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Neural network models for DMT-induced visual hallucinations

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...

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Autores principales: Schartner, Michael M, Timmermann, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734438/
https://www.ncbi.nlm.nih.gov/pubmed/33343929
http://dx.doi.org/10.1093/nc/niaa024
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author Schartner, Michael M
Timmermann, Christopher
author_facet Schartner, Michael M
Timmermann, Christopher
author_sort Schartner, Michael M
collection PubMed
description 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.
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spelling pubmed-77344382020-12-17 Neural network models for DMT-induced visual hallucinations Schartner, Michael M Timmermann, Christopher Neurosci Conscious Spotlight Commentaries 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. Oxford University Press 2020-12-12 /pmc/articles/PMC7734438/ /pubmed/33343929 http://dx.doi.org/10.1093/nc/niaa024 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Spotlight Commentaries
Schartner, Michael M
Timmermann, Christopher
Neural network models for DMT-induced visual hallucinations
title Neural network models for DMT-induced visual hallucinations
title_full Neural network models for DMT-induced visual hallucinations
title_fullStr Neural network models for DMT-induced visual hallucinations
title_full_unstemmed Neural network models for DMT-induced visual hallucinations
title_short Neural network models for DMT-induced visual hallucinations
title_sort neural network models for dmt-induced visual hallucinations
topic Spotlight Commentaries
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734438/
https://www.ncbi.nlm.nih.gov/pubmed/33343929
http://dx.doi.org/10.1093/nc/niaa024
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