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Related Experiment Video

Updated: Nov 8, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Functional Connectivity During Visuospatial Processing in Schizophrenia: A Classification Study Using Lasso

Stéphane Potvin1,2, Charles-Édouard Giguère1, Adrianna Mendrek3

  • 1Centre de recherche de l'Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada.

Neuropsychiatric Disease and Treatment
|April 23, 2021
PubMed
Summary

Schizophrenia impairs visuospatial processing due to brain region dysconnectivity. This functional connectivity analysis achieved 86.1% classification accuracy, offering insights into cognitive deficits in schizophrenia.

Keywords:
functional connectivitymachine learningmental rotationschizophrenia

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Psychiatry

Background:

  • Schizophrenia is strongly linked to significant cognitive impairments, particularly in visuospatial abilities.
  • While research has explored other cognitive domains, neural correlates of visuospatial deficits in schizophrenia remain understudied.

Purpose of the Study:

  • To investigate functional connectivity during visuospatial processing in schizophrenia.
  • To assess the accuracy of classifying schizophrenia based on observed functional connectivity alterations.

Main Methods:

  • Functional magnetic resonance imaging (fMRI) was used to scan 39 schizophrenia patients and 42 healthy controls during a mental rotation task.
  • Task-based functional connectivity was analyzed using a region-of-interest (ROI) to ROI approach with the CONN Toolbox.
  • Logistic regression with Lasso regularization and train-test cross-validation was employed for classification.

Main Results:

  • Schizophrenia exhibited dysconnectivity between frontal, precentral, parietal, and occipital brain regions.
  • The study achieved a classification accuracy of 86.1% for distinguishing schizophrenia patients.
  • Dysconnectivity between specific frontal and parietal regions predicted mental rotation performance.

Conclusions:

  • Visuospatial processing reveals widespread dysconnectivity in schizophrenia, linking executive, motor, and visual brain networks.
  • Functional connectivity data related to visuospatial tasks can achieve high classification accuracy in schizophrenia.