Anastasios Ziogas, Andreas Mokros, Wolfram Kawohl, Mateo de Bardeci, Ilyas Olbrich, Benedikt Habermeyer, Elmar Habermeyer, Sebastian Olbrich
Introduction: It is unclear if sexual orientation is a biological trait that has neurofunctional footprints. With deep learning, the power to classify biological datasets without an a priori selection of features has increased by magnitudes. The aim of this study was to correctly classify resting-state electroencephalogram (EEG) data from males with different sexual orientation using deep learning and to explore techniques to identify the learned distinguishing features.
Methods: Three cohorts (homosexual men, heterosexual men, and a mixed sex cohort), one pretrained network on sex classification, and one newly trained network for sexual orientation classification were used to classify sex. Further, Grad-CAM methodology and source localization were used to identify the spatiotemporal patterns that were used for differentiation by the networks.
Results: Using a pretrained network for classification of males and females, no differences existed between classification of homosexual and heterosexual males. The newly trained network was able, however, to correctly classify the cohorts with a total accuracy of 83%. The retrograde activation using Grad-CAM technology yielded distinctive functional EEG patterns in the Brodmann area 40 and 1 when combined with Fourier analysis and a source localization.
Discussion: This study shows that electrophysiological trait markers of male sexual orientation can be identified using deep learning. These patterns are different from the differentiating signatures of males and females in a resting-state EEG.
{"title":"Deep Learning in the Identification of Electroencephalogram Sources Associated with Sexual Orientation.","authors":"Anastasios Ziogas, Andreas Mokros, Wolfram Kawohl, Mateo de Bardeci, Ilyas Olbrich, Benedikt Habermeyer, Elmar Habermeyer, Sebastian Olbrich","doi":"10.1159/000530931","DOIUrl":"https://doi.org/10.1159/000530931","url":null,"abstract":"<p><strong>Introduction: </strong>It is unclear if sexual orientation is a biological trait that has neurofunctional footprints. With deep learning, the power to classify biological datasets without an a priori selection of features has increased by magnitudes. The aim of this study was to correctly classify resting-state electroencephalogram (EEG) data from males with different sexual orientation using deep learning and to explore techniques to identify the learned distinguishing features.</p><p><strong>Methods: </strong>Three cohorts (homosexual men, heterosexual men, and a mixed sex cohort), one pretrained network on sex classification, and one newly trained network for sexual orientation classification were used to classify sex. Further, Grad-CAM methodology and source localization were used to identify the spatiotemporal patterns that were used for differentiation by the networks.</p><p><strong>Results: </strong>Using a pretrained network for classification of males and females, no differences existed between classification of homosexual and heterosexual males. The newly trained network was able, however, to correctly classify the cohorts with a total accuracy of 83%. The retrograde activation using Grad-CAM technology yielded distinctive functional EEG patterns in the Brodmann area 40 and 1 when combined with Fourier analysis and a source localization.</p><p><strong>Discussion: </strong>This study shows that electrophysiological trait markers of male sexual orientation can be identified using deep learning. These patterns are different from the differentiating signatures of males and females in a resting-state EEG.</p>","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10645442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Front & Back Matter","authors":"G. Bologna, P. Monteleone, G. Okugawa","doi":"10.1159/000528497","DOIUrl":"https://doi.org/10.1159/000528497","url":null,"abstract":"","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44079516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Founded 1975 by J. Mendlewicz (Brussels) Since 1983 integrating ‘International Pharmacopsychiatry’, founded 1968 by F.A. Freyhan (New York), N. Petrilowitsch (Mainz), P. Pichot (Paris) Section Editor ‘Biological Psychiatry’ and Associate Editor 1975–2007 J. Mendlewicz (Brussels) Section Editor ‘Pharmacopsychiatry’ and Associate Editor 1990–2006 B. Saletu (Vienna) Section Editor ‘Biological Psychology/Pharmacopsychology’ and Associate Editor 1990– P. Netter (Giessen) Section Editor ‘Pharmacoelectroencephalography’ and Associate Editor 1990–2002 W.M. Herrmann (Berlin), 2003– T. Kinoshita (Osaka) Official Journal of the International Pharmaco-EEG Society (IPEG)
1975年由J. Mendlewicz(布鲁塞尔)创立，1983年开始整合“国际药物精神病学”，1968年由F.A. Freyhan(纽约)，N. Petrilowitsch(美因茨)，P. Pichot(巴黎)“生物精神病学”分科编辑和副编辑1975-2007 J. Mendlewicz(布鲁塞尔)“药物精神病学”分科编辑和副编辑1990 - 2006 B. Saletu(维也纳)“生物心理学/药物心理”分科编辑和副编辑1990 - P. Netter(吉森)“药物脑电图”分科编辑和副编辑1990 - 2002 W.M. Herrmann(柏林)，2003 - T.木下(大阪)国际药物脑电图学会官方杂志(IPEG)
{"title":"Contents Vol. 81, 2022","authors":"P. Monteleone, G. Okugawa","doi":"10.1159/000528492","DOIUrl":"https://doi.org/10.1159/000528492","url":null,"abstract":"Founded 1975 by J. Mendlewicz (Brussels) Since 1983 integrating ‘International Pharmacopsychiatry’, founded 1968 by F.A. Freyhan (New York), N. Petrilowitsch (Mainz), P. Pichot (Paris) Section Editor ‘Biological Psychiatry’ and Associate Editor 1975–2007 J. Mendlewicz (Brussels) Section Editor ‘Pharmacopsychiatry’ and Associate Editor 1990–2006 B. Saletu (Vienna) Section Editor ‘Biological Psychology/Pharmacopsychology’ and Associate Editor 1990– P. Netter (Giessen) Section Editor ‘Pharmacoelectroencephalography’ and Associate Editor 1990–2002 W.M. Herrmann (Berlin), 2003– T. Kinoshita (Osaka) Official Journal of the International Pharmaco-EEG Society (IPEG)","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45718201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Front & Back Matter","authors":"G. Bologna, P. Monteleone, G. Okugawa","doi":"10.1159/000526299","DOIUrl":"https://doi.org/10.1159/000526299","url":null,"abstract":"","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45124351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Front & Back Matter","authors":"T. Fuchs, S. Herpertz, P. Monteleone, G. Okugawa","doi":"10.1159/000525329","DOIUrl":"https://doi.org/10.1159/000525329","url":null,"abstract":"","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42274146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Front & Back Matter","authors":"P. Monteleone, G. Okugawa","doi":"10.1159/000524410","DOIUrl":"https://doi.org/10.1159/000524410","url":null,"abstract":"","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42895867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hanta Bachofner, Konstantin A. Scherer, T. Vanbellingen, S. Bohlhalter, K. Stegmayer, S. Walther
Introduction: Deficits in social interaction and community functioning, including impaired use, performance, and perception of hand gestures, are key features in schizophrenia. A well-established tool to assess gesture deficits is the test of upper limb apraxia (TULIA). However, given its time-consuming application based on video analyses, research has proposed the bedside apraxia screen of TULIA (AST). This study aims to test the validity and reliability of the AST to detect gesture abnormalities at bedside in a sample of 27 patients diagnosed with schizophrenia, schizotypal disorder, acute and transient psychotic disorders, or schizoaffective disorder. Methods: Patients completed the 48-item TULIA and the 12-item AST. Two different raters assessed the AST: one at bedside (online) and the other based on the video recordings. Results: The total AST scores demonstrated a high parallel reliability, moderate inter-rater reliability on a single-item level, and good construct validities. Conclusions: The psychometric properties of the AST suggest it can well be used for the clinical assessment of gesture deficits in schizophrenia. However, when detailed information is required, the AST rated from video or conducting the full TULIA is recommended. The findings call for refining the selection of the TULIA items for a psychosis-AST bedside test to increase specificity.
{"title":"Validation of the Apraxia Screen TULIA (AST) in Schizophrenia","authors":"Hanta Bachofner, Konstantin A. Scherer, T. Vanbellingen, S. Bohlhalter, K. Stegmayer, S. Walther","doi":"10.1159/000523778","DOIUrl":"https://doi.org/10.1159/000523778","url":null,"abstract":"Introduction: Deficits in social interaction and community functioning, including impaired use, performance, and perception of hand gestures, are key features in schizophrenia. A well-established tool to assess gesture deficits is the test of upper limb apraxia (TULIA). However, given its time-consuming application based on video analyses, research has proposed the bedside apraxia screen of TULIA (AST). This study aims to test the validity and reliability of the AST to detect gesture abnormalities at bedside in a sample of 27 patients diagnosed with schizophrenia, schizotypal disorder, acute and transient psychotic disorders, or schizoaffective disorder. Methods: Patients completed the 48-item TULIA and the 12-item AST. Two different raters assessed the AST: one at bedside (online) and the other based on the video recordings. Results: The total AST scores demonstrated a high parallel reliability, moderate inter-rater reliability on a single-item level, and good construct validities. Conclusions: The psychometric properties of the AST suggest it can well be used for the clinical assessment of gesture deficits in schizophrenia. However, when detailed information is required, the AST rated from video or conducting the full TULIA is recommended. The findings call for refining the selection of the TULIA items for a psychosis-AST bedside test to increase specificity.","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45215320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Zech, M. Reichert, U. Ebner-Priemer, H. Tost, M. Rapp, A. Heinz, R. Dolan, M. Smolka, L. Deserno
Introduction: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. Method: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. Results: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that – although more systematic studies are necessary – task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. Conclusion: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.
{"title":"Mobile Data Collection of Cognitive-Behavioral Tasks in Substance Use Disorders: Where Are We Now?","authors":"H. Zech, M. Reichert, U. Ebner-Priemer, H. Tost, M. Rapp, A. Heinz, R. Dolan, M. Smolka, L. Deserno","doi":"10.1159/000523697","DOIUrl":"https://doi.org/10.1159/000523697","url":null,"abstract":"Introduction: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. Method: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. Results: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that – although more systematic studies are necessary – task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. Conclusion: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.","PeriodicalId":19239,"journal":{"name":"Neuropsychobiology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44515509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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