The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.
Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data
Open accessAbstract
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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Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Self-citationFischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.021 · Cited by 9,526
Self-citationCortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
Self-citationMeasuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,995
Self-citationBrain development during childhood and adolescence: a longitudinal MRI study
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Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011) · Wiley Series in Probability and Statistics · doi:10.1002/9781119513469 · Cited by 4,639
Small sample inference for fixed effects from restricted maximum likelihood
Kenward, M. G., & Roger, J. H. (1997) · Biometrics · doi:10.2307/2533558 · Cited by 4,552
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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
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