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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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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. |
format | Online Article Text |
id | pubmed-7734438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT schartnermichaelm neuralnetworkmodelsfordmtinducedvisualhallucinations AT timmermannchristopher neuralnetworkmodelsfordmtinducedvisualhallucinations |