Bayesian reasoning with emotional material in patients with schizophrenia
Loading...
Download
Full text at PDC
Publication date
2022
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Frontiers
Citation
Romero-Ferreiro V, Susi R, Sánchez-Morla EM, Marí-Beffa P, Rodríguez-Gómez P, Amador J, Moreno EM, Romero C, Martínez-García N, Rodriguez-Jimenez R. Bayesian reasoning with emotional material in patients with schizophrenia. Front Psychol. 2022 Nov 3;13:827037. doi: 10.3389/fpsyg.2022.827037. PMID: 36405220; PMCID: PMC9670539.
Abstract
Delusions are one of the most classical symptoms described in schizophrenia. However, despite delusions are often emotionally charged, they have been investigated using tasks involving non-affective material, such as the Beads task. In this study we compared 30 patients with schizophrenia experiencing delusions with 32 matched controls in their pattern of responses to two versions of the Beads task within a Bayesian framework. The two versions of the Beads task consisted of one emotional and one neutral, both with ratios of beads of 60:40 and 80:20, considered, respectively, as the "difficult" and "easy" variants of the task. Results indicate that patients showed a greater deviation from the normative model, especially in the 60:40 ratio, suggesting that more inaccurate probability estimations are more likely to occur under uncertainty conditions. Additionally, both patients and controls showed a greater deviation in the emotional version of the task, providing evidence of a reasoning bias modulated by the content of the stimuli. Finally, a positive correlation between patients' deviation and delusional symptomatology was found. Impairments in the 60:40 ratio with emotional content was related to the amount of disruption in life caused by delusions. These results contribute to the understanding of how cognitive mechanisms interact with characteristics of the task (i.e., ambiguity and content) in the context of delusional thinking. These findings might be used to inform improved intervention programs in the domain of inferential reasoning.