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Why does it feel good to be sure? A unifying framework of decision confidence and affect

Human decisions are accompanied by a sense of confidence. Confidence is often described as a feeling, which can either be positive or negative. Although the computations of confidence in simple decisions are relatively well understood, the affective aspect of confidence remains unexplained. In this project, we propose to integrate models of decision confidence with affective science theories and develop an integrative framework that accounts for affect as well as confidence. For this, we translate our theory into a mathematical model, which allows us to generate model predictions concerning confidence and affect judgments. These predictions will be tested in a novel perceptual decision-making task, in which both behavioral reports will be collected, as well as electrophysiological measures of brain activity and facial muscle activity which are known to reflect confidence and affect, respectively. Understanding the interplay between confidence and affect is crucial, because it elucidates important consequences of human decision making. This knowledge is of critical importance, because it has the potential to develop interventions for overconfidence (e.g., as seen in gambling disorders) and underconfidence (e.g., as seen in anxiety disorders).
Date:1 Oct 2021 →  Today
Keywords:Decision making, Decision confidence, Affect, Drift diffusion modeling, Computational modeling
Disciplines:Mathematical psychology, Cognitive processes, Psychophysiology