"a unique nonlinear network [..] exhibits hypoconnectivity in schizophrenia"

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A paper published yesterday, 21 Nov 2024:

# Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls

Schizophrenia is a chronic brain disorder associated with widespread alterations in functional brain connectivity. Although data-driven approaches such as independent component analysis are often used to study how schizophrenia impacts linearly connected networks, alterations within the underlying nonlinear functional connectivity structure remain largely unknown. Here we report the analysis of networks from explicitly nonlinear functional magnetic resonance imaging connectivity in a case–control dataset. We found systematic spatial variation, with higher nonlinear weight within core regions, suggesting that linear analyses underestimate functional connectivity within network centers. We also found that a unique nonlinear network incorporating default-mode, cingulo-opercular and central executive regions exhibits hypoconnectivity in schizophrenia, indicating that typically hidden connectivity patterns may reflect inefficient network integration in psychosis. Moreover, nonlinear networks including those previously implicated in auditory, linguistic and self-referential cognition exhibit heightened statistical sensitivity to schizophrenia diagnosis, collectively underscoring the potential of our methodology to resolve complex brain phenomena and transform clinical connectivity analysis.

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Explained on MedicalXpress

# Researchers uncover new ways to identify signatures of mental disorders using fMRI scans

New research by a team at Georgia State University is uncovering surprising insights about brain pathways that could offer alternative ways for practitioners to identify early signs of schizophrenia. The research is published in the journal Nature Mental Health.

The study identifies connections that show unique spatial variation across the brain and enhanced sensitivity in the brains of patients with schizophrenia.

“This research marks an exciting leap forward, offering an entirely new lens to capture the complex, hidden fluctuations within functional brain networks,” said Distinguished University Professor of Psychology Vince Calhoun, one of the principal investigators on the study.