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Reality monitoring decision policies and the slowness of consciousness.

Megan A. K. Peters

The Behavioral and brain sciences June 25, 2026 DOI: 10.1017/s0140525x25103075 (opens in new tab) via PubMed

Summary

AI-generated from the abstract

Conscious vision may stem from a reality monitoring mechanism that evolved to distinguish planning from perception. The standard model assumes a slow, winner-take-all strategy that tags only one representation as real. This paper argues that expectations about environmental stability could conceal alternative decision policies, which would have important consequences for learning and for understanding how consciousness evolved and what it does.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Key finding Argues that the reality monitoring decision policy implied by Fleming and Michel—a slow, winner-take-all strategy—may mask alternative policies with implications for learning and the evolutionary emergence of consciousness.

Abstract

Fleming and Michel suggest that conscious vision reflects a reality monitoring (RM) mechanism that evolved to separate planning from perception. Here, I critically examine the RM decision policy implied by the authors - a slow, winner-take-all strategy tagging only one first-order representation as "real." Specifically, I explore how expectations about environmental or reality-tagging stability may mask alternative RM decision policies, with important implications for learning and the evolutionary emergence and function of consciousness.

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