ArticleNeuroImage2013
Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data.
Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 71 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
71 citing papers in PubMed.
- Hippocampal plasticity underpins long-term cognitive gains from resistance exercise in MCI.NeuroImage. Clinical · 2020Trial
- Empathy in primary progressive aphasia: Neural signatures and longitudinal trajectories.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Longitudinal Trajectories of Cortical Folding in Schizophrenia Spectrum Disorders: A 13-Year Follow-Up Study.Schizophrenia bulletin · 2026Article
- Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.bioRxiv : the preprint server for biology · 2025Article
- A lightweight generative model for interpretable subject-level prediction.Medical image analysis · 2025Article
- Mapping individual differences in intermodal coupling in neurodevelopment.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Sex differences in trajectories of cortical development in autistic children from 2-13 years of age.Molecular psychiatry · 2024Article
- Distinct biological property of tau in tau-first cognitive proteinopathy: Evidence by longitudinal clinical neuroimaging profiles and compared with late-onset Alzheimer disease.Psychiatry and clinical neurosciences · 2024Article
- Associations of CSF BACE1 with amyloid pathology, neurodegeneration, and cognition in Alzheimer's disease.Acta neuropathologica · 2024Article
- SAN: Mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.Human brain mapping · 2024Article
- SAN: mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.bioRxiv : the preprint server for biology · 2024Article
- Estimating Dementia Onset: AT(N) Profiles and Predictive Modeling in Mild Cognitive Impairment Patients.Current Alzheimer research · 2024Article
- Spatial-extent inference for testing variance components in reliability and heritability studies.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Serum neurofilament light concentrations are associated with cortical thinning in anorexia nervosa.Psychological medicine · 2023Article
- Applying Joint Graph Embedding to Study Alzheimer's Neurodegeneration Patterns in Volumetric Data.Neuroinformatics · 2023Article
- Article
- Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex.eLife · 2023Article
- Trajectories of brain volumes in young children are associated with maternal education.Human brain mapping · 2023Article
- Accelerated cortical thinning precedes and predicts conversion to psychosis: The NAPLS3 longitudinal study of youth at clinical high-risk.Molecular psychiatry · 2023Article
- Applying joint graph embedding to study Alzheimer's neurodegeneration patterns in volumetric data.bioRxiv : the preprint server for biology · 2023Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
We present an extension of the Linear Mixed Effects (LME) modeling approach to be applied to the mass-univariate analysis of longitudinal neuroimaging (LNI) data. The proposed method, called spatiotemporal LME or ST-LME, builds on the flexible LME framework and exploits the spatial structure in image data. We instantiated ST-LME for the analysis of cortical surface measurements (e.g. thickness) computed by FreeSurfer, a widely-used brain Magnetic Resonance Image (MRI) analysis software package. We validate the proposed ST-LME method and provide a quantitative and objective empirical comparison with two popular alternative methods, using two brain MRI datasets obtained from the Alzheimer's disease neuroimaging initiative (ADNI) and Open Access Series of Imaging Studies (OASIS). Our experiments revealed that ST-LME offers a dramatic gain in statistical power and repeatability of findings, while providing good control of the false positive rate.
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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.