ArticleFrontiers in human neuroscience2013
Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA.
Article in Frontiers in human neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 4 of them syntheses that pooled it.
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Who cites it
64 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Artificial intelligence approaches for schizophrenia prediction and its biomarkers using medical imaging data.Frontiers in psychiatry · 2026Pooled it
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Abnormalities of intrinsic regional brain activity in first-episode and chronic schizophrenia: a meta-analysis of resting-state functional MRIJournal of psychiatry & neuroscience : JPN · 2020Pooled it
- Altered Spontaneous Brain Activity in Schizophrenia: A Meta-Analysis and a Large-Sample Study.BioMed research international · 2015Pooled it
- Cognitive enrichment through art: a randomized controlled trial on the effect of music or visual arts group practice on cognitive and brain development of young children.BMC complementary medicine and therapies · 2024Trial
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- Lucid Dreaming Frequency Associated With Grey-White Matter Networks: An Exploratory Multimodal MRI Study.Journal of sleep research · 2026Article
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- Identifying transdiagnostic neurobiomarkers for precision major psychiatric disordersJournal of translational internal medicine · 2026Article
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- Cognitive heterogeneity in major depressive disorder: classification by IQ trajectory and multimodal neuroimaging profiles.BMC psychiatry · 2025Article
- The network characteristics in schizophrenia with prominent negative symptoms: a multimodal fusion study.Schizophrenia (Heidelberg, Germany) · 2024Article
- The covariant structural and functional neuro-correlates of cognitive impairments in patients with end-stage renal diseases.Frontiers in neuroscience · 2024Article
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- Multi-view fusion of diffusion MRI microstructural models: a preterm birth study.Frontiers in neuroscience · 2024Article
- Developmental coupling of brain iron and intrinsic activity in infants during the first 150 days.Developmental cognitive neuroscience · 2023Article
- Abnormal Brain Circuits Characterize Borderline Personality and Mediate the Relationship between Childhood Traumas and Symptoms: A mCCA+jICA and Random Forest Approach.Sensors (Basel, Switzerland) · 2023Article
- Article
- Data-driven multimodal fusion: approaches and applications in psychiatric research.Psychoradiology · 2023Review
- Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter.Frontiers in neurology · 2023Article
4 more citing papers are in PubMed but not listed here.
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10 authors.
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Abstract
Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called "mCCA + jICA" as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.
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