Proc Natl Acad Sci U S A
January 28, 2019
Katrin H. Preller, Adeel Razi, Peter Zeidman et al.
303 citations
LSD alters communication within brain pathways that filter sensory information, according to a brain imaging study. Using a double-blind, placebo-controlled design with 25 healthy participants, researchers found that LSD increased signaling from the thalamus to the posterior cingulate cortex—an effect dependent on serotonin 2A receptor activation—and decreased signaling from the ventral striatum to the thalamus independently of those receptors. These changes in directed connectivity within cortico-striato-thalamo-cortical loops support the thalamic filter model of psychedelic action, which proposes that psychedelics disrupt the gating of sensory information to the cortex. The findings advance understanding of how psychedelics alter consciousness and may inform development of new therapeutics.
bioRxiv Preprint Server
April 10, 2019
Micah Allen, Andrew Levy, Thomas Parr et al.
100 citations
preprint
A formal model of cardiac active inference explains how signals from the heart influence perception of the outside world and confidence in that perception. Simulated experiments reproduce the defensive startle reflex and the link between the cardiac cycle and fear perception. Simulated interoceptive lesions reduce fear expectations, cause psychosomatic hallucinations, and worsen metacognitive biases. Synthetic heart-rate variability analyses show how the balance of arousal-priors and visceral prediction errors creates distinct patterns of physiological reactivity. The model provides a way to computationally characterize disordered brain-body interaction.
Frontiers in Robotics and AI
March 8, 2018
A. Linson, A. Clark, S. Ramamoorthy et al.
94 citations
The active inference framework (AIF) offers a unified, naturalistic account of life, mind, and consciousness by grounding them in the principle of free energy minimization. It bridges computational neuroscience, robotics, ecological psychology, and phenomenology, treating particles, organisms, and artificial agents under a common information-theoretic foundation. The paper introduces AIF, then examines its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics, concluding with considerations for machine consciousness.
Frontiers in Psychology
June 3, 2024
Darius Parvizi-Wayne, Lars Sandved-Smith, Riddhi J. Pitliya et al.
20 citations
Flow is a state of optimal performance experienced across domains like art, athletics, gaming, and writing. Its puzzling features include a reported loss of self-awareness despite skilled agency, and effortlessness despite task complexity. Using the active inference framework—where action and perception minimize variational free energy—the authors propose that flow arises from high precision weighting on expected sensory consequences of action and beliefs about sequential action. This draws the embodied system to exploit pragmatic affordances while restricting counterfactual planning, leading to inhibition of the sense of self as a temporally extended object and higher-order self-conceptualization. However, self-awareness is not entirely lost; it remains pre-reflective and bodily.
Phys Life Rev
July 11, 2025
Simone Battaglia, Philippe Servajean, Karl J. Friston
2 citations
No Summary
PloS one
January 1, 2026
Clement Abbatecola, Bernard Marius ’t Hart, Belén M. Montabes De la Cruz et al.
The subjective experience of space around the visual blind spot is investigated to test three theories of consciousness: Integrated Information Theory (IIT), Predictive Processing Active Inference (AI), and Predictive Processing Neurorepresentationalism (NREP). IIT predicts that the blind spot region, lacking feedforward input from one eye, should contribute differently to perceived spatial quality. The Predictive Processing accounts argue that internal models accommodate structural deviations based on sensory evidence. Participants evaluate distances, areas, and illusory motion with or without the blind spot involved. Psychometric models quantify bias and precision in perceived versus objective space. Simulated results correspond to each theory's predictions, and challenges for dissemination are discussed.
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.