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Christopher J. Whyte

7 papers in the library · 27 citations · publishing 2020-2026

Papers

An active inference model of conscious access: How cognitive action selection reconciles the results of report and no-report paradigms.

Current Research in Neurobiology January 1, 2022 Christopher J. Whyte, Jakob Hohwy, Ryan Smith 21 citations

Cognitive theories of consciousness link frontoparietal circuits to conscious access, but no-report paradigms challenge this by showing conscious accessibility without prefrontal cortex (PFC) activation. This paper presents a computational model based on active inference, treating working memory gating as a cognitive action. Simulating a visual masking task, the model shows that late P3b-like event-related potentials and increased PFC activity arise from the working memory demands of self-report generation. Removing reporting demands eliminates these late potentials and reduces PFC activity, reproducing no-report paradigm results. However, even without reporting, simulated PFC activity on visible trials still crosses the threshold for reportability, maintaining the link between PFC and conscious access. Thus, no-report paradigm evidence does not necessarily contradict cognitive theories.

On the minimal theory of consciousness implicit in active inference.

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.

The role of active inference in conscious awareness

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.

A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.

Neuroscience of Consciousness January 1, 2026 Annie G Bryant, Christopher J. Whyte

A family of functional connectivity measures based on tracking the 'center of mass' between two brain signals outperforms other measures at decoding conscious visual perception from magnetoencephalography data. These measures generalize across brain regions central to both Integrated Information Theory and Global Neuronal Workspace Theory. Neural mass models simulating each theory's hypothesized dynamics showed that both the GNWT-based model (featuring delayed ignition dynamics) and the IIT-based model (relying on synchronous sensory dynamics) captured the observed connectivity patterns. However, the presence of ignition dynamics independent of task-demand conditions contradicts IIT predictions, lending tentative support to GNWT. The work introduces a framework for systematically identifying and testing neural correlates of conscious vision.

On the Minimal Theory of Consciousness Implicit in Active Inference

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.

A thalamocortical substrate for integrated information via critical synchronous bursting.

Proceedings of the National Academy of Sciences of the United States of America November 14, 2023 Brandon R Munn, Eli J Müller, Jaan Aru et al.

Integrated information, a proposed signature of consciousness, is maximized in a biophysical network model when the nonspecific thalamus drives thick-tufted layer 5 pyramidal neurons into a regime of time-varying synchronous bursting. In this regime, variable spiking dynamics with broad pairwise correlations support enhanced integrated information. The peak in integrated information coincides with criticality signatures and empirically observed layer 5 pyramidal bursting rates. These findings suggest that the thalamocortical core of the mammalian brain may be evolutionarily configured to optimize effective information processing, offering a potential neuronal mechanism linking microscale theories to macroscale signatures of consciousness.

The Predictive Global Neuronal Workspace: A Formal Active Inference Model of Visual Consciousness

bioRxiv Preprint Server February 11, 2020 Christopher J. Whyte, Ryan Smith preprint

A new computational model called the 'predictive global workspace' combines ideas from the global neuronal workspace (GNW) theory of consciousness with Active Inference, a framework that treats brain activity as Bayesian inference. The model reproduces electrophysiological and behavioral results from studies of inattentional blindness and a four-way taxonomy linking consciousness, attention, and sensory signal strength. It also reconciles conflicting findings, extends the taxonomy to include prior expectations, and suggests new experimental paradigms. The model addresses limitations of current GNW research by enabling precise, testable predictions at both behavioral and neural levels.