The Brain Chart of Aging: Machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans

N4ITK: Improved N3 Bias Correction

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Cardia: study design, recruitment, and some characteristics of the examined subjects

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Harmonization of cortical thickness measurements across scanners and sites

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Memory and Executive Function in Aging and AD

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Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain

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Generalized additive models for medical research

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Building better biomarkers: brain models in translational neuroimaging

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Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers

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Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline

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Trajectories of brain aging in middle-aged and older adults: Regional and individual differences

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Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

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Walking energetics and white matter hyperintensities in mid‐to‐late adulthood

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Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples

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A Multiform Heterogeneity Framework for Alzheimer’s Disease Based on Multimodal Neuroimaging

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Dense longitudinal neuroimaging reveals individual brain change trajectories

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Analysis of the anti-Alzheimer potential of bioactive compounds from Citrus hystrix DC. peel, leaf, and essential oil by network pharmacology

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CSF Levels of NPTX2 Are Associated With Less Brain Atrophy Over Time in Cognitively Unimpaired Individuals

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Beyond network connectivity: A classification approach to brain age prediction with resting-state fMRI

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Reply: From ‘loose fitting’ to high-performance, uncertainty-aware brain-age modelling

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Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging dataPreprint

Bučková, B. R., Fraza, C., Rehák, R., Kolenič, M., Beckmann, C. F., Španiel, F., Marquand, A. F., & Hlinka, J. (2024) · eLife · doi:10.7554/elife.95823 · Cited by 10

An evaluation of image-based and statistical techniques for harmonizing brain volume measurements

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Deep learning-based brain age predicts stroke recurrence in acute ischemic cerebrovascular disease

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Cerebrovascular lesion loads and accelerated brain aging: insights into the cognitive spectrum

Beheshti, I., Potvin, O., Dadar, M., & Duchesne, S. (2024) · Frontiers in Dementia · doi:10.3389/frdem.2024.1380015 · Cited by 5

Heart rate fragmentation and brain MRI markers of small vessel disease in MESA

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A normative model–based assessment framework for large-scale, multi-site EEG data

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Midlife sleep characteristics and Alzheimer's disease biomarkers 20 years later

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APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts

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Identification of Distinct Brain MRI Phenotypes and Their Association With Long-Term Dementia Risk in Community-Dwelling Older Adults

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TREML2 Gene Expression and Its Missense Variant rs3747742 Associate with White Matter Hyperintensity Volume and Alzheimer’s Disease-Related Brain Atrophy in the General Population

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Site effects how-to & when: an overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analysesPreprint

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Using normative models pre-trained on cross-sectional data to evaluate longitudinal changes in neuroimaging dataPreprint

Bučková, B. R., Fraza, C., Rehák, R., Kolenič, M., Beckmann, C. F., Španiel, F., Marquand, A. F., & Hlinka, J. (2024) · eLife · doi:10.7554/elife.95823.1 · Cited by 4

Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning

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Age-related changes of human brain metabolism

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Regional growth rates of white matter hyperintensities are associated with beta-amyloid burden

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Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals

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Identifying sex-specific risk architectures for predicting amyloid deposition using neural networks

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High Blood Pressure and Impaired Brain Health: Investigating the Neuroprotective Potential of Magnesium

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Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer’s disease from MR images

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Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging dataPreprint

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Brain age gap as a diffusion MRI-based marker of traumatic brain injury-related brain changes and associated outcomes

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Ascertainment and Statistical Issues for Randomized Trials of Cardiovascular Interventions for Cognitive Impairment and Dementia

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Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population

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Additive effects of cerebrovascular disease functional connectome phenotype and plasma p‐tau181 on longitudinal neurodegeneration and cognitive outcomes

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Mapping the relationships between structural brain MRI characteristics and sleep electroencephalography patterns: the Multi-Ethnic Study of atherosclerosis

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Individual prediction and classification of cognitive impairment in patients with white matter lesions based on gray matter volume

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Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measuresPreprint

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Clinical relevance of brain MRI changes in primary central nervous system lymphoma after high-dose-chemotherapy and autologous stem cell transplantation

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Accelerated brain aging in prolonged grief disorder of later life: Influence of comorbid depression

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Multimodal MRI and machine learning for identifying depression in cerebral small vessel disease: a multicenter study

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Association of epigenetic age acceleration with MRI biomarkers of aging and Alzheimer’s disease neurodegeneration

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Association of sleep duration with Alzheimer's disease and cognition

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Brain age monotonicity and functional connectivity differences of healthy subjects

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Development of Simple Risk Scores for Prediction of Brain β-Amyloid and Tau Status in Older Adults With Mild Cognitive Impairment: A Machine Learning Approach

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Harmonization with Flow-based Causal InferencePreprint

Wang, R., Chaudhari, P., & Davatzikos, C. A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.06845 · Cited by 1

Using normative models pre-trained on cross-sectional data to evaluate longitudinal changes in neuroimaging dataPreprint

Bučková, B. R., Fraza, C., Rehák, R., Kolenič, M., Beckmann, C. F., Španiel, F., Marquand, A. F., & Hlinka, J. (2024) · eLife · doi:10.7554/elife.95823.2 · Cited by 1

Cardiovascular Health at Midlife and Alzheimer Disease BiomarkersPreprint

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Association of Lacunes with Risk Factors, Cognition, and Atrophy: The Multi-Ethnic Study of Atherosclerosis (MESA)Preprint

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Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and geneticsPreprint

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Brain signatures for neuropsychological and everyday memory achieve high replicability and explanatory power in two data cohortsPreprint

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Multiscale functional connectivity patterns of the aging brain learned from rsfMRI data of 4,259 individuals of the multi-cohort iSTAGING studyPreprint

Zhou, Z., Srinivasan, D., Li, H., Abdulkadir, A., Nasrallah, I. M., Wen, J., Doshi, J. J., Erus, G., Mamourian, E., Bryan, R. N., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.27.501626

Machine learning in the context of better healthcare in aging

Henriques, J. M. O., Ribeiro, C., Rocha, T., Paredes, S., Carvalho, P., Duarte, A. I., Freitas, A. A., Cunha‐Oliveira, T., & Pereira, F. B. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-823761-8.00015-x

Normative modeling for developmental populationneuroscience: A “microscope” through which the lawsand characteristics of individual differentiation can bequantified in human brain-mind development

Zhang, Q., Wang, Y., Chen, L., Zhang, J., Zhou, Z., & Zuo, X. (2022) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2022-1170 · Cited by 3

Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical NeurosciencePreprint

Wang, R., Erus, G., Chaudhari, P., & Davatzikos, C. A. (2023) · PubMed · doi:10.48550/arxiv.2308.03175 · Cited by 1

Cerebrovascular Lesion Loads and Accelerated Brain Ageing: Insights into the Cognitive SpectrumPreprint

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SWGP: Semi-supervised clustering via Wasserstein generative adversarial network with gradient penalty for uncovering brain disease heterogeneity from medical images

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Parsing disease heterogeneity in structural and functional MRI-derived measures using normative modeling and generative adversarial networks (GANs)

Chintapalli, S. S., Govindarajan, S. T., Shou, H., Yong Fan, A., Huang, H., & Davatzikos, C. A. (2025) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.3040541

High-dimensional mediation analysis reveals the mediating role of physical activity patterns in genetic pathways leading to AD-like brain atrophy

Xu, H., Mu, S., Bao, J., Davatzikos, C. A., Shou, H., & Shen, L. (2025) · BioData Mining · doi:10.1186/s13040-025-00432-1

Trajectories of brain functional connectivity in brain aging

Sala‐Llonch, R., Wurm, R., Roura, I., & Segura, B. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-19099-5.00001-5

The predictive power of brain-predicted age and leg strength on mobility decline in aging: findings from the Baltimore Longitudinal Study of Aging

Vaughan, B. A., Terrera, G. M., Simon, J. E., Grooms, D. R., Clark, B. C., Davatzikos, C. A., Erus, G., Tian, Q., Ferrucci, L., Resnick, S. M., et al. (2025) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaf222

Modeling the age-specific incidence of mild cognitive impairment incorporating the time-varying relationship of Alzheimer's disease biomarkers over 28 years

Wang, K., Zhu, Y., Albert, M., Miller, M. I., Davatzikos, C. A., Moghekar, A., Soldan, A., & Wang, M. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251393729

Integrated Aerobic Exercise and Multisensory Environment Training for Age-related Cognitive Decline via Hippocampal-prefrontal Neural Circuit Modulation

Lin, H., Qiu, Y., Hu, Z., Chen, L., Dai, Y., Jiang, T., Li, R., Wang, S., Cao, Y., Li, J., et al. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05302-9

Source-Free Active Learning for Adapting Alzheimer’s Diagnostic Deep Learning Models Across Neuroimaging Cohorts

Ganitidis, T., Vlontzou, M. E., Athanasiou, M., Nikita, K. S., & Davatzikos, C. A. (2025) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi67747.2025.11269546

Early life blood pressure and cognitive function in mid/late life: A synthetic longitudinal cohort analysisPreprint

Bustillo, A., Hazzouri, A. Z. A., Glymour, M. M., & Kezios, K. (2026) · medRxiv · doi:10.64898/2026.02.24.26346790

Semi-disentangled Spatiotemporal Implicit Neural Representations of Longitudinal Neuroimaging Data for Trajectory Classification

Aulakh, A., Forkert, N. D., & Wilms, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-16128-4_4

Regression-based normative data for neuropsychological assessment in Buenos Aires, Argentina: RAVLT, trail making test, digit span, and verbal fluency

Corvalán, N., García, F. M., Leiva, S., Allegri, R., & Crivelli, L. (2026) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617726101994

Artificial Intelligence and Medical Imaging: A Review of the Application of Vascular Cognitive Impairment

Chen, X., Fu, P., Luo, X., Kang, C., Huang, G., Wu, Y., Zhang, M., Yin, X., & Chen, Z. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10668-7

Charting Cervical Spinal Cord Morphometry Across the LifespanPreprint

Schilling, K., Kim, M. E., Amandola, M., Gao, C., Ramadass, K., Kanakaraj, P., Bogdanov, S., Rudravaram, G., Newlin, N. R., Archer, D. B., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.03.729823

Beyond gray matter: unveiling the critical role of white matter in Alzheimer's disease

Gao, K., Bao, J., 宋友军, Lin, C., Iturria‐Medina, Y., Biswal, B. B., & Wang, P. (2026) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2026.111816

White matter abnormalities in Alzheimer's disease: Implications for pathophysiology, diagnosis, and treatment

Chen, Z., Yang, K., Lin, F., Tang, W., Shi, Y., Zhou, S., Liu, J. S., & You, Y. (2026) · Ageing Research Reviews · doi:10.1016/j.arr.2026.103229

Topography of Juxtaventricular white matter hyperintensities and cognitive associations in Alzheimer's disease: a dual-cohort study

Bao, Y., Ji, Y.-Q., Wang, L., Zhou, Y., Wang, F., Shen, D.-M., Pylypenko, D., Tong, Q., Mak, K.-F., & Guo, L. (2026) · European Radiology Experimental · doi:10.1186/s41747-026-00776-1

SIRT1 in brain aging: molecular mechanisms and therapeutic potential of pharmacological and natural modulators

Mosalam, E. M., Abdallah, M. S., Gardouh, A. R., Hamza, E., Bahaa, M. M., Nazih, M., Al-Dhelaan, R. A., & Kamal, N. (2026) · Biogerontology · doi:10.1007/s10522-026-10480-7

Predicting biological age of the brain using magnetic resonance imaging and deep learning methods

Pilli, R., & Goel, T. (2026) · Elsevier eBooks · doi:10.1016/b978-0-44-330291-6.00013-5

Integration of neuroimaging signatures of aging and Alzheimer's with fluid biomarkers

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Advanced brain age and longitudinal cognitive decline in healthy older adults

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Role of probiotics in geriatric health: Enhancing immunity, digestion, and cognitive function

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IC‐P‐108: WHITE MATTER HYPERINTENSITIES IN RELATION TO PATTERNS OF ACCELERATED BRAIN AGING, AD‐LIKE ATROPHY AND AMYLOID BURDEN: RESULTS FROM THE ISTAGING CONSORTIUM ON MACHINE LEARNING AND LARGE‐SCALE IMAGING ANALYTICS

Habes, M., Pomponio, R., Shou, H., Doshi, J. J., Sotiras, A., Erus, G., Launer, L. J., Mamourian, E., Bilgel, M., Yaffe, K. S., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.06.4222

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Longitudinal change of white matter-specific brain age is associated with Alzheimer's disease-related regional atrophy

Chen, C., Li, J., Wang, L., Schweitzer, N., Tudorascu, D., Aizenstein, H. J., & Wu, M. (2024) · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · doi:10.58530/2023/2785

A computer approach to assess age-related changes of the brain white matter in Alzheimer's disease

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Magnitude and kinetics of a set of neuroanatomic volume and thickness together with white matter hyperintensity is definitive of cognitive status and brain age

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