Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression

Stéphane Potvin,1,2 Charles-Édouard Giguère,1 Adrianna Mendrek3 1Centre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada; 2Department of Psychiatry and Addiction, Faculty of Medicine, Univ...

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Autores principales:	Potvin S, Giguère CÉ, Mendrek A
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2021
Materias:	schizophrenia - mental rotation - functional connectivity - machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/44aa5c5709434a1195fc3370f8888826
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spelling	oai:doaj.org-article:44aa5c5709434a1195fc3370f88888262021-12-02T18:02:21ZFunctional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression1178-2021https://doaj.org/article/44aa5c5709434a1195fc3370f88888262021-04-01T00:00:00Zhttps://www.dovepress.com/functional-connectivity-during-visuospatial-processing-in-schizophreni-peer-reviewed-article-NDThttps://doaj.org/toc/1178-2021Stéphane Potvin,1,2 Charles-Édouard Giguère,1 Adrianna Mendrek3 1Centre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada; 2Department of Psychiatry and Addiction, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada; 3Department of Psychology, Bishop’s University, Lennoxville, Quebec, CanadaCorrespondence: Stéphane PotvinCentre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, 7331 Hochelaga, Montreal, Quebec, H1N 3V2, CanadaEmail stephane.potvin@umontreal.caBackground: Robust evidence shows that schizophrenia is associated with significant cognitive impairments, including deficits in visuospatial abilities. While other cognitive domains have sparked several functional neuroimaging studies in schizophrenia, only a few brain activation studies have examined the neural correlates of visuospatial abilities in schizophrenia.Purpose: Here, we propose to perform a functional connectivity study on visuospatial processing in schizophrenia, and to determine the classification accuracy of the observed alterations.Methods: Thirty-nine schizophrenia patients and 42 healthy controls were scanned using functional magnetic resonance imaging while performing a mental rotation task. Task-based functional connectivity was examined using a region-of-interest (ROI) to ROI approach, as implemented in the CONN Toolbox. ROIs were selected from a previous meta-analysis on mental rotation. Logistic regression with Lasso regularization was performed, using train-test cross-validation.Results: Schizophrenia was associated with a complex pattern of dysconnectivity between the superior, middle and inferior frontal gyrus, the precentral gyrus, the superior parietal lobule (SPL) and the inferior lateral occipital cortex. The classification accuracy was 86.1%. Mental rotation performance was predicted by the dysconnectivity between the right and left superior frontal gyrus (SFG), as well as between the left SFG and left SPL.Conclusion: The results of the current study highlight that visuospatial processing is useful for examining the widespread dysconnectivity between executive, motor and visual brain regions in schizophrenia. We also demonstrate that very good classification accuracy can be achieved using visuospatial-related functional connectivity data.Keywords: schizophrenia, mental rotation, functional connectivity, machine learningPotvin SGiguère CÉMendrek ADove Medical Pressarticleschizophrenia - mental rotation - functional connectivity - machine learningNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571Neurology. Diseases of the nervous systemRC346-429ENNeuropsychiatric Disease and Treatment, Vol Volume 17, Pp 1077-1087 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	schizophrenia - mental rotation - functional connectivity - machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429
spellingShingle	schizophrenia - mental rotation - functional connectivity - machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429 Potvin S Giguère CÉ Mendrek A Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
description	Stéphane Potvin,1,2 Charles-Édouard Giguère,1 Adrianna Mendrek3 1Centre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada; 2Department of Psychiatry and Addiction, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada; 3Department of Psychology, Bishop’s University, Lennoxville, Quebec, CanadaCorrespondence: Stéphane PotvinCentre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, 7331 Hochelaga, Montreal, Quebec, H1N 3V2, CanadaEmail stephane.potvin@umontreal.caBackground: Robust evidence shows that schizophrenia is associated with significant cognitive impairments, including deficits in visuospatial abilities. While other cognitive domains have sparked several functional neuroimaging studies in schizophrenia, only a few brain activation studies have examined the neural correlates of visuospatial abilities in schizophrenia.Purpose: Here, we propose to perform a functional connectivity study on visuospatial processing in schizophrenia, and to determine the classification accuracy of the observed alterations.Methods: Thirty-nine schizophrenia patients and 42 healthy controls were scanned using functional magnetic resonance imaging while performing a mental rotation task. Task-based functional connectivity was examined using a region-of-interest (ROI) to ROI approach, as implemented in the CONN Toolbox. ROIs were selected from a previous meta-analysis on mental rotation. Logistic regression with Lasso regularization was performed, using train-test cross-validation.Results: Schizophrenia was associated with a complex pattern of dysconnectivity between the superior, middle and inferior frontal gyrus, the precentral gyrus, the superior parietal lobule (SPL) and the inferior lateral occipital cortex. The classification accuracy was 86.1%. Mental rotation performance was predicted by the dysconnectivity between the right and left superior frontal gyrus (SFG), as well as between the left SFG and left SPL.Conclusion: The results of the current study highlight that visuospatial processing is useful for examining the widespread dysconnectivity between executive, motor and visual brain regions in schizophrenia. We also demonstrate that very good classification accuracy can be achieved using visuospatial-related functional connectivity data.Keywords: schizophrenia, mental rotation, functional connectivity, machine learning
format	article
author	Potvin S Giguère CÉ Mendrek A
author_facet	Potvin S Giguère CÉ Mendrek A
author_sort	Potvin S
title	Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
title_short	Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
title_full	Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
title_fullStr	Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
title_full_unstemmed	Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression
title_sort	functional connectivity during visuospatial processing in schizophrenia: a classification study using lasso regression
publisher	Dove Medical Press
publishDate	2021
url	https://doaj.org/article/44aa5c5709434a1195fc3370f8888826
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Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso Regression

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