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Doktorandské kolokvium KAI - Milica Kiš (11.5.2026)

v pondelok 11.5.2026 o 13:10 hod. v miestnosti I 9


05. 05. 2026 13.51 hod.
Od: Damas Gruska

Prednášajúci: Milica Kiš

Názov: Computational modeling of the effects of psychedelics on cognitive functions

Termín: 11.5.2026, 13:10 hod., I/9


Abstrakt:
Psychedelics are a class of psychoactive substances known to induce alterations in perception, mood, and cognitive processes. Recent studies have reported promising therapeutic outcomes for several psychiatric conditions, including anxiety, treatment-resistant depression (TRD), and posttraumatic stress disorder (PTSD).

However, the impact of psychedelics on cognitive functions remains insufficiently explored. Computational modeling provides a valuable approach for elucidating the mechanisms underlying psychedelic effects. This project aims to integrate methodologies from computer science (spiking neural networks, entropy measures), physics (criticality theory), mathematics (graph theory), statistics (Bayesian framework), and neuroscience to model, analyze, and investigate the complex dynamics of brain activity under the influence of psychedelics.

The research project will proceed as follows: (1) select a specific cognitive function and replicate its typical operation in a computational model, such as human vision; (2) manipulate the model, informed by existing literature, to reproduce psychedelic effects, such as visual hallucinations; (3) hypothesize emergent properties within the system, for example, an increase in entropy; (4) quantify, analyze, and validate findings using appropriate measures and metrics grounded in established literature, such as entropy measures; (5) compare and refine the models based on the results. If possible, the final step will involve validating the model against externally obtained experimental data or open-source datasets.

We are currently focusing on reproducing psychedelic effects in the domain of human vision, specifically visual hallucinations, by manipulating precision in a hierarchical predictive coding model.

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