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Conscious and nonconscious thought: Insights from the neuroscience of decision-making

N. Shadlen Michael

Proceedings of the National Academy of Sciences May 26, 2026 DOI: 10.1073/pnas.2601239123 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Topics Philosophy of mind
Keywords Qualia Narrative Perception Action physics Experiential learning Mechanism biology Consciousness Variety cybernetics Space punctuation Cognitive science Epistemology Cognitive psychology Intentionality Interpretation philosophy
Key points Argues that conscious thought arises from a distinctive use of neural representations already engaged in nonconscious thought, rather than from a unique mechanism.

Abstract

Conscious thought is often treated as a special class of neural processing, distinct from the nonconscious computations that guide most behavior. Here I offer a different perspective, grounded in the neuroscience of decision-making. I argue that conscious thought arises not from a unique mechanism but from a distinctive use of neural representations already engaged in nonconscious thought. Nonconscious thoughts are structured as interrogations that yield provisional intentions-decision-like commitments that guide action or inquiry without entering awareness. Using examples from perceptual decision-making and neurophysiology, I suggest that such thoughts depend on persistent neural representations that encode not only potential actions but the questions that give them meaning. These knowledge states may also preserve source-sensitive structure that supports a minimal experiential organization even when they remain nonconscious. Conscious thought, on this account, emerges when such a state is reformatted for potential report to another mind, or to oneself, recruiting theory of mind and narrative structure and placing its content in a space presumed to be shared. This proposal identifies a tractable bridge from nonconscious decision mechanisms to phenomenal consciousness, thereby placing part of the hard problem within empirical reach.

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