A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development

Whole Brain Segmentation

Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610

Unbiased average age-appropriate atlases for pediatric studies

Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.033 · Cited by 2,290

Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template

Lancaster, J. L., Tordesillas‐Gutiérrez, D., Martinez, M., Salinas, F., Evans, A., Zilles, K., Mazziotta, J. C., & Fox, P. T. (2007) · Human Brain Mapping · doi:10.1002/hbm.20345 · Cited by 1,464

Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children

Sowell, E. R., Thompson, P. M., Leonard, C. M., Welcome, S. E., Kan, E., & Toga, A. W. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.1798-04.2004 · Cited by 1,481

Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation

Sowell, E. R., Thompson, P. M., Tessner, K. D., & Toga, A. W. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-22-08819.2001 · Cited by 983

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

the Alzheimer’s Disease Neuroimaging Initiative, E. C., Thompson, P. M., Stein, J. L., Medland, S. E., Hibar, D. P., Vasquez, A. A., Renteria, M. E., Toro, R., Jahanshad, N., Schumann, G., et al. (2014) · Brain Imaging and Behavior · doi:10.1007/s11682-013-9269-5 · Cited by 838

A review of diffusion tensor imaging studies in schizophrenia

Kubicki, M., McCarley, R., Westin, C.-F., Park, H.-J., Maier, S., Kikinis, R., Jolesz, F. A., & Shenton, M. E. (2007) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2005.05.005 · Cited by 769

Sex differences in cortical thickness mapped in 176 healthy individuals between 7 and 87 years of age

Sowell, E. R., Peterson, B. S., Kan, E., Woods, R. P., Yoshii, J., Bansal, R., Xu, D., Zhu, H., Thompson, P. M., & Toga, A. W. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl066 · Cited by 695

Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories

Pruessner, J. C. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.4.433 · Cited by 706

Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements

Tustison, N. J., Cook, P. A., Klein, A., Song, G., Das, S. R., Duda, J. T., Kandel, B. M., van Strien, N., Stone, J. R., Gee, J. C., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.044 · Cited by 670

Cortical abnormalities in children and adolescents with attention-deficit hyperactivity disorder

Sowell, E. R., Thompson, P. M., Welcome, S. E., Henkenius, A. L., Toga, A. W., & Peterson, B. S. (2003) · The Lancet · doi:10.1016/s0140-6736(03)14842-8 · Cited by 567

Localizing Age-Related Changes in Brain Structure between Childhood and Adolescence Using Statistical Parametric Mapping

Sowell, E. R., Thompson, P. M., Holmes, C. J., Batth, R., Jernigan, T. L., & Toga, A. W. (1999) · NeuroImage · doi:10.1006/nimg.1999.0436 · Cited by 554

Effects of Aβ immunization (AN1792) on MRI measures of cerebral volume in Alzheimer disease

Fox, N. C., Black, R. S., Gilman, S., Rossor, M. N., Griffith, S. G., Jenkins, L., & Koller, M. (2005) · Neurology · doi:10.1212/01.wnl.0000159743.08996.99 · Cited by 550

Neural basis of anxiolytic effects of cannabidiol (CBD) in generalized social anxiety disorder: A preliminary report

Crippa, J. A. S., Derenusson, G. N., Ferrari, T. B., Wichert-Ana, L., Duran, F. L., Martin-Santos, R., Simões, M. V., Bhattacharyya, S., Fusar-Poli, P., Atakan, Z., et al. (2011) · Journal of Psychopharmacology · doi:10.1177/0269881110379283 · Cited by 535

Studying the human brain anatomical network via diffusion-weighted MRI and graph theory

Iturria-Medina, Y., Sotero, R. C., Canales-Rodríguez, E. J., Alemán-Gómez, Y., & Melie-García, L. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.060 · Cited by 506

From threat to fear: the neural organization of defensive fear systems in humans.

Mobbs, D., Marchant, J. L., Hassabis, D., Seymour, B., Tan, G., Gray, M., Petrovic, P., Dolan, R. J., & Frith, C. D. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2378-09.2009 · Cited by 476

Dopaminergic Mechanisms of Reduced Basal Ganglia Responses to Hedonic Reward During Interferon Alfa Administration

Capuron, L., Pagnoni, G., Drake, D. F., Woolwine, B. J., Spivey, J. R., Crowe, R. J., Votaw, J. R., Goodman, M. M., & Miller, A. H. (2012) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.2094 · Cited by 382

Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention

Tuch, D. S., Salat, D. H., Wisco, J. J., Zaleta, A. K., Hevelone, N. D., & Rosas, H. D. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407259102 · Cited by 364

Gray matter differences correlate with spontaneous strategies in a human virtual navigation task

Bohbot, V. D., Lerch, J., Thorndycraft, B., Iaria, G., & Zijdenbos, A. P. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1763-07.2007 · Cited by 347

Observer-independent method for microstructural parcellation of cerebral cortex: a quantitative approach to cytoarchitectonics.

Schleicher, A., Amunts, K., Geyer, S., Morosan, P., & Zilles, K. (1999) · NeuroImage · doi:10.1006/nimg.1998.0385 · Cited by 353

Brain structures mediating cardiovascular arousal and interoceptive awareness

Pollatos, O., Schandry, R., Auer, D. P., & Kaufmann, C. (2007) · Brain Research · doi:10.1016/j.brainres.2007.01.026 · Cited by 351

Three-dimensional statistical analysis of sulcal variability in the human brain

Thompson, P. M., Schwartz, C., Lin, R. T., Khan, A. A., & Toga, A. W. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-13-04261.1996 · Cited by 346

Trajectories of cortical thickness maturation in normal brain development — The importance of quality control procedures

Ducharme, S., Albaugh, M. D., Nguyen, T.-V., Hudziak, J. J., Mateos-Pérez, J. M., Labbe, A., Evans, A. C., & Karama, S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.010 · Cited by 304

Self-esteem, locus of control, hippocampal volume, and cortisol regulation in young and old adulthood

Pruessner, J. C., Baldwin, M. W., Dedovic, K., Renwick, R., Mahani, N. K., Lord, C., Meaney, M., & Lupien, S. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.014 · Cited by 336

Abnormal Amygdala Resting-State Functional Connectivity in Adolescent Depression

Cullen, K. R., Westlund, M. K., Klimes-Dougan, B., Mueller, B. A., Houri, A., Eberly, L. E., & Lim, K. O. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.1087 · Cited by 324

Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study

Ridha, B. H., Barnes, J., Bartlett, J. W., Godbolt, A., Pepple, T., Rossor, M. N., & Fox, N. C. (2006) · The Lancet Neurology · doi:10.1016/s1474-4422(06)70550-6 · Cited by 326

Effects of cannabidiol (CBD) on regional cerebral blood flow

Crippa, J. A. D. S., Zuardi, A. W., Garrido, G. E. J., Wichert-Ana, L., Guarnieri, R., Ferrari, L., Azevedo-Marques, P. M., Hallak, J. E. C., McGuire, P. K., & Busatto, G. F. (2004) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300340 · Cited by 307

Volumetry of temporopolar, perirhinal, entorhinal and parahippocampal cortex from high-resolution MR images: considering the variability of the collateral sulcus

Pruessner, J. C. (2002) · Cerebral Cortex · doi:10.1093/cercor/12.12.1342 · Cited by 297

Age and gender predict volume decline in the anterior and posterior hippocampus in early adulthood

Pruessner, J. C., Collins, D. L., Pruessner, M., & Evans, A. C. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-01-00194.2001 · Cited by 292

A brief history of human brain mapping

Raichle, M. E. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2008.11.001 · Cited by 286

Relationship between white matter fractional anisotropy and other indices of cerebral health in normal aging: tract-based spatial statistics study of aging

Kochunov, P., Thompson, P. M., Lancaster, J. L., Bartzokis, G., Smith, S., Coyle, T., Royall, D. R., Laird, A., & Fox, P. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.12.021 · Cited by 250

Reducing between scanner differences in multi-center PET studies

Joshi, A., Koeppe, R. A., & Fessler, J. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.057 · Cited by 247

Meta-analysis of reward processing in major depressive disorder reveals distinct abnormalities within the reward circuit

Ng, T. H., Alloy, L. B., & Smith, D. V. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0644-x · Cited by 244

Cognition and brain structure following early childhood surgery with anesthesia

Backeljauw, B., Holland, S. K., Altaye, M., & Loepke, A. W. (2015) · PEDIATRICS · doi:10.1542/peds.2014-3526 · Cited by 239

Hippocampal Morphology and Distinguishing Late-Onset From Early-Onset Elderly Depression

Ballmaier, M., Narr, K. L., Toga, A. W., Elderkin-Thompson, V., Thompson, P. M., Hamilton, L., Haroon, E., Pham, D., Heinz, A., & Kumar, A. (2008) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2007.07030506 · Cited by 226

A Parametric Approach to Orthographic Processing in the Brain: An fMRI Study

Tagamets, M. A., Novick, J. M., Chalmers, M. L., & Friedman, R. B. (2000) · Journal of Cognitive Neuroscience · doi:10.1162/089892900562101 · Cited by 224

Effortless awareness: using real time neurofeedback to investigate correlates of posterior cingulate cortex activity in meditators' self-report

Garrison, K. A., Santoyo, J. F., Davis, J. H., Thornhill, T. A., Kerr, C. E., & Brewer, J. A. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00440 · Cited by 219

Hemispheric and Gender-related Differences in the Gross Morphology of the Anterior Cingulate/Paracingulate Cortex in Normal Volunteers: An MRI Morphometric Study

Yucel, M., Stuart, G. W., Maruff, P., Velakoulis, D., Crowe, S. F., Savage, G., & Pantelis, C. (2001) · Cerebral Cortex · doi:10.1093/cercor/11.1.17 · Cited by 222

Mapping sulcal pattern asymmetry and local cortical surface gray matter distribution in vivo: maturation in perisylvian cortices

Sowell, E. R. (2002) · Cerebral Cortex · doi:10.1093/cercor/12.1.17 · Cited by 212

Functional interactions of the inferior frontal cortex during the processing of words and word-like stimuli

Bokde, A. L. W., Tagamets, M.-A., Friedman, R. B., & Horwitz, B. (2001) · Neuron · doi:10.1016/s0896-6273(01)00288-4 · Cited by 211

A survey of methods for 3D histology reconstruction

Pichat, J., Iglesias, J. E., Yousry, T., Ourselin, S., & Modat, M. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.02.004 · Cited by 207

The Kuleshov Effect: the influence of contextual framing on emotional attributions

Mobbs, D., Weiskopf, N., Lau, H. C., Featherstone, E., Dolan, R. J., & Frith, C. D. (2006) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsl014 · Cited by 178

Hippocampal volume is as variable in young as in older adults: implications for the notion of hippocampal atrophy in humans

Lupien, S. J., Evans, A., Lord, C., Miles, J., Pruessner, M., Pike, B., & Pruessner, J. C. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.041 · Cited by 167

Parallel distributed networks resolved at high resolution reveal close juxtaposition of distinct regions

Braga, R. M., Van Dijk, K. R. A., Polimeni, J. R., Eldaief, M. C., & Buckner, R. L. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00808.2018 · Cited by 162

Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures.

Uddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S., & Figley, C. R. (2019) · Scientific Reports · doi:10.1038/s41598-019-39199-x · Cited by 151

Elucidating a magnetic resonance imaging-based neuroanatomic biomarker for psychosis: classification analysis using probabilistic brain atlas and machine learning algorithms

Sun, D., van Erp, T. G. M., Thompson, P. M., Bearden, C. E., Daley, M., Kushan, L., Hardt, M. E., Nuechterlein, K. H., Toga, A. W., & Cannon, T. D. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.07.019 · Cited by 148

Dynamic 11 C-PiB PET Shows Cerebrospinal Fluid Flow Alterations in Alzheimer Disease and Multiple Sclerosis

Schubert, J. J., Veronese, M., Marchitelli, L., Bodini, B., Tonietto, M., Stankoff, B., Brooks, D. J., Bertoldo, A., Edison, P., & Turkheimer, F. E. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.118.223834 · Cited by 121

Gray matter volumes in obsessive-compulsive disorder before and after fluoxetine or cognitive-behavior therapy: a randomized clinical trial

Hoexter, M. Q., de Souza Duran, F. L., D'Alcante, C. C., Dougherty, D. D., Shavitt, R. G., Lopes, A. C., Diniz, J. B., Deckersbach, T., Batistuzzo, M. C., Bressan, R. A., et al. (2012) · Neuropsychopharmacology · doi:10.1038/npp.2011.250 · Cited by 123

Selective attention modulates inferior frontal gyrus activity during action observation

Chong, T. T.-J., Williams, M. A., Cunnington, R., & Mattingley, J. B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.11.030 · Cited by 118

Identifying incipient dementia individuals using machine learning and amyloid imaging

Mathotaarachchi, S., Pascoal, T. A., Shin, M., Benedet, A. L., Kang, M. S., Beaudry, T., Fonov, V. S., Gauthier, S., & Rosa-Neto, P. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.06.027 · Cited by 118

A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom

Lee, J. K., Lee, J.-M., Kim, J. S., Kim, I. Y., Evans, A. C., & Kim, S. I. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.044 · Cited by 108

Comparison of 18F‐florbetaben quantification results using the standard Centiloid, MR‐based, and MR‐less CapAIBL® approaches: Validation against histopathology

Doré, V., Bullich, S., Rowe, C. C., Bourgeat, P., Konate, S., Sabri, O., Stephens, A. W., Barthel, H., Fripp, J., Masters, C. L., et al. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.02.005 · Cited by 93

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Chincarini, A., Sensi, F., Rei, L., Gemme, G., Squarcia, S., Longo, R., Brun, F., Tangaro, S., Bellotti, R., Amoroso, N., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.065 · Cited by 94

Mapping Cortical Thickness in Children with 22q11.2 Deletions

Bearden, C. E., van Erp, T. G. M., Dutton, R. A., Tran, H., Zimmermann, L., Sun, D., Geaga, J. A., Simon, T. J., Glahn, D. C., Cannon, T. D., et al. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl097 · Cited by 92

Mapping brain size and cortical gray matter changes in elderly depression

Ballmaier, M., Sowell, E. R., Thompson, P. M., Kumar, A., Narr, K. L., Lavretsky, H., Welcome, S. E., DeLuca, H., & Toga, A. W. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2003.09.004 · Cited by 91

Viewing one’s own face being touched modulates tactile perception: An fMRI study

Cardini, F., Costantini, M., Galati, G., Romani, G. L., Làdavas, E., & Serino, A. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21484 · Cited by 92

Using executive control training to suppress amygdala reactivity to aversive information

Cohen, N., Margulies, D. S., Ashkenazi, S., Schaefer, A., Taubert, M., Henik, A., Villringer, A., & Okon-Singer, H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.069 · Cited by 90

Functional Connectivity of the Striatum Links Motivation to Action Control in Humans

Harsay, H. A., Cohen, M. X., Oosterhof, N. N., Forstmann, B. U., Mars, R. B., & Ridderinkhof, K. R. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5415-10.2011 · Cited by 75

Neural correlates of suicidality in adolescents with major depression: Resting-state functional connectivity of the precuneus and posterior cingulate cortex

Schreiner, M. W., Klimes‐Dougan, B., & Cullen, K. R. (2019) · Suicide and Life-Threatening Behavior · doi:10.1111/sltb.12471 · Cited by 69

Measuring disease progression in frontotemporal lobar degeneration: A clinical and MRI study

Gordon, E., Rohrer, J. D., Kim, L. G., Omar, R., Rossor, M. N., Fox, N. C., & Warren, J. D. (2010) · Neurology · doi:10.1212/wnl.0b013e3181d1a879 · Cited by 70

Detecting Sisease-Specific Patterns of Brain Structure Using Cortical Pattern Matching and a Population-Based Probabilistic Brain Atlas

Thompson, P. M., Mega, M. S., Vidal, C., Rapoport, J. L., & Toga, A. W. (2001) · Lecture Notes in Computer Science · doi:10.1007/3-540-45729-1_52 · Cited by 67

Reward-related frontostriatal activity and smoking behavior among adolescents in treatment for smoking cessation

Garrison, K. A., Yip, S. W., Balodis, I. M., Carroll, K. M., Potenza, M. N., & Krishnan-Sarin, S. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2017.03.035 · Cited by 65

Recruitment of occipital cortex during sensory substitution training linked to subjective experience of seeing in people with blindness

Ortiz, T., Poch, J., Santos, J. M., Requena, C., Martínez, A. M., Ortiz-Terán, L., Turrero, A., Barcia, J., Nogales, R., Calvo, A., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023264 · Cited by 63

A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes

Nitzsche, B., Frey, S., Collins, L. D., Seeger, J., Lobsien, D., Dreyer, A., Kirsten, H., Stoffel, M. H., Fonov, V. S., & Boltze, J. (2015) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2015.00069 · Cited by 61

Abnormal striatal resting-state functional connectivity in adolescents with obsessive–compulsive disorder

Bernstein, G. A., Mueller, B. A., Schreiner, M. W., Campbell, S. M., Regan, E. K., Nelson, P. M., Houri, A. K., Lee, S. S., Zagoloff, A. D., Lim, K. O., et al. (2016) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2015.11.002 · Cited by 49

Identifying good practices for detecting inter-regional linear functional connectivity from EEG

Pellegrini, F., Delorme, A., Nikulin, V., & Haufe, S. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120218 · Cited by 43

Neuroanatomical correlates of behavioral rating versus performance measures of working memory in typically developing children and adolescents.

Faridi, N., Karama, S., Burgaleta, M., White, M. T., Evans, A. C., Fonov, V., Collins, D. L., & Waber, D. P. (2015) · Neuropsychology · doi:10.1037/neu0000079 · Cited by 42

Hypnosis and pain perception: an Activation Likelihood Estimation (ALE) meta-analysis of functional neuroimaging studies

Del Casale, A., Ferracuti, S., Rapinesi, C., De Rossi, P., Angeletti, G., Sani, G., Kotzalidis, G. D., & Girardi, P. (2015) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2016.01.001 · Cited by 39

Abnormal grey matter in victims of rape with PTSD in mainland China: a voxel - based morphometry study

Sui, S. G., Wu, M. X., King, M. E., Zhang, Y., Ling, L., Xu, J. M., Weng, X. C., Duan, L., Shan, B. C., & Li, L. J. (2010) · Acta Neuropsychiatrica · doi:10.1111/j.1601-5215.2010.00459.x · Cited by 36

On the Usage of Brain Atlases in Neuroimaging Research

Hess, A., Hinz, R., Keliris, G. A., & Boehm-Sturm, P. (2018) · Molecular Imaging and Biology · doi:10.1007/s11307-018-1259-y · Cited by 30

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data

Mitchell, J. R., Kamnitsas, K., Singleton, K. W., Whitmire, S. A., Clark-Swanson, K. R., Ranjbar, S., Rickertsen, C. R., Johnston, S. K., Egan, K. M., Rollison, D. E., et al. (2020) · Journal of Medical Imaging · doi:10.1117/1.jmi.7.5.055501 · Cited by 15

Machine Learning Based Analysis of Structural MRI for Epilepsy Diagnosis

Sahebzamani, G., Saffar, M., & Soltanian-Zadeh, H. (2019) · 2019 4th International Conference on Pattern Recognition and Image Analysis (IPRIA) · doi:10.1109/pria.2019.8785985 · Cited by 8

Correlation of Parkinson's disease severity and duration with123I-FP-CIT SPECT striatal uptake

Benamer, H. T. S., Patterson, J., Wyper, D. J., Hadley, D. M., Macphee, G. J. A., & Grosset, D. G. (2000) · Movement Disorders · doi:10.1002/1531-8257(200007)15:4<692::aid-mds1014>3.0.co;2-v