Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images

A global optimisation method for robust affine registration of brain images

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Multimodality image registration by maximization of mutual information

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Movement‐Related effects in fMRI time‐series

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Spatial registration and normalization of images

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Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space

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A survey of medical image registration

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Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data

Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001) · NeuroImage · doi:10.1006/nimg.2001.0931 · Cited by 2,859

MRI-PET Registration with Automated Algorithm

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Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

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Recent Developments in Nonparametric Density Estimation

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Functional neuroimaging of belief, disbelief, and uncertainty

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Surprise and Error: Common Neuronal Architecture for the Processing of Errors and Novelty

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Ipsilesional anodal tDCS enhances the functional benefits of rehabilitation in patients after stroke

Allman, C., Amadi, U., Winkler, A. M., Wilkins, L., Filippini, N., Kischka, U., Stagg, C. J., & Johansen‐Berg, H. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aad5651 · Cited by 225

Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

Chen, J., Tam, A., Kebets, V., Orbán, C., Ooi, L. Q. R., Asplund, C. L., Marek, S. A., Dosenbach, N. U. F., Eickhoff, S. B., Bzdok, D., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29766-8 · Cited by 240

Integrated Imaging Approach with MEG and DTI to Detect Mild Traumatic Brain Injury in Military and Civilian Patients

Huang, M., Theilmann, R. J., Robb, A., Angeles, A., Nichols, S., Drake, A., DAndrea, J., Levy, M. L., Holland, M., Song, T., et al. (2009) · Journal of Neurotrauma · doi:10.1089/neu.2008.0672 · Cited by 227

Optimized Brain Extraction for Pathological Brains (optiBET)

Lutkenhoff, E. S., Rosenberg, M., Chiang, J. N., Zhang, K., Pickard, J. D., Owen, A. M., & Monti, M. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0115551 · Cited by 226

Adding dynamics to the Human Connectome Project with MEG

Larson‐Prior, L. J., Oostenveld, R., Penna, S. D., Michalareas, G., Prior, F., Abbas Babajani-feremi, A., Schoffelen, J., Marzetti, L., de Pasquale, F., Pompeo, F., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.056 · Cited by 222

Neural correlates of training-related working-memory gains in old age

Brehmer, Y., Rieckmann, A., Bellander, M., Westerberg, H., Fischer, H., & Bäckman, L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.06.079 · Cited by 218

Distinction of seropositive NMO spectrum disorder and MS brain lesion distribution

Matthews, L., Marasco, R., Jenkinson, M., Küker, W., Luppe, S., Leite, M. I., Giorgio, A., De Stefano, N., Robertson, N., Johansen-Berg, H., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e3182887957 · Cited by 225

Motion correction in MRI of the brain

Godenschweger, F., Kägebein, U., Stucht, D., Yarach, U., Sciarra, A., Yakupov, R., Lüsebrink, F., Schulze, P., & Speck, O. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/5/r32 · Cited by 225

Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine in humans

Driesen, N. R., McCarthy, G., Bhagwagar, Z., Bloch, M., Calhoun, V, D'Souza, D. C., Gueorguieva, R., He, G., Ramachandran, R., Suckow, R. F., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.194 · Cited by 224

Cortical maturation and myelination in healthy toddlers and young children

Deoni, S. C. L., Dean, D. C., Remer, J., Dirks, H., & O’Muircheartaigh, J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.058 · Cited by 221

A Common Network in the Left Cerebral Hemisphere Represents Planning of Tool Use Pantomimes and Familiar Intransitive Gestures at the Hand-Independent Level

Króliczak, G., & Frey, S. H. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn261 · Cited by 224

Early nutrition influences developmental myelination and cognition in infants and young children

Deoni, S., Dean, D., Joelson, S., O’Regan, J., & Schneider, N. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.056 · Cited by 242

Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin

Lord, L.-D., Expert, P., Atasoy, S., Roseman, L., Rapuano, K. M., Lambiotte, R., Nutt, D., Deco, G., Carhart-Harris, R. L., Kringelbach, M. L., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.060 · Cited by 221

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

Reward circuitry function in autism during face anticipation and outcomes

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Manifestations of early brain recovery associated with abstinence from alcoholism

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Sensory uncertainty decoded from visual cortex predicts behavior

van Bergen, R. S., Ma, W. J., Pratte, M. S., & Jehee, J. F. M. (2015) · Nature Neuroscience · doi:10.1038/nn.4150 · Cited by 235

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks

Guerrero, R., Qin, C., Oktay, O., Bowles, C. T., Chen, L., Joules, R., Wolz, R., Valdés-Hernández, M. C., Dickie, D. A., Wardlaw, J. M., et al. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.12.022 · Cited by 222

Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

Grech‐Sollars, M., Hales, P. W., Miyazaki, K., Raschke, F., Rodriguez, D., Wilson, M., Gill, S. K., Banks, T., Saunders, D. E., Clayden, J. D., et al. (2015) · NMR in Biomedicine · doi:10.1002/nbm.3269 · Cited by 213

Molecular, Pathological, Radiological, and Immune Profiling of Non-brainstem Pediatric High-Grade Glioma from the HERBY Phase II Randomized Trial

Mackay, A. G., Burford, A., Molinari, V., Jones, D., Izquierdo, E., Brouwer‐Visser, J., Giangaspero, F., Haberler, C., Pietsch, T., Jacques, T. S., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.04.004 · Cited by 229

Disrupted structural and functional brain networks in Alzheimer's disease

Dai, Z., Lin, Q., Li, T., Wang, X., Yuan, H., Yu, X., Yong He, A., & Wang, H. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.11.005 · Cited by 222

Resting state networks distinguish human ventral tegmental area from substantia nigra

Murty, V. P., Shermohammed, M., Smith, D. V., Carter, R., Huettel, S. A., & Adcock, R. A. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.047 · Cited by 222

fMRI reveals neural activity overlap between adult and infant pain

Goksan, S., Hartley, C., Emery, F., Cockrill, N., Poorun, R., Moultrie, F., Rogers, R., Campbell, J., Sanders, M., Adams, E., et al. (2015) · eLife · doi:10.7554/elife.06356 · Cited by 220

Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma

Kickingereder, P., Neuberger, U., Bonekamp, D., Piechotta, P. L., GOETZ, M. A., Wick, A., Sill, M., Kratz, A., Shinohara, R. T., Jones, D., et al. (2017) · Neuro-Oncology · doi:10.1093/neuonc/nox188 · Cited by 219

Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics

Mennes, M., Zuo, X., Kelly, C. A. M., Martino, A. D., Zang, Y., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.046 · Cited by 218

Age-related differences in regional brain volumes: A comparison of optimized voxel-based morphometry to manual volumetry

Kennedy, K. M., Erickson, K. I., Rodrigue, K. M., Voss, M. W., Colcombe, S. J., Kramer, A. F., Acker, J. D., & Raz, N. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.12.020 · Cited by 214

Mnemonic Training Reshapes Brain Networks to Support Superior Memory

Dresler, M., Shirer, W. R., Konrad, B. N., Müller, N. C. J., Wagner, I. C., Fernández, G., Czisch, M., & Greicius, M. D. (2017) · Neuron · doi:10.1016/j.neuron.2017.02.003 · Cited by 221

Parallel distributed networks dissociate episodic and social functions within the individual

DiNicola, L. M., Braga, R. M., & Buckner, R. L. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00529.2019 · Cited by 230

Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI: Motion Bias in Analyses of Structural MRI

Alexander-Bloch, A., Clasen, L., Stockman, M., Ronan, L., Lalonde, F., Giedd, J., & Raznahan, A. (2016) · Human Brain Mapping · doi:10.1002/hbm.23180 · Cited by 178

Automatic independent component labeling for artifact removal in fMRI

Tohka, J., Foerde, K., Aron, A. R., Tom, S. M., Toga, A. W., & Poldrack, R. A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.013 · Cited by 217

GLISTR: Glioma Image Segmentation and Registration

Gooya, A., Pohl, K. M., Bilello, M., Cirillo, L., Biros, G., Melhem, E. R., & Davatzikos, C. A. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2210558 · Cited by 217

Dorsal and ventral pathways in language development

Bräuer, J., Anwander, A., Perani, D., & Friederici, A. D. (2013) · Brain and Language · doi:10.1016/j.bandl.2013.03.001 · Cited by 217

The Rotterdam Scan Study: design update 2016 and main findings

Ikram, M. A., van der Lugt, A., Niessen, W. J., Koudstaal, P. J., Krestin, G. P., Albert Hofman, D., Bos, D., & Vernooij, M. W. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-0105-7 · Cited by 218

Aerobic fitness is associated with greater efficiency of the network underlying cognitive control in preadolescent children

Voss, M. W., Chaddock, L., Kim, J. S., VanPatter, M., Pontifex, M. B., Raine, L. B., Cohen, N. J., Hillman, C. H., & Kramer, A. F. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2011.10.009 · Cited by 242

Network localization of cervical dystonia based on causal brain lesions

Joutsa, J., Darby, R. R., Delnooz, C. C. S., van de Warrenburg, B. P. C., Cooke, D., Prudente, C. N., Ren, J., Reich, M. M., Batla, A., Bhatia, K. P., et al. (2019) · Brain · doi:10.1093/brain/awz112 · Cited by 217

Infra-Slow EEG Fluctuations Are Correlated with Resting-State Network Dynamics in fMRI

Hiltunen, T., Kantola, J., Elseoud, A. A., Lepola, P., Suominen, K., Starck, T., Nikkinen, J., Remes, J. J., Tervonen, O. A., Palva, S., et al. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0276-13.2014 · Cited by 227

Disrupted Functional Connectivity of the Pain Network in Fibromyalgia

Cifré, I., Sitges, C., Fraiman, D., Muñoz, M. Á., Balenzuela, P., González‐Roldán, A. M., Martínez-Jauand, M., Birbaumer, N., Chialvo, D. R., & Montoya, P. (2011) · Psychosomatic Medicine · doi:10.1097/psy.0b013e3182408f04 · Cited by 215

The neural correlates of statistical learning in a word segmentation task: An fMRI study

Karuza, E. A., Newport, E. L., Aslin, R. Ν., Starling, S. J., Tivarus, M. E., & Bavelier, D. (2013) · Brain and Language · doi:10.1016/j.bandl.2012.11.007 · Cited by 208

Human and Monkey Ventral Prefrontal Fibers Use the Same Organizational Principles to Reach Their Targets: Tracing versus Tractography

Jbabdi, S., Lehman, J. F., Haber, S. N., & Behrens, T. E. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2457-12.2013 · Cited by 213

A Distinct Role of the Temporal-Parietal Junction in Predicting Socially Guided Decisions

Carter, R. M., Bowling, D. L., Reeck, C., & Huettel, S. A. (2012) · Science · doi:10.1126/science.1219681 · Cited by 238

Neural mechanisms supporting maladaptive food choices in anorexia nervosa

Foerde, K., STEINGLASS, J. E., Daphna Shohamy, A., & Walsh, B. T. (2015) · Nature Neuroscience · doi:10.1038/nn.4136 · Cited by 218

Aerobic fitness is associated with gray matter volume and white matter integrity in multiple sclerosis

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Structural and functional connectivity of the precuneus and thalamus to the default mode network

Cunningham, S. I., Tomasi, D. G., & Volkow, N. D. (2016) · Human Brain Mapping · doi:10.1002/hbm.23429 · Cited by 218

Blood-brain barrier impairment and hypoperfusion are linked in cerebral small vessel disease

Wong, S. M., Jansen, J. F. A., Zhang, C. E., Hoff, E. I., Staals, J., van Oostenbrugge, R. J., & Backes, W. H. (2019) · Neurology · doi:10.1212/wnl.0000000000007263 · Cited by 213

Neuroimaging of inhibitory control areas in children with attention deficit hyperactivity disorder who were treatment naive or in long-term treatment

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Noradrenaline mediates amygdala activation in men and women during encoding of emotional material

van Stegeren, A. H., Goekoop, R., Everaerd, W., Scheltens, P., Barkhof, F., Kuijer, J. P. A., & Rombouts, S. A. R. B. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.011 · Cited by 212

Longitudinal Evaluation of Resting-State fMRI After Acute Stroke With Hemiparesis

Golestani, A., Tymchuk, S., Demchuk, A. M., Goodyear, B. G., & VISION-2 Study Group (2012) · Neurorehabilitation and neural repair · doi:10.1177/1545968312457827 · Cited by 209

Left hemisphere plasticity and aphasia recovery

Fridriksson, J., Richardson, J. D., Fillmore, P., & Cai, B. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.057 · Cited by 215

Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network

Liu, J., Li, M., Lan, W., Wu, F., Pan, Y. F., & Wang, J. (2016) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2016.2635144 · Cited by 214

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer’s disease

Lu, D., Popuri, K., Ding, G. W., Balachandar, R., & Beg, M. F. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.02.002 · Cited by 215

Impaired Gut-Liver-Brain Axis in Patients with Cirrhosis

Ahluwalia, V., Betrapally, N. S., Hylemon, P. B., White, M. B., Gillevet, P. M., Unser, A. B., Fagan, A., Daita, K., Heuman, D. M., Zhou, H., et al. (2016) · Scientific Reports · doi:10.1038/srep26800 · Cited by 213

Untitled work

Cavanagh (2010) · doi:10.1016/j.neuropsychologia.2010.02.016 · Cited by 201

Relief as a reward: hedonic and neural responses to safety from pain

Leknes, S., Lee, M., Berna, C., Andersson, J., & Tracey, I. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017870 · Cited by 207

The Control of Global Brain Dynamics: Opposing Actions of Frontoparietal Control and Default Mode Networks on Attention

Hellyer, P. J., Shanahan, M., Scott, G., Wise, R. J. S., Sharp, D. J., & Leech, R. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1853-13.2014 · Cited by 205

Overview of fMRI analysis

Smith, S. M. (2004) · British Journal of Radiology · doi:10.1259/bjr/33553595 · Cited by 211

How can we combat multicenter variability in MR radiomics? Validation of a correction procedure

Orlhac, F., Lecler, A., Savatovsky, J., Goya-Outi, J., Nioche, C., Charbonneau, F., Ayache, N., Frouin, F., Duron, L., & Buvat, I. (2020) · European Radiology · doi:10.1007/s00330-020-07284-9 · Cited by 224

Broca’s region: linking human brain functional connectivity data and non‐human primate tracing anatomy studies

Kelly, C. A. M., Uddin, L. Q., Shehzad, Z. E., Margulies, D. S., Castellanos, F. X., Milham, M. P., & Petrides, M. (2010) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07279.x · Cited by 213

Mapping the mouse brain with rs-fMRI: an optimized pipeline for functional network identification

Zerbi, V., Grandjean, J., Rudin, M., & Wenderoth, N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.090 · Cited by 178

Whole-Brain Multimodal Neuroimaging Model Using Serotonin Receptor Maps Explains Non-linear Functional Effects of LSD

Deco, G., Cruzat, J., Cabral, J., Knudsen, G. M., Carhart-Harris, R. L., Whybrow, P. C., Logothetis, N. K., & Kringelbach, M. L. (2018) · Current Biology · doi:10.1016/j.cub.2018.07.083 · Cited by 211

The evolution of white matter microstructural changes after mild traumatic brain injury: A longitudinal DTI and NODDI study

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Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment

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Access to Vagal Projections via Cutaneous Electrical Stimulation of the Neck: fMRI Evidence in Healthy Humans

Frangos, E., & Komisaruk, B. R. (2016) · Brain stimulation · doi:10.1016/j.brs.2016.10.008 · Cited by 209

Contralateral cerebello-thalamo-cortical pathways with prominent involvement of associative areas in humans in vivo

Palesi, F., Tournier, J., Calamante, F., Muhlert, N., Castellazzi, G., Chard, D., D'Angelo, E. U., & Wheeler‐Kingshott, C. A. M. G. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0861-2 · Cited by 212

Magnetic resonance imaging evidence for presymptomatic change in thalamus and caudate in familial Alzheimer’s disease

Ryan, N. S., Keihaninejad, S., Shakespeare, T. J., Lehmann, M., Crutch, S. J., Malone, I. B., Thornton, J. S., Mancini, L., Hyare, H., Yousry, T., et al. (2013) · Brain · doi:10.1093/brain/awt065 · Cited by 205

Correcting Brain-Wide Correlation Differences in Resting-State FMRI

Saad, Z. S., Reynolds, R. C., Jo, H. J., Gotts, S. J., Chen, G., Martin, A. D., & Cox, R. W. (2013) · Brain Connectivity · doi:10.1089/brain.2013.0156 · Cited by 200

The role of trauma-related distractors on neural systems for working memory and emotion processing in posttraumatic stress disorder

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Whole-Brain T1 Mapping in Multiple Sclerosis: Global Changes of Normal-appearing Gray and White Matter

Vrenken, H., Geurts, J. J. G., Knol, D. L., van Dijk, L. N., Dattola, V., Jasperse, B., van Schijndel, R. A., Polman, C. H., Castelijns, J. A., Barkhof, F., et al. (2006) · Radiology · doi:10.1148/radiol.2403050569 · Cited by 205

Separate neural representations of prediction error valence and surprise: Evidence from an fMRI meta‐analysis

Fouragnan, E., Retzler, C., & Philiastides, M. G. (2018) · Human Brain Mapping · doi:10.1002/hbm.24047 · Cited by 176

Dialectical behavior therapy alters emotion regulation and amygdala activity in patients with borderline personality disorder

Goodman, M., Carpenter, D., Tang, C. Y., Goldstein, K. E., Avedon, J., Fernandez, N., Mascitelli, K. A., Blair, N. J., New, A. S., Triebwasser, J., et al. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.06.020 · Cited by 198

Hemispheric Specialization for Processing Auditory Nonspeech Stimuli

Jamison, H. L., Watkins, K. E., Bishop, D., & Matthews, P. M. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhj068 · Cited by 203

Cognitive status correlates with white matter alteration in Parkinson's disease

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Development of BOLD signal hemodynamic responses in the human brain

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Cluster-based analysis of FMRI data

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Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination

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Functional Connectivity Is Associated With Altered Brain Chemistry in Women With Endometriosis-Associated Chronic Pelvic Pain

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“Aha!”: The neural correlates of verbal insight solutions

Aziz‐Zadeh, L., Kaplan, J., & Iacoboni, M. (2008) · Human Brain Mapping · doi:10.1002/hbm.20554 · Cited by 199

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