Computational signatures of uncertainty are reflected in motor cortex excitatory neurochemistry

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 glutamate+ glutamine levels and prediction errors and volatility beliefs. High trait anxiety is associated with faster post-reversal responses. This study establishes a direct neurochemical correlate of hierarchical belief updating, identifying motor cortex glutamate + glutamine as an important neural marker of inter-individual differences in uncertainty processing.

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Publication Details

Journal
Nature Communications
Published
2025-11-04
DOI
https://doi.org/10.1038/s41467-025-64702-6
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Computational signatures of uncertainty are reflected in motor cortex excitatory neurochemistry

Christopher T. Rodgers, Owen Parsons, Christoph D. Mathys, John Suckling et al.
Nature Communications
Neural and Behavioral Psychology Studies
article

Computational signatures of uncertainty are reflected in motor cortex excitatory neurochemistry

Christopher T. Rodgers, Owen Parsons, Christoph D. Mathys, John Suckling, Rebecca Lawson, Simon Baron‐Cohen, Peter Thestrup Waade, Frederike H. Petzschner, Nazia Jassim, Catarina Rua
article en

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 glutamate+ glutamine levels and prediction errors and volatility beliefs. High trait anxiety is associated with faster post-reversal responses. This study establishes a direct neurochemical correlate of hierarchical belief updating, identifying motor cortex glutamate + glutamine as an important neural marker of inter-individual differences in uncertainty processing.

Nature CommunicationsVol. 16(1)
Allen Institute for Brain Science (US), Aarhus University (DK), University of Cambridge (GB), Brown University (US), Perceptive Engineering (United Kingdom) (GB)
Wellcome Trust, Dell EMC, Simons Foundation Autism Research Initiative, National Institute for Health and Care Research, Lister Institute of Preventive Medicine, Medical Research Council, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council, Newnham College, University of Cambridge
Openalex Percentile: Top 68%
Neural and Behavioral Psychology Studies
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