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Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Bidirectional connectivity alterations in schizophrenia: a multivariate, machine-learning approach.

Minhoe Kim¹, Ji Won Seo², Seokho Yun³

¹Computer Convergence Software Department, Korea University, Sejong, Republic of Korea.

Frontiers in Psychiatry

|September 25, 2023

Summary

This summary is machine-generated.

Altered functional connectivity is key in schizophrenia. This study found that while both increased and decreased connectivity patterns exist, decreased resting-state functional connectivity (rsFC) in the motor network was most consistent across patients.

Keywords:

connectome-based predictive modeling machine learning multivariate analysis resting state functional connectivity schizophrenia

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Area of Science:

Neuroimaging
Psychiatry
Computational Neuroscience

Background:

Altered functional connectivity is a known neuroimaging marker in schizophrenia.
Inconsistent findings exist regarding the direction (increased or decreased) of these connectivity alterations.

Purpose of the Study:

To determine the direction of functional connectivity alterations in schizophrenia using a data-driven approach.
To investigate the predictive power of increased, decreased, and combined resting-state functional connectivity (rsFC) patterns.

Main Methods:

Utilized resting-state functional magnetic resonance imaging (rsFC) data from individuals with schizophrenia and controls across two datasets.
Employed a modified connectome-based predictive model (CPM) with support vector machine (SVM) for classification.
Analyzed three feature sets: increased rsFC, decreased rsFC, and both.

Main Results:

Combining increased and decreased rsFC significantly improved prediction accuracy in both datasets.
The prediction model using decreased rsFC demonstrated the best performance across datasets.
Decreased rsFC patterns were primarily localized within the motor network.

Conclusions:

Schizophrenia is associated with bidirectional alterations in rsFC.
Decreased rsFC patterns show greater consistency across different populations and may be a more robust marker.