Physics of life reviews
March 1, 2026
Christopher J Whyte, Andrew W Corcoran, Jonathan Robinson et al.
5 citations
Subjective experience is multifaceted, making it hard for traditional neuroscientific theories of consciousness to be compared because each focuses on different aspects like perceptual awareness or global states. This work instead starts from active inference, a first-principles framework that models behavior as approximate Bayesian inference, and builds a minimal theory of consciousness from shared features of computational models derived under active inference. By reviewing studies that apply active inference models to consciousness, the authors identify a small set of theoretical commitments implicit in these models, pointing toward a minimal and testable theory of consciousness.
PLoS ONE
December 4, 2025
Jonathan Robinson, Andrew W. Corcoran, Christopher J. Whyte et al.
1 citation
Active inference, a framework for modeling how sentient agents behave, is being tested as necessary for changes in conscious content. In an adversarial collaboration, active inference will be contrasted with two other theories that do not require it for consciousness. This study protocol describes an adaptation of the motion-induced blindness paradigm: an active condition where participants direct their gaze toward a target after it disappears from consciousness and report its reappearance, versus a passive condition where participants fixate centrally while the stimulus array moves in a replay of active eye-tracking data. Two experiments will compare target reappearance across conditions to evaluate active inference's contribution to conscious awareness.
arXiv Preprint Archive
October 9, 2024
Christopher J. Whyte, Andrew W. Corcoran, Jonathan Robinson et al.
Subjective experience is multifaceted, making consciousness hard to study because traditional theories often focus on isolated aspects like perception or wakefulness and are difficult to compare. This work starts from active inference—a first-principles framework that models behavior as approximate Bayesian inference—and builds toward a minimal theory of consciousness derived from shared features of computational models under active inference. Reviewing models applied to consciousness, the authors argue that these models imply a small set of theoretical commitments pointing to a minimal, testable theory of consciousness.