Frontal cortex function as derived from hierarchical predictive coding

Scientific Reports
William H Alexander, Joshua W Brown

Abstract

The frontal lobes are essential for human volition and goal-directed behavior, yet their function remains unclear. While various models have highlighted working memory, reinforcement learning, and cognitive control as key functions, a single framework for interpreting the range of effects observed in prefrontal cortex has yet to emerge. Here we show that a simple computational motif based on predictive coding can be stacked hierarchically to learn and perform arbitrarily complex goal-directed behavior. The resulting Hierarchical Error Representation (HER) model simulates a wide array of findings from fMRI, ERP, single-units, and neuropsychological studies of both lateral and medial prefrontal cortex. By reconceptualizing lateral prefrontal activity as anticipating prediction errors, the HER model provides a novel unifying account of prefrontal cortex function with broad implications for understanding the frontal cortex across multiple levels of description, from the level of single neurons to behavior.

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Citations

Oct 28, 2018·Journal of Neurology, Neurosurgery, and Psychiatry·Campbell Le HeronMasud Husain
Mar 26, 2019·ChemSusChem·Qun Zhao, Michal Szostak
Sep 29, 2019·Journal of Vision·Milosz KralaFrank Bremmer
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Jan 5, 2019·Cognitive, Affective & Behavioral Neuroscience·Eliana VassenaWilliam H Alexander
Feb 6, 2020·PLoS Computational Biology·Hadar Levi-AharoniNaftali Tishby
Aug 20, 2020·Cognitive, Affective & Behavioral Neuroscience·Diamantis Petropoulos PetalasHein T van Schie
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Dec 1, 2020·Brain and Cognition·Emiliano ZaccarellaAngela D Friederici
Oct 22, 2020·Biological Psychiatry : Cognitive Neuroscience and Neuroimaging·Sophie C A BrolsmaRoshan Cools
Feb 23, 2021·Frontiers in Computational Neuroscience·William H Alexander, Thilo Womelsdorf
Jun 8, 2021·Frontiers in Artificial Intelligence·Sascha FrölichStefan J Kiebel
Jun 29, 2021·Frontiers in Neural Circuits·Norbert Hájos

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