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Attention in the predictive mind.

Madeleine Ransom, Sina Fazelpour, Christopher Mole

Consciousness and Cognition 2017 DOI: 10.1016/j.concog.2016.06.011 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Hohwy Philosophy of perception Prediction-error coding Voluntary attention
Citations 38
Key points Argues that Bayesian prediction error minimization cannot account for all forms of voluntary attention, contrary to claims that it explains all brain activity.

Abstract

It has recently become popular to suggest that cognition can be explained as a process of Bayesian prediction error minimization. Some advocates of this view propose that attention should be understood as the optimization of expected precisions in the prediction-error signal (Clark, 2013, 2016; Feldman & Friston, 2010; Hohwy, 2012, 2013). This proposal successfully accounts for several attention-related phenomena. We claim that it cannot account for all of them, since there are certain forms of voluntary attention that it cannot accommodate. We therefore suggest that, although the theory of Bayesian prediction error minimization introduces some powerful tools for the explanation of mental phenomena, its advocates have been wrong to claim that Bayesian prediction error minimization is 'all the brain ever does'.