Neural network models for DMT-induced visual hallucinations
Michael Schartner, Christopher Timmermann
Neuroscience of Consciousness 2020 DOI: 10.1093/nc/niaa024 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Serotonin DMT |
| Keywords | Visual hallucination Cognitive psychology Sensory system Visual perception Sensory gating Cognitive science |
| Citations | 17 |
| Key points | Proposes that generative deep neural networks can serve as a medium to illustrate phenomenological visual effects of psychedelics and to conceptualize serotonergic gating of exogenous and endogenous information in visual perception. |
Abstract
Abstract The regulatory role of the serotonergic system on conscious perception can be investigated perturbatorily with psychedelic drugs such as N,N-Dimethyltryptamine. There is increasing evidence that the serotonergic system gates prior (endogenous) and sensory (exogenous) information in the construction of a conscious experience. Using two generative deep neural networks as examples, we discuss how such models have the potential to be, firstly, an important medium to illustrate phenomenological visual effects of psychedelics—besides paintings, verbal reports and psychometric testing—and, secondly, their utility to conceptualize biological mechanisms of gating the influence of exogenous and endogenous information on visual perception.