Computational signatures of uncertainty are reflected in motor cortex excitatory neurochemistry.

ABSTRACT: How individuals process and respond to uncertainty has important implications for cognition and mental health. Here, we use computational phenotyping to examine inter-individual differences in uncertainty processing in relation to neurometabolites and trait anxiety in humans. We introduce a categorical state-transition extension of the Hierarchical Gaussian Filter to model individuals' evolving beliefs about transition probabilities in a four-choice probabilistic sensorimotor learning task with a reversal. Using 7-Tesla Magnetic Resonance Spectroscopy, we measure neurotransmitter levels in the primary motor cortex. Model-based results reveal dynamic belief updating in response to environmental changes. We further find region-specific relationships between baseline primary motor cortex glut

SUBMITTER: Jassim N 

PROVIDER: S-EPMC12586698 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature