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The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing

Previous studies suggest there is a complex relationship between sexual and general affective stimulus processing, which varies across individuals and situations. We examined whether sexual and general affective processing can be distinguished at the brain level. In addition, we explored to what deg...

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Autores principales: van ’t Hof, Sophie R, Van Oudenhove, Lukas, Janssen, Erick, Klein, Sanja, Reddan, Marianne C, Kragel, Philip A, Stark, Rudolf, Wager, Tor D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290618/
https://www.ncbi.nlm.nih.gov/pubmed/34905775
http://dx.doi.org/10.1093/cercor/bhab397
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author van ’t Hof, Sophie R
Van Oudenhove, Lukas
Janssen, Erick
Klein, Sanja
Reddan, Marianne C
Kragel, Philip A
Stark, Rudolf
Wager, Tor D
author_facet van ’t Hof, Sophie R
Van Oudenhove, Lukas
Janssen, Erick
Klein, Sanja
Reddan, Marianne C
Kragel, Philip A
Stark, Rudolf
Wager, Tor D
author_sort van ’t Hof, Sophie R
collection PubMed
description Previous studies suggest there is a complex relationship between sexual and general affective stimulus processing, which varies across individuals and situations. We examined whether sexual and general affective processing can be distinguished at the brain level. In addition, we explored to what degree possible distinctions are generalizable across individuals and different types of sexual stimuli, and whether they are limited to the engagement of lower-level processes, such as the detection of visual features. Data on sexual images, nonsexual positive and negative images, and neutral images from Wehrum et al. (2013) (N = 100) were reanalyzed using multivariate support vector machine models to create the brain activation-based sexual image classifier (BASIC) model. This model was tested for sensitivity, specificity, and generalizability in cross-validation (N = 100) and an independent test cohort (N = 18; Kragel et al. 2019). The BASIC model showed highly accurate performance (94–100%) in classifying sexual versus neutral or nonsexual affective images in both datasets with forced choice tests. Virtual lesions and tests of individual large-scale networks (e.g., visual or attention networks) show that individual networks are neither necessary nor sufficient to classify sexual versus nonsexual stimulus processing. Thus, responses to sexual images are distributed across brain systems.
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spelling pubmed-92906182022-07-18 The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing van ’t Hof, Sophie R Van Oudenhove, Lukas Janssen, Erick Klein, Sanja Reddan, Marianne C Kragel, Philip A Stark, Rudolf Wager, Tor D Cereb Cortex Original Article Previous studies suggest there is a complex relationship between sexual and general affective stimulus processing, which varies across individuals and situations. We examined whether sexual and general affective processing can be distinguished at the brain level. In addition, we explored to what degree possible distinctions are generalizable across individuals and different types of sexual stimuli, and whether they are limited to the engagement of lower-level processes, such as the detection of visual features. Data on sexual images, nonsexual positive and negative images, and neutral images from Wehrum et al. (2013) (N = 100) were reanalyzed using multivariate support vector machine models to create the brain activation-based sexual image classifier (BASIC) model. This model was tested for sensitivity, specificity, and generalizability in cross-validation (N = 100) and an independent test cohort (N = 18; Kragel et al. 2019). The BASIC model showed highly accurate performance (94–100%) in classifying sexual versus neutral or nonsexual affective images in both datasets with forced choice tests. Virtual lesions and tests of individual large-scale networks (e.g., visual or attention networks) show that individual networks are neither necessary nor sufficient to classify sexual versus nonsexual stimulus processing. Thus, responses to sexual images are distributed across brain systems. Oxford University Press 2021-12-16 /pmc/articles/PMC9290618/ /pubmed/34905775 http://dx.doi.org/10.1093/cercor/bhab397 Text en © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
van ’t Hof, Sophie R
Van Oudenhove, Lukas
Janssen, Erick
Klein, Sanja
Reddan, Marianne C
Kragel, Philip A
Stark, Rudolf
Wager, Tor D
The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title_full The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title_fullStr The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title_full_unstemmed The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title_short The brain activation-based sexual image classifier (BASIC): a sensitive and specific fMRI activity pattern for sexual image processing
title_sort brain activation-based sexual image classifier (basic): a sensitive and specific fmri activity pattern for sexual image processing
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290618/
https://www.ncbi.nlm.nih.gov/pubmed/34905775
http://dx.doi.org/10.1093/cercor/bhab397
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