Evaluating the neurophysiological evidence for predictive processing as a model of perception

Walsh, Kevin S, McGovern, David P, Clark, Andy and O'Connell, Redmond G (2020) Evaluating the neurophysiological evidence for predictive processing as a model of perception. Annals of the New York Academy of Sciences. pp. 1-27. ISSN 0077-8923

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Abstract

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long‐standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.

Item Type: Article
Additional Information: Acknowledgements K.S.W. was supported by an Irish Research Council Government of Ireland Postgraduate Scholarship. R.G.O. was supported by Horizon 2020 European Research Council Starting Grant Human Decisions - 63829.
Keywords: Predictive Processing; Perception; Neurophysiology; Sensory Processing; Perceptual Inference.
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Lucy Arnold
Date Deposited: 19 Feb 2020 08:26
Last Modified: 16 Mar 2020 16:45
URI: http://sro.sussex.ac.uk/id/eprint/89978

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Project NameSussex Project NumberFunderFunder Ref
Expecting Ourselves: Embodied Prediction and the Construction of Conscious Experience (XSPECT)UnsetEUROPEAN UNION692739