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Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data
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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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“Multivariate LME models can increased statistical power and reliability compared to univariate methods30,31.”
From Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study (2018) · cites this paper as [30]
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Zuo, X., & Xing, X.-X. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.05.009 · Cited by 678
Gordon, B. A., Blazey, T. M., Su, Y., Hari-Raj, A., Dincer, A., Flores, S., Christensen, J., McDade, E., Wang, G., Xiong, C., et al. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30028-0 · Cited by 602
Head motion during MRI acquisition reduces gray matter volume and thickness estimates
Reuter, M., Tisdall, M. D., Qureshi, A., Buckner, R. L., van der Kouwe, A. J. W., & Fischl, B. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.006 · Cited by 457
Self-citationWeiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Cedarbaum, J., Green, R. C., Harvey, D., Jack, C. R., Jagust, W., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.11.001 · Cited by 348
On the right side? A longitudinal study of left- versus right-lateralized semantic dementia
Kumfor, F., Landin-Romero, R., Devenney, E., Hutchings, R., Grasso, R., Hodges, J. R., & Piguet, O. (2016) · Brain · doi:10.1093/brain/awv387 · Cited by 224
Metadata
- Authors
- Bernal-Rusiel, J. L., Reuter, M., Greve, D. N., Fischl, B., & Sabuncu, M. R.
- Affiliations
- Harvard University (US)
- Corresponding author
- Sabuncu, Mert R.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 81
- Pages
- 358-370
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3816382
- OpenAlex
- W2132114367
- Cited by
- 125
- References
- 93
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 7 · 2023: 9 · 2022: 13 · 2021: 11 · 2020: 16 · 2019: 6 · 2018: 10 · 2017: 12 · 2016: 13 · 2015: 11 · 2014: 6
- FWCI
- 5.46
- Type
- journal article
- Language
- en
- Update notices
- erratum (2015-03-01)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (AG022381)
- National Institute of Neurological Disorders and Stroke (1R01NS070963, 1R21NS072652-01, 2R01NS042861-06A1, 5P01NS058793-03, R01 NS052585-01)
- BrightFocus Foundation (AHAF-A2012333)
- National Center for Research Resources (P41-RR14075)
- NIH Blueprint for Neuroscience Research (5U01-MH093765)
- Ellison Medical Foundation
- National Institute of Biomedical Imaging and Bioengineering (1K25EB013649-01, R01EB006758)
- National Institute of Child Health and Human Development (1S10RR019307, 1S10RR023043, 1S10RR023401, R01-HD071664)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- longitudinal neuroimaging, mass univariate analysis, cortical thickness, FreeSurfer, Alzheimer's disease, statistical power, false positive rate control, brain MRI
- MeSH terms
- Brain, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Software, Linear Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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