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Frontal cortex function as derived from hierarchical predictive coding.

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.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Alexander WH,Brown JW

doi

10.1038/s41598-018-21407-9

subject

Has Abstract

pub_date

2018-03-01 00:00:00

pages

3843

issue

1

issn

2045-2322

pii

10.1038/s41598-018-21407-9

journal_volume

8

pub_type

杂志文章

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