Fast robust automated brain extraction

Snakes: Active contour models

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Cortical Surface-Based Analysis

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Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628

A global optimisation method for robust affine registration of brain images

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

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Normalized Accurate Measurement of Longitudinal Brain Change

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Elastic model-based segmentation of 3-D neuroradiological data sets

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Fully automatic segmentation of the brain in MRI

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Automatic detection of brain contours in MRI data sets

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3-D segmentation of MR images of the head for 3-D display

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Advances in functional and structural MR image analysis and implementation as FSL

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The minimal preprocessing pipelines for the Human Connectome Project

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Consistent resting-state networks across healthy subjects

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Investigations into resting-state connectivity using independent component analysis

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Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

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Regional homogeneity approach to fMRI data analysis.

Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.12.030 · Cited by 2,614

Unbiased average age-appropriate atlases for pediatric studies

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A Bayesian model of shape and appearance for subcortical brain segmentation

Patenaude, B., Smith, S. M., Kennedy, D. N., & Jenkinson, M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.046 · Cited by 2,287

Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

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Grasping the intentions of others with one's own mirror neuron system

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Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers

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Harmonization of multi-site diffusion tensor imaging data

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Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging

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Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth

Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.063 · Cited by 1,125

Reduced resting-state brain activity in the “default network” in normal aging

Damoiseaux, J. S., Beckmann, C. F., Arigita, E. J. S., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Rombouts, S. A. R. B. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm207 · Cited by 1,187

Deep learning for brain MRI segmentation: state of the art and future directions

Akkus, Z., Galimzianova, A., Hoogi, A., Rubin, D. L., & Erickson, B. J. (2017) · Journal of Digital Imaging · doi:10.1007/s10278-017-9983-4 · Cited by 1,129

The pulvinar regulates information transmission between cortical areas based on attention demands

Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012) · Science · doi:10.1126/science.1223082 · Cited by 1,016

Aerobic fitness reduces brain tissue loss in aging humans.

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Organizing conceptual knowledge in humans with a gridlike code

Constantinescu, A. O., O’Reilly, J. X., & Behrens, T. E. J. (2016) · Science · doi:10.1126/science.aaf0941 · Cited by 937

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Ritchie, S. J., Cox, S. R., Shen, X., Lombardo, M. V., Reus, L. M., Alloza, C., Harris, M. A., Alderson, H. L., Hunter, S., Neilson, E., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy109 · Cited by 855

Training writing skills: a cognitive developmental perspective

Kellogg, R. T. (2008) · Journal of Writing Research · doi:10.17239/jowr-2008.01.01.1 · Cited by 868

Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry

Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjornerud, A., Due-Tonnessen, P., Engvig, A., Grydeland, H., Tamnes, C. K., Ostby, Y., & Fjell, A. M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp280 · Cited by 765

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

Wen, J., Thibeau-Sutre, E., Diaz-Melo, M., Samper-González, J., Routier, A., Bottani, S., Dormont, D., Durrleman, S., Burgos, N., & Colliot, O. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101694 · Cited by 809

Automatic Segmentation of MR Brain Images With a Convolutional Neural Network

Moeskops, P., Viergever, M. A., Mendrik, A. M., de Vries, L. S., Benders, M. J. N. L., & Isgum, I. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2548501 · Cited by 861

Whole brain resting-state analysis reveals decreased functional connectivity in major depression

Veer, I. M. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00041 · Cited by 753

SIFT: Spherical-deconvolution informed filtering of tractograms

Smith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.049 · Cited by 752

Resting-state networks in the infant brain

Fransson, P., Skiöld, B., Horsch, S., Nordell, A., Blennow, M., Lagercrantz, H., & Åden, U. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704380104 · Cited by 696

Human iPS cell-derived dopaminergic neurons function in a primate Parkinson’s disease model

Kikuchi, T., Morizane, A., Doi, D., Magotani, H., Onoe, H., Hayashi, T., Mizuma, H., Takara, S., Takahashi, R., Inoue, H., et al. (2017) · Nature · doi:10.1038/nature23664 · Cited by 702

Neural mechanisms of foraging

Kolling, N., Behrens, T. E. J., Mars, R. B., & Rushworth, M. F. S. (2012) · Science · doi:10.1126/science.1216930 · Cited by 629

How Green Is the Grass on the Other Side? Frontopolar Cortex and the Evidence in Favor of Alternative Courses of Action

Boorman, E. D., Behrens, T. E. J., Woolrich, M. W., & Rushworth, M. F. S. (2009) · Neuron · doi:10.1016/j.neuron.2009.05.014 · Cited by 665

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

Loss of ‘Small-World’ Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity

Sanz-Arigita, E. J., Schoonheim, M. M., Damoiseaux, J. S., Rombouts, S. A. R. B., Maris, E., Barkhof, F., Scheltens, P., & Stam, C. J. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013788 · Cited by 608

Effort-Based Cost–Benefit Valuation and the Human Brain

Croxson, P. L., Walton, M. E., O'Reilly, J. X., Behrens, T. E. J., & Rushworth, M. F. S. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.4515-08.2009 · Cited by 560

Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD

Fotenos, A. F., Snyder, A. Z., Girton, L. E., Morris, J. C., & Buckner, R. L. (2005) · Neurology · doi:10.1212/01.wnl.0000154530.72969.11 · Cited by 579

Age-related changes in grey and white matter structure throughout adulthood

Giorgio, A., Santelli, L., Tomassini, V., Bosnell, R., Smith, S., De Stefano, N., & Johansen-Berg, H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.004 · Cited by 532

Anatomical connectivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression

Johansen-Berg, H., Gutman, D. A., Behrens, T. E. J., Matthews, P. M., Rushworth, M. F. S., Katz, E., Lozano, A. M., & Mayberg, H. S. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm167 · Cited by 561

The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: Results of a one‐year exercise intervention

Voss, M. W., Heo, S., Prakash, R. S., Erickson, K. I., Alves, H., Chaddock, L., Szabo, A. N., Mailey, E. L., Wójcicki, T. R., White, S. M., et al. (2013) · Human Brain Mapping · doi:10.1002/hbm.22119 · Cited by 553

Differential development of high-level visual cortex correlates with category-specific recognition memory.

Golarai, G., Ghahremani, D. G., Whitfield-Gabrieli, S., Reiss, A., Eberhardt, J. L., Gabrieli, J. D. E., & Grill-Spector, K. (2007) · Nature Neuroscience · doi:10.1038/nn1865 · Cited by 541

The Resting Human Brain and Motor Learning

Albert, N. B., Robertson, E. M., & Miall, R. C. (2009) · Current Biology · doi:10.1016/j.cub.2009.04.028 · Cited by 510

White matter development in adolescence: A DTI study

Asato, M. R., Terwilliger, R., Woo, J., & Luna, B. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp282 · Cited by 512

Deep MRI brain extraction: A 3D convolutional neural network for skull stripping

Kleesiek, J., Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., & Biller, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.024 · Cited by 505

Mapping Infant Brain Myelination with Magnetic Resonance Imaging

Deoni, S. C. L., Mercure, E., Blasi, A., Gasston, D., Thomson, A., Johnson, M., Williams, S. C. R., & Murphy, D. G. M. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.2106-10.2011 · Cited by 497

Quantitative susceptibility mapping: current status and future directions

Haacke, E. M., Liu, S., Buch, S., Zheng, W., Wu, D., & Ye, Y. (2015) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2014.09.004 · Cited by 511

Physical activity predicts gray matter volume in late adulthood: The Cardiovascular Health Study

Erickson, K. I., Raji, C. A., Lopez, O. L., Becker, J. T., Rosano, C., Newman, A. B., Gach, H. M., Thompson, P. M., Ho, A. J., & Kuller, L. H. (2010) · Neurology · doi:10.1212/wnl.0b013e3181f88359 · Cited by 508

Abnormal functional connectivity in autism spectrum disorders during face processing

Kleinhans, N. M., Richards, T., Sterling, L., Stegbauer, K. C., Mahurin, R., Johnson, L. C., Greenson, J., Dawson, G., & Aylward, E. (2008) · Brain · doi:10.1093/brain/awm334 · Cited by 498

A review of fronto-striatal and fronto-cortical brain abnormalities in children and adults with Attention Deficit Hyperactivity Disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attention

Cubillo, A., Halari, R., Smith, A., Taylor, E., & Rubia, K. (2012) · Cortex · doi:10.1016/j.cortex.2011.04.007 · Cited by 520

MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping

Bilgic, B., Pfefferbaum, A., Rohlfing, T., Sullivan, E. V., & Adalsteinsson, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.077 · Cited by 499

Vicarious responses to pain in anterior cingulate cortex: Is empathy a multisensory issue?

Morrison, I., Lloyd, D., Di Pellegrino, G., & Roberts, N. (2004) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.4.2.270 · Cited by 490

Exploring the role of the posterior middle temporal gyrus in semantic cognition: integration of anterior temporal lobe with executive processes

Davey, J., Thompson, H. E., Hallam, G., Karapanagiotidis, T., Murphy, C., De Caso, I., Krieger-Redwood, K., Bernhardt, B. C., Smallwood, J., & Jefferies, E. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.051 · Cited by 433

The underlying anatomical correlates of long-term meditation: Larger hippocampal and frontal volumes of gray matter

Luders, E., Toga, A. W., Lepore, N., & Gaser, C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.061 · Cited by 469

Reward processing in autism

Scott‐Van Zeeland, A. A., Dapretto, M., Ghahremani, D. G., Poldrack, R. A., & Bookheimer, S. Y. (2010) · Autism Research · doi:10.1002/aur.122 · Cited by 458

Direct Activation of the Ventral Striatum in Anticipation of Aversive Stimuli

Jensen, J., McIntosh, A. R., Crawley, A. P., Mikulis, D. J., Remington, G., & Kapur, S. (2003) · Neuron · doi:10.1016/s0896-6273(03)00724-4 · Cited by 455

Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength

Deistung, A., Schäfer, A., Schweser, F., Biedermann, U., Turner, R., & Reichenbach, J. R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.055 · Cited by 442

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation

Nair, T., Precup, D., Arnold, D. L., & Arbel, T. (2020) · Medical Image Analysis · doi:10.1016/j.media.2019.101557 · Cited by 451

A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression

Riva-Posse, P., Choi, K. S., Holtzheimer, P. E., Crowell, A. L., Garlow, S. J., Rajendra, J. K., McIntyre, C. C., Gross, R. E., & Mayberg, H. S. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.59 · Cited by 441

Methodological considerations on tract-based spatial statistics (TBSS)

Bach, M., Laun, F. B., Leemans, A., Tax, C. M. W., Biessels, G. J., Stieltjes, B., & Maier-Hein, K. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.021 · Cited by 445

The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder

Hahamy, A., Behrmann, M., & Malach, R. (2015) · Nature Neuroscience · doi:10.1038/nn.3919 · Cited by 416

Neurocognitive endophenotypes of obsessive-compulsive disorder

Menzies, L., Achard, S., Chamberlain, S. R., Fineberg, N., Chen, C.-H., del Campo, N., Sahakian, B. J., Robbins, T. W., & Bullmore, E. (2007) · Brain · doi:10.1093/brain/awm205 · Cited by 443

Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest

Cabral, J., Vidaurre, D., Marques, P., Magalhães, R., Silva Moreira, P., Miguel Soares, J., Deco, G., Sousa, N., & Kringelbach, M. L. (2017) · Scientific Reports · doi:10.1038/s41598-017-05425-7 · Cited by 386

Neurobiological markers of exercise-related brain plasticity in older adults

Voss, M. W., Erickson, K. I., Prakash, R. S., Chaddock, L., Kim, J. S., Alves, H., Szabo, A., Phillips, S. M., Wójcicki, T. R., Mailey, E. L., et al. (2013) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2012.10.021 · Cited by 418

Considering the role of semantic memory in episodic future thinking: evidence from semantic dementia

Irish, M., Addis, D. R., Hodges, J. R., & Piguet, O. (2012) · Brain · doi:10.1093/brain/aws119 · Cited by 405

Quantitative Investigation of Connections of the Prefrontal Cortex in the Human and Macaque using Probabilistic Diffusion Tractography

Croxson, P. L., Johansen-Berg, H., Behrens, T. E. J., Robson, M. D., Pinsk, M. A., Gross, C. G., Richter, W., Richter, M. C., Kastner, S., & Rushworth, M. F. S. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.1311-05.2005 · Cited by 410

Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks

Musso, F., Brinkmeyer, J., Mobascher, A., Warbrick, T., & Winterer, G. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.093 · Cited by 387

Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies

Radua, J., Rubia, K., Canales-Rodríguez, E. J., Pomarol-Clotet, E., Fusar-Poli, P., & Mataix-Cols, D. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00013 · Cited by 406

Abnormal structure of frontostriatal brain systems is associated with aspects of impulsivity and compulsivity in cocaine dependence

Ersche, K. D., Barnes, A., Jones, P. S., Morein-Zamir, S., Robbins, T. W., & Bullmore, E. T. (2011) · Brain · doi:10.1093/brain/awr138 · Cited by 389

Immaturities in reward processing and its influence on inhibitory control in adolescence.

Geier, C. F., Terwilliger, R., Teslovich, T., Velanova, K., & Luna, B. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp225 · Cited by 396

Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease

Acosta-Cabronero, J., Williams, G. B., Pengas, G., & Nestor, P. J. (2010) · Brain · doi:10.1093/brain/awp257 · Cited by 393

Longitudinal changes in grey and white matter during adolescence

Giorgio, A., Watkins, K. E., Chadwick, M., James, S., Winmill, L., Douaud, G., De Stefano, N., Matthews, P. M., Smith, S. M., Johansen-Berg, H., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.003 · Cited by 394

Corticostriatal connectivity underlies individual differences in the balance between habitual and goal-directed action control

de Wit, S., Watson, P., Harsay, H. A., Cohen, M. X., van de Vijver, I., & Ridderinkhof, K. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1088-12.2012 · Cited by 373

Oxytocin modulates amygdala, insula, and inferior frontal gyrus responses to infant crying: a randomized controlled trial

Riem, M. M. E., Bakermans-Kranenburg, M. J., Pieper, S., Tops, M., Boksem, M. A. S., Vermeiren, R. R. J. M., van IJzendoorn, M. H., & Rombouts, S. A. R. B. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.02.006 · Cited by 366

fMRI evidence of compensatory mechanisms in older adults at genetic risk for Alzheimer disease

Bondi, M. W., Houston, W. S., Eyler, L. T., & Brown, G. G. (2005) · Neurology · doi:10.1212/01.wnl.0000150885.00929.7e · Cited by 372

Microstructure Abnormalities in Adolescents with Internet Addiction Disorder

Yuan, K., Qin, W., Wang, G., Zeng, F., Zhao, L., Yang, X., Liu, P., Liu, J., Sun, J., von Deneen, K. M., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020708 · Cited by 367

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

Development of Cortical Surface Area and Gyrification in Attention-Deficit/Hyperactivity Disorder

Shaw, P., Malek, M., Watson, B., Sharp, W., Evans, A., & Greenstein, D. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.01.031 · Cited by 357

Brain Imaging Correlates of Depressive Symptom Severity and Predictors of Symptom Improvement After Antidepressant Treatment

Chen, C.-H., Ridler, K., Suckling, J., Williams, S., Fu, C. H. Y., Merlo-Pich, E., & Bullmore, E. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.09.018 · Cited by 354

Early brain enlargement and elevated extra-axial fluid in infants who develop autism spectrum disorder

Shen, M. D., Nordahl, C. W., Young, G. S., Wootton-Gorges, S. L., Lee, A., Liston, S. E., Harrington, K. R., Ozonoff, S., & Amaral, D. G. (2013) · Brain · doi:10.1093/brain/awt166 · Cited by 345

A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention

Fiebelkorn, I. C., Pinsk, M. A., & Kastner, S. (2018) · Neuron · doi:10.1016/j.neuron.2018.07.038 · Cited by 356

Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging

Nir, T. M., Jahanshad, N., Villalon-Reina, J. E., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.07.006 · Cited by 348

Visual inspection of independent components: defining a procedure for artifact removal from fMRI data

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How the Opinion of Others Affects Our Valuation of Objects

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