creators_name: Spratling, Michael W type: journale datestamp: 2009-02-13 01:12:14 lastmod: 2011-03-11 08:57:19 metadata_visibility: show title: Reconciling Predictive Coding and Biased Competition Models of Cortical Function ispublished: pub subjects: neuro-mod subjects: comp-neuro-sci subjects: percep-cog-psy subjects: comp-sci-neural-nets full_text_status: public keywords: neural networks; cortical circuits; cortical feedback; biased competition; predictive coding abstract: A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model. date: 2008 date_type: published publication: Frontiers in Computational Neuroscience volume: 2 number: 4 refereed: TRUE citation: Spratling, Michael W (2008) Reconciling Predictive Coding and Biased Competition Models of Cortical Function. [Journal (On-line/Unpaginated)] document_url: http://cogprints.org/6353/1/pc_equals_bc.pdf