ArticleIEEE transactions on medical imaging2018
Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.
Article in IEEE transactions on medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.
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Who cites it
61 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.
- A technical review of canonical correlation analysis for neuroscience applications.Human brain mapping · 2020Pooled it
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Multimodal fusion of brain imaging and proteomics reveals a brain-body pathway linking depression and metabolic dysfunction.Psychological medicine · 2026Article
- Fusion of Multi-Task fMRI Data: Guided Solutions for IVA and Transposed IVA.Sensors (Basel, Switzerland) · 2026Article
- Multimodal neuroimaging reveals brain neurochemical disturbances associated with superoxide dismutase in first-episode drug-naïve schizophrenia.Translational psychiatry · 2026Article
- Multisite Chronic Pain Reveals Neuro-Immune-Metabolic Dysregulation across Rheumatoid Arthritis and Depression.Research (Washington, D.C.) · 2026Article
- Alterations in miR-151a-3p of plasma-derived exosomes and associated multimodal neuroimaging patterns in major depressive disorder.Molecular psychiatry · 2025Article
- AI-powered integration of multimodal imaging in precision medicine for neuropsychiatric disorders.Cell reports. Medicine · 2025Review
- Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade.Schizophrenia bulletin · 2025Review
- Confound Controlled Multimodal Neuroimaging Data Fusion and Its Application to Developmental Disorders.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2025Article
- Co-citation analysis of molecular imaging in neuropsychiatric disorders: integrating perspectives from radiology, neuroscience, and psychiatry.Psychoradiology · 2025Article
- A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies.Human brain mapping · 2024Article
- Abnormal multimodal neuroimaging patterns associated with social deficits in male autism spectrum disorder.Human brain mapping · 2024Article
- Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging.Translational psychiatry · 2024Article
- Symptom-guided multimodal neuroimage fusion patterns in children with attention-deficit/hyperactivity disorder and its potential "brain structure-function-cognition-behavior" pathological pathways.European child & adolescent psychiatry · 2024Article
- Brain identification of IBS patients based on GBDT and multiple imaging techniques.Physical and engineering sciences in medicine · 2024Article
- Article
- Chromatic fusion: Generative multimodal neuroimaging data fusion provides multi-informed insights into schizophrenia.Human brain mapping · 2023Article
- TDFusion: When Tensor Decomposition Meets Medical Image Fusion in the Nonsubsampled Shearlet Transform Domain.Sensors (Basel, Switzerland) · 2023Article
- Chromatic fusion: generative multimodal neuroimaging data fusion provides multi-informed insights into schizophrenia.medRxiv : the preprint server for health sciences · 2023Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
20 authors at 10 institutions in 2 countries.
Funding
Abstract
By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. There is increasing interest to uncover the neurocognitive mapping of specific clinical measurements on enriched brain imaging data; hence, a supervised, goal-directed model that employs prior information as a reference to guide multimodal data fusion is much needed and becomes a natural option. Here, we proposed a fusion with reference model called "multi-site canonical correlation analysis with reference + joint-independent component analysis" (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to the reference, such as cognitive scores. In a three-way fusion simulation, the proposed method was compared with its alternatives on multiple facets; MCCAR+jICA outperforms others with higher estimation precision and high accuracy on identifying a target component with the right correspondence. In human imaging data, working memory performance was utilized as a reference to investigate the co-varying working memory-associated brain patterns among three modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Similar brain maps were identified between the two cohorts along with substantial overlaps in the central executive network in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports and MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the ability of the proposed method to identify potential neuromarkers for mental disorders.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.