Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.05.16.092304v1?rss=1 Authors: Ziaei, M., Bonyadi, M. R., Reutens, D. Abstract: Prior knowledge and beliefs influence our reasoning in daily life and may lead us to draw unwarranted conclusions with undesirable consequences. The underlying neural correlates of the interaction between belief and logic, prior to making logical decisions, are largely unknown. In this study, we aimed to identify brain regions important in distinguishing belief load of assumptions in logical decision making. Thirty-one healthy volunteers (18-29 years old) participated in an fMRI study and were asked to respond to a series of syllogistic arguments in which assumptions were either congruent (believable) or incongruent (unbelievable) with currently-held beliefs. An interpretable machine learning algorithm, an L1 regularized Support Vector Machine, was used to explain the discriminatory pattern of conditions given the brain activation patterns. Behavioral results confirmed that believable premises were endorsed more than unbelievable ones. Imaging results revealed that the thalamus, superior temporal gyrus, inferior frontal gyrus (IFG), posterior cingulate gyrus, precuneus, insula, and caudate are important in distinguishing belief load. Several connectivity patterns between the insula, amygdala, and IFG were deemed to be important in distinguishing believable from unbelievable assumptions. This is the first study to investigate neural mechanisms important in distinguishing belief load of assumptions using interpretable machine learning. We uncovered brain connections involved in differentiating belief load at different time points preceding the making of a logical decision. Our discovery provides new insights into the interaction between belief load of assumptions and logic systems and has important practical implications for social decisions. Copy rights belong to original authors. Visit the link for more info