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Updated: Sep 9, 2025
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Frontoparietal Hubs Leverage Probabilistic Representations and Integrated Uncertainty to Guide Cognitive Flexibility.
Stephanie C Leach1, Hannah Hollow1, Jiefeng Jiang1,2
1Psychological and Brain Sciences, The University of Iowa, Iowa City, IA.
Biorxiv : the Preprint Server for Biology
|September 5, 2025
Summary
The brain integrates internal beliefs and external cues using distinct neural regions. Frontoparietal hubs resolve uncertainty by dynamically adjusting brain connectivity, enabling flexible behavior.
Area of Science:
- Neuroscience
- Cognitive Science
- Computational Modeling
Background:
- Adaptive behavior relies on integrating information from multiple sources, often stochastic and uncertain.
- Neural and computational mechanisms for integrating noisy internal and external information remain largely unknown.
Purpose of the Study:
- To elucidate how brain systems integrate internally maintained and externally cued stochastic information to guide behavior.
- To introduce a computational neuroimaging framework for analyzing information integration.
Main Methods:
- Collected neuroimaging data from healthy adult humans.
- Developed a computational model to estimate trial-by-trial beliefs and integrate them into a joint probability distribution.
- Quantified uncertainty using the entropy of the joint distribution to track beliefs, prediction errors, and updating dynamics.
Main Results:
- Distinct brain regions encode latent state beliefs (anterior middle frontal gyrus, mediodorsal thalamus, inferior parietal lobule) and perceptual beliefs (lateral temporo-occipital areas, intraparietal sulcus, precentral sulcus).
- Integrated information and its entropy converged in frontoparietal hubs (middle frontal gyrus, intraparietal sulcus).
- Entropy adaptively reconfigured connectivity with sensory, motor, premotor, and prediction error circuits.
Conclusions:
- Frontoparietal hubs integrate and resolve distributed uncertainty to guide flexible behavior.
- The findings reveal how frontoparietal systems implement cognitive integration of multiple noisy inputs.
- Distinct neural populations encode internal and external information, which is then integrated by frontoparietal networks.
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