title: Predictive coding as a model of biased competition in visual attention.
abstract: Attention acts, through cortical feedback pathways, to enhance the response of cells encoding expected or predicted information. Such observations are inconsistent with the predictive coding theory of cortical function which proposes that feedback acts to suppress information predicted by higher-level cortical regions. Despite this discrepancy, this article demonstrates that the predictive coding model can be used to simulate a number of the effects of attention. This is achieved via a simple mathematical rearrangement of the predictive coding model, which allows it to be interpreted as a form of biased competition model. Nonlinear extensions to the model are proposed that enable it to explain a wider range of data.
authors.affiliation: Division of Engineering, King's College, London, UK. michael.spratling@kcl.ac.uk <michael.spratling@kcl.ac.uk>
authors.forename: M W
authors.initials: MW
authors.lastname: Spratling
mesh_terms: D001288:Attention / Q000502:physiology*; D003463:Cues; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D010775:Photic Stimulation; D014793:Visual Cortex / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*