Person: Melero Carrasco, Helena
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First Name
Helena
Last Name
Melero Carrasco
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Psicología
Department
Psicobiología y Metodología en Ciencias del Comportamiento
Area
Psicobiología
Identifiers
4 results
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Item Variability in the analysis of a single neuroimaging dataset by many teams(Nature, 2020) Botvinik-Nezer, R.; Holzmeister, F.; Camerer, C. F.; Dreber, A.; Huber, J.; Johannesson, M.; Kirchler, M.; Iwanir, R.; Mumford, J. A.; Adcock, R. A.; Avesani, P.; Baczkowski, B. M.; Bajracharya, A.; Bakst, L.; Ball, S.; Barilari, M.; Bault, N.; Beaton, D.; Beitner, J.; Benoit, R. G.; Berkers, R. M. W. J.; Bhanji, J. P.; Biswal, B. B.; Bobadilla-Suarez, S.; Bortolini, T.; Bottenhorn, K. L.; Bowring, A.; Braem, S.; Brooks, H. R.; Brudner, E. G.; Calderon, C. B.; Camilleri, J. A.; Castrellon, J. J.; Cecchetti, L.; Cieslik, E. C.; Cole, Z. J.; Collignon, O.; Cox, R. W.; Cunningham, W. A.; Czoschke, S.; Dadi, K.; Davis, C. P.; Luca, A. D.; Delgado, M. R.; Demetriou, L.; Dennison, J. B.; Di, X.; Dickie, E. W.; Dobryakova, E.; Donnat, C. L.; Dukart, J.; Duncan, N. W.; Durnez, J.; Eed, A.; Eickhoff, S. B.; Erhart, A.; Fontanesi, L.; Fricke, G. M.; Fu, S.; Galván, A.; Gau, R.; Genon, S.; Glatard, T.; Glerean, E.; Goeman, J. J.; Golowin, S. A. E.; González-García, C.; Gorgolewski, K. J.; Grady, C. L.; Green, M. A.; Guassi Moreira, J. F.; Guest, O.; Hakimi, S.; Hamilton, J. P.; Hancock, R.; Handjaras, G.; Harry, B.B.; Hawco, C.; Herholz, P.; Herman, G.; Heunis, S.; Hoffstaedter, F.; Hogeveen, J.; Holmes, S.; Hu, C. P.; Huettel, S. A.; Hughes, M. E.; Iacovella, V.; Iordan, A. D.; Isager, P. M.; Isik, A. I.; Jahn, Andrew; Johnson, Matthew R.; Johnstone, Tom; Joseph, Michael J. E.; Juliano, Anthony C.; Kable, Joseph W.; Kassinopoulos, Michalis; Koba, Cemal; Kong, Xiang-Zhen; Koscik, Timothy R.; Kucukboyaci, Nuri Erkut; Kuhl, Brice A.; Kupek, Sebastian; Laird, Angela R.; Lamm, Claus; Langner, Robert; Lauharatanahirun, Nina; Lee, Hongmi; Lee, Sangil; Leemans, Alexander; Leo, Andrea; Lesage, Elise; Li, Flora; Li, Monica Y. C.; Lim, Cheng Phui; Lintz, Evan N.; Liphardt, Schuyler W.; Losecaat Vermeer, Annabel B.; Love, Bradley C.; Mack, Michael L.; Malpica, Norberto; Marins, Theo; Maumet, Camille; McDonald, Kelsey; McGuire, Joseph T.; Méndez Leal, Adriana S.; Meyer, Benjamin; Meyer, Kristin N.; Mihai, Glad; Mitsis, Georgios D.; Moll, Jorge; Nielson, Dylan M.; Nilsonne, Gustav; Notter, Michael P.; Olivetti, Emanuele; Onicas, Adrian I.; Papale, Paolo; Patil, Kaustubh R.; Peelle, Jonathan E.; Pérez, Alexandre; Pischedda, Doris; Poline, Jean-Baptiste; Prystauka,Yanina; Ray, Shruti; Reuter-Lorenz, Patricia A.; Reynolds, Richard C.; Ricciardi, Emiliano; Rieck, Jenny R.; Rodriguez-Thompson, Anais M.; Romyn, Anthony; Salo, Taylor; Samanez-Larkin, Gregory R.; Sanz-Morales, Emilio; Schlichting, Margaret L.; Schultz, Douglas H.; Shen, Qiang; Sheridan, Margaret A.; Silvers, Jennifer A.; Skagerlund, Kenny; Smith, Alec; Smith, David V.; Sokol-Hessner, Peter; Steinkamp, Simon R.; Tashjian, Sarah M.; Thirion, Bertrand; Thorp, John N.; Tinghög, Gustav; Tisdall, Loreen; Tompson, Steven H.; Toro-Serey, Claudio; Torre Tresols, Juan Jesus; Tozzi, Leonardo; Truong, Vuong; Turella, Luca; van ‘t Veer, Anna E.; Verguts, Tom; Vettel, Jean M.; Vijayarajah, Sagana; Vo, Khoi; Wall, Matthew B.; Weeda, Wouter D.; Weis, Susanne; White, David J.; Wisniewski, David; Xifra-Porxas, Alba; Yearling, Emily A.; Yoon, Sangsuk; Yuan, Rui; Yuen, Kenneth S. L.; Lei Zhang; Zhang, Xu; Zosky, Joshua E.; Thomas E. Nichols,; Poldrack, Rusell A.; Schonberg, Tom; Melero Carrasco, HelenaData analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.Item Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study(Multiple Sclerosis Journal, 2023) Benito León, Julián; Pino, Ana Belén del; Aladro, Yolanda; Cuevas, Constanza; Domingo-Santos, Ángela; Galán Sánchez-Seco, Victoria; Labiano-Fontcuberta, Andrés; Gómez-López, Ana; Salgado-Cámara, Paula; Costa-Frossard, Lucienne; Monreal, Enrique; Sainz de la Maza, Susana; Matías-Guiu, Jordi A; Matías-Guiu Guía, Jorge; Delgado Álvarez, Alfonso; Montero-Escribano, Paloma; Martínez-Ginés, María Luisa; Higueras Hernández, Yolanda; Ayuso-Peralta, Lucía; Malpica, Norberto; Melero Carrasco, HelenaBackground: Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus ( pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.Item Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study(Multiple Sclerosis Journal, 2023) del Pino, Ana Belén; Aladro, Yolanda; Cuevas, Constanza; Domingo-Santos, Ángela; Galán Sánchez-Seco, Victoria; Labiano-Fontcuberta, Andrés; Gómez-López, Ana; Salgado-Cámara, Paula; Costa-Frossard. Lucienne; Monreal. Enrique; Sainz de la Maza, Susana; Montero-Escribano, Paloma; Martínez-Ginés, María Luisa; Higueras, Yolanda; Ayuso-Peralta, Lucía; Malpica, Norberto; Melero Carrasco, Helena; Benito León, Julián; Higueras Hernández, Yolanda; Matías-Guiu Guía, JorgeRadiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus (pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.Item Graph theory analysis of resting‐state functional magnetic resonance imaging in essential tremor(Human Brain Mapping, 2019) Benito León, Julián; Sanz‐Morales, Emilio; Melero Carrasco, Helena; Louis, Elan D.; Romero, Juan P.; Rocon, Eduardo; Malpica, NorbertoEssential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting‐state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small‐worldness values than healthy controls—less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo‐occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.