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Attention in the predictive mind
Madeleine Ransom1, Sina Fazelpour1, Christopher Mole1
1Department of Philosophy, University of British Columbia, Vancouver, Canada.
Consciousness and Cognition
|July 9, 2016
Summary
Bayesian prediction error minimization is a popular theory of cognition. However, this study argues it cannot fully explain all forms of voluntary attention, challenging the claim that it is
Area of Science:
- Cognitive Science
- Neuroscience
- Philosophy of Mind
Background:
- The theory of Bayesian prediction error minimization suggests cognition arises from minimizing prediction errors.
- Attention is proposed to function by optimizing the precision of these prediction errors.
Purpose of the Study:
- To evaluate the comprehensive explanatory power of Bayesian prediction error minimization for attention.
- To identify limitations of the Bayesian framework in explaining all facets of voluntary attention.
Main Methods:
- Conceptual analysis of existing theories on Bayesian prediction error minimization and attention.
- Examination of specific phenomena of voluntary attention that may challenge the proposed framework.
Main Results:
- The Bayesian prediction error minimization framework successfully explains several attention-related phenomena.
- Certain forms of voluntary attention present a challenge to the current Bayesian framework, indicating it is not a complete explanation.
Conclusions:
- While powerful, Bayesian prediction error minimization is not a sufficient explanation for all cognitive processes, specifically certain types of voluntary attention.
- The claim that Bayesian prediction error minimization is 'all the brain ever does' is an overstatement.
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