ArticleNeuroImage2014
Sparse canonical correlation analysis relates network-level atrophy to multivariate cognitive measures in a neurodegenerative population.
Article in NeuroImage, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it, 89 citations in OpenAlex.
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- Lesion-symptom mapping with NIHSS sub-scores in ischemic stroke patients.Stroke and vascular neurology · 2022Trial
- Spatial Correlates of Dementia and Disability After Intracerebral Hemorrhage.Journal of the American Heart Association · 2025Article
- Network biomarkers of Alzheimer's disease risk derived from joint volume and texture covariance patterns in mouse models.PloS one · 2025Article
- Partial least squares multimodal analysis of brain network correlates of language deficits in aphasia.Brain communications · 2025Article
- Neurological Effects of Repeated Blast Exposure in Special Operations Personnel.Journal of neurotrauma · 2024Article
- Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample.Network neuroscience (Cambridge, Mass.) · 2024Article
- Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches.Frontiers in neuroscience · 2024Article
- Neurophysiological signatures of cortical micro-architecture.Nature communications · 2023Article
- Identifying vulnerable brain networks associated with Alzheimer's disease risk.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample.bioRxiv : the preprint server for biology · 2023Article
- Behavioural and neural structure of fluent speech production deficits in aphasia.Brain communications · 2023Article
- Common genetic variation is associated with longitudinal decline and network features in behavioral variant frontotemporal degeneration.Neurobiology of aging · 2021Article
- An integrative multivariate approach for predicting functional recovery using magnetic resonance imaging parameters in a translational pig ischemic stroke model.Neural regeneration research · 2021Article
- Similarity-driven multi-view embeddings from high-dimensional biomedical data.Nature computational science · 2021Article
- Machine learning suggests polygenic risk for cognitive dysfunction in amyotrophic lateral sclerosis.EMBO molecular medicine · 2021Article
- Functional and Structural Neuroimaging Correlates of Repetitive Low-Level Blast Exposure in Career Breachers.Journal of neurotrauma · 2020Article
- Linking language features to clinical symptoms and multimodal imaging in individuals at clinical high risk for psychosis.European psychiatry : the journal of the Association of European Psychiatrists · 2020Article
- Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth.Biological psychiatry · 2020Review
- Visuospatial performance in patients with statistically-defined mild cognitive impairment.Journal of clinical and experimental neuropsychology · 2020Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
This study establishes that sparse canonical correlation analysis (SCCAN) identifies generalizable, structural MRI-derived cortical networks that relate to five distinct categories of cognition. We obtain multivariate psychometrics from the domain-specific sub-scales of the Philadelphia Brief Assessment of Cognition (PBAC). By using a training and separate testing stage, we find that PBAC-defined cognitive domains of language, visuospatial functioning, episodic memory, executive control, and social functioning correlate with unique and distributed areas of gray matter (GM). In contrast, a parallel univariate framework fails to identify, from the training data, regions that are also significant in the left-out test dataset. The cohort includes164 patients with Alzheimer's disease, behavioral-variant frontotemporal dementia, semantic variant primary progressive aphasia, non-fluent/agrammatic primary progressive aphasia, or corticobasal syndrome. The analysis is implemented with open-source software for which we provide examples in the text. In conclusion, we show that multivariate techniques identify biologically-plausible brain regions supporting specific cognitive domains. The findings are identified in training data and confirmed in test 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.