ArticleIEEE transactions on image processing : a publication of the IEEE Signal Processing Society2021
Multidataset Independent Subspace Analysis With Application to Multimodal Fusion.
Article in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- aNy-way ICA and its application to estimate cortico-thalamo-cerebellar functional links in schizophrenia.bioRxiv : the preprint server for biology · 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
- Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition.IEEE transactions on bio-medical engineering · 2024Article
- Chromatic fusion: Generative multimodal neuroimaging data fusion provides multi-informed insights into schizophrenia.Human brain mapping · 2023Article
- Chromatic fusion: generative multimodal neuroimaging data fusion provides multi-informed insights into schizophrenia.medRxiv : the preprint server for health sciences · 2023Article
- Data-driven multimodal fusion: approaches and applications in psychiatric research.Psychoradiology · 2023Review
- Heterogeneous data integration methods for patient similarity networks.Briefings in bioinformatics · 2022Review
- Three-way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data.Human brain mapping · 2022Article
- Dynamic Invariant-Specific Representation Fusion Network for Multimodal Sentiment Analysis.Computational intelligence and neuroscience · 2022Article
- A multimodal IVA fusion approach to identify linked neuroimaging markers.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Multidataset Independent Subspace Analysis With Application to Multimodal Fusion.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2021Article
- aNy-way Independent Component Analysis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020Article
- Evolution of spatial and temporal features of functional brain networks across the lifespan.NeuroImage · 2018Article
- Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling.IEEE journal of selected topics in signal processing · 2016Article
- Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2015Article
- Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and function.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Unsupervised latent variable models-blind source separation (BSS) especially-enjoy a strong reputation for their interpretability. But they seldom combine the rich diversity of information available in multiple datasets, even though multidatasets yield insightful joint solutions otherwise unavailable in isolation. We present a direct, principled approach to multidataset combination that takes advantage of multidimensional subspace structures. In turn, we extend BSS models to capture the underlying modes of shared and unique variability across and within datasets. Our approach leverages joint information from heterogeneous datasets in a flexible and synergistic fashion. We call this method multidataset independent subspace analysis (MISA). Methodological innovations exploiting the Kotz distribution for subspace modeling, in conjunction with a novel combinatorial optimization for evasion of local minima, enable MISA to produce a robust generalization of independent component analysis (ICA), independent vector analysis (IVA), and independent subspace analysis (ISA) in a single unified model. We highlight the utility of MISA for multimodal information fusion, including sample-poor regimes ( N = 600 ) and low signal-to-noise ratio, promoting novel applications in both unimodal and multimodal brain imaging data.
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Registered trials
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.