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Updated: Jun 6, 2026
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Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
Published on: December 2, 2015
Machine learning-based morphological brain analysis in schizophrenia and unaffected siblings: a multisite study of
Ishida Manabu1, Kenji Tanigaki2, Nobuhiro Ogawa3
1Department of Neurology, Shimane University, Matsue, Shimane, Japan.
Frontiers in Neuroscience
|June 5, 2026
Summary
Unaffected siblings of schizophrenia patients show similar brain patterns, indicating early risk. An enlarged ventral striatum in siblings may signal future schizophrenia development.
Area of Science:
- Neuroimaging
- Psychiatry
- Machine Learning
Background:
- Identifying schizophrenia risk factors is vital for early intervention.
- Unaffected siblings share genetic risk and may display early neuroanatomical changes.
Purpose of the Study:
- To investigate neuroanatomical similarities between schizophrenia patients and their unaffected siblings.
- To develop a machine learning model for identifying individuals at high risk for schizophrenia.
Main Methods:
- Analysis of brain MRIs from 1,018 participants across five public databases.
- Voxel-based morphometry and ensemble support vector machine (SVM) for brain signature extraction.
- Development of a schizophrenia-like score (SPS) based on regional brain volumes.
Main Results:
- High classification performance (AUC=0.99861) using the ensemble SVM.
- Patients showed reduced volumes in frontal, temporal, insular, and thalamic regions, with globus pallidus enlargement.
- Siblings were 3.8 times more likely than controls to have schizophrenia-like brain morphology, with a novel finding of increased ventral striatal volume.
Conclusions:
- Machine learning effectively identifies structural endophenotypes in large-scale neuroimaging data.
- An enlarged ventral striatum is a potential biomarker for identifying high-risk individuals before clinical onset.
- This finding may represent a compensatory mechanism or a transient developmental marker of risk.
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