Frontal cortex function as derived from hierarchical predictive coding

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 i...

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Vydané v:Scientific reports Ročník 8; číslo 1; s. 3843 - 11
Hlavní autori: Alexander, William H., Brown, Joshua W.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 01.03.2018
Nature Publishing Group
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ISSN:2045-2322, 2045-2322
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Shrnutí: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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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-018-21407-9