ArticleNeuroImage. Clinical2021
Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA.
Article in NeuroImage. Clinical, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 20 citations in OpenAlex.
- White matter microstructure and motor function in amnestic mild cognitive impairment and Alzheimer's dementia.Neuroimage. Reports · 2026Article
- Macro-Micro structural integration for characterizing severity-related structural alterations in mild cognitive impairment.NeuroImage. Clinical · 2026Article
- Leveraging AI-Driven Neuroimaging Biomarkers for Early Detection and Social Function Prediction in Autism Spectrum Disorders: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Explaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis.Journal of neurology · 2025Article
- Research progress on brain network imaging biomarkers of subjective cognitive decline.Frontiers in neuroscience · 2025Review
- Reduced GM-WM concentration inside the Default Mode Network in individuals with high emotional intelligence and low anxiety: a data fusion mCCA+jICA approach.Social cognitive and affective neuroscience · 2024Article
- Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study.Journal of Alzheimer's disease : JAD · 2024Article
- Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links.NeuroImage · 2024Article
- The covariant structural and functional neuro-correlates of cognitive impairments in patients with end-stage renal diseases.Frontiers in neuroscience · 2024Article
- Vision impairment, hearing impairment and functional Limitations of subjective cognitive decline: a population-based study.BMC geriatrics · 2023Article
- Altered Functional Connectivity Density in Type 2 Diabetes Mellitus with and without Mild Cognitive Impairment.Brain sciences · 2023Article
- Data-driven multimodal fusion: approaches and applications in psychiatric research.Psychoradiology · 2023Review
- Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data.Sensors (Basel, Switzerland) · 2022Article
- Differential Abnormality in Functional Connectivity Density in Preclinical and Early-Stage Alzheimer's Disease.Frontiers in aging neuroscience · 2022Article
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrevious multimodal neuroimaging studies analyzed each dataset independently in subjective cognitive decline (SCD) and mild cognitive impairment (MCI), missing the cross-information. Multi-modal fusion analysis can provide more integral and comprehensive information regarding the brain. There has been a paucity of research on fusion analysis of sMRI and DTI in SCD and MCI. MATERIALS AND
methodsIn the present study, we conducted fusion analysis of structural MRI and DTI by applying multimodal canonical correlation analysis with joint independent component analysis (mCCA-jICA) to capture the cross-information of gray matter (GM) and white matter (WM) in 62 SCD patients, 99 MCI patients, and 70 healthy controls (HCs). We further analyzed correlations between the mixing coefficients of mCCA-jICA and neuropsychological scores among the three groups.
resultsA set of joint-discriminative independent components of GM and fractional anisotropy (FA) exhibited significant links between SCD and HCs, as well as between MCI and HCs. The covariant abnormalities primarily involved the frontal lobe/middle temporal gyrus/calcarine sulcus-anterior thalamic radiation/superior longitudinal fasciculus in SCD, and middle temporal gyrus/ fusiform gyrus/caudate necleus-forceps minor/anterior thalamic radiation in MCI. There was no significant difference between SCD and MCI groups.
conclusionsThe covariant GM-WM abnormalities in SCD and MCI were found in specific brain regions involved in cognitive processing, which confirms the simultaneous GM and WM changes underlying cognitive decline. These findings suggest that multimodal fusion analysis allows for a more comprehensive understanding of the association among different types of brain tissues and its crucial role in the neuropathological mechanism of SCD and MCI.
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