Neural dynamics of causal inference in the macaque frontoparietal circuit
Natural perception relies inherently on inferring causal structure in the environment. However, the neural mechanisms and functional circuits essential for representing and updating the hidden causal structure and corresponding sensory representations during multisensory processing are unknown. To address this, monkeys were trained to infer the probability of a potential common source from visual and proprioceptive signals based on their spatial disparity in a virtual reality system. The proprioceptive drift reported by monkeys demonstrated that they combined previous experience and current multisensory signals to estimate the hidden common source and subsequently updated the causal structure and sensory representation. Single-unit recordings in premotor and parietal cortices revealed that neural activity in the premotor cortex represents the core computation of causal inference, characterizing the estimation and update of the likelihood of integrating multiple sensory inputs at a trial-by-trial level. In response to signals from the premotor cortex, neural activity in the parietal cortex also represents the causal structure and further dynamically updates the sensory representation to maintain consistency with the causal inference structure. Thus, our results indicate how the premotor cortex integrates previous experience and sensory inputs to infer hidden variables and selectively updates sensory representations in the parietal cortex to support behavior. This dynamic loop of frontal-parietal interactions in the causal inference framework may provide the neural mechanism to answer long-standing questions regarding how neural circuits represent hidden structures for body awareness and agency.
All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 1-6. Datasets Generated: Code and dataset have been uploaded to Dryad
Code and dataset for neural dynamics of causal inference in the macaque frontoparietal circuitDryad Digital Repository, doi:10.5061/dryad.rr4xgxd9h.
Article and author information
National Science and Technology Innovation 2030 Major Program (2021ZD0204204)
- Wen Fang
Shanghai Municipal Science and Technology Major Project (2021SHZDZX)
- Liping Wang
Lingang Laboratory Grant (LG202105-02-01)
- Liping Wang
Strategic Priority Research Programs (XDB32070201)
- Liping Wang
National Natural Science Foundation of China (32100830)
- Wen Fang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: All animal procedures were approved by the Animal Care Committee of Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences (Permit Number: CEBSIT-2020034).
- Hugo Merchant, National Autonomous University of Mexico, Mexico
- Received: December 6, 2021
- Preprint posted: December 7, 2021 (view preprint)
- Accepted: October 23, 2022
- Accepted Manuscript published: October 24, 2022 (version 1)
- Version of Record published: November 8, 2022 (version 2)
© 2022, Qi et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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