Date created: | Last Updated:

Category: Project

Description: Psychedelic research has remerged within the last three decades after a hiatus of more than twenty-five years. Recent findings suggest that the psychedelic state is a high-entropy state and this entropic state leads to a richer repertoire of dynamical brain states that are less predictable in their functioning. Moreover, via their entropic effect on spontaneous cortical activity, psychedelics work to relax the precision weighting of high-level priors or beliefs, thus freeing bottom-up information flow, as put forward by the relaxed beliefs under psychedelics (REBUS) and the anarchic brain model. This effect of psychedelics on the brain makes them impressive tools to examine the complex neural mechanisms underlying cognitive and emotional processes, as they lead to the loosening of the brain’s priors by impairing the top-down function of the highest level of the brain’s functional hierarchy. This mind-manifesting action of psychedelics can be framed in terms of the predictive coding framework and advance our understanding of the neural mechanisms underlying uniquely human cognitive processes in health and disease. However, certain cognitive processes central to human cognition and conscious experience are largely unexplored in the psychedelic state and the predictive coding framework. Language processing and self-related processing are such processes. These processes are disrupted and altered greatly by psychedelics and in psychiatric and neurodevelopmental disorders such as psychosis, schizophrenia, and ASD as well. The neural mechanisms of these disruptions in the psychedelic state and the previously mentioned disorders share some commonalities, as suggested by REBUS and the anarchic brain model. Therefore, this project aims to explore these processes in the psychedelic state and advance our understanding of them, with four studies focusing on semantic processing, self-other processing, speech categorization, and sensory-motor integration during speech production using neuroimaging, naturalistic and ecologically valid measures, and advanced data analysis methods. This project is being supported by the Heffter Institute Young Investigator Program Grant.