SIFT: Spherical-deconvolution informed filtering of tractograms

Fast robust automated brain extraction

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

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How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging

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The Human Connectome: A Structural Description of the Human Brain

Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260

White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI

Jones, D. K., Knösche, T. R., & Turner, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.081 · Cited by 2,402

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

Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution

Tournier, J., Calamante, F., & Connelly, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.016 · Cited by 2,191

Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution

Tournier, J.-D., Calamante, F., Gadian, D. G., & Connelly, A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.037 · Cited by 1,635

MRtrix: Diffusion tractography in crossing fiber regions

Tournier, J., Calamante, F., & Connelly, A. (2012) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22005 · Cited by 1,370

Three‐dimensional magnetization‐prepared rapid gradient‐echo imaging (3D MP RAGE)

Mugler, J. P., & Brookeman, J. R. (1990) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910150117 · Cited by 1,276

Connectome analysis with diffusion MRI in idiopathic Parkinson's disease: Evaluation using multi-shell, multi-tissue, constrained spherical deconvolution

Kamagata, K., Zalesky, A., Hatano, T., Biase, M. A. D., Samad, O. E., Saiki, S., Shimoji, K., Kumamaru, K. K., Kamiya, K., Hori, M., et al. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.11.007 · Cited by 53

Fiber length profiling: a novel approach to structural brain organization

Bajada, C. J., Schreiber, J., & Caspers, S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.070 · Cited by 55

Structural network underlying visuospatial imagery in humans

Whittingstall, K., Bernier, M., Houde, J., Fortin, D., & Descoteaux, M. (2013) · Cortex · doi:10.1016/j.cortex.2013.02.004 · Cited by 55

Objective Detection of Eloquent Axonal Pathways to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery Using Diffusion Tractography and Convolutional Neural Networks

Xu, H., Dong, M., Lee, M., O'Hara, N. B., Asano, E., & Jeong, J. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2902073 · Cited by 56

Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping

Calamante, F., Smith, R. E., Tournier, J., Raffelt, D. A., & Connelly, A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.070 · Cited by 54

Intrinsic connectivity of the human brain provides scaffold for tau aggregation in clinical variants of Alzheimer’s disease

Therriault, J., Pascoal, T. A., Savard, M., Mathotaarachchi, S. S., Benedet, A. L., Chamoun, M., Tissot, C., Lussier, F. Z., Rahmouni, N., Stevenson, J., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abc8693 · Cited by 58

Structural connectivity‐based topography of the human globus pallidus: Implications for therapeutic targeting in movement disorders

Cacciola, A., Milardi, D., Bertino, S., Basile, G. A., Calamuneri, A., Chillemi, G., Rizzo, G., Anastasi, G., & Quartarone, A. (2019) · Movement Disorders · doi:10.1002/mds.27712 · Cited by 55

Network-based brain–computer interfaces: principles and applications

Gonzalez-Astudillo, J., Cattai, T., Bassignana, G., Corsi, M., & Fallani, F. D. V. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc760 · Cited by 60

Structural network differences in chronic musculoskeletal pain: Beyond fractional anisotropy

Bishop, J. H., Shpaner, M., Kubicki, A., Clements, S., Watts, R., & Naylor, M. R. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.021 · Cited by 50

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Maffei, C., Girard, G., Schilling, K. G., Aydogan, D. B., Adluru, N., Zhylka, A., Wu, Y., Mancini, M., Hamamcı, A., Sarica, A., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119327 · Cited by 49

A Direct Cortico-Nigral Pathway as Revealed by Constrained Spherical Deconvolution Tractography in Humans

Cacciola, A., Milardi, D., Anastasi, G., Basile, G. A., Ciolli, P., Irrera, M., Cutroneo, G., Bruschetta, D., Rizzo, G., Mondello, S., et al. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00374 · Cited by 48

Filtering in tractography using autoencoders (FINTA)

Legarreta, J. H., Petit, L., Rheault, F., Theaud, G., Lemaire, C., Descoteaux, M., & Jodoin, P. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102126 · Cited by 53

Track-weighted functional connectivity (TW-FC): A tool for characterizing the structural–functional connections in the brain

Calamante, F., Masterton, R. A. J., Tournier, J., Smith, R. E., Willats, L., Raffelt, D. A., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.12.054 · Cited by 49

Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET)

Chamberland, M., Scherrer, B., Prabhu, S. P., Madsen, J. R., Fortin, D., Whittingstall, K., Descoteaux, M., & Warfield, S. K. (2016) · Human Brain Mapping · doi:10.1002/hbm.23399 · Cited by 51

Global tractography with embedded anatomical priors for quantitative connectivity analysis

Lemkaddem, A., Skiöldebrand, D., Dal Palú, A., Thiran, J.-P., & Daducci, A. (2014) · Frontiers in Neurology · doi:10.3389/fneur.2014.00232 · Cited by 47

Track Orientation Density Imaging (TODI) and Track Orientation Distribution (TOD) based tractography

Dhollander, T., Emsell, L., Hecke, W. V., Maes, F., Sunaert, S. G., & Suetens, P. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.047 · Cited by 49

Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington’s disease

McColgan, P., Seunarine, K. K., Gregory, S., Razi, A., Papoutsi, M., Long, J. D., Mills, J. A., Johnson, E. B., Dürr, A., Roos, R. A. C., et al. (2017) · JCI Insight · doi:10.1172/jci.insight.92641 · Cited by 46

Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer’s Disease

Oxtoby, N. P., Garbarino, S., Firth, N. C., Warren, J. D., Schott, J. M., Alexander, D. C., & Initiative, A. D. N. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00580 · Cited by 47

Connectivity-enhanced diffusion analysis reveals white matter density disruptions in first episode and chronic schizophrenia

Grazioplene, R. G., Bearden, C., Subotnik, K., Ventura, J., Haut, K. M., Nuechterlein, K., & Cannon, T. D. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.02.015 · Cited by 46

Multivariate pattern classification of brain white matter connectivity predicts classic trigeminal neuralgia

zhong, J., Chen, D. Q., Hung, P. S.-P., Hayes, D. J., Liang, K. E., Davis, K. D., & Hodaie, M. (2018) · Pain · doi:10.1097/j.pain.0000000000001312 · Cited by 47

Connectomes from streamlines tractography: Assigning streamlines to brain parcellations is not trivial but highly consequential

Yeh, C., Smith, R. E., Dhollander, T., Calamante, F., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.005 · Cited by 45

Anatomical accuracy of standard-practice tractography algorithms in the motor system - A histological validation in the squirrel monkey brain

Schilling, K. G., Gao, Y., Stepniewska, I., Janve, V. A., Landman, B. A., & Anderson, A. W. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.09.004 · Cited by 48

Microstructural Alterations in Hippocampal Subfields Mediate Age-Related Memory Decline in Humans

Radhakrishnan, H., Stark, S. M., & Stark, C. E. L. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00094 · Cited by 49

MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI

Cai, L. Y., Yang, Q., Kanakaraj, P., Nath, V., Newton, A. T., Edmonson, H. A., Luci, J. J., Conrad, B. N., Price, G. R., Hansen, C. B., et al. (2021) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28926 · Cited by 50

TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography

Poulin, P., Theaud, G., Rheault, F., St‐Onge, E., Boré, A., Renauld, E., Beaumont, L. D., Guay, S., Jodoin, P., & Descoteaux, M. (2022) · Scientific Data · doi:10.1038/s41597-022-01833-1 · Cited by 49

White matter predicts functional connectivity in premanifest Huntington's disease

McColgan, P., Gregory, S., Razi, A., Seunarine, K. K., Gargouri, F., Dürr, A., Roos, R. A. C., Leavitt, B. R., Scahill, R. I., Clark, C. A., et al. (2017) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.384 · Cited by 42

Six Months of Piano Training in Healthy Elderly Stabilizes White Matter Microstructure in the Fornix, Compared to an Active Control Group

Jünemann, K., Marié, D., Worschech, F., Scholz, D. S., Grouiller, F., Kliegel, M., Ville, D. V. D., James, C. E., Krüger, T. H. C., ALTENMÜLLER, E. O., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.817889 · Cited by 46

Functional and structural brain network development in children with attention deficit hyperactivity disorder

Soman, S. M., Vijayakumar, N., Thomson, P., Ball, G., Hyde, C. E., & Silk, T. J. (2023) · Human Brain Mapping · doi:10.1002/hbm.26288 · Cited by 47

White matter alterations at pubertal onset

Genc, S., Seal, M. L., Dhollander, T., Malpas, C. B., Hazell, P., & Silk, T. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.05.017 · Cited by 46

Changes in white matter fiber density and morphology across the adult lifespan: A cross‐sectional fixel‐based analysis

Choy, S. W., Bagarinao, E., Watanabe, H., Ho, E. T. W., Maesawa, S., Mori, D., Hara, K., Kawabata, K., Yoneyama, N., Ohdake, R., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25008 · Cited by 44

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis

Arun, A. H., Connelly, A., Smith, R., & Calamante, F. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117505 · Cited by 44

Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data

Román, C., Hernández, C., Figueroa, M. E., Houenou, J., Poupon, C., Mangin, J., & Guevara, P. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119550 · Cited by 44

Mapping the structural connectivity between the periaqueductal gray and the cerebellum in humans

Cacciola, A., Bertino, S., Basile, G. A., Mauro, D. D., Calamuneri, A., Chillemi, G., Duca, A., Bruschetta, D., Flace, P., Favaloro, A., et al. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01893-x · Cited by 39

Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis

Yang, Y., Ye, C., Sun, J., Li, L., Lv, H., Gao, L., Fang, J., Ma, T., & Wu, T. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102715 · Cited by 40

The glial framework reveals white matter fiber architecture in human and primate brains

Schurr, R., & Mezer, A. (2021) · Science · doi:10.1126/science.abj7960 · Cited by 42

Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution

Portegies, J. M., Fick, R., Sanguinetti, G., Meesters, S., Girard, G., & Duits, R. (2015) · PLoS ONE · doi:10.1371/journal.pone.0138122 · Cited by 39

Multicenter dataset of multi-shell diffusion MRI in healthy traveling adults with identical settings

Tong, Q., He, H., Gong, T., Li, C., Liang, P., Qian, T., Sun, Y., Ding, Q., Li, K., & Zhong, J. (2020) · Scientific Data · doi:10.1038/s41597-020-0493-8 · Cited by 43

Diffusion MRI of the infant brain reveals unique asymmetry patterns during the first-half-year of development

Liu, T.-T., Gao, F.-S., Zheng, W., You, Y., Zhao, Z.-Y., Lv, Y., Chen, W., Zhang, H.-X., Ji, C., & Wu, D. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118465 · Cited by 37

Subtle white matter alterations in schizophrenia identified with a new measure of fiber density

Stämpfli, P., Sommer, S., Manoliu, A., Burrer, A., Schmidt, A., Herdener, M., Seifritz, E., Kaiser, S., & Kirschner, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-40070-2 · Cited by 40

Regionconnect: Rapidly extracting standardized brain connectivity information in voxel-wise neuroimaging studies

Qi, X., & Arfanakis, K. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117462 · Cited by 40

Tract‐specific atrophy in focal epilepsy: Disease, genetics, or seizures?

Vaughan, D., Raffelt, D., Curwood, E., Tsai, M.-H., Tournier, J.-D., Connelly, A., & Jackson, G. (2017) · Annals of Neurology · doi:10.1002/ana.24848 · Cited by 44

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

Baraković, M., Tax, C. M. W., Rudrapatna, U. S., Chamberland, M., Rafael‐Patiño, J., Granziera, C., Thiran, J., Daducci, A., Canales-Rodríguez, E. J., & Jones, D. K. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117617 · Cited by 39

Structural control energy of resting‐state functional brain states reveals less cost‐effective brain dynamics in psychosis vulnerability

Zöller, D., Sandini, C., Schaer, M., Eliez, S., Bassett, D. S., & Ville, D. V. D. (2021) · Human Brain Mapping · doi:10.1002/hbm.25358 · Cited by 39

Patient-Specific Network Connectivity Combined With a Next Generation Neural Mass Model to Test Clinical Hypothesis of Seizure Propagation

Gerster, M., Taher, H., Škoch, A., Hlinka, J., Guye, M., Bartoloméi, F., Jirsa, V., Zakharova, A., & Olmi, S. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.675272 · Cited by 39

Beyond the Lesion: Neuroimaging Foundations For Post-Stroke Recovery

Carey, L. M., Seitz, R. J., Parsons, M. W., Levi, C. R., Farquharson, S., Tournier, J., Palmer, S., & Connelly, A. (2013) · Future Neurology · doi:10.2217/fnl.13.39 · Cited by 39

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

McColgan, P., Razi, A., Gregory, S., Seunarine, K. K., Dürr, A., Roos, R. A. C., Leavitt, B. R., Scahill, R. I., Clark, C. A., Langbehn, D. R., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23527 · Cited by 38

Centralized and distributed cognitive task processing in the human connectome

Amico, E., Arenas, À., & Goñi, J. (2018) · Network Neuroscience · doi:10.1162/netn_a_00072 · Cited by 35

Gender-specific structural abnormalities in major depressive disorder revealed by fixel-based analysis

Lyon, M., Welton, T., Varda, A., Maller, J. J., Broadhouse, K. M., Korgaonkar, M. S., Koslow, S. H., Williams, L. M., Gordon, E., Rush, A. J., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101668 · Cited by 39

Fixel-Based Analysis of Visual Pathway White Matter in Primary Open-Angle Glaucoma.

Haykal, S., Ćurčić-Blake, B., Jansonius, N., & Cornelissen, F. (2019) · Investigative Ophthalmology and Visual Science · doi:10.1167/iovs.19-27447 · Cited by 35

Structural constraints of functional connectivity drive cognitive impairment in the early stages of multiple sclerosis

Koubiyr, I., Deloire, M., Brochet, B., Besson, P., Charré‐Morin, J., Saubusse, A., Tourdias, T., & Ruet, A. (2020) · Multiple Sclerosis Journal · doi:10.1177/1352458520971807 · Cited by 39

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

Reid, L. B., Cunnington, R., Boyd, R. N., & Rose, S. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159540 · Cited by 36

Impaired rich club and increased local connectivity in children with traumatic brain injury: Local support for the rich?

Verhelst, H., Linden, C. V., Pauw, T. D., Vingerhoets, G., & Caeyenberghs, K. (2018) · Human Brain Mapping · doi:10.1002/hbm.24041 · Cited by 36

Multi-Site Harmonization of Diffusion MRI Data via Method of Moments

Huynh, K. M., Chen, G., Wu, Y., Shen, D. G., & Yap, P. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2895020 · Cited by 36

Network diffusion modeling predicts neurodegeneration in traumatic brain injury

Poudel, G. R., D, J. F. D., Verhelst, H., Linden, C. V., Deblaere, K., Jones, D. K., Cerin, E., Vingerhoets, G., & Caeyenberghs, K. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50984 · Cited by 36

Longitudinal patterns of white matter fibre density and morphology in children are associated with age and pubertal stage

Genc, S., Malpas, C. B., Gülenç, A., Sciberras, E., Efron, D., Silk, T. J., & Seal, M. L. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100853 · Cited by 37

Modelling white matter in gyral blades as a continuous vector field

Cottaar, M., Bastiani, M., Boddu, N., Glasser, M. F., Haber, S. N., Essen, D. C. V., Sotiropoulos, S. N., & Jbabdi, S. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117693 · Cited by 36

Quantification of track-weighted imaging (TWI): Characterisation of within-subject reproducibility and between-subject variability

Willats, L., Raffelt, D. A., Smith, R. E., Tournier, J., Connelly, A., & Calamante, F. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.016 · Cited by 36

Comparative neuroanatomy: Integrating classic and modern methods to understand association fibers connecting dorsal and ventral visual cortex

Takemura, H., Pestilli, F., & Weiner, K. S. (2018) · Neuroscience Research · doi:10.1016/j.neures.2018.10.011 · Cited by 36

Improvement in White Matter Tract Reconstruction with Constrained Spherical Deconvolution and Track Density Mapping in Low Angular Resolution Data: A Pediatric Study and Literature Review

Toselli, B., Tortora, D., Severino, M., Arnulfo, G., Canessa, A., Morana, G., Rossi, A., & Fato, M. (2017) · Frontiers in Pediatrics · doi:10.3389/fped.2017.00182 · Cited by 35

MR g-ratio-weighted connectome analysis in patients with multiple sclerosis

Kamagata, K., Zalesky, A., Yokoyama, K., Andica, C., Hagiwara, A., Shimoji, K., Kumamaru, K. K., Takemura, M. Y., Hoshino, Y., Kamiya, K., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-50025-2 · Cited by 35

Microstructural changes in the reward system are associated with post-stroke depression

Oestreich, L., Wright, P. K., & O'Sullivan, M. J. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102360 · Cited by 36

Reorganization of the structural connectome in primary open angle Glaucoma

Ciò, F. D., Garaci, F. G., Minosse, S., Passamonti, L., Martucci, A., Lanzafame, S., Giuliano, F. D., Picchi, E., Cesareo, M., Guerrisi, M., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102419 · Cited by 37

Mapping the organization and dynamics of the posterior medial network during movie watching

Cooper, R. A., Kurkela, K. A., Davis, S. W., & Ritchey, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118075 · Cited by 40

Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain

Wilson, S., Pietsch, M., Cordero‐Grande, L., Christiaens, D., Uus, A. U., Karolis, V. R., Kyriakopoulou, V., Colford, K., Price, A. N., Hutter, J. M., et al. (2023) · eLife · doi:10.7554/elife.83727 · Cited by 36

Reproducibility of multi-shell diffusion tractography on traveling subjects: A multicenter study prospective

Tong, Q., He, H., Gong, T., Li, C., Liang, P., Qian, T., Sun, Y., Ding, Q., Li, K., & Zhong, J. (2019) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2019.02.011 · Cited by 35

Sensory‐motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy

Schiavi, S., Petracca, M., Battocchio, M., Mendili, M. M. E., Paduri, S., Fleysher, L., Inglese, M., & Daducci, A. (2020) · Human Brain Mapping · doi:10.1002/hbm.24989 · Cited by 34

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Abramian, D., Larsson, M., Eklund, A., Aganj, I., Westin, C., & Behjat, H. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118095 · Cited by 33

Indirect structural disconnection-symptom mapping

Sperber, C., Griffis, J. C., & Kasties, V. (2022) · Brain Structure and Function · doi:10.1007/s00429-022-02559-x · Cited by 32

Longitudinal thalamic white and grey matter changes associated with visual hallucinations in Parkinson’s disease

Zarkali, A., McColgan, P., Leyland, L. A., Lees, A. J., & Weil, R. S. (2022) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-326630 · Cited by 32

More than blindsight: Case report of a child with extraordinary visual capacity following perinatal bilateral occipital lobe injury

Mundiñano, I.-C., Chen, J., de Souza, M., Sarossy, M., Joanisse, M. F., Goodale, M. A., & Bourne, J. A. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.11.017 · Cited by 32

Advances in computational and statistical diffusion MRI

O’Donnell, L. J., Daducci, A., Wassermann, D., & Lenglet, C. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3805 · Cited by 32

The Superoanterior Fasciculus (SAF): A Novel White Matter Pathway in the Human Brain?

Dávid, S., Heemskerk, A. M., Corrivetti, F., de Schotten, M. T., Sarubbo, S., Corsini, F., BENEDICTIS, A. D., Petit, L., Viergever, M. A., Jones, D. K., et al. (2019) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2019.00024 · Cited by 32

Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis

Verhelst, H., Giraldo, D. L., Linden, C. V., Vingerhoets, G., Jeurissen, B., & Caeyenberghs, K. (2019) · Neurorehabilitation and neural repair · doi:10.1177/1545968319868720 · Cited by 32

Subdividing the superior longitudinal fasciculus using local quantitative MRI

Schurr, R., Zelman, A., & Mezer, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116439 · Cited by 32

Long-term development of white matter fibre density and morphology up to 13 years after preterm birth: A fixel-based analysis

Kelly, C. E., Thompson, D. K., Genc, S., Chen, J., Yang, J. Y., Adamson, C. L., Beare, R. J., Seal, M. L., Doyle, L. W., Cheong, J. L. Y., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117068 · Cited by 34

MRI biomarkers for Alzheimer's disease: the impact of functional connectivity in the default mode network and structural connectivity between lobes on diagnostic accuracy

Mohtasib, R., Alghamdi, J., Jobeir, A., Masawi, A., de Barros, N. D., Billiet, T., Struyfs, H., Phan, T. V., van Hecke, W., & Ribbens, A. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e08901 · Cited by 32

Increased cognitive complexity reveals abnormal brain network activity in individuals with corpus callosum dysgenesis

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Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

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