Neurocomputational mechanisms of affected beliefs

We are truely excited about our new preprint on #affectedbeliefs! What are affected beliefs? Beliefs are never neutral – they always depend on the context, on the learning experience, on motivations etc. Here we present an attempt of an empirical spell-out of the “value of beliefs” model published by Bromberg-Martín & Sharot in 2020 and show how the formation of performance beliefs is biased by the affect during learning. Biases in belief formation were associated with pupil measures, activity of the AI, amygdala, VTA/SN, and mPFC but also with embarrassment and pride. This reflects the reciprocal relation between the affected (i.e. biased) formation of beliefs and the affective (i.e. emotional) experience during learning.

Abstract

The feedback people receive on their behavior shapes the process of belief formation and self-efficacy in mastering a given task. The neural and computational mechanisms of how the subjective value of these beliefs and corresponding affect bias the learning process are yet unclear. Here we investigate this question during learning of self-efficacy beliefs using fMRI, pupillometry, computational modeling and individual differences in affective experience. Biases in the formation of self-efficacy beliefs were associated with affect, pupil dilation and neural activity within the anterior insula, amygdala, VTA/SN, and mPFC. Specifically, neural and pupil responses map the valence of the prediction errors in correspondence to the experienced affect and learning bias people show during belief formation. Together with the functional connectivity dynamics of the anterior insula within this network our results hint towards neural and computational mechanisms that integrate affect in the process of belief formation.

Authors:

Müller-Pinzler L, Czekalla N, Mayer AV, Schröder A, Stolz DS, Paulus FM, Krach S. Neurocomputational mechanisms of affected beliefs. https://www.biorxiv.org/content/10.1101/2021.10.26.465922v3