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Hallucinogens are psychoactive substances that profoundly alter perceptual experiences, generating unreal visual and sensory images. Often referred to as psychedelic drugs — a term derived from the Greek words "psyche" (mind) and "delos" (revealing) — these substances include marijuana and lysergic acid diethylamide (LSD), among others. These drugs vary in intensity and effects.
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Hallucinogens, also known as psychedelic drugs, are a class of substances known for their ability to alter perception, cognition, and emotions. Despite their profound effects on the mind, these drugs are non-addictive, setting them apart from many other abused substances. The mechanism of action of these drugs lies in their impact on the 5-HT2A receptor in the brain. Upon activation, this receptor couples to Gq-type G proteins, triggering a cascade that releases intracellular calcium. This...
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Psychedelics and schizophrenia: Distinct alterations to Bayesian inference.

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Schizophrenia and drug-induced states show similar neural signal diversity but differ in brain information flow. Schizophrenia increases front-to-back brain communication, while drugs decrease it, offering insights into consciousness and mental health treatments.

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Computational Biology

Background:

  • Schizophrenia and psychotomimetic drug states share some properties but differ fundamentally.
  • Understanding these altered states of consciousness is crucial for mental health research.
  • LSD and ketamine are being explored for therapeutic potential in mental illnesses.

Purpose of the Study:

  • To compare neural dynamics in schizophrenia with those induced by LSD and ketamine in healthy volunteers.
  • To investigate differences in brain information processing between schizophrenia and drug-induced states.
  • To model these neural changes using a predictive processing framework.

Main Methods:

  • Resting-state M/EEG recordings were used to observe neural dynamics.
  • Analysis included neural signal diversity and transfer entropy.
  • A computational model based on Bayesian inference and predictive processing was employed.

Main Results:

  • Both schizophrenia and drug-induced states showed increased neural signal diversity.
  • Schizophrenia exhibited increased front-to-back brain transfer entropy.
  • LSD and ketamine showed an overall reduction in transfer entropy.

Conclusions:

  • Neural dynamics in schizophrenia and drug-induced states diverge in information flow patterns.
  • Altered Bayesian inference, specifically prior precision (drugs) versus sensory precision (schizophrenia), underlies these differences.
  • Findings offer insights into consciousness and potential therapeutic strategies for mental health conditions.