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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 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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41467-025-64702-6

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Role:
Author
ORCID:
0000-0001-9761-7784
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Role:
Author
ORCID:
0000-0002-6061-0084
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Role:
Author
ORCID:
0000-0003-0163-5609
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Role:
Author
ORCID:
0000-0003-4108-2105
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Role:
Author
ORCID:
0000-0002-0404-4399


Publisher:
Nature Research
Journal:
Nature Communications More from this journal
Volume:
16
Issue:
1
Pages:
9737-9737
Publication date:
2025-11-04
DOI:
EISSN:
2041-1723
ISSN:
2041-1723


Language:
English
Pubs id:
2329118
Local pid:
pubs:2329118
Source identifiers:
W4415880284
Deposit date:
2025-11-22
ARK identifier:
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