Laminar fMRI and computational theories of brain function

NeuroImage
K E StephanJ Heinzle

Abstract

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing.

Citations

Oct 23, 2018·ELife·James J BonaiutoSven Bestmann
Sep 26, 2019·Nature Neuroscience·Emily S FinnPeter A Bandettini
May 21, 2020·Schizophrenia Bulletin·Albert R PowersPhilip R Corlett
Jun 6, 2020·Frontiers in Psychiatry·Zina-Mary Manjaly, Sandra Iglesias
Mar 8, 2021·Schizophrenia Research·Brandon K AshinoffGuillermo Horga
May 1, 2021·Progress in Neurobiology·Kamil Uludag, Martin Havlicek
May 24, 2021·NeuroImage·Viktor PfaffenrotPeter J Koopmans
Aug 22, 2021·Current Biology : CB·Jelle A van DijkSerge O Dumoulin

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