Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis

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

Fast robust automated brain extraction

Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496

Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?

Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471

Characterization and propagation of uncertainty in diffusion-weighted MR imaging

Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038

Within-subject template estimation for unbiased longitudinal image analysis

Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.084 · Cited by 2,356

Aerobic Exercise Training Increases Brain Volume in Aging Humans

Colcombe, S. J., Erickson, K. I., Scalf, P. E., Kim, J. S., Prakash, R., McAuley, E., Elavsky, S., Marquez, D. X., Hu, L., & Kramer, A. F. (2006) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/61.11.1166 · Cited by 2,134

Ocrelizumab versus Interferon Beta-1a in Relapsing Multiple Sclerosis

Hauser, S. L., Bar-Or, A., Comi, G., Giovannoni, G., Hartung, H.-P., Hemmer, B., Lublin, F., Montalban, X., Rammohan, K. W., Selmaj, K., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1601277 · Cited by 2,021

Ocrelizumab versus Placebo in Primary Progressive Multiple Sclerosis

Montalban, X., Hauser, S. L., Kappos, L., Arnold, D. L., Bar-Or, A., Comi, G., de Seze, J., Giovannoni, G., Hartung, H.-P., Hemmer, B., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1606468 · Cited by 1,905

Chronic back pain is associated with decreased prefrontal and thalamic gray matter density

Apkarian, A. V., Sosa, Y., Sonty, S., Levy, R. M., Harden, R. N., Parrish, T. B., & Gitelman, D. R. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.2541-04.2004 · Cited by 1,434

Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD

Jack, C. R., Shiung, M. M., Gunter, J. L., O’Brien, P. C., Weigand, S. D., Knopman, D. S., Boeve, B. F., Ivnik, R. J., Smith, G. E., Cha, R. H., et al. (2004) · Neurology · doi:10.1212/01.wnl.0000110315.26026.ef · Cited by 827

Genome-wide association studies of brain imaging phenotypes in UK Biobank

Elliott, L. T., Sharp, K., Alfaro-Almagro, F., Shi, S., Miller, K. L., Douaud, G., Marchini, J., & Smith, S. M. (2018) · Nature · doi:10.1038/s41586-018-0571-7 · Cited by 834

Homocysteine-Lowering by B Vitamins Slows the Rate of Accelerated Brain Atrophy in Mild Cognitive Impairment: A Randomized Controlled Trial

Smith, A. D., Smith, S. M., de Jager, C. A., Whitbread, P., Johnston, C., Agacinski, G., Oulhaj, A., Bradley, K. M., Jacoby, R., & Refsum, H. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012244 · Cited by 813

Resistance Training and Executive Functions: A 12-Month Randomized Controlled Trial

Liu-Ambrose, T. (2010) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.494 · Cited by 775

Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease

Karas, G. B., Scheltens, P., Rombouts, S. A. R. B., Visser, P. J., van Schijndel, R. A., Fox, N. C., & Barkhof, F. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.006 · Cited by 613

Structural Brain Imaging Evidence for Multiple Pathological Processes at Different Stages of Brain Development in Schizophrenia

Pantelis, C. (2005) · Schizophrenia Bulletin · doi:10.1093/schbul/sbi034 · Cited by 573

Serum neurofilament light levels in normal aging and their association with morphologic brain changes

Khalil, M., Pirpamer, L., Hofer, E., Voortman, M. M., Barro, C., Leppert, D., Benkert, P., Ropele, S., Enzinger, C., Fazekas, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14612-6 · Cited by 572

Strongly reduced volumes of putamen and thalamus in Alzheimer’s disease: an MRI study

de Jong, L. W., van der Hiele, K., Veer, I. M., Houwing, J. J., Westendorp, R. G. J., Bollen, E. L. E. M., de Bruin, P. W., Middelkoop, H. A. M., van Buchem, M. A., & van der Grond, J. (2008) · Brain · doi:10.1093/brain/awn278 · Cited by 557

Ventricular enlargement as a possible measure of Alzheimer’s disease progression validated using the Alzheimer’s disease neuroimaging initiative database

Nestor, S. M., Rupsingh, R., Borrie, M., Smith, M., Accomazzi, V., Wells, J. L., Fogarty, J., Bartha, R., & Initiative, T. A. D. N. (2008) · Brain · doi:10.1093/brain/awn146 · Cited by 543

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

Ageing and brain white matter structure in 3,513 UK Biobank participants

Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., Wardlaw, J. M., Gale, C. R., Bastin, M. E., & Deary, I. J. (2016) · Nature Communications · doi:10.1038/ncomms13629 · Cited by 487

Genome-wide association analysis of susceptibility and clinical phenotype in multiple sclerosis

Baranzini, S. E., Wang, J., Gibson, R. A., Galwey, N., Naegelin, Y., Barkhof, F., Radue, E.-W., Lindberg, R. L. P., Uitdehaag, B. M. G., Johnson, M. R., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddn388 · Cited by 476

Assessing the effects of age on long white matter tracts using diffusion tensor tractography

Davis, S. W., Dennis, N. A., Buchler, N. G., White, L. E., Madden, D. J., & Cabeza, R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.068 · Cited by 458

White matter lesion progression, brain atrophy, and cognitive decline: The Austrian stroke prevention study

Schmidt, R., Ropele, S., Enzinger, C., Petrovic, K., Smith, S., Schmidt, H., Matthews, P. M., & Fazekas, F. (2005) · Annals of Neurology · doi:10.1002/ana.20630 · Cited by 408

Hippocampal atrophy rates in Alzheimer disease: Added value over whole brain volume measures

Henneman, W. J. P., Sluimer, J. D., Barnes, J., van der Flier, W. M., Sluimer, I. C., Fox, N. C., Scheltens, P., Vrenken, H., & Barkhof, F. (2009) · Neurology · doi:10.1212/01.wnl.0000344568.09360.31 · Cited by 350

The effects of physical activity on functional MRI activation associated with cognitive control in children: a randomized controlled intervention

Chaddock-Heyman, L., Erickson, K. I., Voss, M. W., Knecht, A. M., Pontifex, M. B., Castelli, D. M., Hillman, C. H., & Kramer, A. F. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00072 · Cited by 305

Diffusion tensor imaging in preclinical and presymptomatic carriers of familial Alzheimer’s disease mutations

Ringman, J. M., O'Neill, J., Geschwind, D., Medina, L., Apostolova, L. G., Rodriguez, Y., Schaffer, B., Varpetian, A., Tseng, B., Ortiz, F., et al. (2007) · Brain · doi:10.1093/brain/awm102 · Cited by 290

Structural network efficiency is associated with cognitive impairment in small-vessel disease

Lawrence, A. J., Chung, A. W., Morris, R. G., Markus, H. S., & Barrick, T. R. (2014) · Neurology · doi:10.1212/wnl.0000000000000612 · Cited by 285

Blood-brain barrier permeability is increased in normal-appearing white matter in patients with lacunar stroke and leucoaraiosis

Topakian, R., Barrick, T. R., Howe, F. A., & Markus, H. S. (2010) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2009.172072 · Cited by 281

Confound modelling in UK Biobank brain imaging

Alfaro-Almagro, F., McCarthy, P., Afyouni, S., Andersson, J. L. R., Bastiani, M., Miller, K. L., Nichols, T. E., & Smith, S. M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2020.117002 · Cited by 249

Multiple DTI index analysis in normal aging, amnestic MCI and AD. Relationship with neuropsychological performance

Bosch, B., Arenaza-Urquijo, E. M., Rami, L., Sala-Llonch, R., Junqué, C., Solé-Padullés, C., Peña-Gómez, C., Bargalló, N., Molinuevo, J. L., & Bartrés-Faz, D. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.02.004 · Cited by 272

A phase 2 randomized trial of ELND005, scyllo-inositol, in mild to moderate Alzheimer disease

Salloway, S., Sperling, R., Keren, R., Porsteinsson, A. P., van Dyck, C. H., Tariot, P. N., Gilman, S., Arnold, D., Abushakra, S., Hernandez, C., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e3182309fa5 · Cited by 258

Memory training impacts short‐term changes in aging white matter: A Longitudinal Diffusion Tensor Imaging Study

Engvig, A., Fjell, A. M., Westlye, L. T., Moberget, T., Sundseth, Ø., Larsen, V. A., & Walhovd, K. B. (2012) · Human Brain Mapping · doi:10.1002/hbm.21370 · Cited by 250

Perivascular spaces—MRI marker of inflammatory activity in the brain?

Wuerfel, J., Haertle, M., Waiczies, H., Tysiak, E., Bechmann, I., Wernecke, K. D., Zipp, F., & Paul, F. (2008) · Brain · doi:10.1093/brain/awn171 · Cited by 244

Brain Activity and Functional Connectivity Associated with Hypnosis

Jiang, H., White, M. P., Greicius, M. D., Waelde, L. C., & Spiegel, D. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw220 · Cited by 246

The default network of the human brain is associated with perceived social isolation

Spreng, R. N., Dimas, E., Mwilambwe-Tshilobo, L., Dagher, A., Koellinger, P., Nave, G., Ong, A., Kernbach, J. M., Wiecki, T. V., Ge, T., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-20039-w · Cited by 236

Hippocampal volume across age: Nomograms derived from over 19,700 people in UK Biobank

Nobis, L., Manohar, S. G., Smith, S. M., Alfaro-Almagro, F., Jenkinson, M., Mackay, C. E., & Husain, M. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101904 · Cited by 236

Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans

Hua, X., Hibar, D. P., Lee, S., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.033 · Cited by 234

Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in CADASIL

Duering, M., Zieren, N., Hervé, D., Jouvent, E., Reyes, S., Peters, N., Pachai, C., Opherk, C., Chabriat, H., & Dichgans, M. (2011) · Brain · doi:10.1093/brain/awr169 · Cited by 200

Teaching an adult brain new tricks: A critical review of evidence for training-dependent structural plasticity in humans

Thomas, C., & Baker, C. I. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.069 · Cited by 204

Dehydration confounds the assessment of brain atrophy

Duning, T., Kloska, S., Steinsträter, O., Kugel, H., Heindel, W., & Knecht, S. (2005) · Neurology · doi:10.1212/01.wnl.0000150542.16969.cc · Cited by 190

Functional network connectivity in the behavioral variant of frontotemporal dementia

Filippi, M., Agosta, F., Scola, E., Canu, E., Magnani, G., Marcone, A., Valsasina, P., Caso, F., Copetti, M., Comi, G., et al. (2013) · Cortex · doi:10.1016/j.cortex.2012.09.017 · Cited by 177

Thalamic and extrathalamic mechanisms of consciousness after severe brain injury

Lutkenhoff, E. S., Chiang, J., Tshibanda, L., Kamau, E., Kirsch, M., Pickard, J. D., Laureys, S., Owen, A. M., & Monti, M. M. (2015) · Annals of Neurology · doi:10.1002/ana.24423 · Cited by 162

A diffusion tensor imaging study of white matter in obsessive–compulsive disorder

Cannistraro, P. A., Makris, N., Howard, J. D., Wedig, M. M., Hodge, S. M., Wilhelm, S., Kennedy, D. N., & Rauch, S. L. (2007) · Depression and Anxiety · doi:10.1002/da.20246 · Cited by 154

Multimodal MRI in Cerebral Small Vessel Disease: Its Relationship With Cognition and Sensitivity to Change Over Time

Nitkunan, A., Barrick, T. R., Charlton, R. A., Clark, C. A., & Markus, H. S. (2008) · Stroke · doi:10.1161/strokeaha.107.507475 · Cited by 153

Long-term follow-up from the ORATORIO trial of ocrelizumab for primary progressive multiple sclerosis: a post-hoc analysis from the ongoing open-label extension of the randomised, placebo-controlled, phase 3 trial

Wolinsky, J. S., Arnold, D. L., Brochet, B., Hartung, H.-P., Montalban, X., Naismith, R. T., Manfrini, M., Overell, J., Koendgen, H., Sauter, A., et al. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30342-2 · Cited by 150

FUNDAMANT: an interventional 72-week phase 1 follow-up study of AADvac1, an active immunotherapy against tau protein pathology in Alzheimer's disease

Novak, P., Schmidt, R., Kontsekova, E., Kovacech, B., Smolek, T., Katina, S., Fialova, L., Prcina, M., Parrak, V., Dal-Bianco, P., et al. (2018) · Alzheimer's Research & Therapy · doi:10.1186/s13195-018-0436-1 · Cited by 147

Assessment and impact of cognitive impairment in multiple sclerosis: An overview

Macías Islas, M. Á., & Ciampi, E. (2019) · Biomedicines · doi:10.3390/biomedicines7010022 · Cited by 144

Mechanisms of cognitive impairment in cerebral small vessel disease: multimodal MRI results from the St George’s cognition and neuroimaging in stroke (SCANS) study

Lawrence, A. J., Patel, B., Morris, R. G., MacKinnon, A. D., Rich, P. M., Barrick, T. R., & Markus, H. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061014 · Cited by 140

Brain Atrophy and Cerebral Small Vessel Disease: A Prospective Follow-Up Study

Nitkunan, A., Lanfranconi, S., Charlton, R. A., Barrick, T. R., & Markus, H. S. (2011) · Stroke · doi:10.1161/strokeaha.110.594267 · Cited by 135

Brain volume changes in CADASIL: A serial MRI study in pure subcortical ischemic vascular disease

Peters, N., Holtmannspötter, M., Opherk, C., Gschwendtner, A., Herzog, J., Sämann, P., & Dichgans, M. (2006) · Neurology · doi:10.1212/01.wnl.0000216271.96364.50 · Cited by 130

Mindfulness training for older adults with subjective cognitive decline: Results from a pilot randomized controlled trial.

Smart, C. M., Segalowitz, S. J., Mulligan, B. P., Koudys, J., & Gawryluk, J. R. (2016) · Journal of Alzheimer's Disease · doi:10.3233/jad-150992 · Cited by 123

The effect of exercise on hippocampal volume and neurotrophines in patients with major depression–a randomized clinical trial.

Krogh, J., Rostrup, E., Thomsen, C., Elfving, B., Videbech, P., & Nordentoft, M. (2014) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.04.041 · Cited by 123

Combined volumetry and DTI in subcortical structures of mild cognitive impairment and Alzheimer’s disease patients.

Cherubini, A., Péran, P., Spoletini, I., Di Paola, M., Di Iulio, F., Hagberg, G. E., Sancesario, G., Gianni, W., Bossù, P., Caltagirone, C., et al. (2010) · Journal of Alzheimer s Disease · doi:10.3233/jad-2010-091186 · Cited by 123

Influence of aging on brain gray and white matter changes assessed by conventional, MT, and DT MRI

Benedetti, B., Charil, A., Rovaris, M., Judica, E., Valsasina, P., Sormani, M. P., & Filippi, M. (2006) · Neurology · doi:10.1212/01.wnl.0000198510.73363.c6 · Cited by 119

Evaluating imaging biomarkers for neurodegeneration in pre-symptomatic Huntington's disease using machine learning techniques

Rizk-Jackson, A., Stoffers, D., Sheldon, S., Kuperman, J., Dale, A., Goldstein, J., Corey-Bloom, J., Poldrack, R. A., & Aron, A. R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.273 · Cited by 107

Whole-brain atrophy rate in Alzheimer disease: Identifying fast progressors

Sluimer, J. D., Vrenken, H., Blankenstein, M. A., Fox, N. C., Scheltens, P., Barkhof, F., & van der Flier, W. M. (2008) · Neurology · doi:10.1212/01.wnl.0000311446.61861.e3 · Cited by 110

Brain atrophy is related to lacunar lesions and tissue microstructural changes in CADASIL

Jouvent, E., Viswanathan, A., Mangin, J.-F., O’Sullivan, M., Guichard, J.-P., Gschwendtner, A., Cumurciuc, R., Buffon, F., Peters, N., Pachaï, C., et al. (2007) · Stroke · doi:10.1161/strokeaha.106.478263 · Cited by 109

Whole-brain atrophy rate and CSF biomarker levels in MCI and AD: a longitudinal study

Sluimer, J. D., Bouwman, F. H., Vrenken, H., Blankenstein, M. A., Barkhof, F., van der Flier, W. M., & Scheltens, P. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.06.016 · Cited by 106

Cerebral Microbleeds and Cognition in Patients With Symptomatic Small Vessel Disease

Patel, B., Lawrence, A. J., Chung, A. W., Rich, P., MacKinnon, A. D., Morris, R. G., Barrick, T. R., & Markus, H. S. (2013) · Stroke · doi:10.1161/strokeaha.112.670216 · Cited by 105

In vivo evidence of glutamate toxicity in multiple sclerosis

Azevedo, C. J., Kornak, J., Chu, P., Sampat, M., Okuda, D. T., Cree, B. A., Nelson, S. J., Hauser, S. L., & Pelletier, D. (2014) · Annals of Neurology · doi:10.1002/ana.24202 · Cited by 100

Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment

Clerx, L., van Rossum, I. A., Burns, L., Knol, D. L., Scheltens, P., Verhey, F., Aalten, P., Lapuerta, P., van de Pol, L., van Schijndel, R., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.02.002 · Cited by 98

A diffusion tensor MRI study of patients with MCI and AD with a 2-year clinical follow-up

Scola, E., Bozzali, M., Agosta, F., Magnani, G., Franceschi, M., Sormani, M. P., Cercignani, M., Pagani, E., Falautano, M., Filippi, M., et al. (2010) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2009.189639 · Cited by 98

Thalamic shape and connectivity abnormalities in children with attention- deficit/hyperactivity disorder

Xia, S., Li, X., Kimball, A. E., Kelly, M. S., Lesser, I., & Branch, C. (2012) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2012.04.011 · Cited by 92

Effect of leukocyte telomere length on total and regional brain volumes in a large population-based cohort

King, K. S., Kozlitina, J., Rosenberg, R. N., Peshock, R. M., McColl, R. W., & Garcia, C. K. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.1926 · Cited by 95

Identification of a strategic brain network underlying processing speed deficits in vascular cognitive impairment

Duering, M., Gonik, M., Malik, R., Zieren, N., Reyes, S., Jouvent, E., Hervé, D., Gschwendtner, A., Opherk, C., Chabriat, H., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.084 · Cited by 89

Hippocampal volume is an independent predictor of cognitive performance in CADASIL

O'Sullivan, M., Ngo, E., Viswanathan, A., Jouvent, E., Gschwendtner, A., Saemann, P. G., Duering, M., Pachai, C., Bousser, M.-G., Chabriat, H., et al. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.09.002 · Cited by 85

Volume estimation of the thalamus using freesurfer and stereology: consistency between methods

Keller, S. S., Gerdes, J. S., Mohammadi, S., Kellinghaus, C., Kugel, H., Deppe, K., Ringelstein, E. B., Evers, S., Schwindt, W., & Deppe, M. (2012) · Neuroinformatics · doi:10.1007/s12021-012-9147-0 · Cited by 84

Low-dose ladostigil for mild cognitive impairment: A phase 2 placebo-controlled clinical trial

Schneider, L. S., Geffen, Y., Rabinowitz, J., Thomas, R. G., Schmidt, R., Ropele, S., Weinstock, M., & on behalf of the Ladostigil Study Group (2019) · Neurology · doi:10.1212/wnl.0000000000008239 · Cited by 75

Predicting neuropsychological abnormalities in multiple sclerosis

Benedict, R. H. B., & Zivadinov, R. (2006) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2005.05.020 · Cited by 73

Neuronal and behavioral effects of multi-day brain stimulation and memory training

Antonenko, D., Külzow, N., Sousa, A., Prehn, K., Grittner, U., & Flöel, A. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.09.017 · Cited by 70

The Vitamin D to Ameliorate Multiple Sclerosis (VIDAMS) trial: Study design for a multicenter, randomized, double-blind controlled trial of vitamin D in multiple sclerosis

Bhargava, P., Cassard, S., Steele, S. U., Azevedo, C., Pelletier, D., Sugar, E. A., Waubant, E., & Mowry, E. M. (2014) · Contemporary Clinical Trials · doi:10.1016/j.cct.2014.10.004 · Cited by 69

Education modifies the relation of vascular pathology to cognitive function: cognitive reserve in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy

Zieren, N., Duering, M., Peters, N., Reyes, S., Jouvent, E., Hervé, D., Gschwendtner, A., Mewald, Y., Opherk, C., Chabriat, H., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.04.019 · Cited by 65

The relationship between episodic long-term memory and white matter integrity in normal aging

Charlton, R. A., Barrick, T. R., Markus, H. S., & Morris, R. G. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.08.018 · Cited by 55

Tractography in the presence of multiple sclerosis lesions

Lipp, I., Parker, G. D., Tallantyre, E. C., Goodall, A., Grama, S., Patitucci, E., Heveron, P., Tomassini, V., & Jones, D. K. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2019.116471 · Cited by 51

Longitudinal assessment of global and regional atrophy rates in Alzheimer's disease and dementia with Lewy bodies

Mak, E., Su, L., Williams, G. B., Watson, R., Firbank, M., Blamire, A. M., & O'Brien, J. T. (2015) · NeuroImage: Clinical · doi:10.1016/j.nicl.2015.01.017 · Cited by 51

A Polygenic Score for Higher Educational Attainment is Associated with Larger Brains

Elliott, M. L., Belsky, D. W., Anderson, K., Corcoran, D. L., Ge, T., Knodt, A., Prinz, J. A., Sugden, K., Williams, B., Ireland, D., et al. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhy219 · Cited by 50

Boosting diagnosis accuracy of Alzheimer's disease using high dimensional recognition of longitudinal brain atrophy patterns

Farzan, A., Mashohor, S., Ramli, A. R., & Mahmud, R. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.04.010 · Cited by 46

Discriminative Analysis of Mild Alzheimer’s Disease and Normal Aging Using Volume of Hippocampal Subfields and Hippocampal Mean Diffusivity: An In Vivo Magnetic Resonance Imaging Study

Li, Y.-D., Dong, H.-B., Xie, G.-M., & Zhang, L.-J. (2013) · American Journal of Alzheimer's Disease & Other Dementias® · doi:10.1177/1533317513494452 · Cited by 42

Vasoreactivity in CADASIL: comparison to structural MRI and neuropsychology

Moreton, F. C., Cullen, B., Delles, C., Santosh, C., Gonzalez, R. L., Dani, K., & Muir, K. W. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17710375 · Cited by 37

Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer’s disease deficits

Nir, T. M., Jahanshad, N., Villalon‐Reina, J. E., Isaev, D., Zavaliangos‐Petropulu, A., Zhan, L., Leow, A. D., Jack, C. R., Weiner, M. W., Thompson, P. M., et al. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26623 · Cited by 34

White matter differences between healthy young APOE4 carriers and non-carriers identified with tractography and support vector machines

O'Dwyer, L., Lamberton, F., Matura, S., Scheibe, M., Miller, J., Rujescu, D., Prvulovic, D., & Hampel, H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036024 · Cited by 34

REST, a master regulator of neurogenesis, evolved under strong positive selection in humans and in non human primates

Mozzi, A., Guerini, F. R., Forni, D., Costa, A. S., Nemni, R., Baglio, F., Cabinio, M., Riva, S., Pontremoli, C., Clerici, M., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-10245-w · Cited by 28

PBMCs protein expression profile in relapsing IFN-treated multiple sclerosis: A pilot study on relation to clinical findings and brain atrophy

De Masi, R., Vergara, D., Pasca, S., Acierno, R., Greco, M., Spagnolo, L., Blasi, E., Sanapo, F., Trianni, G., & Maffia, M. (2009) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2009.03.002 · Cited by 26

Brain atrophy in paediatric sickle cell anaemia: findings from the silent infarct transfusion (SIT) trial

Kawadler, J. M., Clark, C. A., McKinstry, R. C., & Kirkham, F. J. (2017) · British Journal of Haematology · doi:10.1111/bjh.14039 · Cited by 22

Diffusion tensor imaging findings in children with sluggish cognitive tempo comorbid attention deficit hyperactivity disorder

Ünsel-Bolat, G., Baytunca, M. B., Kardaş, B., İpçi, M., İnci İzmir, S. B., Özyurt, O., Çallı, M. C., & Ercan, E. S. (2020) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2020.1772364 · Cited by 14

Resting state connectivity and cognitive performance in adults with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy

Cullen, B., Moreton, F. C., Stringer, M. S., Krishnadas, R., Kalladka, D., López-González, M. R., Santosh, C., Schwarzbauer, C., & Muir, K. W. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16636395 · Cited by 12

Effects of rhythmic-cued gait training on gait-like task related brain activation in people with multiple sclerosis

Helmlinger, B., Seebacher, B., Ropele, S., Hechenberger, S., Heschl, B., Reishofer, G., Jordan, S., Tinauer, C., Wurth, S., Valsasina, P., et al. (2025) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2025.123426 · Cited by 4