Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

Abstract Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in n...

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Autores principales:	Jelena Trajkovic, Francesco Di Gregorio, Francesca Ferri, Chiara Marzi, Stefano Diciotti, Vincenzo Romei
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7c3d266cbfe349078e0e1d7a6dc2e570
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spelling	oai:doaj.org-article:7c3d266cbfe349078e0e1d7a6dc2e5702021-12-02T15:45:21ZResting state alpha oscillatory activity is a valid and reliable marker of schizotypy10.1038/s41598-021-89690-72045-2322https://doaj.org/article/7c3d266cbfe349078e0e1d7a6dc2e5702021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89690-7https://doaj.org/toc/2045-2322Abstract Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals).Jelena TrajkovicFrancesco Di GregorioFrancesca FerriChiara MarziStefano DiciottiVincenzo RomeiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jelena Trajkovic Francesco Di Gregorio Francesca Ferri Chiara Marzi Stefano Diciotti Vincenzo Romei Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
description	Abstract Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals).
format	article
author	Jelena Trajkovic Francesco Di Gregorio Francesca Ferri Chiara Marzi Stefano Diciotti Vincenzo Romei
author_facet	Jelena Trajkovic Francesco Di Gregorio Francesca Ferri Chiara Marzi Stefano Diciotti Vincenzo Romei
author_sort	Jelena Trajkovic
title	Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
title_short	Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
title_full	Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
title_fullStr	Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
title_full_unstemmed	Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
title_sort	resting state alpha oscillatory activity is a valid and reliable marker of schizotypy
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7c3d266cbfe349078e0e1d7a6dc2e570
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Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

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