Rats treated with psilocybin achieved more rewards in a decision-making task, driven by increased task engagement, altered forgetting rates, and reduced loss aversion. Computational modeling of the rats' behavior revealed that psilocybin may induce an optimism bias through changes in how beliefs are updated. This finding has potential relevance for clinical populations characterized by a lack of optimism, such as those with depression.
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.
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.