega, L., ... & Martín-Loeches, M. (2019). Neurofunctional 

characterization of early prefrontal processes contributing to interpersonal 

guilt. Cognitive, Affective, & Behavioral Neuroscience, 19(5), 1192-1202. 

 

** Publicado en Brain Structure and Function 



	 18	

Chapter 1. Introduction 

 

1.1. Emotional processing: Basic and Social emotions	

To say it bluntly, emotions have been considered ‘bad press’, although they don´t 

deserve that adjective. Throughout our human history, reason represents the top 

knowledge in mind hierarchy. From Plato, in which reason rides in a horse-

drawn carriage (horses, emotions; reason, charioteer) to Descartes (“I think, therefore I 

am”), emotions seemed to take a minor and disturbing role in human motives and goals.  

Thanks to psychological and neuroscience research advances, emotions appear now to 

represent a central role in understanding human mind. As Charles Darwin proposed, if 

emotions exist, they must accomplish a positive function to meet survival needs. 

In The Expression of the Emotions in Man and Animals book, Darwin opened 

the field to ongoing investigations reinforcing the communicative aspect of emotions. 

Fear, joy, sadness or anger play an adaptive role informing others about our intentions 

and feelings. They also seem to share some commonalities with other species, stemming 

from common origins. 

Several definitions and classifications of emotions have been proposed 

thoroughly by field experts reaching to agreement in considering emotions as 

multidimensional processes. 

Emotions are thus defined as a multifactorial episode which includes subjective 

feelings, cognitions, motivational tendencies, physiological processes and behavioral 

expressions in response to conscious or unconscious stimuli (Scherer, 2009).  

Emotions, therefore, are neural dispositions for adaptive reactions to meaningful 

biological and/or cultural events. An emotion as fear, at the sight of a snake, prepares us 

to flee or fight increasing heart rate, blood pressure, cortisol release and blood flow to 



	 19	

muscles. Sadness, due to a loss or withdrawal, inhibits our sympathetic system, alters 

our breathing capacity, depletes activation levels and bends inward our posture. 

This triad of subjective feelings, physiological reactions and behaviors can be 

triggered by either external or internal stimuli such as memories and thoughts, 

consciously or out of awareness, and serve to survival and social needs.  

Emotions, as rapid reactions to stimuli, are brief. They fade away in seconds. Moods, on 

the other hand, last longer periods and may not need an eliciting event to startle 

(Verduyn, et al. 2015). 

Two main groups of classifications are used to describe emotions: dimensional 

and categorical: 

Dimensional theories set a specific emotion to deploy on a two-dimension scale: 

valence and arousal (Barrett, Lewis, & Haviland-Jones, 2016). Valence can be positive 

or negative regarding its relative pleasantness or unpleasantness, whereas arousal relates 

to the intensity of the emotion. Dimensional theories display emotions in vector or 

circumplex models. Several researchers (Larsen et al., 1992; Remington et al. 2000; Yik 

et al. 2002) consider this two-dimensional model to be scarce. Alternatively, Fontaine et 

al., (2007) propose four dimensions to apprehend emotion complexity: evaluation-

pleasantness, potency-control, activation-arousal and unpredictability. This model 

considers emotion as a six-component process: (a) appraisals of events, (b) 

psychophysiological changes, (c) motor expressions, (d) action tendencies, (e) 

subjective experiences, and (f) emotion regulation. 

Categorical classifications discriminate between basic and social (also called complex 

or self-conscious) emotions as discrete entities.  

Basic emotions are described as universal (showing presumably an unique 

feature of expression), innate, heritable and first to develop (Tracy and Randles, 20011). 



	 20	

Social emotions are cross-cultural modulated, require high cognitive skills to be 

processed, emerge later in development, are influenced by language and imply a sense 

of self (Lewis, 1992). This discrete classification is currently considered more as a 

continuum with several degrees of interaction than a strict domain classification. Basic 

emotions are best studied and understood due to their simplicity compared with social 

emotions and even by assuming shared commonalities with nonhuman animals, who 

provide valuable research and theoretical perspectives. 

There is not a clear consensus between authors in the number of basic emotions. 

Proposals vary from 4, to up to 10. Surprise, anger, sadness, fear, joy and disgust are the 

6 main basic emotions in Ekman’s model (Ekman, Levenson, & Friesen, 1983). Fear, 

anger, joy, sadness, confidence, disgust, anticipation and surprise are the 8 basic 

emotions for Plutchik (2001).  

Many feelings, the subjective experience of emotion, can apply to social 

emotion definition: envy, shame, resignation, jealous, hope, remorse, longing, guilt, 

pride and others. Main social emotions studied so far are guilt, shame, pride and 

embarrassment (Tagney, 2003). As expected, social emotions are even more difficult to 

categorize because they are sensitive to cross-cultural differences, they do not rely 

easily in external features as face or body expression, and depend more on social 

context and self-implication than basic emotions. Considering these classifications, it is 

clear that emotions are not fully understood.  In the last decades several theories have 

emerged to explain the affective human domain. 

 

1.2. Overview of neurobiological theories of emotion 

One of the first emotional theories proposals was the James-Lang theory (Cannon, 

1987). For William James, for instance, when we are escaping from a predator, the acts 



	 21	

of running, sweating, breathing and other physiological changes is what  produces the 

subjective feeling of fear. The experience of an emotion depends on the prior feedbacks 

from the brain and body responses. Carl Lange emphasized the role of the heart and 

brainstem nuclei controlling cardiac function in emotion generation. 

The Cannon-Bard theory argued that a specific autonomic nervous system 

response, as those stated by James–Lang theory, cannot discriminate the enormous 

variety of emotional states (Dror 2014). Cannon and Bard even demonstrated that and 

injection of hormones as noradrenaline does not elicit a particular emotional state, 

similar to Gregorio Marañón’s experiments back in 1920´s (being this consideration –

mainly based in James’ theory- crucial to the constructed emotional theory, which will 

be exposed below). James – Lang and Cannon-Bard theories rely in the neurobiological 

basis of emotions. They suggested that the body´s fight or flight response is coordinated 

via the autonomic nervous system, preparing the individual to deal with an emotional 

situation. Through transection experiments in decorticated animals and absence or 

presence of emotional reaction they highlighted the role of the diencephalon (thalamus 

and hypothalamus) to direct the information to the neocortex, generating emotional 

feelings, and to the periphery, then generating emotional (physiological) reactions. 

Some years later, James Papez proposed the limbic system theory by including 

the cingulare gyrus to mediate emotional feelings (Papez, 1937).  In the Papez’s circuit 

theory, cortical and subcortical inputs are integrated in the cingulate gyrus, linking 

emotional feelings and body reactions. The stream of thought, or cortical route, carries 

input from the thalamus or memories to the cingulate, while the stream of feeling, or 

subcortical route, carries input from the hypothalamus and thalamus to the cingulate, 

reinforcing the cortical route.  



	 22	

In an essay to integrate Cannon-Bard, Papez and even Freud ideas, Paul 

MacLean proposed an evolutionary 3-steps brain model in which emotions were linked 

to the limbic system, now including amygdala and orbitofrontal cortex, then broadening 

the scope of Papez´s circuit (Cory, 2002). Despite its conceptualization, the triune brain, 

as named in MacLean’s model, was openly surpassed by Joseph Ledoux’s findings 

(Ledoux, 2012). Ledoux stated that there are no real independent anatomical criteria to 

split the brain in 3 separate functional areas. For instance, an area fully recognized as 

the amygdala shows cognitive and categorization functions, while the most rational 

brain area, the dorsolateral prefrontal cortex, is recognized to serve different emotional 

regulation functions. Triune brain hypothesis is too simplistic: rarely a brain area serves 

for a single function and vice versa. Ledoux therefore surpasses the isolated triune brain 

theory to enhance the role of the connectivity between amygdala and prefrontal cortex 

in emotional processing. Amygdala lesions in human brain disrupt fear conditioning 

(Labar et al, 1996), and frontal lobe lesions impair fear processing, showing no signals 

of anxiety, stress or fear behavior. Prefrontal–amygdala connective pathways play a 

lead role in emotional processing and regulation. Deepening the understanding of 

neocortex in emotional processes, several researchers (Ross 2008, Harmon-Jones, 2010) 

have added valuable contributions by studying the hemispheric specialization and its 

influence in understanding emotions.  Prosody and frontal asymmetry are two examples 

of this hemispheric discrimination. Affective prosody of language, based on functional 

and anatomical evidence in patients with focal ischemic strokes, is a dominant and 

lateralized function of the right hemisphere (Ross, 2008). Greater left than right frontal 

cortical activity is associated to positive affect and approach motivation, which can be 

positive (e.g., enthusiasm) or negative (e.g., anger) in valence.  



	 23	

Based on William James’ previous emotional theories, Damasio´s somatic 

marker theory (Bechara and Damasio, 2005) focuses in brain and body change states in 

response to a stimulus. This theory emphasizes the role of emotions in decision making 

processes. Physiological changes, sensations and feelings, considered as pleasant, 

unpleasant or neutral, adjoin instincts, previous experiences and desires participate to 

form a final decision. They may even overcome rational thoughts: for instance, when 

jumping from a bridge to the void despite three security belts and a 100% success 

probability, body sensations reject jumping. In psyco- or sociopats, somatic markers do 

not function properly, avoiding guilt feelings from misbehaviors, infringement, non-

compliance, trespass or harm to others. When brain injuries affect the frontal lobes, as 

in the famous case of Phineas Gage, decision making processes are severely impaired 

and social misconduct compulsorily appears. Damasio proposes that the neural control 

of emotions implies limbic structures, prefrontal cortex, somatosensory cortex, basal 

ganglia, forebrain and brainstem. Rational decision making is linked to emotional 

processing, being the somatic markers a tool to integrate and accomplish in an adaptive 

way. 

 

1.2.1 The Theory of constructed emotions – Feldman Barret 

All the theories reviewed above are based in neurobiological signatures of 

emotions. They all see emotion as a fixed reaction to internal or external stimuli, shaped 

by evolutionary needs and linked to precise neuroanatomical and physiological areas 

and functions. Universality emerges from this perspective and each emotion has a 

“fingerprint”.  They assume these are responses to external or internal stimuli, deeply 

rooted in evolutionary schemes and somehow universal, if not fully in the expression of 

emotions, at least in their unique neural feature. They even show a sort of ethno- and 



	 24	

anthropocentrism, leading to explicitly assume that even animals, from chimpanzees to 

rats, experience feelings such as fear, joy or sadness in the same manner as we humans 

do, which is an extraordinarily controversial assumption. 

Therefore, a constructionist view is very relevant to understand the dynamics 

and interchangeable aspects of social emotions, which are prone to cultural and context 

influences difficult to cope with fixed neurobiological standards. The brain, on the other 

hand, and despite the counterintuitive self-awareness of its function in ourselves, is far 

from a stimulus–response device. 

If the brain were exclusively a reactive organ, it would be extraordinarily slow, 

unadaptive and ineffective (Frith, 2014; Friston 2010). The brain is more a predictive 

than a reactive system to cope and manage real-time processes. By predicting 

physiological resources and coordinating motor activity, the brain enables learning, 

lessening error predictions and reinforcing adaptive responses. Simulations and 

predictions are the main activity of the brain (De Ridder, 2013; Clark 2013). In every 

moment a huge amount of visual, auditory, vestibular, interoceptive, somatosensory and 

olfactory information arrives to the brain, not passively but predictably constructed. 

This simulation stems from our memories, context and expectations (Hoeman et al 

2020). We are not passive spectators, rather active constructors of perceptions, 

sensations and… emotions, far from a linear cause – effect vision.   

This construction is counterintuitive. We tend to feel reality is out there, unified 

and equally shared by others, and that the brain captures it as clear as it is. Nevertheless, 

only some of the wavelengths of light are perceived by our eyes and a small percentage 

of it is converted into seen objects. Not all the frequencies of sound are perceived by our 

auditory cortex, but in that limited human range only some of the air pressure changes 

are heard as words, sounds or music. By the same token only some bodily changes are 



	 25	

felt as emotions (Barret, 2012). 

Emotions, in the theory of constructed emotions (TCE) (Barret, 2017), emerge 

when people make meaning out of sensory body input and outside world, using memory 

of past experiences. Emotions arise from concepts adaptive to the immediate 

environment and preparing the person to respond to sensory inputs in a way suitable to 

the situation (Barrett 2006b).  The process arises from an initial top down prediction 

about the meaning of the sensory information and context being hold (Bar 2007). The 

error between the prediction and the sensory activity is then minimized to produce a 

unified conscious field (Friston 2010). 

Different to the prevailing idea that some specific networks or areas are 

responsible for the emotional activity, the TCE assumes that the functionality of 

individual brain depends largely on the connecting network regions firing in sync 

(McIntosh 2004).  

Usually, each emotion is assumed to produce neural activity in a specific brain 

region or network along a coordinated set of physiological responses, facial expressions, 

and voluntary behaviors, like freezing, fleeing, and fighting, emerging from the 

stimulus (Ekman, 1972) or after the evaluation of the stimulus (causal appraisal models; 

e.g., Ekman & Cordaro, 2011; Lazarus, 1991; Roseman, 1991). Each emotion is thought 

to produce a pattern compulsorily (Ekman, 1992) or probabilistically (Roseman, 2011). 

If small variations appear in this observed emotional pattern, they are accepted, but 

significant deviations are considered as errors, or caused by processes far from the 

emotional response. Nevertheless, heterogeneity within each emotion as well as 

similarities across different categories are the norm, not the exception (Barrett, 2006a, 

2009). Indeed, heterogeneity within emotion categories has been well studied and 

reported, both within individuals and across cultures (Ceulemans, Kuppens, & Van 



	 26	

Mechelen, 2012; Hortensius, Schutter, & Harmon-Jones, 2012; Kuppens, Van 

Mechelen & Rijmen, 2008; Kuppens, Van Mechelen, Smits, De Boeck & Ceulemans, 

2007; Nezlek & Kuppens, 2008; Stemmler, Aue, & Wacker, 2007). Variation is 

observed even when comparing patterns with exactly the same method and stimuli 

(Kragel & LaBar, 2013, Stephens, Christie, & Friedman, 2010). In turn, similarities 

may emerge from distinct emotional categories, such as fear and anger where neural 

responses are similar when elicited in a similar context of social threat (Wilson-

Mendenhall, Barrett, Simmons, & Barsalou, 2011).  

Overall, heterogeneity in emotional response challenges classical views of 

emotion (basic, appraisal or functionalist theories). Data contradicts the idea that each 

emotion has an essence or fingerprint that other emotions do not share such as a unique 

expression or a pattern of autonomous nervous system activity, or a set of specific 

appraisals. Consequently, comparing emotional categories of humans from different 

cultures with other non-human animals is not consistent with this lack of homogeneity 

(Russell, 1991; Gendron et al., 2014a,b, 2015; Wierzbicka, 2014; Crivelli et al., 2016). 

Heterogeneity may be explained by degeneracy (a concept derived from genetics), as 

many neural networks and areas respond to one emotional category (Lindquist et al., 

2012; Kragel and LaBar, 2015). 

  Therefore, for the TCE, emotions are predicted by concepts, rooted in our 

memories and interoceptive networks responding to the external environment. These 

concepts are embodied (Oosterwijk et al., 2012, 2015) and emerge as multimodal 

summaries represented in the default mode network and the salience network (Peelen et 

al., 2010; Skerry and Saxe, 2015; Raz et al., 2016).  

The TCE defines all sensory input from the body, such as raw somatic, visceral, 

vascular, and motor cues (James 1884), arousal (Duffy 1957; Mandler 1975; 1990; 



	 27	

Schachter & Singer 1962), or affect (Harlow & Stagner 1932; Hunt 1941; Wundt 

1897/1998), as core affect, to outline mental representations of body changes and 

arousal (pleasant or unpleasant) (Barrett & Bliss-Moreau 2009; Russell 2003; Russell & 

Barrett 1999). In fact, bodily cues are essential for consciousness (Craig 2009; Damasio 

1999). 

This core affect is attached to an object; described in the TCE as categorization. 

In this process, we make meaning of our core affective state by engaging in a 

conceptual categorization linking to an object or event. Concept categorization is 

therefore the process by which stored past experiences are used to create meaning from 

sensations emerging in the moment (Wilson-Mendenhall et al. 2011). 

The brain predictive primary purpose, regulating physiological resources, 

learning and meeting body needs before they arise is much more efficient than reacting 

after events. The TCE, by core affect and categorization, includes a top down view of 

constructing emotions that embraces heterogeneity, cultural differences and context 

interdependence. 

 

1.3. The social emotions 

As seen before in the TCE, heterogeneity and variety match with a non-fixed view of 

emotions as fingerprints and open up a social view of emotions. Most people seem to be 

daily involved in behaviors leading to get social approbation or to avoid social rejection. 

We engage daily in behaviors for losing or winning status, work hard to achieve specific 

goals and behave in such ways our relations are kept safe and stable (Baumeister, 

Stillwell and Heatherton, 1994). Social emotions, as opposed to basic ones, imply 

complex elicitors from social environment. In order to understand social emotions, 



	 28	

special attention should be payed to the sense of self, moral values and social 

relationships (Tracy, Robins and Tangney, 2007) .   

 

1.3.1. The Self aspect 

Basic emotions may not necessarily imply self-awareness, but social emotions must 

involve this process (Lewis 1989, Tangney 2002). This is proposed by several theories, 

even if it is highly controversial. Sometimes we experience guilt or shame without a 

complete awareness of the process. It is true that sometimes we may feel fear or anger 

in a self-evaluative process, but social emotions usually require a sense of self 

awareness.  

This self-identity allows self-representations and self-evaluation to occur. Social 

emotions require comparisons between other(s) and oneself, and an evaluative outcome 

of this comparison leading to promote or avoid behavior, or to repair the harm. 

Tracy and Robins (2004) proposed a model for social emotions deeply rooted in 

the sense of self. For a social emotion to emerge, an identity goal must appear first. If 

the evaluation is relevant to survival, a basic emotion arises; if, in turn, it is relevant to 

our self-identity, a social one arises.  

A second step to generate this sort of emotions is through attentional focus on 

the self. If this event is important for me, self-representations are activated stablishing 

comparison with the external event.  

The third step relies on “Is this important for me or who I want to be?”. This 

consideration is crucial because a social emotion is experienced if the person´s identity 

is in danger or heightened when an eliciting event is relevant to the self. Negative 

evaluations from others do not produce embarrassment or shame if they are about non 



	 29	

relevant personal domains. Positive evaluations may not heighten our personal status if 

they do not match our self-evaluative appraisals.  

The fourth step to set up a social emotion is based in congruency. When the 

event is relevant to our identity, the question is: “is it congruent or incongruent with the 

identity goals?” The outcome is a positive emotion when feeling congruent with the 

event, and negative in the opposite case. Our current self-representations may collide 

with our long term identity goals, as a sportsman failing a shot ruining his chances to 

win the tournament or a student failing an exam confronting the self-representation of 

being a smart student.  

Attribution of a causal locus of the actual event leads to the fifth step: “Am I the 

cause of the event?”. If the person feels the cause is outside, an external control locus, a 

basic but not social emotion may emerge, as sadness of anger, as a result of 

uncontrollable circumstances. In fact, this is a common way to elicit basic emotions, as 

threats to survival needs are not ubiquitous in our daily lives, but we usually feel anger, 

fear or sadness, due to external attacks to our identity which we consider truly relevant. 

If the cause attribution is internal, related to the sense of self, a social emotion may 

emerge, leading to the sixth step: “Is it about me or about something I can´t control?” 

When we assume stable, uncontrollable and global attributions causing the event, shame 

or embarrassment may appear. When causes are internal, unstable, controllable and 

specific guilt arises. “Did I study wrongly or am I a worse student?” represents the two 

approaches focusing in a concrete action or a self-characteristic.  On the other hand, if 

the result of the event is a positive evaluation, either authentic or hubristic pride 

appears. “Was it good because of my effort or due to my special genes and talent?”. 

Authentic pride relates to merit, will and effort to achieve a desired outcome. On the 



	 30	

other hand, hubristic pride relies in the sense of having special skills or natural talent to 

which we may attribute our success (Holbrook, 2014).  

This sixth step integrates self and emotions to understand the different thoughts, 

behaviors and feelings in the process and to set up clear distinctions between basic and 

social emotions and furthermore disentangle the social ones more clearly. Social 

emotions therefore imply an awareness of discrepancy between a current state and an 

identity goal resulting in negative or positive affect. The result of this affect leads to the 

appearance of the distinctive shame, embarrassment, guilt or pride emotions. 

 

1.3.2. The Moral side of social emotions 

The discrepancy between a current state and an identity goal implies a comparison 

between one´s self and its evaluation according to ethics, moral and social norms. Social 

emotions give rise to moral behaviors as they produce immediate reward or punishment. 

We evaluate by ethic the consequence to others of our actions and assess our own self 

behavior in relation to moral standards. This evaluation is not only consequential. We 

may easily forecast and anticipate shame, pride or guilt in response to a full range of 

potential situations. Three components are studied to support moral behavior: standards, 

cognitions and emotions. 

Moral standards are diverse and culturally oriented, although most people feel it 

is wrong to cheat, lie, do harm, hate or murder others. According to Shweder et al., 

(1997), ethics may be classified in three main groups: divinity, autonomy and 

community.  

Divinity shows a high cultural variability and usually relates to purity (even 

physical). In fact, appearance of moral gods, usually by enhancing intrapersonal guilt 

feelings, are intertwined to social complexity (Whitehouse et al., 2019).Autonomy 



	 31	

approaches to justice, equity, human rights and no harm banning. Community relates to 

social norms such as duty, loyalty, honesty and respect. 

Moral cognitions are a core set of ideas believed to foster behavior according to 

our moral standards. This assumption is surpassed by researchers as people may use 

rationalization and cognitive dissonance (Bandura, 1990) to perpetuate a wrong or 

harming behavior by diminishing the consequences, show contempt to the victims or 

downplaying psychological harm to others. 

Moral emotions are the motivational power to practise goodness and avoid bad 

(Kroll and Ega, 2004), linking moral cognitions to moral standards. According to Haidt 

(2000, 2003) moral emotions “are linked to the interests or welfare either of society as a 

whole or at least of person other than the judge or agent”. Not only negative or 

unpleasant social emotions serve to moral functions. Compassion, awe, gratitude, 

empathy oriented actions or forgiveness may contribute to the common good by 

enhancing motivation to foster equity, rights and shared social values. 

 

1.3.3. The social aspect. Attributional theories and social valuation theories  

As we have exposed in the previous paragraphs social emotions activation depend 

mainly on how the individual assesses herself (Tangney and Dearing 2002, Tracy and 

Robbins 2004). Attributional theories set emphasis on the intrapersonal nature of social 

emotions as they emerge when events relevant to self-identity goals are attributed to 

internal causes. If this event does not match with our goal, guilt arises. If the event is 

attributed to an uncontrollable or stable aspect of the self, shame emerges. If the event is 

congruent with our goal-oriented action and produces a pleasant feeling, pride is 

elicited. If the result of the positive event is attributed to a stable aspect of ourselves, 

relatively independent of our actions, hubris pride appears. Therefore, for this 



	 32	

attributional view, social emotions depend on how the individual evaluates successes 

and mistakes.  

According to Sznycer et al., (2018), social valuation theories rely on the 

interpersonal, instead of intrapersonal, nature of these emotions, as they favour adaptive 

solutions to social valuation situations such as attend, associate, trade personal welfare, 

or reject others. These adaptive solutions provide the opportunity to promote others by 

a) increasing their valuations of the self (pride); b) devaluate them if needed (shame), 

and c) reassure social balance when one did not put effort or attention on the welfare of 

a valuable other (guilt). 

The interpersonal nature of social emotions relies on human behavior shaped by 

natural selection (Barrett, 2014).  

In a world full of scarcity, predators, diseases, uncertainty, fellow members of 

the group provide assistance to each other to guarantee survival, reproduction and 

thrive. In social groups, attend or forget a partner, choose the right fellows for 

collaboration and reward, selecting reliable mates and value, and help or punish others’ 

reputation are cognitive mechanisms who serve to solve social adaptive problems. 

These social adaptive problems shaped decisions to confer benefits or inflict costs, 

valuating others socially based on the value they provide to the group (Lieberman et al. 

2007). 

The interpersonal nature of social emotions can be estimated when our own 

internal valuation, as in self-esteem, reflects directly the degree others accept and 

include us as  part of a social group. Self-esteem seems to be a construct where social 

status evaluation from others guide our behavior to match group needs and standards 

(Eisenberg et al. 2011). On the other hand, ostracism is felt when, despite our efforts or 

successes, we are excluded and other´s impression of our self is devalued (Williams, 



	 33	

K.D. and Nida, S.A. 2011).    

Social valuation theories focus on other´s assessments of individual attitudes and 

action leading to value or disvalue the self. When others reflect upon ourselves’ 

motivations, ideas and actions, they assess us up or downward, influencing our inner 

states, creating consequently social emotions to cope with this interpersonal nature. 

 

1.4. A social brain 

As exposed in previous paragraphs, consistently with the TCE and interpersonal 

theories, in order for these social emotions to emerge there must be a set of specialized 

brain functions  allowing it. Before considering us as rational actors, we are social ones. 

Brain human evolution is deeply rooted in our social structure and function (Dunbar, 

1998). We are hardwired to connect (and be vulnerable) to others, not being possible to 

easily disentangle an emotional brain from a social one, even in the so-called basic 

emotions, as neuroimaging supports (Adolphs, 2003). Many human adaptations emerge 

from a social need: white sclera in the eyes, face anatomy or face expressions serve to 

social functions. Inside our minds, mentalizing seems to be a default mode in the human 

brain (Raichle, 2001). We constantly infer intentions and solutions to other´s actions. 

The social brain allows us to interact fluently with people. By predicting what others are 

going to do next, we may set up the best decision: the better our predictions are, the 

more the success possibilities. This type of behaviour appears in short term emotional 

states, long term dispositions, desires or beliefs: they all need a mental state based on 

predictions about social interactions (Frith, 2007).  

Several brain regions play a key role in the social functions. Amygdala has a 

main role in recognizing the intensity of emotional expressions. Even prejudice or 

untrustworthy faces activate this region (Winston et al, 2002; Phelps et al, 2000). 



	 34	

Amygdala is involved in social cognition by associating a value to an object, including 

social ones (Ledoux, 2000).  

The temporal poles seem to be related to our ability for mentalizing, as they 

seem to serve as a convergent region for our knowledge of individuals, actions and 

social situations. Thoughts and feelings most likely to occur in a social interaction, 

based in previous situations and the possibility to modify them, assign to the temporal 

poles (Damasio et al 2004).  

A third neural structure of interest is the mirror neurons system. It comprises the 

same brain areas when observing another person emotional experience (or movement) 

and ourselves. It also works for pain and touch: somatosensory regions are active when 

we see someone suffering or receiving pain (Singer et al, 2004). Although the mirror 

neurons system tracks emotional states and intentions from others, it does not inform 

about their attitudes (Mitchell et al 2006). 

The posterior superior temporal sulcus (pSTS) and the temporo parietal junction 

(TPJ) are also involved in the social brain. The pSTS predicts movements’ trajectories, 

allowing to be aware of prediction errors in our estimations. It is important to note that 

in social interactions, eye movements of others inform about their intentions and 

actions. The pSTS functions even for non- biological movements (Kawawaki et al. 

2006). The TPJ is activated when we evoke other persons’ view perspective. This 

ability helps us to infer that other´s people knowledge about the world might be 

different to ours (Saxe and Kanwisher, 2003).  

Medial prefrontal cortex (MPFC) activity is observed when people engage in 

mentalizing situations (Amodio and Frith, 2006), mainly in low demands tasks, such as 

understanding the behavior of characters (Gallagher et al. 2000), observing social 

interactions (Iacoboni et al. 2004), answering questions about attitudes (Mitchell et al 



	 35	

2005) or about current oneself’s feelings (Oschner et al, 2004). It is not surprising the 

extensive role of the MPFC in social interactions, being one of the most expanded areas 

in brain evolution compared to non-human primates (Dunbar and Schultz, 2007). 

The complexity of social living drives cognition and emotion in our brains. We 

infer from eyes, face expression and body movements the personality of others, and we 

imagine other´s perspective to take an immediate action. We store stories from the 

people we know, to behave socially in our next encounter. We represent others in us as 

well as we are in others’ brains to keep social living according to norms, values and 

standards. A social brain handles all these processes. Research through brain techniques 

might add extraordinary value to a better understanding of emotions, specifically of 

social emotions. 

 

1.5. Electrophysiological correlates of emotions 	

Traditionally, several techniques have been used to study emotions in the brain. Since 

1995, different neuroimaging techniques such as PET of fMRI opened the field to study 

dynamic and current processes in the brain. The advantage of neuroimaging with these 

techniques relies in its spatial resolution. The study of emotions with fMRI allows to 

understand networks, areas and regions involved, therefore adding knowledge to the 

structure and nature of emotions (Barrett, 2006). 

Despite its popularity and advantages, the temporal resolution of PET or fMRI is 

very limited. In turn, electroencephalography (EEG) is one of the most valuable 

techniques to study the temporal processes in the brain. This signal reflects the summed 

activity of postsynaptic potentials of pyramidal neurons that fire synchronously while 

processing information (Peterson et al., 1995).  By placing electrodes over the scalp, 

EEG recollects information in real time.  



	 36	

Back in 1875, Richard Caton, a British physiologist, wrote in “The electric 

Currents of the Brain” (Caton, 1875) about the different currents observed in rabbits and 

monkeys when placing electrodes on two different points of the external surface of the 

skull, opening the field to study brain electrical activity. 

The birth of EEG, due to the technological advances, relies in Hans Berger 

(Berger, 1929).  He was also the first to describe the different brain waves, such as 

alpha and the alpha blockage appearing when the subject opened the eyes. He is also 

recognized as a pioneer in describing EEG alterations in brain diseases as epilepsy. 

However, to study cognitive and emotional processes and behaviour along its 

underlying neural substrates, raw EEG cannot be used. Its activity includes random 

oscillations, and sensory, motor and cognitive brain fluctuations lacking the needed 

specificity of a precise cognitive process. 

This limitation is surpassed by the Event Related Potentials (ERP) technique. 

ERP  are very small voltages generated in the brain structures in response to specific 

events or stimuli (Blackwood and Muir, 1990). They are time-locked and phase-locked 

to sensory, motor or cognitive events and, by averaging the EEG activity of several 

single trials associated to an event, signal-to-noise ratio is increased (Luck, 2014). ERP 

waveforms consist of a series of positive and negative voltage deflections, which are 

related to a set of underlying components (Luck et al., 2014). ERP components in 

humans are classified in 2 categories. The early waves (‘sensory’ or ‘exogenous’), 

components peaking roughly within the first 100 milliseconds after stimulus and 

depending mainly on the physical parameters of the stimulus. The late waves 

(cognitive’ or ‘endogenous’), occurring after 100 ms post stimulus, reflect the way the 

subject evaluates the stimulus. The waveforms are described according to latency and 

amplitude (Sur and Sinha, 2009), though they are usually displayed through a 



	 37	

topographic map, a 2D or 3D figure representing the voltages across the electrode 

locations on a specific time (Hari & Puce, 2017). Therefore, each component can be 

defined by its amplitude, latency and topography, relative to a stage of cognitive or 

emotional process. ERP components may have positive or negative voltage at different 

latencies, so they may help to know the underlying cognitive processes related to 

specific events linked to experimental manipulation (Luck, 2014).  

Several ERP components have been thoroughly studied (Sur and Sinha, 2009), 

as described in the following.  

The N100 (also called “vertex potential”) is a negative deflection peaking between 90 

and 200 ms after stimulus onset. It is observed across sensory, motor, cognitive, and 

behavioral tasks, reflecting GABA-mediated	inhibition	processes.  

The P200 or P2 is a positive deflection peaking around 100-250 ms after 

stimulus onset. Current evidence suggests that the P2 component reflects attentional 

processes. 

The N200 is a negative deflection peaking at about 200 msec after presentation 

of the stimulus and can elicited by any discriminable change (Näätänen and Tiitinen, 

1997). 

The P300 dates back to Sutton et al. in 1965 and reflects processes involved in 

stimulus categorization, as it discriminates one event from another. Greater attention 

produces larger P3 waves. It is usually elicited using the oddball paradigm with a 

latency of 250 to 500 ms, and is measured mainly by the parietal lobe electrodes. The 

P300 signal is used as a way to assess cognitive functions in decision making.  

The N400 is a negative wave appearing 300–600 ms post-stimulus (Kutas and 

Hillyard, 1980) and linked to semantic incongruity. The more incongruent a stimulus is, 



	 38	

the larger the N400. Its activity peaks over centro-parietal electrodes. The N400 is 

multimodal, responding to visual, auditory, language and faces stimuli. 

The P600 is a positive wave appearing 300–600 ms post-stimulus (Kutas and 

Hillyard, 1980) mainly used in language processing. Its effect occurs to sentences that 

contain some sort of syntactic violations (Osterhout and Holcomb, 1992). 

As opposed to other techniques such as fMRI, ERP offers a high temporal 

resolution of milliseconds of the underlying cognitive and emotional operations 

occurring within the brain. By scientifically defining the experimental conditions, the 

ERP can discern the time course of the processing involved in each condition. 

In addition to ERP, there are several methods (such as sLORETA, VARETA, S-MAP, 

ST-MAP, Backus-Gilbert, LAURA, SSLOFO. ALF, BESA, MUSIC or FINES) to 

localize electrical activity in different brain areas from EEG or ERP recording (Grech et 

al., 2008). They are based in inverse problem solution, a way to convert measurement 

into information about EEG observed signals. We selected Low-resolution brain 

electromagnetic tomography (LORETA) as EEG-based neuro-imaging technique in our 

experiments. LORETA computes a unique 3D electrical source distribution of 2394 

voxels of 7x7x7 mm of neural activity in brain grey matter.   It selects from all possible 

inverse solutions the smoothest one as neighboring neurons are active synchronously 

during a task. The solution space provided by LORETA is restricted to cortical gray 

matter and hippocampus. Subcortical structures are not accessible by this mean, being 

one of the main limitations of this technique. Several constraints are being exposed by 

authors (Kincses et al. 1999, Michel et al. 1999) along with its validation (Pascual-

Marqui et al. 2002, Phillips et al. 2002, Yao et al. 2001). Despite its limitations, 

LORETA analysis may reinforce ERP temporal results and provide a source 



	 39	

localization estimation of regions associated to brain functionalities, based in 

Brodmann’s areas mapping.   

 
 

1.6. The neuroanatomical correlates of social emotions 

Social emotions hold several shared characteristics despite individual differences. They 

all serve to keep behavior under the constraint of social norms (Beer and Keltner, 2004; 

Tangney and Fisher, 1995). Feelings of embarrasment, guilt or shame are painful 

enough, leading people to avoid experiencing them again. Pride, on the other hand, feels 

so pleasant, that an individual is drawn to repeat the behavior. In order to feel a social 

emotion, individuals need different levels of self-awareness: a) own self, b) other(s) 

judging that self, c) social norms right or wrong for that self-knowledge. These three 

levels point to specific brain structures involved in social emotions.  

a. Self -encoding processes involve the activity of medial prefrontal cortex 

(Fossati et al, 2003, Gilligan and Farah, 2005). Different processes are included in self 

encoding, such as self vs others judgments, own face vs others faces, or positive vs 

negative self-judgments, being all linked to frontal lobes’ activity comparing actual and 

self behavior to others or social behavior. Damage to the medial prefrontal cortex or the 

orbitofrontal cortex show some sort of anosognosia or lack of insight to our own social 

behavior (Beer et al, 2006) and impairment of social behavior (Clark et al, 2008; 

Anderson et al, 1999). 

b. Self of others is a crucial process in social emotions to emerge as one needs 

the awareness of other(s) self to feel they are judging yourself. That is, by other means, 

mentalizing, the capacity to infer other´s people minds and emotions. 



	 40	

Emotional inference of others is associated with amygdala activity, as several studies 

report (Sato et al, 1994, Damasio and Damasio, 1994, Shaw et al. 2004, Stone et al. 

2003) 

Mental inferences about others that enables inferences to be made about goals, beliefs 

or moral issues are associated to medial prefrontal cortex, posterior cingulate/precuneus, 

and temporo-parietal junction (TPJ) activation (Denny et al.,2012; Van Overwalle and 

Baetens, 2009; Lombardo et al 2010). 

Social emotions require that and individual is aware of other´s evaluating self behavior 

and positive or negative emotional reactions to that interaction. 

c. Knowledge of social norms are a crucial part to elicit social emotions. Social 

norms are the rules others and self judge to ascribe or refrain from certain behaviors. 

Social brain networks involve the activation of several areas such as the amygdala, the 

somatosensory cortices, the temporal lobes and the frontal lobes (Frith, 2007; Johnson 

et al. 2005). 

 

1.7. The neurophysiological study of social emotions in the lab  

As we may infer from previous arguments the vast variety of emotions we experience 

opens up the field of scientific study of emotions so much that it is difficult to set its 

boundaries, definitions and define a scope or an appropriate approach. We do not even 

have yet an agreed definition of what an emotion is. Research often lies in either the 

evaluative process, the physiological changes, the facial or bodily expressions, the 

subjective experience, the mental processes, the behavioral dispositions or the brain 

correlates.  

Neurophysiological studies of emotions are usually focused on few categories or 

dimensions (Ekman, 2016; Rotttengerg et. al, 2007, Russell, 2009). Koide-Majima et al. 



	 41	

(2020) selected up to 80 emotion categories to study emotions and broadening classic 

neuroimaging studies which are usually limited to a few emotional representations in 

the brain. 25 representative BOLD clusters of emotions, representing the 65% of the 

total variance, were founded. A  subtantially large across-subject variability in the 

number of dimensions emerging from brain representation (from 18 to 36) was found, 

possibly reflecting the emotional granularity across subjects as proposed by the TCE. 

The emotions founded in this semantic space match a cortical gradient of representation, 

from sensory to abstract information, involving superior temporal area, inferior parietal 

area, precuneus and post central area. Future studies are needed to be performed to 

understand better these cortical representations of emotions. Furthermore, subcortical 

areas are known to play a key role in emotional processing (Damasio et al. 2000; 

Costafreda et al., 2008) and neuroelectrophysiological techniques advances may 

provide, in a future, a way to assess the complex study of social emotions.  

In our research our aim is to study the social emotions of guilt, shame and pride 

under ecological conditions in the laboratory by concurrently measuring ERP and neural 

source analysis (LORETA). These are the most relevant, prominent and well known 

social emotions and share a crucial role in our interactions and behaviors. As we 

uncover in the coming chapters, our approach tries to resemble, as far as possible, a 

social emotion as it emerges in our daily environments. 

 

 

  



	 42	

Chapter 2. Objectives and hypothesis 

 

From previous literature cited in chapter 1, the main objectives and hypothesis of this 

thesis are: 

General objectives 

• Highlight the importance of social contexts in social emotions.  

• Explore the effects of social interactions on emotional processing. 

• Study the temporal and spatial neural correlates of social emotions in ecological 

settings. 

• Replicate and extent previous  findings relative to the neural correlates of social 

emotions. 

• Design ecological paradigms to study social emotions in the lab. 

  

Specific objectives and hypotheses 

The objectives and hypothesis are organized around three studies, as follows: 

• Study One: investigates the characteristics of ERP fluctuations elicited by guilt 

emotions, broadening previous research (Leng et al., 2016) by: a) analyzing 

neuroanatomical sources; b) establishing relations between emotional and personality 

variables, and c) exploring a different cultural sample (other than the Asiatic in Leng et 

al., 2016). Participants performed a dot estimation task together with a partner, in which 

four experimental conditions occurred along 320 trials: partner wrong, self wrong, both 

wrong and both right situations. We hypothesize that interpersonal guilt could be clearly 

differenciated from the other (non guilt conditions) involving a first, fast and early brain 

process followed by a late one linked to self analysis and reappraisal process. We 

estimate there will not be substantial differences between our western sample and the 



	 43	

eastern one (Leng et al., 2016).  Self wrong condition is expected to elicit maximal 

feelings of guilt and the corresponding ERP fluctuations. We expect a frontal early 

negativity and a posterior late positivity, related to different stages in the analysis of the 

social situation. 

 

• Study Two: investigates the neural correlates of shame extending a previous paradigm 

by Zhu et al (2017) by changing feedback outcome in an advice-decision game.  

Participants performed again a dot estimation task though, through different settings. 

Specifically, the participant plays the role of adviser giving place to the capacity to give 

advice and take responsibility. In this manner, shame may emerge as a function of the 

final outcome by the partner. We hypothesize that shame could be disentangle from 

guilt based in this particular setting of the experimental design and again involving a 

first, fast and early brain process in which a social shame situation is valued, followed 

by a late one linked to a self assessment process. An early distinction of shame 

compared to other conditions is expected in the ERP fluctuations, characterizing this 

emotion in this respect. We expect centro-parietal negativities reflecting the integration 

of emotional information in relation to social validation situations. 

 

• Study Three: investigates the neural correlates of shame and pride at the same 

experiment, in a novel (original) setting in which the participant competes with 3 other 

online students and increasing social exposure. We hypothesize that shame and pride 

could be studied live, as opposed social emotions, ranging from the loss to gain in social 

status and again involving an early brain process in which shame or pride are valued, 

followed by a late one linked to a self assessment and self relevance processes. We 

expect early negativities and late positivities to the two emotions, linked to 



	 44	

autobiographical (shame) and hedonic value (pride) areas such as the precuneus/PCC 

(shame) and the mPFC (pride). 

 

  



	 45	

Chapter 3. Study one. Interpersonal guilt. 

 

3.1. Introduction 

The study of interpersonal guilt has recently gained interest due to its social 

significance. Social emotions influence our daily lives and guilt plays a major role in 

bringing the group together and rejoining bonds. Guilt, along with shame, 

embarrassment and pride (Lewis, 2000) is one of the social and self-conscious emotions 

that appears when someone feels responsible for harming or negatively affecting 

another person when a different action might have avoided the situation. As a moral and 

prosocial emotion, it protects social relationships by punishing interpersonal 

wrongdoings, and promoting and rebalancing behavior (Haidt, 2003; Amodio et al., 

2007). Moreover, it also acts as a marker for future partner behaviors in a clear 

prosocial focus as it prevents people from committing wrongful actions (Chang et al., 

2011). Its absence is manifest in psychopaths, who behave abnormally and immorally 

and feel no remorse about those they hurt (Kiehl, 2006). Guilt is based on self-agency 

and, when our actions affect another individual, empathy is required by adopting the 

perspective of the affected individual(s) (Hoffman, 2000). Two main types of guilt have 

been studied: deontological or intrapsychic (Monteith, 1993; Wertheim & Schwartz, 

1983) and altruistic or interpersonal (Baumeister et al., 1994; Tangney & Dearing, 

2002), the latter being the aim of the present study. 

Neuroimaging studies (namely, using functional magnetic resonance imaging, 

fMRI) have found several brain structures consistently involved in interpersonal guilt. 

These areas relate to highly studied networks involving social cognition, such as the 

medial prefrontal cortex –including both the ventromedial and dorsomedial, and the 

anterior cingulate cortex-, the orbitofrontal cortex, temporal poles, temporal-parietal 

junction, precuneus, posterior cingulate, posterior superior temporal sulcus, and insular 



	 46	

cortex (Shin et al., 2000; Takahashi et al., 2004; Kédia et al., 2008; Morey et al., 2012; 

Zahn et al., 2009; Basile et al., 2011; Mclatchie et al., 2016; Bastin et al., 2016). 

The information provided by most of these studies, however, exhibits two main 

limitations. On the one hand, the most extensively used paradigm has been the 

elicitation of feelings of guilt by means of instructing participants to imagine or 

remember personal experiences in which they felt guilty, or by presenting participants 

with hypothetical scenarios of guilt. This approach is far from reminiscent of a situation 

of natural and real moral conflict, guilt being mediated by episodic memory and 

imagination and, hence, arguably lacking validity and intensity. As a result, several of 

the reported brain regions might not be primarily related to the feeling of guilt. 

This limitation was largely overcome in Yu et al. (2014), who used a paradigm 

to elicit interpersonal guilt in the neuroimaging setup, largely used in behavioral studies 

(e.g., Fliessbach et al., 2007). In this paradigm, two participants perform a dot 

estimation task with monetary rewards. In Yu et al. (2014), only one of the participants 

was recorded by the MRI scanner, and there were four experimental conditions: when 

both participants were right in the dot estimation task (BR), the partner of the recorded 

person did not receive a pain stimulus, the opposite being the case in the other 3 

conditions. These were: only the recorded participant was wrong (self-wrong, SW), 

only the partner was wrong (PW), or both were wrong (BW). After the dot estimation, a 

feedback screen indicated the outcome and responsibility of their action. In these 

paradigms, interpersonal guilt is more intense in the SW condition, as a participant’s 

mistake is the direct cause of the partner’s pain (De Hooge et al., 2011; Nelissen, 2009). 

The main finding of Yu et al. (2014) was that the brain area mainly involved in 

interpersonal guilt is the anterior cingulate cortex (aCC), with a secondary implication 

of bilateral anterior insula. 



	 47	

A second limitation of these studies is that the neuroimaging techniques 

employed do not provide information on the timing and dynamics of the processes 

involved, but a still picture of possibly involved brain regions. This shortcoming may be 

overcome by using event-related brain electrical potentials (ERP). Although relatively 

limited in their spatial resolution, ERP provide a resolution in milliseconds. To our 

knowledge, only two studies have addressed interpersonal guilt with ERP, using the dot 

estimation task paradigm described above. In the study by Leng et al. (2016), instead of 

pain stimulation to the partner, the authors used the variant that both participants could 

earn money in the BR condition, losing money instead in the other three situations. 

Their results indicated that the effect of guilt was initiated at about 350 ms and peaked 

round 500-600 ms after the feedback onset, with larger amplitudes for a frontal 

negativity on the high-guilt condition (SW) compared with the low-guilt condition 

(BW). The SW–BW contrast also showed a Late Positive Complex (LPC) 500-800 ms 

after feedback onset with a centroparietal distribution, probably related to sustained 

processes of reanalysis, evaluation and memory encoding (Kissler et al., 2007). The 

LPC was nevertheless not replicated in the second of the two experiments in Leng et al. 

(2016), while frontal negativity appeared to be a robust finding (in their words, “an 

index of interpersonal guilt”), proposed to reflect interactions of self-reflection, 

condemnation, and negative emotion. The study by Zhu et al. (2018) used instead a 

variant in which the economic outcome for the participant was fixed, while that of the 

partner was contingent exclusively on the rightness or wrongness of her own 

performance, with the recorded participant playing a limited role as advisor. With this 

paradigm, only a distinctive ERP pattern for shame could be reported, while guilt was 

hard to discriminate either from happiness or from shame –depending on the time 

interval considered. 



	 48	

Overall, the number of studies on the neural foundations of interpersonal guilt is 

still insufficient, particularly those using ERP. The main aim of the current study is to 

contribute doubly to this research by replicating and further extending the ERP study of 

Leng et al. 2016, which needs replication to settle the issue of the actual robustness of a 

possible electrophysiological index of guilt, given the potential value of such a measure. 

Furthermore, our study will also extend this data in several meaningful manners. 

First, the study of Leng et al. was conducted on a group of Chinese participants, 

while the present study works with a European (Spanish) population. This is 

particularly interesting, given that cultural differences have been proven to exist in the 

experience of emotions, at least when comparing eastern and western societies (e.g., 

Lim et al., 2016), and this is particularly significant for complex social emotions such as 

guilt (Walbott & Scherer, 1995; Anolli & Pascucci, 2005). It could be the case that the 

frontal negativity reported by Leng et al. might show a different latency, amplitude, or 

topography in the present study, or it may even be absent. Cultural differences of the 

samples would be a main underlying reason if replication were not achieved. 

Second, a neural source analysis on frontal negativity will be performed, in case 

it emerges. In addition to the high temporal resolution, ERP can provide an estimation 

of the current distribution from the scalp’s electrical potentials. In the present study, 

Low Resolution Electromagnetic Tomography Analysis (LORETA) will be used, one of 

the most established and widely used reconstruction algorithms (Pascual-Marqui et al., 

2002). It enables an estimation to be made of distributed activity throughout the brain 

by decomposing the overlapping EEG voltage patterns into their underlying sources and 

positioning them within the brain. Leng et al did not perform this kind of assessment. In 

view of the fMRI study by Yu et al. (2014) with an analogous paradigm, it appears 



	 49	

plausible that guilt-related frontal negativity originates in the aCC. A LORETA 

estimation in this regard would strongly support this possibility. 

Third, whether the frontal negativity actually reflects feelings of interpersonal 

guilt and its relationship to emotional variables must be demonstrated. This approach is 

absent in Leng et al. (2016). The authors discarded that frontal negativity was reflecting 

fluctuations related to conflict or error monitoring because it emerged solely in the 

condition in which interpersonal guilt would be more intensive, SW, and was absent in 

the other cases of conflict or self-committed errors, i.e., BW and PW. These last two 

appeared very similar to each other. This is a valid but possibly partial argument with 

regard to the specificity of the processes actually reflected by frontal negativity. Guilt is 

a complex emotion, conceivably involving several brain areas and networks, as the 

neuroimaging studies reviewed above would suggest, with each node arguably 

contributing differently to the eventual emotional feeling. In this study, we wanted to 

better specify the significance of frontal negativity or other ERP fluctuations to 

interpersonal guilt by relating them to a series of variables linked to emotions and social 

cognition. 

A first important variable in this regard is the degree of interpersonal guilt 

actually reported by the participants throughout the experiment. Following procedures 

similar to those used in Leng et al. (2016) or Yu et al. (2014), participants will be asked 

whether they felt guilt after each trial. The number of trials in which a positive response 

is delivered is expected to be highest in the SW condition. The number of responses in 

this condition will be correlated to the amplitude of the frontal negativity or other ERP 

fluctuations found to be specific of the SW condition. Second, feeling bad for personal 

actions that harm others requires empathy (Morey et al, 2012), and for that reason we 

also wanted to see whether frontal negativity (or other ERP fluctuations associated with 



	 50	

guilt) can be related to differences in empathy. This was measured with TECA (a test of 

affective and cognitive empathy adapted to the Spanish population, Fernández-Pinto, et 

al., 2008). The test assesses four different empathy factors; two of them are cognitive 

(perspective taking and emotional understanding) and two emotional (empathic stress 

and empathic joy). Third, increased anxiety or arousal is linked to distressing feelings of 

guilt (Etxebarria & Apodaca, 2008). In this regard, skin conductance response (SCR) is 

widely used for measuring stress, anxiety and emotional reactions (Liu et al, 2014). 

Therefore, we measured SCR throughout the experiment in each participant in order to 

estimate whether SW trials increased arousal as compared to the other conditions, and 

its possible relationship to ERP fluctuations linked to guilt. Furthermore, and along 

these same lines, we used the STAI test (Skapinakis, 2014) to assess state- and trait- 

anxiety levels of our participants. 

Finally, our sample was composed exclusively of female participants. The 

purpose is to homogenize the sample and reduce sex-related variability in 

psychophysiological measures, as in Amodio et al. (2007). Guilt and empathy seem 

stronger in females than in males (Etxebarria et al. 2009; Silfver & Helkama, 2007), 

while they are functionally equivalent for both women and men (Monteith, 1993; 

Monteith et al., 2002). Working with females could increase the power of possible ERP 

fluctuations related to interpersonal guilt while assessing our results, which would also 

be applicable to males. 

 

3.2. Material and methods  

3.2.1. Participants 

Twenty-four pairs of best friends (all undergraduate females) participated in the 

experiment. Only one member of each pair (n=24) was randomly selected to be EEG 



	 51	

recorded and the results presented below will refer exclusively to these selected 

participants. Their ages varied between 18 and 25 years, (mean age = 19.9; SD=1.54). 

All were right handed, ranging from 50 to 100 (M=84,44%) according to the Edinburgh 

Handedness Inventory (Oldfield, 1971). Participants reported no history of psychiatric 

or neurological illnesses and provided written informed consent before the experiment. 

The study was performed in accordance with the Declaration of Helsinki and approved 

by the ethics committee of the Hospital Clínico San Carlos (Madrid). Participants were 

reimbursed for taking part in the experiment. 

 

3.2.2. Procedure 

Before the ERP experiment, the participating couple individually completed two 

different questionnaires:  STAI (Spielberger et al., 1983) and TECA (Fernández-Pinto, 

et al., 2008). Thereafter, one of the participants was invited to enter the EEG shielded 

chamber room while her partner sat in an adjacent room. Both received the same 

instructions and completed the task on a computer connected to two LCD screens. 

Stimuli were presented on a screen placed 65 cm away from their eyes.  

Each trial (Fig. 1) began with a fixation cross appearing at the center of the 

screen for 500 ms, followed by a black screen with twenty white dots (dot size = 3x3 

pixels), randomly displayed, in a 300x300 pixels frame around the center of the monitor 

(x=0, y=0) to minimize ocular movements. Participants were instructed to estimate the 

number of dots on the screen. The dot stimuli were displayed for up to 1500 ms. After 

the dots disappeared, a number (19, 20 or 21, randomly chosen) appeared on the screen 

for 3000 ms. Meanwhile, participants had to press one of two buttons as soon as 

possible using the index or middle finger, respectively (counterbalanced across sessions 

and participants), to indicate whether the number of dots estimated was larger or smaller 



	 52	

than the number shown. The response hand was also counterbalanced across 

participants, while the other hand was used to measure the SCR. 

 

Figure 3.1. Experimental procedure. A fixed cross appears for 500 ms at the center of 

the screen before the onset of random dots for 1500 ms, where participants estimate the 

number. After a blank screen, 19, 20 or 21 appears for 3 s while participants have to 

choose whether the actual number was greater or lesser. Feedback 1 screen appears for 

1.5 s assessing money loss or reward. After another blank screen, Feedback 2 with 

portraits of the participants appears for 2 s with a tick or a cross for individual 

performance. A “do you feel guilty?” question (yes/no) ends a trial. 

	
After the presentation of a blank screen for 800, 1000 or 1200 ms depending on 

the trial (randomly chosen to avoid habituation), a number was displayed on the screen 

to indicate how much money the participants earned (or lost) for their performance 

(feedback 1). This feedback 1 screen was displayed for 1500 ms and followed by a 

blank screen. Then the feedback of the performance of each player was presented for 

2000 ms with either a green tick or a red cross below each participant’s picture, 

indicating a right or wrong outcome (feedback 2). After completing a trial, a yes-no 



	 53	

question appeared on the screen for 2000 ms, and participants were asked to indicate 

whether they felt guilty upon seeing the outcome of their cooperation performance. The 

position of the response alternatives (‘yes’, ‘no’) at the left/right of the screen was 

counterbalanced across participants. Importantly, participants received the instruction 

that they could leave the question unanswered if they were uncertain about their feelings 

of guilt. Accordingly, this is not a forced choice task. We only asked our participants 

whether they actually felt guilt, following the procedure by Leng et al. (2016). Other 

studies (e.g., Zhu et al., 2017) have included a choice between alternative emotions that 

could play some role in the corresponding condition. In our case, shame might also be 

present in the SW condition because of bad performance of the participant, and 

therefore shame and guilt would be ideal choice alternatives. However, when we 

performed a pre-study (with n=15) exploring this procedure, most of the trials were left 

unanswered. Shame and guilt seem highly overlapping and difficult to unravel at the 

subjective level (Giner-Sorolla et al., 2011). Although it is admissible that shame is 

present to a similar degree in both SW and BW conditions, both conditions would 

noticeably differ in the degree of guilt experienced. Asking only for guilt therefore 

avoided participants’ conflict and indecision (i.e., non-responded trials), while the 

ratings relative to feelings of guilt in each condition (cf. the Results section) were 

largely consistent with the expected outcomes (see also below). 

All performance feedbacks were predetermined by the experimenter as follows: 

there were a total of 320 trials consisting of 80 PW (partner wrong), 80 SW (self 

wrong), 80 BW (both wrong) and 80 BR (both right) trials, so earning trials were one 

out of every four. The participants were unaware of this manipulation. Indeed, the 

number of dots remained constant at 20 on every trial although their spatial distribution 

varied randomly. Participants were told to perform a cooperative task with their partner; 



	 54	

receiving additional payment only if both performed successfully. Both participants lose 

€0.65 when one or both responded incorrectly. Only when both participants answered 

correctly did both earn €0.65 each. The last situation occurred in only ¼ of the trials, so 

during the complete task they would inevitably lose money. Accordingly, participants 

were told that they started with an initial payment of €30 for participation, and that their 

outcome would depend on their performance (i.e. 65 cents would be discounted from 

this amount in a wrong trial and added in a correct one). As the task was highly 

demanding, we assumed that they could not be mentally updating on the exact amount 

of money lost while doing it. They probably felt that they were losing some money, but 

not exactly how much. At the end of the study, participants were told that considering 

their incorrect and correct responses, together with compensation for participating in the 

study, they would receive a final total amount of 20 EUR, but they were never informed 

of the exact amount of money that they had lost. Overall, the whole experiment lasted 

about 55 min. 

We wanted to explore whether the difference between SW and BW conditions 

involves other emotions apart from guilt by conducting a behavioral study with a 

sample of 18 participants (other than those in the ERP main study). Their ages also 

varied between 18 and 25 years (mean age = 22.5; SD=2.21), and all were right handed, 

ranging from 50 to 100 (M=89,47%) according to the Edinburgh Handedness Inventory 

(Oldfield, 1971). They performed 60 trials of the same task as in the ERP study but 

rated their feelings of happiness, guilt, shame, frustration and pride in a 0-7 Likert scale 

after each trial. Guilt, shame and frustration were considered possible candidates to 

differ between SW and BW conditions, while happiness and pride were used as controls 

as well as possibly involved in PW and BR conditions. On the other hand, Yu et al. 

(2014) already proved that the conditions of interest do not differ in the negative 



	 55	

feelings of fear or anger. The participants were told that in order to avoid confusing 

guilt and shame (see above), guilt was defined as the unpleasant feeling subsequent to 

one’s own action harming others, while shame refers to the unpleasant feeling due to a 

negative evaluation of oneself by others. The main results appear in Table 1. An 

ANOVA revealed that the main effects of Emotion [F(4,68) = 14.38, p<.001], 

Condition [F(3,51) = 8.94, p<.001]  and interaction “Emotion x Condition” [F(12,204) 

= 37.6, p<.001] were significant. The results exhibited the following pattern (all ps 

Bonferroni corrected). Frustration appeared the dominant feeling in the two conditions 

of interest (BW and SW), with a small but significant increase from BW to SW 

[T(17)=3.7, p=.007]. In this comparison, there was also a significant increase of the 

feeling of guilt [T(17)=7.4, p<.001], this increment being of larger magnitude than that 

of frustration (1.1 vs. 0.5 points, respectively). In turn, shame displayed lower values 

than guilt or frustration in either condition, and although it appeared to increase from 

BW to SW, this was not significant [T(17)=3, p=.06]. Importantly, the difference 

between reported frustration and guilt in the SW condition was not significant 

[T(17)=1.6, p=.8], which suggests that both were equally dominant in this condition.  

 Happiness Guilt Shame Frustration Pride 

BR 4.6 - 1.6 0.3 - 0.59 0.2 - 0.3 1.3 - 1.4 3.8 - 2 

PW 2.4 - 1.9 0.5 - 0.7 0.3 - 0.5 2.6 - 1.8 2.1 - 1.9 



	 56	

 

Table 1. Mean and standard deviation values of reported feelings for each condition in 

the behavioral study 

 

3.2.3. Electrophysiological recording and analysis 

EEG was recorded from 59 scalp electrodes mounted on an electrode cap (EasyCap), 

following the 10/20 International System. Bipolar vertical and horizontal EOGs were 

recorded to monitor blinks and horizontal eye movements. During recording, all scalp 

electrodes as well as one electrode at the left mastoid, were originally referenced to one 

electrode at the right mastoid; offline, they were re-referenced to the average of the right 

and left mastoids. The impedance of all electrodes was kept below 5 kΩ. EEG data were 

analyzed with Brain Vision Analyzer® software. Raw data were filtered online with a 

band-pass from 0.01 to 100 Hz and sampled at 250 Hz; they were digitally filtered 

offline from 0.1 to 30 Hz. 

The continuous EEG was segmented into 1200-ms epochs, starting 200 ms 

before the feedback 2 screen onset. Eye movements were corrected using Independent 

Component Analysis (ICA, Makeig et al., 2000) as implemented in BrainVision 

Analyzer®. Remaining artefacts were further removed by a semi-automatic rejection 

procedure, eliminating epochs exceeding ± 100 µV in any of the channels. The mean 

rejection rate of epochs was 4.8%, and there were no significant differences between 

conditions [F(3,69) = 1.98; p = 0.142; ɳp2 = 0.079]. Mean rejected epochs (and SDs) 

for conditions were: BR (Mean = 3.69; SD = 4.768), PW (Mean = 5.29; SD = 6.931), 

SW (Mean = 5.50; SD = 8.119) and BW (Mean = 4.75; SD = 6.732). 

SW 0.4 - 0.5 3.7 - 1.8 2.2 - 1.72 4.2 - 1.9 0.2 - 0.5 

BW 0.4 - 0.6 2.6 - 1.7 1.6 - 1.5 3.7 - 1.9 0.2 - 0.6 



	 57	

 

Figure 3.2. Location of the electrodes covered by the two main regions of interest 

(ROIs); a frontal ROI (ROI1) and a parieto-occipital one (ROI2). 

  

Statistical analyses were computed with IBM SPSS Statistics (Version 22). An 

overall repeated measures ANOVA was first performed including two factors: 

Electrode (59 levels) and Condition (4 levels: BR, PW, SW, BW). Amplitude was 

measured as the mean amplitude within a particular time interval (from 200 to 1000 ms 

in 100ms-wide windows). To avoid a loss of statistical power, based on ERPs and 

components found, second ANOVAs were performed in two regions of interest (ROIs) 

(Fig. 2): One frontal ROI that included the electrodes AF3, AF4, F1, Fz, F2, Fc1, Fcz 

and Fc2 (ROI1), and one parieto-occipital ROI, that included P1, Pz, P2, PO3, PO4, O1, 

Oz and O2 (ROI2). For the aforementioned analyses, specific time windows (350-450 

and 750-950 ms) were selected as based upon visual inspection of the main ERP 

components. The Geisser–Greenhouse correction for non-sphericity was applied when 



	 58	

necessary (Greenhouse and Geisser, 1959). Post-hoc tests were corrected with the 

Bonferroni procedure. 

 

3.2.4. SCR recording and analyses 

The skin conductance response (SCR) was monitored throughout the experiment in each 

participant. An 8-channel Multibox polygraph (Brain Products, Munich) was connected 

to the index and middle fingers of the non-responding hand in the experimental task. 

SCR results were analyzed with Ledalab software (Benedek & Kaernbach, 2010a). 

Downsampling was applied to the original data to 125 Hz, and pre-processed by 

adaptive smoothing and filter selection. Following these procedures, a composition 

decomposition analysis (CDA) was performed to separate from the raw SCR both the 

tonic and the phasic signals (Benedek & Kaernbach, 2010b). Phasic data were 

considered with a minimum SCR amplitude of 0.01 µS; the examining window covered 

from 1 to 5 s after the onset of feedback 2. Individual measures of SCR in µS were 

separately averaged for each participant. Six out of 24 participants were discarded due 

to artefacts in SCR signals. Phasic mean activity data were standardized within subjects 

to facilitate the comparison of SCR means across the conditions: SW, BW, PW, BR.  

 

3.2.5. Source generator analyses 

LORETA software, an algorithm based on an inverse problem solution that offers brain-

activated areas from EEG neural activity, was used to measure the sources of the ERP 

components in selected time windows for the difference between SW and BW 

conditions. This difference presumably best reflecting the isolation of the maximum 

values of feelings of interpersonal guilt (Leng et al., 2016), as it is the result of 

subtracting two degrees of relatively comparable emotions (see performance results) 



	 59	

without the contamination of other confounding emotional responses. 

 

3.3. Results 

3.3.1. Performance 

Throughout the experiment the rating scores for the feeling of guilt (yes/no question in 

the screen after feedback 2) for participants in the EEG chamber under the different 

conditions were calculated as percentage scores by dividing the total number of “yes” 

responses by the overall sum of trials (80) in each condition. The mean and SD for the 

individual ratings obtained were: SW (M=63.4%, SD=0.3), BW (M=33.6%, SD=0.3), 

BR (M=5.4%, SD=0.06) and PW (M=6.8%, SD=0.07). As expected, rating scores 

revealed the highest feelings of interpersonal guilt in the SW condition, a minor 

presence of this feeling was found BW, and for BR and PW it was negligible. ANOVA 

yielded significant differences between the four conditions [F(3,69) = 41.174, p<0.001]. 

Post hoc analyses showed significant differences between all conditions (ps<0.001) 

with the exception of BR vs PW (p=0.054). 

3.3.2. SCR 

Feedback 2 did not generate significant differences in the phasic activity between 

conditions [F(3,51) = 0.137, p=0.86; ɳp2 = 0.008]. 

3.3.3 ERPs and LORETA analyses 

A visual inspection of ERP overall averages (Figure 3) suggested possible differences 

between the four conditions starting at around 300 ms and up to the end of the epoch. 

BR shows a clear difference from the other three conditions at all the electrodes, as is 

the case of SW, which was more negative than BW and PW in frontal sites. In the main 

conditions of interest, SW and BW required further detailed comparisons (Figures 4 and 

5), showing a clear negative difference wave between about 300 and 500 ms after the 



	 60	

onset of accuracy feedback 2, as well as minor positivity in parieto-occipital regions 

from about 700 ms up to the end of the epoch.  

 

Figure 3.3. ERP grand means for BW (both wrong), SW (self wrong) BR (both right), 

and PW (partner wrong) conditions at selected electrodes. 

 

An Electrode (59) by Condition (BR, PW, SW, BW) overall ANOVA showed 

significant effects of Condition between 200 and 1000 ms with all Fs (3,69) > 2.36 and 

all ps<0.05, endorsing subsequent ANOVAs at selected ROIs and time windows. An 

ANOVA at ROI1 for the 350-450 ms window revealed significant effects of Condition 

[F(3,69) = 17.373; p<0.001; ɳp2 = 0.430] and “Electrode x Condition” [F(21,483) = 

6.808; p<0.001;  ɳp2 = 0.228]. Post hoc analyses exhibited significant differences 

between all conditions BR vs. PW, BR vs. SW, BR vs. BW, PW vs. SW and SW vs. 

BW (all ps<0.05), with the exception of PW vs. BW (p=0.1). 

An ANOVA at ROI2 within the 750-950 ms window showed significant effects 

of Condition [F(3,69) = 16.86; p<0.001; ɳp2 =0.423] and “Electrode x Condition” [F 

(21,483) = 7.04; p<0.001; ɳp2 = 0.235]. Post hoc analyses in ROI2, however, revealed 



	 61	

that these effects were the consequence of the differences between the BR condition and 

the other conditions (all ps<0.001), while the latter did not differ significantly (ps>0.1).  

 

Figure 3.4. Guilt effect as the difference wave between SW (self wrong) and BW (both 

wrong) in electrode FZ, and a map representing the 350 – 450 ms interval. 

 

Figure 3.5: Guilt effect as the difference wave between SW (self wrong) and BW (both 

wrong) in electrode Pz, and a map representing the 750 – 950 ms interval (LPC).  



	 62	

In order to estimate the origin of frontal negativity (FN) related to interpersonal guilt, a 

LORETA analysis was performed for the SW difference minus BW conditions around a 

peak at about 400 ms (namely, 380-416 ms window) to increase the specificity of the 

solution. This consisted of an involvement of frontal regions with the highest value 

(0.95 mA/m2) at MNI coordinates (X=-10, y=45, z=50), corresponding to the dorsal 

medial prefrontal cortex (mPFC) (Fig. 6). A second minor contribution by the superior 

medial and lateral parietal cortex could also be mentioned, though this appeared to be an 

overlap of later, non-significant effects. 

 

Figure 3.6. Neural generators (LORETA analysis) of frontal negativity, performed for 

the difference SW minus BW (self wrong vs both wrong) conditions, around its peak of 

about 400 ms (380-416 ms window) to increase the specificity of the solution. 

 

 

3.3.4. Correlations between frontal negativity and variables linked to emotions and 

social cognition  

Remarkably, the feeling of guilt reported during the experimental sessions and the 

amplitude of frontal negativity (FN) did not significantly correlate to each other, neither 

State-and trait-anxiety (STAI) scores with FN or reported guilt feelings. Reported guilt 

significantly correlated with empathic overall scores in TECA (Spearman’s rho = 0.5, 

p=.012). Of main interest, the amplitude of the FN correlated highly and significantly 

with the TECA subscale Emotional understanding, related to cognitive empathy 

(Spearman’s rho = -0.7, p<.001 after Bonferroni correction). 



	 63	

 

 

3.4. Discussion 

Our study aimed to explore the behavioral, electrophysiological and anatomical 

correlates of interpersonal guilt, by concurrently measuring ERP, neural source analysis 

(LORETA), SCR, state- and trait-anxiety (STAI), and empathy (TECA). Our main aim 

was to replicate and expand the study conducted by Leng et al. (2016) on a Chinese 

sample, using a group of western participants. The goal was to further define the 

processes plausibly reflected by the main ERP modulations in an interpersonal guilt 

paradigm based on a dot estimation task game, with economic incentives, that 

presumably elicits interpersonal guilt.  

The ERP fluctuations obtained in the present study largely replicate those of 

Leng et al. The components found here and in that study, as well as their latency and 

topography, are almost identical, with the only difference being relatively larger 

amplitudes in the present study –probably due to differences in the technical setup. 

These fluctuations consisted of a frontal long-lasting negativity (FN) in the SW 

condition, starting at about 300 ms and peaking around 400 ms, and a Late Positive 

Complex (LPC) with parieto-occipital distribution, from 500 ms onwards. The latter did 

not hold after statistical analyses, also largely paralleling the results in Leng et al. 

(2016), while the FN resulted in a robust finding. Of even greater interest, the FN 

appeared in our sample of Western (European) participants. This implies that at least the 

processes reflected by the FN and possibly connected with guilt appear to be universal 

and common across cultures under similar circumstances, despite reported cultural 

dissimilarities in experiencing complex social emotions (e.g. Walbott & Scherer, 1995; 

Anolli & Pascucci, 2005). 



	 64	

Leng et al. (2016) claimed that the FN was related to interpersonal guilt, as it 

emerged in the SW condition, which yielded the noticeably highest levels of self-

reported guilt, while BW and PW did not differ from each other. This pattern is 

replicated here and the argument seems consistent. The rating of the feeling of guilt 

induced in participants in the SW (self wrong, partner right) condition was noticeably 

and significantly higher than that in the BW (both self and partner wrong) condition, 

while this feeling was essentially non-existent in the other conditions. This suggest that 

SW and BW conditions involve different levels of interpersonal guilt, and that the 

comparison SW minus BW might enable this variable to be isolated experimentally. 

However, to our surprise, we could not find a significant correlation between the 

amplitude of the FN and the reported feelings of guilt in the SW condition. There are 

two possibilities to explain this result. One is that the difference between SW and BW 

conditions yielding the FN involves other emotions apart from guilt. Indeed, shame 

might also be present because of the poor performance of the participant. Overall, the 

task appeared frustrating, and this feeling might be present in all conditions and even 

increase in the SW condition. The second possibility is that the FN is not specifically 

reflecting the feeling of guilt, but intermediate processes contributing to its final 

achievement.  

We explored the first of these possibilities in deep and investigated the extent to 

which other emotions might account for the differences between SW and BW by 

conducting a behavioral study with a different sample of participants, as detailed in the 

Procedure subsection of the Materials and Methods section.  

Overall, it appeared confirmed that other emotions can be present in the 

conditions of interest. Importantly, however, the results of this behavioral study also 

suggested that the differences between SW and BW are predominantly contributed by 



	 65	

differences in the degree of guilt, even if smaller differences in frustration are also 

present. In sum, the paradigm still appears an appropriate experimental approach to 

study guilt, though with some limitations that must be pondered. This also applies to the 

studies by Leng et al. (2017) and Yu et al. (2014) employing it. 

Accordingly, guilt seems importantly contributing to the differences between 

SW and BW, but the FN did not correlate with the reported feelings of guilt. This 

suggests that other processes, unobserved with the present paradigm, would also be 

required to finally yield this emotion, the FN reflecting only part of the operations 

necessary for achieving it. Overall, guilt seems a complex emotion, and it would be 

surprising if it were reflected by a single ERP modulation. The involvement of a 

number of areas in fMRI studies of guilt, as reviewed in the introduction, further 

reinforces this assertion. It remains to be elucidated what exactly the FN is reflecting in 

relation to guilt. The variables measured in the present study might provide clues in this 

respect.  

The FN does not seem to be related to anxiety. Although the feeling of guilt is 

linked to personal distress (Etxebarria, & Apodaca, 2008), this did not seem to differ 

across conditions, as reflected in SCR. Similarly, overall levels of state- or trait- anxiety 

as measured with STAI did not correlate with the FN. Accordingly, the FN does not 

appear related to anxiety or arousal.  

The most revealing results corresponded to scores in the measurements of 

empathy (TECA). The amplitude of the FN highly and significantly correlated with 

emotional understanding, a cognitive factor of empathy. Also of interest, the degree of 

reported guilt in the SW condition correlated with overall scores in TECA, which 

conveys an indirect link between the FN and self-reported guilt in our study, apparently 

mediated through empathy. Previous literature suggests that empathy is a core element 



	 66	

for guilt to emerge (Baumeisteret al., 1994; Hoffman, 2000; Eisenberg, 2000; Morey et 

al, 2012). In view of our results, it can be suggested that the FN relates to cognitively 

understanding that the outcome of one’s own action has caused distress to the partner, 

since people with higher scores in this factor exhibited higher FN values. Importantly, it 

is not the mere comprehension of the other’s distress that would be reflected in the FN, 

since it did not emerge in other conditions that were possibly also upsetting for the 

partner (BW and, particularly, PW). It would rather reflect an empathic component 

specifically related to situations of self-caused harm to others, necessary for ultimately 

achieving feelings of interpersonal guilt. The result also reinforces the idea that the FN 

seems primarily related to processes involved in interpersonal guilt, disregarding the 

possible contribution of frustration to this fluctuation, even if frustration differed 

somehow between SW and BW conditions.  

The processes reflected in the FN start as early as about 300 ms after the 

appearance of the information that permits participants to understand their own and 

other people’s achievements in a joint task, which seems to originate in frontal brain 

regions. In this respect, the LORETA analysis showed that dorsal medial prefrontal 

(mPFC) areas appear critical in the generation of the FN. This is consistent with 

findings that relate this region with social cognition networks (e.g., Kédia et al., 2008; 

Morey et al., 2012), and, indeed, it emerges as one of the main areas underlying the 

feelings of guilt in a recent meta-analysis (Bastin et al., 2016). What is more important, 

dorsal mPFC is also a core area underlying empathy (Seitz et al., 2006). Overall, the 

evidence seems consistent with the processes suggested here, underlying the FN and 

their contribution to the feelings of guilt through empathic assessment. However, our 

result is not in line with the fMRI study by Yu et al (2014) employing a relatively 

similar paradigm to elicit guilt in the experimental contexts, as these authors reported a 



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main implication of the aCC while our results were distributed more dorsally. Although 

this discrepancy might relate to the inherent risk of inaccuracies in the solutions for 

ERP generators, it appears to us that it is rather the result of important dissimilarities in 

the experimental procedures. These include the fact that the partner would receive 

physical pain stimulation in the wrong conditions. The aCC has been closely related 

with feelings of physical pain, both one’s own and observed in others (Singer et al., 

2004), as is the case of the anterior insula, a secondary finding in the Yu et al. (2014) 

study. 

 

3.5. Conclusion 

To conclude, we have been able to validate a frontal ERP modulation that seems 

consistent across cultures and that plausibly reflects empathic processes necessary for a 

final outcome of feelings of interpersonal guilt, though not the feelings of guilt 

themselves. Those processes, presumably occurring in dorsal mPFC areas, start around 

300 ms after performance feedback is presented, and peak around 400 ms. The present 

data contribute to a better understanding of the dynamics of the neural mechanisms 

underlying such a complex social emotion as guilt.  

 

 

 

  



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Chapter 4. Study Two. Shame 

 

4.1. Introduction 
 

As previously cited in the introduction chapter emotions have been commonly 

classified into basic and social (Tangney & Fisher, 1995; Lewis, M. 2000). Basic 

emotions are the first to develop, are heritable and seem characterized by universal 

facial expressions, although this assumption is lately being discussed (Barret et al, 2011; 

Crivelli et al 2016; Fernandez-Dols & Ruiz-Belda, 1995). On the other hand, most 

social emotions require superior cognitive abilities that involve the self (Lewis, 2000; 

Tangney & Dearing, 2002). These imply self-evaluation, self-consciousness and the 

consideration about how the self is being evaluated by the others as we have broadly 

exposed in Chapter 1. Among them, guilt and shame are considered as highly relevant 

for human sociality, because of their relationship with moral rules, and their tendency to 

ensure the adherence to social norms through their internalization. The present study 

investigates on shame. 

Shame requires self-evaluation and self-consciousness and usually appears in 

social evaluative situations as feelings of incompetence, when failing a task, or when we 

have as a consequence of an inappropriate social behavior (Menesini & Camodeca, 

2008). Shame implies a damaged self and the devaluation of self-esteem, and could as 

well derive in aggressive behaviors such as anger, hostility or resentment (Tagney, 

Wagner, Hill-Barlow, Marschall & Gramzow, 1996), as responses to protect self-esteem 

(Thomaes, Stegge, Olthof, Bushman & Nezlek, 2011) and seems to emerge in order to 

avoid the loss of the individual or group status (Tracy & Robins, 2007).  

Most of the functional neuroimaging studies have found that shame activates 

neural networks related with self-reflection, inner thoughts and mentalization (e.g.,  



	 69	

Basile et al., 2011; Gilead et al., 2016; Mitchell et al., 2006; Takahashi et al., 2004; 

Whittle et al., 2016). Indeed, two of the most consistent findings involve the 

dorsomedial prefrontal cortex (dmPFC) as well as the precuneus/posterior cingulate 

cortex (PCC) and the temporal poles, core areas of the so-called ‘default mode network’ 

(DMN) implicated in decoding the mental states of social agents (Andrews-Hanna, 

2012). As a negative social emotion, it causes negative feelings and psychological pain 

(Tangney et al., 1996). Accordingly, the feeling of shame implies greater activation of 

the anterior insula (AI) and amygdala (Basile et al., 2011, Roth et al, 2014).  

Although in social situations shame and guilt feelings usually overlap (Giner-

Sorolla et al., 2011), despite several similarities, differences between shame and guilt in 

terms of involved brain regions seem neither conspicuous nor consistent, this being the 

case even when these social emotions are contrasted with some basic emotions, such as 

sadness or anger (Bastin et al., 2016).  

The few studies performed so far have mostly employed paradigms in which 

these emotions are simply evoked by recalling or imagining situations. This might 

convey the primary involvement of circuits related to memory or imagination, rather 

than shame. This limitation has been recently surpassed by Sánchez-García et al. 

(2019), as we exposed in Study 1. In Zhu et al. (2017, 2019) they induced both guilt and 

shame in the same study, in the frame of an interpersonal context, by means of an 

economic game. In brief, in this paradigm shows some differences from study 1. The 

recorded participant advises a confederate (decider) on the number of dots that had just 

appeared on a screen; the advisor could see the dots for the double the time than the 

decider, the latter finally making a decision on the number of dots, earning money 

whenever the outcome was right. There were four possibilities, from the point of view 

of the feelings of the recorded participant: a) the decider follows the advice and both are 



	 70	

wrong (guilt+shame); b) the advice is wrong, the decider ignores the advice yielding a 

right outcome (shame); c) the decider follows the advice and both are right (joy); d) the 

advice is right, the decider ignores the advice yielding a wrong outcome (uncertainty). 

However, in spite of the good ecological validity of this approach, the results of this 

study reproduced again the outstanding similarities between shame and guilt using 

functional neuroimaging although the authors could nevertheless disentangle both social 

emotions within the anterior cingulate and dmPFC when a multivariate pattern analysis 

was applied (Zhu et al., 2019). 

It is possible that a more noticeable pattern of shame can emerge by studying the 

neural temporal dynamics of these emotions by means of Event-Related brain Potentials 

(ERP). ERPs permit the study of cognitive processes as these unfold over time, with a 

millisecond temporal resolution. This approach was used by Zhu et al. (2017) in order 

to disentangle shame and guilt, also using the interpersonal context of an economic 

game as described above. The authors were able to distinguish shame and guilt as soon 

as about 200 ms after the presentation of the decider’s outcome to the adviser, as a 

significant amplitude increase of the P2 ERP component occurred in the shame 

condition. As the P2 relates to early selective attention (it is actually originated in visual 

associative areas; see Mangun & Hillyard, 1991), the finding was interpreted as an 

index of the self-relevance of the information involved in the shame condition.  

The only studies in which both emotions have been jointly investigated and in 

the frame of interpersonal context are those by Zhu et al. (2017, 2019). The present 

study aims to contribute to this poorly explored field by studying shame in an 

interpersonal context by means of ERP, with a number of relevant novelties relative to 

Zhu et al. (2017, 2019). 



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In our study, a main change with regard to Zhu et al. (2017, 2019) relates to the 

stimuli presentation procedures. In Zhu et al., the adviser was informed about her failed 

advice preceding (by 1s in Zhu et al. 2017; 2s in Zhu et al., 2019) the critical point at 

which she was informed on the choice of the decider. In our view, this procedure might 

notably minimize the strength of shame feelings at the critical point at which it was 

registered in the ERP, that is, the outcome of the decision. As a result of own wrong 

outcome, shame would start earlier and, then, be already present along the baseline used 

to prove its effects. In the present study, based on previous research on guilt approached 

with ERP in an interpersonal context (Leng et al., 2016; Sánchez-García et al., 2019 / 

Study 1), the outcome of both adviser and decider were shown simultaneously. Another 

outstanding difference between the present and Zhu et al. studies is that we analyze the 

activity linked to the ‘uncertainty’ condition, in which the outcome of the adviser is 

right while that of the decider is wrong. Indeed, it might convey in some degree the 

feeling of emotions such as, e.g., pride or others- and then could serve to further 

contrast shame and guilt with emotional conditions other than joy (see Study 3). This 

could be done by increasing the total number of trials in the session, yielding enough 

linked to this condition –which was set to be less than other conditions to enhance 

participant’s feelings of shame, as in Zhu et al. (2017, 2019). 

In the present study, we have also used a different strategy to explore ERP fluctuations 

as used in Zhu et al. (2017). In the latter, the authors focused on a-priori defined ERP 

fluctuations linked to overall cognitive functions such as attention, cognitive control or 

working memory (i.e., P2, N2 and P3 components). Here we will not make hypothesis 

on specific ERP components, in line with previous studies (e.g., Yu et al., 2014; Leng et 

al., 2016, Sánchez-García et al., 2019 / Study 1).  We directly contrasted the ERP 

fluctuations to the conditions of interest without a-priori restrictions, in search of 



	 72	

possible effects specifically linked to the feelings of interest. Further, the so-obtained 

effects will be analyzed with Low Resolution Electromagnetic Tomography Analysis 

(LORETA; Pascual-Marqui et al., 2002). This algorithm decomposes the overlapping 

EEG voltage patterns into their underlying sources, localizing them within the brain. 

This way, a direct contrast of the results with previous neuroimaging studies is feasible. 

With the purpose of better characterizing the functional significance of ERP 

fluctuations related to the social emotions conditions, we explored their possible 

relationship with a number of variables of potential interest that were measured in our 

participants. First, trait levels of guilt and shame were assessed with the Test of Self 

Conscious Affect (TOSCA; Tangney et al., 1996). Finally, we also recorded skin 

conductance response (SCR) along the experimental session as a measure of distress 

feelings, anxiety and emotional reactions (Liu et al, 2016) conceivably caused by shame 

and guilt. 

The present study has two peculiarities that should be highlighted. First, after each trial 

participants only had to report whether they felt shame. Several reasons justify this 

procedure. Zhu et al. (2017) asked their participants to choose between guilt and shame 

after the trials in which either of these could be felt (the guilt and shame conditions), 

letting the participants to choose not to respond if they were uncertain about the 

currently felt emotion. However, when we performed a pre-study with this procedure, 

most of the trials were left unresponded. This was at variance with the results of Zhu et 

al. (2017), who nevertheless found a high number of equivocal responses (i.e., guilt 

responses in trials in which shame was expected, and vice versa). In spite of their 

conceptual differences, shame and guilt seem highly overlapping and difficult to 

unravel at the subjective level consistent with the neuroimaging literature, as discussed 

above. We also think that trials in which guilt is expected in the present paradigm (both 



	 73	

adviser and decider are wrong) may also contain some degree of shame, even if guilt is 

the dominant feeling (as supported in Zhu et al., 2017, 2019), since the adviser is wrong 

despite having double the time than the decider to inspect the dots. Asking only for 

shame is intended to avoid participants’ conflict and indecision (i.e., non-responded 

trials) while boosting participants’ attention to this emotion. This in turn conveys the 

advantage of possibly enhancing the differences between shame and guilt in the ERP 

fluctuations, favoring the former, which on the other hand has been less studied than 

guilt with this technique.  

The second particularity of the present study is that our sample comprises only 

female western participants, so the sample is more homogeneous while reducing sex-

related variability in the psychophysiological and neurophysiological measures, as in 

Amodio et al. (2007) or Sanchez–García et al. (2019 / Study 1). As an outcome, the 

power of the ERP fluctuations related to shame may be enhanced and the results could 

be extendable to males. 

 

4.2. Material and methods  

4.2.1. Participants 

Twenty-six female students (all undergraduate) participated in the experiment. Their 

age varied between 18 and 28 years, (mean age =20.5; SD=2.33). All but one were right 

handed, with scores ranging from 50 to 100 (M=76.91%) according to the Edinburgh 

Handedness Inventory (Oldfield, 1971). Participants reported no history of psychiatric 

or neurological illness and provided written informed consent before the experiment. 

The study was performed in accordance with the Declaration of Helsinki and approved 

by the ethics committee of the Hospital Clínico San Carlos. Participants received course 

credits for taking part in the experiment. 



	 74	

4.2.2. Procedure 

Before the ERP experiment, the participating student met another student in the lab 

(actually, a confederate chosen by experimenters) and both completed two 

questionnaires: TECA (Lopez-Pérez et al., 2008) and TOSCA (Tangney et al., 1996).  

Thereafter, participants were told that they would play an advice-decision game. The 

participant was assigned (apparently for her, by chance) with the role of advisor and 

was invited to enter in the EEG shielded chamber while the confederate played as the 

decider and sat in an adjacent room. Participants would always receive the same amount 

of course credits, but they were told that the amount received by the decider depends on 

their successful decisions. Participants were also informed that the decider might not 

follow the advice. As mentioned in the Introduction section, and following Zhu et al. 

(2017, 2019), there were 4 possible conditions considering the feelings of the 

participant. When the decider follows the advice and both are wrong, this is assumed to 

cause feelings of guilt (as the dominant feeling –Zhu et al. (2017, 2019)-, even if, as 

explained, shame might also be present). When the advice is wrong and the decider 

ignores it yielding a right outcome, the feelings would correspond to shame. If the 

decider follows the advice and both are right, this would elicit joy. Finally, when the 

advice is right but the decider ignores the advice and yields a wrong outcome, this was 

categorized as uncertainty by Zhu et al. (2017, 2019), though in our opinion some 

degree of other emotions could not be discarded.  

Both the adviser and the decider saw the stimuli on two LCD screens located at 

65 cm distance from their eyes. Each trial (Fig. 1) began with a fixation cross appearing 

at the centre of the screen for 500 ms, followed by a black screen with twenty white 

dots (dot size = 3x3 pixels), randomly displayed, in a 300x300 pixels frame around the 

center of the monitor (x=0, y=0) to minimize ocular movements. Participants were 



	 75	

instructed to estimate the number of dots on the screen. The dot stimuli were displayed 

for up to 1500 ms for the student and 750 ms for the confederate. After the dots 

disappeared, a number (19, 20 or 21, randomly chosen) appeared on the screen for 1500 

ms, during which the advisor pressed a button with her response relative to whether the 

number of just-appearing dots was higher of lower than the appearing number. The 

response hand was counterbalanced across participants. Then, the decider made her 

decision within the following 3 s. After the presentation of a blank screen for 800, 1000 

or 1200 ms depending on the trial (randomly chosen to avoid habituation) the feedback 

of the performance of the players was presented for 2 s with either a green tick (right 

response) or a red cross (wrong) below each participant’s picture (feedback stimulus). 

To finish the trial, a yes-no question appeared on the screen for 1500 ms, and 

participants were asked to indicate if they felt shame upon seeing the outcome of 

advisor-decider performance. The position of the response alternatives (‘yes’, ‘no’) at 

the left/right of the screen was also counterbalanced across participants. 

 

 



	 76	

 

Figure 4.1. Experimental procedure. A fixed cross appears for 500 ms at the center of 

the screen before the onset of random dots for 1500 ms, where participants estimate the 

number, advisor for 1500 ms and decider for 750 ms. After a blank screen, 19, 20 or 21 

appears for 3 s while advisor has to choose whether the actual number was greater or 

lesser. Feedback 1 screen appears for 3 s displaying the advice. After another blank 

screen, Feedback 2 with portraits of the participants appears for 2 s with a tick or a 

cross for individual performance. A “do you feel shame?” question (yes/no) ends a 

trial. 

 

Importantly, all performance feedbacks were predetermined by the 

experimenters as follows: of the total of 360 trials (divided into two blocks with a brief 

pause in between), 30 were of the uncertainty condition, 110 of the shame condition, 

110 of the guilt condition, and 110 of the happiness condition. The number of trials in 

the uncertainty condition was notably lower than in the other conditions, (Zhu et al. 



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2017, 2019), to avoid a feeling of disapproval in the advisor against a high negative 

decider response. The number of dots remained constant to 20 on every trial, though 

their spatial distribution varied randomly. The participants were unaware of these 

manipulations. A brief training of 15 trials was set to the adviser but acting as the 

decider, in order to mimic and experience their partners’ role. Then, another training of 

15 trials as advisor was set prior to the experiment. Overall the whole experiment lasted 

about 70 min. 

 

4.2.3. Electrophysiological recording and analysis  

EEG was recorded from 59 scalp electrodes mounted in an electrode cap (EasyCap), 

following the 10/20 International System. Bipolar vertical and horizontal EOGs were 

recorded to monitor blinks and horizontal eye movements. During recording, all scalp 

electrodes as well as one electrode at the left mastoid, were originally referenced to one 

electrode at the right mastoid; offline, they were re-referenced to the average of the right 

and left mastoids. The impedance of all electrodes was kept below 5 kΩ. The EEG data 

was analyzed with Brain Vision Analyzer® software. Raw data were filtered on-line 

with a band-pass from 0.01 to 100 Hz and sampled at 250 Hz; they were digitally 

filtered offline to a 0.1-30 Hz band-pass. 

The continuous EEG was segmented into 1200-ms epochs, starting baseline 200 

ms before the feedback screen onset. Eye-movements were corrected using Independent 

Component Analysis (ICA, Makeig et al., 2000) as implemented in BrainVision 

Analyzer®. Remaining artifacts were further removed by a semi-automatic rejection, 

eliminating epochs exceeding ± 100 µV in any of the channels and manually removing 

drifts or muscular artifacts. The mean rate of accepted epochs was 86.47%, and there 



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were no significant differences between conditions in this regard (F(3,66) = 1.645; p = 

0.19; ɳp2 = 0.07). 

        Statistical analyses were computed with IBM SPSS Statistics (Version 22). A 

first, overall repeated-measures ANOVA was performed including two factors: 

Electrode (59 levels) and Emotion (4 levels: shame, guilt, happiness, uncertainty). ERP 

voltage was measured as the mean amplitude within a particular time interval (from 200 

to 1000 ms, in 100ms-wide windows). Second order post-hoc ANOVAs were thereafter 

performed in two regions of interest (ROIs) (Fig. 2) and at selected specific time 

intervals in order to increase statistical power: one central ROI, that included the 

electrodes, FC1, FCz, FC2, C1, Cz, C2, CP1, CPz, CP2, P1, Pz and P2 (ROI1), and one 

right-frontal ROI, that included AF4, AF8, F2, F4 and F6 (ROI2). The Geisser–

Greenhouse correction for non-sphericity was applied when necessary (Greenhouse and 

Geisser, 1959). Post-hoc tests were corrected with the Bonferroni procedure. Activity 

considered as specific either of shame or of guilt was that in which the fluctuations 

linked to the corresponding condition exhibited a differential pattern when compared 

with the other social emotion as well as with the other two conditions (happiness, 

uncertainty). Specific results and topographies were established as based on the 

differences between shame and guilt or vice versa, as these are the result of subtracting 

two relatively comparable emotions without the influence of other confounding 

emotional responses of different typology and/or valence.   



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Figure 4.2. Location of the electrodes covered by the two main regions of interest 

(ROIs); a central ROI (ROI1) and a right frontal one (ROI2). 

	
4.2.4. Source generator analyses 

LORETA software, an algorithm based on inverse problem solution that offers brain 

activated areas from EEG neural activity (Pascual-Marqui et al., 2002), was used to 

locate the sources of the ERP fluctuations that could be estimated as specific of one of 

the social emotions of interest, i.e., shame and guilt. Only activity that could be 

considered as specific of one of these emotions –in consonance with ERP analyses- was 

used in these computations. These were made at selected time windows and based on 

the contrast values between shame and guilt and vice versa.   

 

4.2.5. SCR recording and analyses  

Skin conductance response (SCR) was monitored in each participant throughout the 

experiment. An 8-channel Multibox polygraph (Brain Products) placed to the index and 

middle fingers of the non-responding hand in the experimental task. SCR results were 



	 80	

analysed with Ledalab software (Benedek & Kaernbach, 2010a). A downsampling 

process was applied to the original data to 125 Hz, and pre-processed by adaptive 

smoothing. Following these procedures, a composition-decomposition analysis (CDA) 

was performed to separate both the tonic and the phasic signals from the raw SCR 

(Benedek & Kaernbach, 2010b). Only phasic data with a minimum SCR amplitude of 

0.1 µS were considered. Individual measures of phasic SCR were then averaged 

separately for each participant and condition. Phasic mean activity was standardized 

within subjects to facilitate the comparison of SCR means across conditions.  

 

4.3. Results  

4.3.1. Performance 

The rating scores of the feeling of shame (yes/no question in the screen after the end of 

the feedback) under the different conditions were: joy (M=3,12%, SD=3,1), uncertainty 

(M=7,68%, SD=10,2), shame (M=60,24%, SD=30,39) and guilt (M=66,60%, 

SD=31,32). An ANOVA yielded significant differences in condition as main factor [F 

(3,66) = 72.5, p<0.05, ɳp2 = 0.76]. Post-hoc analyses showed significant differences 

between all conditions [Ts(22) between 2.2 and 9.9, p always <0.05] with the exception 

of the comparison joy vs. shame [T(22) = 1.1, p>0.1].  

 

4.3.2. SCR 

There were no significant differences in the phasic SCR activity between conditions 

[F(3,51)= 1.04; p>.05;  ɳp2 = 0.058], possibly indicating constant high levels of arousal 

without trial-to-trial noticeable discrepancies, given the difficulty of the task, which is 

in consonance with the results of Sánchez-García et al. (2019) relative to guilt.  

 



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4.3.3 ERP and LORETA analyses 

A visual inspection of the ERP waveforms (Figure 3) suggested differences between the 

four conditions starting around 200 ms after the feedback screen onset up to end of the 

epoch. Happiness and uncertainty revealed the most noticeable differences relative to 

the emotions of interest-shame and guilt-. The former presented smaller but apparent 

and specific differences when compared to the other conditions at two main time points. 

First, between about 200 to 500 ms after the onset of the accuracy feedback, shame 

displayed a more negative ongoing activity when compared to the other three 

conditions, a negativity with a mainly central distribution when compared to the guilt 

condition (Fig. 4.4.). Thereafter, guilt seems to display a specific difference relative to 

the other conditions, consisting in a–mainly right- frontal positivity when compared to 

the shame condition, and covering from about 400 ms to 800 ms (Fig. 4.5). 

 

 

Figure 4.3. ERP grand means for BW (both wrong - guilt), SW (self wrong - shame) BR 

(both right - joy), and PW (partner wrong - uncertainty) conditions at selected 



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electrodes. 

 

Statistical analyses confirmed these observations. First, overall ANOVAs 

showed significant effects of Electrode by Condition at all the 100-ms wide windows 

between 200 and 800 ms, with all F´s (174, 3828) > 4.801 and all p´s<0.05, endorsing 

subsequent ANOVAs at selected ROIs and time windows. An ANOVA at ROI1 for the 

window 300-400 ms, when the central negativity specific to shame exhibited its largest 

values, revealed significant effects of Condition [F(3,66) = 15.4; p<0,05; ɳp2 = 0.412]. 

Post hoc analyses in this ROI and window exhibited significant differences between 

shame vs. guilt [T(22) = 3.7, p<0.001] and shame vs. joy [T(22) = 6.4, p<0.001]. The 

remaining comparisons were also significant (joy vs. guilt [T(22) = 4.6, p<0.001], joy 

vs, uncertainty [T(22) = 4.2, p<0.001]), with the exception of uncertainty vs. guilt 

[T(22) = 0.3, p>0. 1] and shame vs. uncertainty [T(22) = 1.7, p>0.1. An ANOVA at 

ROI2 for the window 450-550 ms, when the frontal negativity specific to guilt exhibited 

its largest values, revealed significant effects of Condition [F(3,66) = 4.170; p<0,05; ɳp2 

= 0.159]. Post hoc analyses in this ROI and window exhibited significant differences 

between all conditions, that is, joy vs. shame [T(22) = 2,8, p<0.001], joy vs. guilt [T(22) 

= 5.6, p<0.001], uncertainty vs. guilt [T(22) = 3.7, p>0.001], uncertainty vs. shame 

[T(22) = 2.6, p<0,05], and shame vs. guilt [T(22) = 2.1, p<0.001], with the exception of 

uncertainty vs. joy [T(22) = 0.7, p>0.1],  



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Figure 4.4. Shame effect as the difference wave between SW (self wrong) and BW (both 

wrong) in electrode Pz, and a map representing the 300 – 400 ms interval at ROI1. 

	

 

 

Figure 4.5. Shame effect as the difference wave between SW (self wrong) and BW (both 

wrong) in electrode F4, and a map representing the 450 – 550 ms interval (LPC) at 

ROI2.  



	 84	

 

To estimate the origin of the central negativity related to shame, a LORETA 

analysis was performed for the difference shame vs guilt around its peak; namely, 300-

400 ms window. The solution consisted of an involvement of mid-parietal regions at 

MNI coordinates (X=5, y=-65, z=65), corresponding to precuneus/posterior cingulate 

(Fig. 5A). The same analyses were performed for the 450-550 ms window, in search of 

the neural origins of the frontal negativity related to guilt. The solution consisted of an 

involvement of mid-parietal regions at MNI coordinates (X=5, y=-65, z=65), 

corresponding to precuneus/posterior cingulate (Fig. 5B). 

 

 

Figure 4.6. Neural generators (LORETA analysis) of shame condition, performed for 

the difference SW minus BW (self wrong vs both wrong) conditions, around its peak of 

about 350 ms  (300-400 ms window) and 500 ms(450-550 ms window) to increase the 

specificity of the solution. 

 

4.3.4. Correlations between ERP results and variables linked to emotions 

Trait levels of guilt and shame as measured by TOSCA did not significantly correlate 

with any of the main ERP fluctuations that appeared to be specific of the corresponding 

conditions, neither with the reported responses about the current feelings of shame. 

Accordingly, traits did not relate with states in this paradigm, at least with the here 

uncovered fluctuations and reported outcomes. The same was the case with cognitive 

and affective empathy measures of the TECA, which is at variance with previous 



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studies in which guilt has been approached with a different paradigm in interpersonal 

context (Sánchez-García et al., 2019).  

Finally, the amplitude of the main ERP fluctuations that seemed specific of either 

shame or guilt did not correlate significantly with the feelings of shame reported after 

each corresponding condition (in both cases, Spearman’s Rho = 0.29, p>.05). 

 

4.4. Discussion 

Our study explored the behavioral, electrophysiological and anatomical correlates of 

shame in an interpersonal context, by concurrently measuring ERP, neural source 

analysis (LORETA), SCR, shame and guilt variables (TOSCA-2), and empathy 

(TECA). Our main aim was to replicate and expand the study by Zhu et al. (2017) in a 

Chinese sample, by using a group of western participants and further defining the 

processes plausibly reflected by the main ERP modulations in dot estimation task 

economic game arguably eliciting these social emotions.  

 The rating score of shame feeling induced in participants in the shame and guilt 

conditions were significantly higher than in the other conditions. This is in line with 

Leng et al. (2016) and Zhu et al. (2017), noticing a higher rating score in our study and 

supports the achievement of a valid procedure to induce this social emotion. 

Nevertheless, shame and guilt scores were noticeably similar suggesting an overlapping 

and semantic confusion between participants to discriminate between the feeling and the 

appropriate word to express similar social emotions.  

The percentage of responses reporting feeling shame in the guilt condition was similar 

to that in the shame condition does not necessarily convey that the intensity of shame 

felt was comparable in both shame and guilt conditions, since the measure is not scoring 

intensity. The result is simply indicating that some degree of shame was felt in the guilt 



	 86	

condition, as predicted. Also as expected, happiness and uncertainty yielded very low 

values of reported shame. 

Beside that our results are opposite to the idea that in non individualistic cultures, the 

feelings of guilt or shame could be higher. These differences are very remarkable for 

complex social emotions such as guilt (Walbott & Scherer, 1995; Anolli & Pascucci, 

2005) and shame (Camras & Fatani, 2004; Tsai, 2006; Tracy & Robins, 2006). For 

instance, in Chinese language there are more than 100 terms related to shame (Li et al., 

2004). In our case, the early shame results found might reflect latencies, amplitudes and 

topography that could not be attributed to cultural differences of the samples suggesting 

an equal feeling and expression of these social emotions between, at least, the two 

samples studied (Chinese Zhu et al. 2018 and our sample). 

On the other hand, the ERP fluctuations obtained in the present study are quite 

different to those of Zhu et al., 2017. The components found, as well as their latency 

and topography, are similar since we find a centro parietal negativity (CPN) in the SW 

minus BW condition, starting at about 200 ms and peaking around 400 ms, CPN was 

significance solely in 200-300 ms window for Zhu et al. (2017). We also found a late 

right frontal positivity, from 450 ms onwards. The latter did hold statistical significance 

in the 450-550 ms time window, further differenciating the results in Zhu et al. (2017) 

and linked to a two step processing (early and late) of social emotions as in Sánchez-

García et al 2019. 

 

The present work therefore adds knowledge to the neuroscientific study of 

emotions by verifying that a centro-parietal negative fluctuation starting about 200 ms 

and a right-frontal positivity at 450 ms concurs with conditions in which people feel 

shame. Of the highest interest, these fluctuations have appeared in our sample of 



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Western (European) participants. This implies several consequences as the shame 

processes reflected by the centro-parietal negativity and  right-frontal positivity seem to 

extend beyond cultures under similar circumstances eliciting these feelings, despite well 

reported cultural differences in experiencing complex social emotions (e.g., Walbott & 

Scherer, 1995; Anolli & Pascucci, 2005). 

 

Zhu et al., (2017) claimed that an early P2 was related to shame, emerging from 

the SW condition. This pattern is replicated here, confirming P2 CPN as an early, and 

longer (up to 400 ms) component of shame linked to early attentional processing of self-

relevant information (Chen et al., 2011). The argument seems consistent as shame, as a 

moral emotion, relates to self reference processes. This early component might reflect 

quick information that leads to social devaluative situations, therefore providing a way 

to protect ourself image and status (De Hooge, et al., 2010). The right frontal positivity 

emerging at 450 ms, not found in Zhu et al. 2018, could reflect reanalysis and self-

assesment processes linked to social comparison. Several studies have reported LPC 

components during social evaluative encounters (Qiu et al., 2010; Wu et al., 2012).  

Furthermore, right-prefontal cortex plays a major role when moral decisions are 

taken, as perceived unfairness (Knoch et al. 2006), negative emotional judgment 

(Grimm et al. 2008) and inhibitory regulation in cognitive and emotional processes 

(Depue et al., 2015) in line with the inhibitory control and re-assesment of shame 

feelings. 

We could not find a significant correlation between the amplitude of the centro parietal 

negativity and right frontal positivity and the reported feelings of shame in the shame 

(SW) condition, which might indicate that both fluctuations do not seem to relate 

directly to the final outcome of shame feelings. Centro parietal negativity (CPN) and 



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right frontal positivity (RFP) are probably reflecting a very important part of the 

processes involved in these feelings, but other processes might also be in play. Our 

interpretation hypothesis relies on the common semantic overlapping when expressing 

in conscious thoughts previously felt. Since shame is a complex emotion, processes of 

late evaluation may indeed involve further reanalysis.  

Although shame feelings may even relate to associations between hypothalamic-

pituittary- adrenal (HPA) and proinflamatory immune cytokines release and shame 

experience related to threaten of social self (Dickerson & Kemeny, 2004; Gruenewald et 

al., 2004). Therefore, linked to personal distress, this did not seem to be different across 

conditions, as reflected in SCR. The presence of other activating emotions in the other 

conditions, and even similar (guilt - BW condition) or high arousal levels throughout 

the session due to the demanding dot estimation task, might explain this result. In fact, 

along the experiment, participants never reached to control the task or actually count the 

total number of dots at ease. The ERP shame results therefore do not seem related to 

distress or arousal.  

The underlying sources of the EEG voltage patterns point to mPFC (second best 

match) and Precuneus/PCC (first match) as source regions. Medial prefrontal (mPFC) 

area appears to be crucial in the generation of the RFP being consistent with findings 

that relate this region with social cognition networks reflecting what might others think 

about our performance and social status (e.g., Kédia et al., 2008; Morey et al., 2012). 

Precuneus and posterior cingulate cortex (PCC) is also involved being linked to 

monitoring environmental changes and memory re-encoding (Andrews-Hanna et al. 

2014).  

As expected, scores in the cognitive and affective measurements of empathy 

(TECA) do not relate to shame feelings. Empathy is a core element for guilt, not shame, 



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to emerge (Baumeister, Stillwell and Heatherton, 1994; Hoffman, 2000; Eisenberg, 

2000; Morey et al, 2012) as the comprehension, cognitive and emotionally of other´s 

distress is crucial to elicit guilt feelings and amending and approaching consequent 

behavior. Empathy indeed is a core component of watching others pain (Singer et al. 

2004) a key issue for feeling interpersonal guilt. On the other hand, shame behavior 

leads to self appeasement, hiding and avoiding, not empathizing, actions.  

This shame process starts as early as about 200 ms after the feedback in which 

participant realizes own and other’s achievements in the advisor task. In this regard, the 

LORETA analysis showed that precuneus area seem to be critical in the generation of 

this CPN and RFP. This is consistent with findings that relate this area to self evaluative 

processes as proposed by Takahashi et al. (2004) comparing fMRI brain activation of 

guilt and shame, showing shame to guilt more activation in the anterior and posterior 

cingulate cortex.  

Overall the evidence seems highly consistent with the suggested dynamic 

processes of centro parietal negativity and right frontal positivity and their contribution 

to the feelings of real shame through a social comparison task.  

 

4.5. Conclusion 

In conclusion, we have been able to validate an early ERP modulation that seems 

consistent across cultures and that extends to late reanalysis processes of emotional 

content. Nevertheless these processes do not relate to the feelings of shame themselves. 

Those processes, presumably occurring at precuneus areas, start as soon as about 200 

ms after performance feedback is presented, peak around 400 ms and keep on with a 

latter phase at 500 ms. The present data contributes to better understand the dynamics 

and complexity of the neural mechanisms underlying the social emotion of shame.  



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Chapter 5. Study Three. Pride and shame 

 

5.1. Introduction 

As we have understood in previous chapters social emotions play a critical role to 

establish social behavior and human moral, being considered of the highest relevance 

for people´s adherence to social norms (Beer & Keltner, 2004; Tangney et al., 2007). 

They regulate and motivate human thoughts, feelings, and behavior, encouraging us to 

achieve actions in order to attain a valued social position (Tracy & Robins, 2007). On 

the other hand, social emotions are cognitively complex. They require self-awareness 

(Abe & Izard, 1999; Lewis, 2000), as well as the ability of mentalizing, as they imply 

concerns about others (Haidt, 2003; Tangney and Dearing, 2003). Despite their 

centrality to understand the distinctiveness of human mind and its evolution (Flinn et 

al., 2005), the neural underpinnings of social emotions have been scarcely studied. The 

present experiment aims at contributing to this field by focusing at the same time on 

two of these emotions: pride and shame.  

Pride is a pleasant emotion which is experienced when an individual improves in 

social status by achievement and effort (Tracy and Robins, 2007). This is called 

authentic pride, and should be discerned from hubristic pride, a non-adaptive emotion 

arising from lack of empathy, narcissism and self-importance (Carver et al. 2010; Tracy 

and Robins, 2007). Shame, by contrast, is an unpleasant emotion that evokes pain and 

aversive feelings arising from situations driven by failure to one or others’ ideal 

standards (Tangney et al., 2007) or from an inappropriate social behavior (Menesini & 

Camodeca, 2008). It implies a damaged global self, leading to anger, hostility, or 

resentment (Tangney et al., 1996), and even anxiety or depression (Gilbert, 2000; 

Tangney et al., 1992). Though the identification of a distinct neurobiological basis is 



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critical for the characterization and definition of any basic emotion (Tracy & Randles, 

2011), this has been highly elusive regarding social emotions. Overall, these emotions 

seem to involve basic emotional processing brain structures, typically located 

subcortically -such as the amygdala-, together with others related to self-reference and 

mentalizing and mostly placed in cortical areas (Bastin et al., 2016). Indeed, the latter 

seem to better characterize the neural underpinnings of social emotions. Yet, the 

depiction of distinct patterns singularizing social emotions like shame and pride within 

these self-reference and mentalizing regions is far from available.  

Recent neuroimaging evidence reveals the special relevance of medial prefrontal 

and posterior regions belonging to self-referential and mentalizing circuits during both 

shame (Michl et al., 2014; Gilead et al., 2016; Roth et al., 2014; Zhu et al., 2019) and 

pride (Zahn et al., 2009, 2014; Simon-Thomas et al., 2012; Roth et al., 2014). Besides, 

other studies have also reported the involvement of the anterior temporal lobes in shame 

(Bastin et al., 2016), and the ventrolateral and dorsolateral prefrontal cortex or the 

superior, middle and inferior temporal regions in pride (Hong et al., 2019; Takahasi et 

al., 2008). Remarkably, however, Roth et al. (2014) studied pride and shame 

concurrently and found them indistinguishable in terms of brain activated areas: both 

emotions engaged the same basic emotion-related (amygdala, insula and ventral 

striatum) and self-referential (dorsomedial prefrontal and posterior cingulate cortex) 

regions. Only a larger activation of the basic emotion-processing areas by pride could 

distinguish these emotions, interpreted as due to an intrinsic hedonic value of pride as a 

positive emotion. If we pursue the identification of distinct underpinnings to better 

characterize and dissociate pride and shame at the neural level, the current situation 

appears restraining. The reduced number of studies is one determining factor. The 



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present study aimed to expand current knowledge on the neural mechanisms by 

dissociating pride and shame in two remarkable ways that we explain below.  

On the one hand, Event-Related brain electrical Potentials (ERP), at variance 

with other neuroimaging techniques, permit to study the neural temporal dynamics in 

milliseconds, which could, by itself, unveil noticeable differences between shame and 

pride. Moreover, ERP can also provide an approach to structural information by means 

of source-estimating algorithms (Awan et al., 2009). Zhu et al. (2017) used ERP to 

disentangle shame and guilt: both emotions were distinguished about 200 ms after the 

presentation of the stimulus prompting either emotion, since a significant increase of the 

P2 component occurred in the shame condition. As the P2 relates to early selective 

attention (it is actually originated in visual association areas; see Luck & Hillyard, 

1984), the finding was interpreted as an index of the self-relevance of the visual 

information eliciting shame. Our second experiment, went a step further to study shame 

finding a centro parietal negativity emerging at 300 ms after presentation of the 

stimulus, linked to early attentional processing of self-relevant information in social 

comparative situations (Chen et al., 2011, De Hooge, et al., 2010) and a right frontal 

positivity emerging at 450 ms linked to and self-assesment in social comparisons. 

To our knowledge, while no other studies has approached shame by means of 

ERP, none has been done in relation to pride. The present study records ERP 

fluctuations to stimuli presumably eliciting pride and shame in the same experimental 

session. 

A second way in which the present work contributes to the literature is through 

the development of an experimental paradigm seemingly prompting genuine feelings of 

pride and shame, in controlled social context in the lab. With the exception of the Zhu et 

al., 2019 (studying shame), most of the neuroimaging literature on pride and shame 



	 93	

elicited these emotions through cue recalling or visual imagination (e.g., reading a 

sentence or viewing a related picture). With these procedures, memory and imagination 

neural processes may interfere with the target emotions processes, while social context 

and evaluations, which are critical factors in shame and pride, might be absent.  

(Robertson et al., 2018). This caveat can be overcome by implementing interpersonal 

games in the lab. This approach has been used in studies on shame (using ERP -Leng et 

al. 2016; Zhu et al., 2017; Sánchez-García et al. 2019- and fMRI -Zhu et al., 2019-), but 

it has never been applied to study pride. 

The present study used an innovative paradigm, endorsing the direct study of 

both emotions at the neural level in the same experiment. In the paradigm developed 

here, the participant played online against three other people in a dot-estimation task. 

After every trial, the participant received feedback on proper and others’ correctness or 

failure. Eight different conditions were created, depending on the feedback pattern. In 4 

of them, the participant was right, and the performance of the other three participants 

could be: a) they all were right, b) two of the others were right, c) one of the others was 

right, or d) none was right. This was repeated in the 4 conditions in which the 

participant was wrong. What is distinctive about this paradigm is that emotions of pride 

and shame can be elicited in the same session, as a function of the comparison between 

proper and others’ performance. Pride would be maximal when the participant is right 

and all the other players are wrong. The corresponding control trial for this condition 

would be when both the participant and the other three players are right. In turn, shame 

would be maximal when the participant is wrong and all the other players are right, and 

the corresponding control trial would be when both the participant and all the other 

three players are wrong.  



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According to previous findings on ERP with social emotions (namely, guilt and 

shame) (Leng et al. 2016; Zhu et al, 2017; Sánchez-García et al. 2019) we expect a 

dual-time processing pattern, i.e., early and late components related to pride and shame, 

possibly reflecting different processing steps contributing to achieve these social 

emotions. Although the ERP technique is relatively unsuitable to explore activity from 

subcortical emotion-processing areas such as the amygdala, it is in turn highly sensible 

to cortical activations, including the medial areas (Luck, 2014). By means of source-

estimating techniques, we expect to find the involvement of self-reference and 

mentalizing areas in both the medial and lateral cortices, presumably differing in their 

dynamic involvement when comparing pride and shame.  

 

5.2. Materials and methods  

5.2.1. Participants 

Thirty-six undergraduate students participated in the experiment. Four were discarded 

due to excessive artifacts in their recordings. The remaining sample was composed of 

16 females and 16 males. Their age varied between 18 and 28 years (M = 19.7 years; 

SD = 1.87). All participants were right-handed, with scores ranging from 50 to 100 

(M=86.66%) according to the Edinburgh Handedness Inventory (Oldfield, 1971). 

Participants reported no history of psychiatric or neurological illness and provided 

written informed consent before the experiment. The study was performed in 

accordance with the Declaration of Helsinki and approved by the ethics committee of 

the Hospital Clínico San Carlos (Madrid). Participants received 15€ for taking part in 

the experiment. 

5.2.2. Procedure 

Before the ERP experiment, the participant was instructed in the experimental 



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procedures. The goal was to play a dot-estimation task online with three other students 

from different universities, other than the host institution. Actually, before the task, 

experimenters showed a simulated conference video call where the three other students 

were being set up their EEG caps in their respective labs to enhance a social context 

setting (Figure 1). The participant was unaware of this pretending manipulation, since 

conference video call was pre-recorded, in a way that appeared realistic to the ongoing 

situation. The aim of the video was to make feasible and reliable the social setting of the 

experiment. In order to balance the gender composition in the social context, the video 

call was different depending on the gender of the participant: for female participants, 

the other 3 participants were two males and one female; for male participants, two 

females and one male. The participant was told that she/he was participating in a 

competition between different universities in Spain on the visuospatial abilities of their 

students, therefore promoting a social comparison situation.  

 

Figure 5.1. Simulated pre-experiment ‘conference video call´, where the three other 

pretended participants are shown to the actual participant  

  



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The task consisted in a dot-estimation task, in which the participant received 

feedback on proper and others’ correctness or failure after every trial. Each feedback 

consisted in a composition with the pictures of the four persons presumably performing 

the task, the one of the participant located at the bottom center of the image, together 

with a hit or an error mark below each person’s picture (Figure 2). As depicted in Figure 

2, there were 16 possible feedbacks, as a function of the combination of the correctness 

of the answer of the participant and of each of the 3 opponents.   

 

Figure 5.2. The 16 possible feedbacks displayed after every trial in the dot-estimation 

task. 

 

The participant was seated on a comfortable chair while the stimuli were 

presented on an LCD screen located at 65 cm distance from her/his eyes. Each trial 

began with a fixation cross appearing at the center of the screen for 500 ms (Figure 3), 

followed by a black screen with twenty white dots (dot size = 3x3 pixels), randomly 

displayed, in a 300x300 pixels frame around the center of the monitor (x=0, y=0) to 

minimize ocular movements. The participant was instructed to estimate the number of 

dots on the screen. The dot stimuli were displayed for up to 1500 ms. After the dots 



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disappeared, a blank screen appeared for 800, 1000 or 1200 ms depending on the trial 

(randomly chosen to avoid habituation), followed by a number (19, 20 or 21, randomly 

chosen) for 1500 ms, during which the participant pressed a button, the response being 

relative to whether the number of just-appearing dots was higher of lower than the 

preceding number. The response hand was counterbalanced across participants. After 

the presentation of a blank screen for 800, 1000 or 1200 ms, depending on the trial, the 

feedback about the performance of the 4 players was presented for 2 s, followed by a 1s 

black screen. 

 

Figure 5.3. Schematic representation of the experimental procedure.  

 

All performance feedbacks were predetermined by the experimenters, the 

participant being unaware of this circumstance, and they were randomly distributed in a 

realistic manner, as follows. There were a total of 480 trials. In half of them, the 



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participant was right, and wrong in the other half. Within the 240 right trials, the 

distribution was: in 35, the other three participants were wrong (pride condition); in 55, 

all the other three participants were also right (control for pride condition); in 75, two of 

the other participants were also right, and in 75, one of the other participants was also 

right. Correspondingly, within the 240 wrong trials, the distribution was: in 35, the 

other three participants were right (shame condition); in 55, all the other three 

participants were also wrong (control for shame condition); in 75, two of the other 

participants were also wrong, and in 75, one of the other participants was also wrong. A 

brief training of 12 trials preceded the experiment. Overall, the whole experiment lasted 

about 90 min, divided into two blocks with a brief pause in between. 

At the end of the recording session, the participant completed a survey on self-

reported emotions to each different feedback, in order to check the validity of our 

assumptions relative to the emotions elicited. To each of the 16 different possible 

feedbacks a 7-point Likert scale was used to assess five different feelings: pride, joy, 

shame, anger and sadness. 

 

5.2.3. Electrophysiological recording and analysis  

EEG was recorded from 59 scalp electrodes mounted in an electrode cap (EasyCap), 

following the 10/20 International System. Bipolar vertical and horizontal EOGs were 

recorded to monitor blinks and horizontal eye movements. All scalp electrodes as well 

as one electrode at the left mastoid were originally referenced to one electrode at the 

right mastoid during recording, and offline re-referenced to the average of the right and 

left mastoids. The impedance of all electrodes was kept below 5 kΩ. The EEG data was 

analyzed with Brain Vision Analyzer® software. Raw data were filtered on-line with a 



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band-pass from 0.01 to 100 Hz and sampled at 250 Hz; they were digitally filtered 

offline to a 0.1-30 Hz band-pass. 

The continuous EEG was segmented into 1200-ms epochs, starting with a 

baseline of 200 ms before the feedback screen onset. Eye-movements were corrected 

using Independent Component Analysis (ICA, Makeig et al., 2000) as implemented in 

BrainVision Analyzer®. Remaining artifacts were further removed by a semi-automatic 

rejection, eliminating epochs exceeding ± 100 µV in any of the channels and manually 

removing drifts or muscular artifacts. The minimum percentage of accepted epochs per 

condition was always 80%, with a mean of 85,55%. 

Statistical analyses were computed separately for pride and shame, as a) these 

emotions elicited activations with dissimilar time windows and b) their corresponding 

control conditions were not comparable. The comparisons comprised the ERP time-

locked to pride and shame conditions feedbacks and those to their corresponding control 

condition. Considering the advantages and disadvantages of different types of analyses, 

two approaches for data analyses were applied: a) factorial cluster-based permutation 

analyses (Fields and Kuperberg, 2019; Groppe et al., 2011a,b), and b) time windows 

analyses based on visual inspection and guided by consideration of the results of the 

cluster analyses. 

 Cluster-based permutation analyses were calculated using the Factorial Mass 

Univariate Matlab® Toolbox. In agreement with the dual-time processing pattern 

observed in the ERP, and guided by previous literature (e.g., Brusini et al., 2017; 

Jiménez-Ortega et al. 2020), we considered early (0-500 ms) and late (500-900 ms) time 

segments for these analyses. Subsequently, two (one per time segment) factorial cluster-

based permutation analyses were calculated separately for each emotion (pride, shame), 

each with 10,000 iterations and alpha level of .05 involving the factor Emotion 



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(Emotion –i.e., pride or shame- vs the corresponding Control condition). For the time 

windows analyses, repeated-measures analyses of variance (ANOVAs) with the SPSS 

22® software were performed. Guided by both visual inspections and cluster analyses, 

two scalp regions of interest (ROIs) and time-windows were used per emotion. For 

pride, ROI1 comprised the electrodes F1, Fz, F2, FC1, FCz, FC2, C1, Cz, C2, CP1, CPz 

and CP2, and was analyzed in the 250-350 ms window. ROI2 for pride comprised the 

electrodes F1, Fz, F2, FC1, FCz and FC2, and was analyzed in the 600-800 ms window 

(Fig.4). For shame, ROI1 comprised the electrodes AF3, AF4, F1, Fz, F2, FC1, FCz, 

and FC2, analyzed in the 330-410 ms window. ROI2 for shame comprised the 

electrodes FC1, FCz, FC2, C1, Cz, C2, CP1, CPz and CP2, and was analyzed in the 

715-875 ms window (Fig.5). The main ANOVA used the mean voltage values of the 

electrodes grouped within each ROI, and involved the factor Emotion, in the same terms 

as in the cluster-based analyses. Violations of the sphericity assumption were corrected 

when necessary by the Greenhouse-Geisser method.    

 

Figure 5.4. Location of the electrodes covered by the two main regions of interest for 

pride (ROIs); a fronto central ROI (ROI1) and a frontal one (ROI2). 



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Figure 5.5. Location of the electrodes covered by the two main regions of interest for 

shame (ROIs); a frontal ROI (ROI1) and other frontal one (ROI2). 

 LORETA software, an algorithm based on inverse problem solution that offers 

brain activated areas from EEG neural activity (Pascual-Marqui et al., 2002), was used 

to locate the sources of the ERP fluctuations that could be estimated as specific of pride 

and shame. Only the activity that could be considered as specific of these emotions, in 

consonance with ERP analyses, was used in these computations. These were made at 

selected time windows and based on the contrast values between pride or shame and the 

corresponding control condition.   

 

5.3. Results 

5.3.1. Self-reported emotions ratings 

The ratings obtained immediately after the experiment (Table 1) showed the largest 

emotions of pride in the condition in which the participant was right and the 3 

opponents were wrong (pride condition), compared to the corresponding control 

condition (both the participant and the opponents were right). This difference was 



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significant (t (31) = 6.45, p < .001) [all ps are Bonferroni-corrected]. Emotions of 

shame, sadness and anger were similarly low in both conditions, with no significant 

difference between them (1.74 < ts (31) < 2.41, all ps > .1). Joy, in turn, was similarly 

high in both conditions, but it was not statistically significant (t(31)= 1.76, p>0.1).  

 PRIDE SHAME JOY SADNESS ANGER 

Pride 

condition 

6.22 (1.34) 1.41 (0.89) 5.84 (1.6) 1.34 (0.81) 1.089 (0.52) 

Control for 

Pride 

4.69 (1.74) 1.03 (0.17) 5.34 (1.42) 1.12 (0.33) 1.25 (0.61) 

Shame 

condition 

1.28 (0.94) 4.15 (2.08) 1.19 (0.55) 3.22 (1.71) 3.94 (1.95) 

Control for 

shame 

1.78 (1.24) 2.22 (1.47) 2.15 (1.54) 2.28 (1.44) 3.09 (1.84) 

Table 1: Ratings in a 7-point Likert scale (Mean, SD) regarding the feelings in different 

emotions as a function of feedback received 

 Regarding the wrong trials, the ratings showed larger feelings of shame in the 

condition in which the participant was wrong and the 3 opponents right (shame 

condition), compared with the corresponding control condition (both the participant and 

the opponents were wrong). This contrast was significant (t(31)= 7.42, p<.001). 

Feelings of pride and joy were similarly low in both conditions; however, even if 

slightly, they were significantly larger in the control condition (t(31)= 3, p=.05 for 

pride; t(31)= 9.87, p<.001 for joy). The values for sadness were relatively moderate in 

the two conditions, but significantly larger in the shame condition (t(31)= 3.11, p<0.05). 

Both conditions also exhibited moderate values in anger, not differing significantly 

(t(31)= 2.46, p>.1).  



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5.3.2. Electrophysiological data: Pride  

Main results corresponding to pride are summarized in Figures 6-8. As can be seen in 

Fig. 6, the pride condition exhibited a fronto-central negativity around 300 ms and a 

long-lasting frontal positivity from around 500 to 900 ms. It can be appreciated that the 

earlier negativity exhibited a progressive amplitude increase, from the control to the 

pride condition, as an inverse function of the number of opponents being right. The late 

positivity, in turn, appeared as an all-or-none process, only present in the pride 

condition. The cluster-based permutation analyses (Fig. 7) in the early time window (0–

500 ms) revealed a significant cluster between 250 and 350 ms, involving up to 44 

electrodes, showing the largest F values around frontocentral and centroparietal 

electrodes. In a later time window (500–900 ms), the cluster-based permutation analysis 

revealed a significant cluster between around 600 and 900 ms involving virtually all 

electrodes, showing the largest F values around the frontal and frontocentral electrodes 

 

Figure 5.6. Mean average ERP fluctuations for pride conditions in a sample of 

electrodes.  



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Figure 5.7. Results of cluster analyses for pride in the 0-500 (left) and 500-900 (right) 

time intervals for the comparison between the pride condition and its corresponding 

control condition. From top to bottom, electrodes are displayed orderly for the left 

hemisphere, midline and the right-hemisphere. 

 

Figure 5.8. Main results of the comparison between the pride condition and its 

corresponding control condition. Left, ERP and difference wave resulting from this 

comparison at FCz electrode. Center and Right, topographic maps of the two main 



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fluctuations related to pride.  

 

The cluster-based permutation analyses complement the data in Fig. 7, where the 

topographies of the early negativity and the late positivity are represented, 

substantiating the ROIs and time-windows employed in the ANOVA analyses. These 

revealed significant differences between the pride and its corresponding control 

condition, both in the early negativity [F(1,31) = 62.9; p<.0001; ɳp2 = .67] as well as in 

the late positivity [F(1,31) = 53.4; p<.0001; ɳp2 = .633]. The progressive amplitude 

increasing of the early negativity across the four conditions in which the participant was 

right seemed to justify an ANOVA analysis of this component comprising all these 

conditions. The results revealed main significant differences between conditions [F 

(3,93) = 43.819; p<0.001; ɳp2 = 0.586], all post-hoc pair-wise Bonferroni-corrected 

comparisons being significant (-7.93 < ts (31) < 8.18, all ps < .001). Finally, neither the 

early negativity nor the late positivity correlated with the self-reported degree of pride 

felt in this condition (Spearman’s R=0.14 and -0.13, respectively; p>0.1). 

To estimate the neural source of the early negativity and late positivity related to 

pride, LORETA analyses were performed for the difference pride vs control around 

their corresponding peaks (250-350 and 600-800 ms time windows, respectively). The 

solution for the early negativity consisted of an involvement of the precuneus and the 

superior parietal regions and, with the best match at MNI coordinates X=20, y=-70, 

z=55 (Fig. 9, top). The solution for the late positivity involved the superior frontal and 

cingulate gyri, the best match being at MNI coordinates X=20, y=0, z=70 (Fig. 9, 

bottom). The solution also seemed to visibly involve right temporal regions.  



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Fig. 5.9. Neural generators proposed by LORETA for the early negativity (top) and the 

late positivity (bottom) obtained in the pride condition. 

 

 

5.3.3. Electrophysiological data: Shame  

Main results corresponding to shame are summarized in Figures 10-13. Fig. 10 shows 

that the shame condition exhibited, when compared to the corresponding control 

condition, a frontal negativity around 370 ms and a long-lasing central positivity from 

around 600 to 1000 ms. The earlier negativity did not exhibit a progressive amplitude 

increase from the control to the pride condition across other conditions. Although not so 

remarkably as in pride, the late positivity appeared again as an all-or-none process, 

mainly present in the shame condition. The cluster-based permutation analyses  during 

the early time segment (0–500 ms) revealed no significant cluster. Possibly, this 

originates in the tendency of this method to miss narrowly distributed effects occurring 



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across a limited number of time points and electrodes (Groppe et al., 2011a); indeed, as 

will be noticed below, the ANOVA analysis was able to find significant effects within 

this period. During the late time segment (500–900 ms), the cluster-based permutation 

analyses (Fig. 12) revealed a significant cluster apparent mainly between around 700 

and 900 ms involving up to 42 electrodes, with largest F values around frontocentral 

and centroparietal electrodes in both hemispheres, with a slight right tendency. 

 

 Figure 5.10. Mean average ERP fluctuations for shame conditions in a sample of 

electrodes. 

 



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Figure 5.11. Main results of the comparison between the shame condition and its 

corresponding control condition. Left, ERP and difference wave resulting from this 

comparison at FCz electrode. Center and Right, topographic maps of the two main 

fluctuations related to shame.  

 



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Figure 5.12. Results of cluster analyses for shame in the 0-500 (left) and 500-900 

(right) time intervals for the comparison between the shame condition and its 

corresponding control condition. From top to bottom, electrodes are displayed orderly 

for the left hemisphere, midline and the right-hemisphere.  

 

The data in Fig. 11, where the topographies of the early negativity and the late 

positivity are represented, are complemented by the cluster-based permutation analyses 

only for the late positivity, verifying the ROI and time-window employed in the 

ANOVA analyses for this component. The ROI and time-window used for the early 

negativity, in turn, was established solely by visual observation of the data. These 

analyses revealed significant differences between the shame and its corresponding 

control condition, both in the early negativity [F(1,31) = 6.74; p<.014; ɳp2 = .179] as 

well as in the late positivity [F(1,31) = 8.29; p<.007; ɳp2 = .211]. Neither the early 

negativity nor the late positivity correlated with the self-reported degree of shame 

(Spearman’s R=-0.03 and -0.23, respectively; p>0.1). 

The neural sources of the early negativity and the late positivity related to shame 

were estimated using LORETA analysis for the difference shame vs control around its 

peaks -i.e., 330-410 and 715-875 ms windows, respectively-. The solution for the early 

negativity involved the superior cuneus, with the best match at MNI coordinates X=15, 

y=-100, z=15 (Fig. 13, top). The solution for the late positivity involved the superior 

parietal lobe and precuneus, with the best match at MNI coordinates X=5, y=-70, z=55 

(Fig. 13, bottom), though it seemed to extend to the cuneus. A possible secondary 

solution for this positivity involved left inferior frontal regions. 



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Fig. 13. Neural generators proposed by LORETA for the early negativity (top) and the 

late positivity (bottom) obtained in the shame condition. 

 

5.4. Discussion 

Brain electrical activity was recorded while participants performed a task in social 

context, with situations seemingly prompting feelings of pride and shame. The ERP 

technique used here permits a dynamic approach to the neural processes as these unfold 

over time, contributing therefore to better describe the neural underpinnings of these 

scarcely studied social emotions. 

 

5.4.1. Prompting pride and shame in experimental environments 

A main contribution of the present study is the setting of a procedure that permits 

studying pride and shame simultaneously and in experimental environments. The 

adaptation of a task previously used to prompt social emotions such as guilt or shame 



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(Leng et al. 2016; Zhu et al, 2017; Sánchez-García et al. 2019), has allowed the 

elicitation of pride and shame within the same participants and session, endorsing direct 

study and comparison of these emotions at the neural level in the same experiment. The 

feelings reported by the participants seem to indicate that the procedure was successful. 

The largest feelings of pride were reported in the pride condition, significantly larger 

than in the corresponding control condition. Other emotions (shame, sadness and anger) 

were low in either the pride or its control condition, with the exception of joy, which 

was equivalent in both conditions. In turn, the feelings exhibiting the largest values in 

the shame condition corresponded to shame, and although anger was also relatively 

high, the latter did not differ with the control condition. Sadness, which appeared also 

moderately present in the shame condition, was less rated than shame (this comparison 

was tested: t(31)= 3.1, p<0.05 after Bonferroni correction). Finally, even if shame and 

the corresponding control condition differed in pride and joy, all these values were 

always low. Overall, the comparison between shame and its control condition could 

yield relatively valid results, even if some cautions could be needed. 

It is noticeable that the amplitude of none of the brain fluctuations obtained 

under these manipulations correlated with the self-reported feelings of either pride or 

shame. This would suggest that although our electrophysiological findings probably 

relate to processes essential to endorse these emotions, they are seemingly not reflecting 

the neural underpinnings of their hedonic component. This feature is of relevance for 

the interpretation of our results. 

 

5.4.2. Neural Mechanisms involved in pride 

The brain activity related to pride exhibited the expected dual-time pattern, consisting of 

an early negativity and a late positivity. The former, occurring around 300 ms after the 



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presentation of the feedback, appeared to originate in medial parietal regions, mainly 

the precuneus. The late positivity emerged along a larger time interval, being visible 

between 600 and 900 ms and seemingly originated in medial frontal areas and the 

anterior cingulate. There is also a possible contribution of right temporal regions to this 

activity. These results harmonize well with previous research using neuroimaging 

(fMRI), in the sense of underscoring the involvement of medial prefrontal and posterior 

regions in situations of pride (Zahn et al., 2009; Simon-Thomas et al., 2012; Roth et al., 

2014). The present findings also provide evidence on the differential involvement of 

anterior and posterior medial areas underlying pride across time. The first and early 

involvement of the medial parietal cortex appeared relevant to bear evaluative processes 

on the degree of individual success, as compared to the other 3 opponents. The 

amplitude of the early negativity to trials in which the participant was right increased 

stepwise as a function of the number of opponents being wrong. Among other 

processes, the medial parietal cortex and the precuneus have been traditionally linked to 

self-referential processing, particularly in situations in which one is compared to other 

people (e.g., Northoff et al., 2006; Qin & Northoff, 2011; Davey et al., 2016; Lou et al., 

2004). It appears plausible, therefore, that this fluctuation is reflecting social 

comparison processes determining the degree of exceptionality of own performance in 

successful trials. 

 As a consequence of the computations reflected in the early negativity, the late 

positivity would emerge uniquely in conditions in which the outcome implied that 

oneself is the only right in the group. This situation was self-reported as maximally 

granting feelings of pride. The areas presumably contributing to this effect -medial 

frontal, anterior cingulate and right temporal regions- have all been involved in pride 

(Roth et al., 2014; Hong et al., 2019) and appear related to appraisals of social meaning 



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and theory of mind (Takahasi, 2008; Schurz et al., 2014). This is compatible with the 

possibility that the late positivity reflects at least part of the processes underlying the 

emotion of pride. This interpretation, however, seems not straightforward, considering 

that a) pride was also appreciable in the control condition, even if with lower values 

than in the pride condition, while the late positivity was an all-or-none process, and b) 

its amplitude did not correlate with the reported feelings of pride, as commented above. 

It might be, accordingly, that the later modulation is rather reflecting the verification of 

the singularity of a successful trial, and this in social terms, in view of its apparent 

origins in brain regions associated with theory of mind and social meaning. Finally, it 

appears plausible that thereafter, and as an outcome of these processes, other, more 

basic emotion-related subcortical regions -such as the amygdala or the ventral striatum- 

become involved, this underlying the feelings of pride. However, these regions are not 

accessible through the ERP technique used here. 

5.4.3. Neural mechanisms involved in shame 

A dual-time pattern consisting of an early negativity and a late positivity was also found 

for shame. The early negativity was not supported by the cluster-based permutation 

analysis, though standard ANOVA analyses yielded significant results. Replication is 

pending. This fluctuation occurred around 370 ms after feedback presentation, and 

seemed originated in the cuneus. Interestingly, Zahn et al. (2014) reported that 

individuals with reduced volumes of the cuneus and the precuneus are more pride-

prone, probably in consonance with the fact that shame and pride are categorically 

opposed emotions. The cuneus has been involved in mental imagery in social situations, 

as compared to when the same situations are imagined as occurring alone (Mochizuki et 

al., 2014). Overall, our results suggest that mental imagery of the social situation might 

be a critical process emerging soon in conditions engendering shame.  



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  The late positivity related to shame was again a long-lasting activity, starting 

about 700 ms and visible until the end of the epoch. This fluctuation was apparently 

originated in the superior parietal lobe and the precuneus, also involving the cuneus and, 

secondarily, left inferior frontal regions. Interestingly, the main involved regions were 

those seemingly originating the early positivity linked to pride. It is tempting to reason, 

given its opposite electrical polarity, that it might be reflecting contrary processes to 

those reflected in the early negativity for pride, i.e., operations determining the degree 

of exceptionality of own performance, in this case in wrong trials, necessary to achieve 

feelings of shame. Though conceivable, this interpretation is nevertheless not clear-cut, 

since an ERP positivity is not necessarily the opposite of a negativity (Luck, 2005; 

Lopes da Silva & Niedermeyer, 2005). Moreover, this late positivity for shame and the 

early negativity for pride also differ in timing, duration and voltage topography. 

Actually, the late positivity for shame also seemed to engage the cuneus, already 

involved alongside the earlier component, while a secondary contribution appeared in 

the left inferior frontal regions, which have been related to emotion recognition in social 

perception (Keuken et al., 2011). Considering that its amplitude did not correlate with 

the reported feelings of shame, it can be speculated that this fluctuation might reflect 

late assessment processes of the social episode presumably necessary for triggering 

feelings of shame, the latter probably involving subcortical neural structures not 

accessible through the ERP technique. 

 

5.4.4. Limitations of the present study 

The main limitations of the present study are intrinsic to the ERP technique. On the one 

hand, some portions of the brain, particularly those subcortically situated and possibly 

underlying primary basic emotional areas, are not accessible to this methodology. Our 



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results, therefore, outline only part of the brain structures involved in pride and shame, 

and must be considered as complementing data obtained with other neuroimaging 

technologies. On the other hand, the areas defined here have to be approached as most 

plausible candidates, i.e., the result of computations based on algorithms that attempt to 

overcome the inverse problem (Pascual-Marqui et al., 2002). Nonetheless, the areas 

defined here largely harmonize with extant literature on pride and shame using 

methodologies with better spatial resolution, while the present data provide outstanding 

temporal resolution.  

Other limitation relates to the data concerning shame. According to self-reports, 

the comparison between shame and its corresponding control condition implies 

outstanding differences in shame, but other emotions can also be present, even if to a 

reduced degree. This contrasts with the more straightforward results for pride. 

Moreover, the early negativity for shame was not supported by the more conservative 

cluster-based permutation analysis. Further research is needed to elucidate the validity 

of our inferences and conclusions on this emotion. 

 

5.4.5. Concluding remarks 

Our results exhibit similarities and differences with previous literature. Some of the 

discrepancies are the consequence of using the ERP technique, while some others 

probably derive from prompting genuine feelings in laboratory conditions, at variance 

with less realistic procedures used previously. Overall, the available literature is notably 

scarce, and more research is granted. The brain regions seemingly involved in our data 

appear concerned in computations related to social cognition and, consequently, would 

be essential for the emergence of emotions that are directly defined by the position of 

the self in relation to others. In line with Roth et al. (2014) it appears plausible that the 



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hedonic facets of pride and shame actually depend on primary basic emotional areas 

(e.g., amygdala, ventral striatum), the joint work of areas involved in social cognition 

being yet essential to establish and define these emotions. The present work suggests 

that the dynamic description of structures underlying social cognition can help to clarify 

their differential involvement in pride and shame, occasionally indistinguishable when 

more static neuroimaging techniques have been used. In conclusion, in pursuit of more 

accurate neural models of social emotions, more research is needed, and this should 

proceed integrating different available techniques.  

 

 

 

 

  



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Chapter 6. Discussion 

The primary objective of our studies was to study the neurophysiological correlates of 

guilt, shame and pride in a social interaction in the lab. Our emphasis was placed on 

how these emotions unfold over time and to address similarities and differences among 

them. To achieve that objective, we conducted our three experiments. 

In our first study we explored interpersonal guilt, by concurrently measuring 

ERP, neural source analysis (LORETA), skin conductance resistance (SCR), state- and 

trait-anxiety (STAI), and empathy (TECA) replicating Leng et al. (2016) study on a 

Spanish sample.  

Our results confirmed the frontal long-lasting negativity (FN) in the self wrong, 

partner right condition (SW), starting at about 300 ms and peaking around 400 ms, and 

a Late Positive Complex (LPC) with parieto-occipital distribution, from 500 ms 

onwards being the former the one who hold statistical analyses. As the FN appeared in 

our Spanish sample we concluded that the processes reflected by the FN related to guilt 

and mediated by empathy seem similar across cultures under these circumstances, 

despite cultural dissimilarities found when experiencing social emotions (Walbott & 

Scherer, 1995; Anolli & Pascucci, 2005). 

The rating of the feeling of guilt induced in participants in the SW condition was 

noticeably and significantly higher than that in the BW (both self and partner wrong) 

condition, confirming a behavioral study we previously run to assess the emotions 

elicited by the different conditions. As the FN did not correlate with the reported 

feelings of guilt, which would be extremely surprising if a complex emotion were 

reflected by a single and early ERP modulation, we addressed whether other processes 

may be involved. Based in our research with personal distress, overall levels of state – 

or trait – anxiety and measurements of empathy we conclude that the latter, which 



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correlates with FN significantly, may reflect processes endorsing guilt. Indeed, empathy 

is a prerequisite for guilt to emerge as it relates to situations in which we may cause 

harm to others (Baumeister et al., 1994; Hoffman, 2000; Eisenberg, 2000; Morey et al, 

2012). Our previous behavioral study and correlations with TECA scores reinforce the 

view of the FN as a fluctuation linked to interpersonal guilt and not to frustration due to 

the inherently difficult task. The LORETA analysis showed that dorsal medial 

prefrontal (mPFC) areas may be the source of the FN. This finding matches previous 

literature research of mPFC as a region for social cognition and empathy processes 

(Kédia et al., 2008; Morey et al., 2012; Bastin et al., 2016; Seitz et al., 2006). 

Our second study explored shame in an interpersonal context, by concurrently 

measuring ERP, neural source analysis (LORETA), skin conductance resistance (SCR), 

shame and guilt variables (TOSCA-2), and empathy (TECA). As with the guilt 

experiment in Study 1, our main aim was to replicate and expand the study done by Zhu 

et al. (2017) with a Chinese sample. The dot estimation task economic game, with some 

adaptations to create the role of advicer-decider, was again used to elicit the social 

emotions of shame and guilt and reflect the main ERP modulations. 

 The rating score of shame feeling in the shame and guilt conditions were 

significantly higher than in the other conditions, supporting the procedure to induce this 

social emotion. Nevertheless, shame and guilt scores were noticeably similar. We 

presumed an overlapping and semantic confusion between participants to discriminate 

between the feeling and the appropriate word to express similar social emotions, 

somehow reflecting the daily mix-up with these feelings (Tangney and Dearing, 2002). 

Two fluctuations were remarkable. The early shame latency appeared to be a 

centro parietal negativity (CPN) starting at about 200 ms and peaking around 400 ms, 

possibly reflecing a social devaluative pre-analysis, to protect ourself image and status 



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(De Hooge, et al., 2010). The late right frontal positivity, from 450 ms onwards, was 

different to Zhu et al. (2017), but nevertheless similar to the one reflected in our first 

study (Sánchez-García et al 2019), yielding a two-step processing (early and late) of 

social emotions. This right frontal positivity emerging at 450 ms may reflect reanalysis 

and self-assessment processes linked to social comparison (Qiu et al., 2010; Wu et al., 

2012). 

As happened with study 1 we could not find a significant correlation between 

the amplitude of either the centro parietal negativity nor the right frontal positivity and 

the reported feelings of shame in the shame (SW) condition, suggesting other processes 

might also be in play.  

Although shame feelings may even relate to personal distress, this did not seem 

to be different across conditions, as reflected in SCR. The high arousal levels along the 

demanding dot estimation task might explain this result. The ERP shame results 

therefore do not seem related to distress or arousal.  

The underlying sources of the EEG voltage patterns point to the medial 

prefrontal cortex (mPFC), part of the social cognition network reflecting what others 

might think about our performance and status, and the precuneus and the posterior 

cingulate cortex (PCC), which are highly involved in  monitoring environmental 

changes and memory re-encoding processes (Andrews-Hanna et al. 2014; Kédia et al., 

2008; Morey et al., 2012. The PCC, as proposed by Takahashi et al. (2004) participates 

in self-evaluative processes, showing more activation in the anterior and posterior 

cingulate cortex fMRI brain activation in shame minus guilt condition.  

In sum, evidence found in study 2 seems highly consistent with the suggested 

dynamic processes of a centro-parietal negativity and a right frontal positivity and their 

contribution to the feelings of real shame through a social comparison task.  



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In our third study the participants performed the dot-estimation task used in 

previous studies (Leng et al. 2016; Zhu et al, 2017; Sánchez-García et al. 2019) but 

modified to a new social context along with other 3 online students and therefore 

increasing social exposure to prompt feelings of pride and shame. Our goal here is the 

elicitation of pride and shame within the same participants and session, and compare 

these emotions at the neural level in the same experiment. A behavioral study confirmed 

that the feelings reported by the participants along the experimental conditions were as 

expected.  

As in the first two studies, the amplitude of the brain fluctuations did not 

correlate with the self-reported feelings, neither of pride nor of shame. ERP fluctuations 

for these emotions probably relate to essential processes in generating these emotions, 

but far from a causal-effect attribution.   

The brain activity related to pride exhibited, as expected, a dual-time pattern 

consisting of an early negativity and a late positivity. The former, occurring around 300 

ms after the presentation of the feedback, appeared to originate in the precuneus (Qin & 

Northoff, 2011; Davey et al., 2016; Lou et al., 2004). The late positivity was visible 

between 600 and 900 ms, with medial frontal areas and the anterior cingulate as possible 

sources. These results fit well with previous neuroimaging research (fMRI), involving 

medial prefrontal regions and the precuneus in situations of pride, both traditionally 

linked to self-referential processing in social comparison, among other functions (Zahn 

et al., 2009; Simon-Thomas et al., 2012; Roth et al., 2014; Takahasi, 2008; Schurz et al., 

2014). This fluctuation may reflect social comparison processes of self successful trials. 

The late positivity for feelings of pride  presumably stems from medial frontal 

regions, anterior cingulate and right temporal regions, all involved being in appraisals of 

social meaning and theory of mind. This later modulation may reflect the verification of 



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the singularity of a successful trial, giving a social meaning to this result through 

mentalizing. 

Shame also exhibited the dual-time pattern of an early negativity and a late 

positivity. The former was not supported by the cluster-based permutation analysis, 

though standard ANOVA analyses yielded significant results. This early negativity 

occurred around 370 ms after feedback presentation, and seemed originated in the 

cuneus, which is usually involved in mental imagery in social situations (Mochizuki et 

al., 2014). The latter started about 700 ms until the end of the epoch, being apparently 

originated in the superior parietal lobe, the precuneus, the cuneus and, secondarily, the 

left inferior frontal regions. We observed that the late positivity related to shame 

implied regions also involved in originating the early negativity linked to pride, which 

therefore in the present case may be reflecting contrary processes, such as the degree of 

exceptionality of own performance, in wrong trials, necessary to achieve feelings of 

shame. Nevertheless, we assume this cautiously as they also differ in timing, duration 

and voltage topography.   

Our secondary objective was to highlight the importance of social contexts in social 

emotions, explore the effects of social interactions on emotional processing, and design 

ecological paradigms to study social emotions in the lab. As we have proved, three 

different social contexts for the same dot estimation task lead the emergence of different 

social emotions. In order to elicit guilt we created an experimental design similar to 

Leng et al. (2016), based on a cooperative situation where, mediated by empathy, the 

participants may felt interpersonal guilt as a result of an economic loss attributed to one 

member of the couple. To try to disentangle shame and guilt, although semantically 

intertwined, we adapted and enhanced Zhu et al. (2017) paradigm, creating a situation 

in which the role of the advisor, a social one, results in shame or guilt, depending on the 



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decision adopted by the decider. Based in these two scenarios, keeping in mind the 

importance of social evaluation, we addressed it in the study of pride and shame by 

creating a whole new setting in which participants’ emotions could vary along a 

continuum from a shame and devaluative feeling to a pride and successful achievement. 

We, therefore, manifest and emphasize that social contexts and interactions are key 

elements on emotional processing. These social contexts and interactions are present, to 

some degree and extent, in the lab situation. This intended similarity to real life 

situations provides more valid results, and the conclusions obtained are more rooted 

than previous designs based on imagining or remembering emotions. 

Altogether, the results of this thesis demonstrate that the neurophysiological 

dynamics of the social emotions of guilt, shame and pride imply a dual time process, 

early and late. This two-step process reflects their complex nature, linked to 

mentalizing, social cognitions networks and involvement of the self in emotional 

processing. The social emotions, as opposed to the basic ones, have no universal and 

external elicitor. Although we may correlate some situations to the occurrence of a 

particular social emotion, it is always the way we think, assess and view ourselves the 

cognitive startup of guilt, shame and pride. They, therefore, require the mental 

representation of the self along with the knowledge and responsibility about standards, 

rules and goals of our social environments.  

Our results exhibit some similarities and differences with previous literature. 

Being the available literature really scarce, the results may be considered under the need 

to do more research. The regions that in which these social emotions may stem in our 

studies, are reinforcing the results of previous studies that show medial cortical areas, 

such as the posterior and the anterior cingulate, the medial prefrontal cortex and the 

precuneus, to be the major structures involved in these social emotions.  



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This two-step neurophysiological dynamic process does not straightforwardly 

reflect the studied social emotion in each experiment. As reported feelings of guilt, 

shame and pride do not correlate with the amplitudes of the ERP´s fluctuations found, 

other processes are necessarily involved and further research is needed.  

Our results agree with a conception of social emotions in which the predictive, 

instead of reactive, nature of our social brain reflects an emotion constructivism view 

(Barret, 2017) and a broad semantic space for them to emerge (Koide-Majima, 2020). 

Limitations of our studies 

One of the main limitations of our studies is intrinsic to the ERP technique. 

Despite its optimal time-course resolution, subcortical regions are not accessible to this 

methodology. Areas such as the amygdala, the hypothalamus, the basal ganglia, the 

ventral tegmental area or the insular cortex play a key role in emotional processing 

(Roth et al. 2014). Our results, therefore, highlight only part some of the brain structures 

involved in social emotions.  

Our spatial approach to study the possible sources of brain areas participating in 

guilt, shame and pride is based in inverse problems algorithms (Pascual-Marqui et al., 

2002). Although the areas defined in our three studies match the ones extensively 

exposed in the literature using technologies with high spatial resolution we are cautious 

about the accuracy and validity of our data. It appears necessary to combine the 

approach used here with other neuroimaging techniques. 

Inherent to this field, we are still far from knowing what an emotion is in the 

brain. It is plausible that there is no such a discrete distinction between emotions and 

thoughts, basic or social, and any intent to search for a fingerprint of emotions is, in its 

roots, incompatible with the dynamic, hyperconnectivity and high variability of the 

neural processes.  



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Chapter 7. Conclusions 

 

1. Our results indicate that a frontal ERP modulation plausibly reflects empathic 

processes necessary for a final outcome of feelings of interpersonal guilt, though 

not the feelings of guilt themselves. Those processes are presumably occurring 

in dorsal mPFC areas.  

2. Our results suggest that shame emotional content processes imply an early ERP 

modulation that extends to late reanalysis. These processes do not relate to the 

feelings of shame themselves. Those processes are presumably occurring at the 

precuneus areas. 

3. Our results indicate that the dual-time pattern consisting of an early negativity 

and a late positivity for pride and shame is replicable. The brain regions 

seemingly involved here apply to social cognition and, consequently, how we 

place ourselves in relation to others.  

4. Our results show that it is possible and advisable to prompt genuine feelings in 

laboratory conditions, at variance with less realistic procedures used previously, 

such as imagining or remembering.  

 

 

 

  



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	Tesis José Sánchez García
	PORTADA
	INDEX
	ABSTRACT
	RESUMEN
	PREFACE
	PREFACIO
	CHAPTER 1. INTRODUCTION
	CHAPTER 2. OBJECTIVES AND HYPOTHESIS
	CHAPTER 3. STUDY ONE. INTERPERSONAL GUILT
	CHAPTER 4. STUDY TWO. SHAME
	CHAPTER 5. STUDY THREE. PRIDE AND SHAME
	CHAPTER 6. DISCUSSION
	CHAPTER 7. CONCLUSIONS
	REFERENCES