The DOI matches its Crossref record; 39 of the 41 references it cites were found in a registry or an index.
Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature
Open accessAbstract
Precise localization of sulco-gyral structures of the human cerebral cortex is important for the interpretation of morpho-functional data, but requires anatomical expertise and is time consuming because of the brain's geometric complexity. Software developed to automatically identify sulco-gyral structures has improved substantially as a result of techniques providing topologically correct reconstructions permitting inflated views of the human brain. Here we describe a complete parcellation of the cortical surface using standard internationally accepted nomenclature and criteria. This parcellation is available in the FreeSurfer package. First, a computer-assisted hand parcellation classified each vertex as sulcal or gyral, and these were then subparcellated into 74 labels per hemisphere. Twelve datasets were used to develop rules and algorithms (reported here) that produced labels consistent with anatomical rules as well as automated computational parcellation. The final parcellation was used to build an atlas for automatically labeling the whole cerebral cortex. This atlas was used to label an additional 12 datasets, which were found to have good concordance with manual labels. This paper presents a precisely defined method for automatically labeling the cortical surface in standard terminology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“The most popularly used cortical parcellation is the Freesurfer Desikan-Killiany cortical parcellation (Desikan et al., 2006; Fischl, 2012), while many other cortical parcellation schemes have also been widely used (Destrieux et al., 2010; Shattuck et al., 2008; Tzourio-Mazoyer et al., 2002).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Destrieux et al., 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Self-citationCortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Self-citationFischl, 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
Self-citationCortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
Self-citationTalairach, J., Tournoux, P., & Rayport, M. (1988) · Thieme eBooks · Cited by 5,058
Automatically Parcellating the Human Cerebral Cortex
Fischl, B. R. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg087 · Cited by 4,208
Self-citationA hybrid approach to the skull stripping problem in MRI
Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D. H., Hahn, H., & Fischl, B. R. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.032 · Cited by 2,227
Self-citationDale, A. M., & Sereno, M. I. (1993) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1993.5.2.162 · Cited by 2,003
Self-citationConstruction of a 3D probabilistic atlas of human cortical structures
Shattuck, D. W., Mirza, M., Adisetiyo, V., Hojatkashani, C., Salamon, G., Narr, K. L., Poldrack, R. A., Bilder, R. M., & Toga, A. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.031 · Cited by 1,208
A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex
Van Essen, D. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.058 · Cited by 1,151
Flagged first, then by citations
2 of the 41 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Destrieux, 1998, Variability of the human brain studied on the flattened cortical surface, Soc. Neurosci., 1164
- Zilles, 1997, Quantitative analysis of sulci in the human cerebral cortex: development, regional heterogeneity, gender difference, asymetry, intersubject variability and cortical architecture, Hum. Brain Mapp., 5, 218, 10.1002/(SICI)1097-0193(1997)5:4<218::AID-HBM2>3.0.CO;2-6 · DOI
Cited by
Sorted by citations
Items 701–800 of 1,008
Maffei, C., Capasso, R., Cazzolli, G., Colosimo, C., Dell’Acqua, F., Piludu, F., Catani, M., & Miceli, G. (2017) · Cortex · doi:10.1016/j.cortex.2017.10.006 · Cited by 35
Visualisation of Brain Statistics with R-packages ggseg and ggseg3dPreprint
Mowinckel, A. M., & Dídac Vidal-piñeiro, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.08200 · Cited by 36
Federated Multi-Site Normative Modeling using Hierarchical Bayesian RegressionPreprint
Kia, S. M., Huijsdens, H., Rutherford, S., Dinga, R., Wolfers, T., Mennes, M., Andreassen, O., Westlye, L., Beckmann, C., & Marquand, A. (2021) · bioRxiv · doi:10.1101/2021.05.28.446120 · Cited by 32
Bhatt, R. R., Haddad, E., Zhu, A. H., Thompson, P. M., Gupta, A., Mayer, E. A., & Jahanshad, N. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.07.016 · Cited by 35
Dynamic phase alignment of ongoing auditory cortex oscillations
Bauer, A. R., Bleichner, M. G., Jaeger, M., Thorne, J. D., & Debener, S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.037 · Cited by 34
The chaotic morphology of the left superior temporal sulcus is genetically constrained
Guen, Y. L., Leroy, F., Auzias, G., Rivière, D., Grigis, A., Mangin, J., Coulon, O., Dehaene‐Lambertz, G., & Frouin, V. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.046 · Cited by 34
Yoo, J. H., Kim, J. I., Kim, B.-N., & Jeong, B. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00164-x · Cited by 35
A series of five population‐specific Indian brain templates and atlases spanning ages 6–60 years
Holla, B., Taylor, P. A., Glen, D., Lee, J. A., Vaidya, N., Mehta, U. M., Venkatasubramanian, G., Pal, P. K., Saini, J. S., Rao, N. P., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25182 · Cited by 34
Ferrari, A., & Noppeney, U. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001465 · Cited by 37
Parietal connectivity mediates multisensory facilitation
Brang, D., Taich, Z. J., Hillyard, S. A., Grabowecky, M., & Ramachandran, V. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.047 · Cited by 34
Roe, J. M., Dídac Vidal-piñeiro, A., Amlien, I. K., Pan, M., Sneve, M. H., de Schotten, M. T., Friedrich, P., Sha, Z., Francks, C., Eilertsen, E. M., et al. (2023) · eLife · doi:10.7554/elife.84685 · Cited by 33
Ohki, T., Gunji, A., Takei, Y., Takahashi, H., Kaneko, Y., Kita, Y., Hironaga, N., Tobimatsu, S., Kamio, Y., Hanakawa, T., et al. (2016) · Scientific Reports · doi:10.1038/srep37973 · Cited by 34
Cortical markers of cognitive syndromes in amyotrophic lateral sclerosis
Consonni, M., Contarino, V. E., Catricalà, E., Bella, E. D., Pensato, V., Gellera, C., Lauria, G., & Cappa, S. F. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.05.020 · Cited by 33
Battal, C., Rezk, M., Mattioni, S., Vadlamudi, J., & Collignon, O. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.2289-18.2018 · Cited by 33
Identifying the neural basis of a language‐impaired phenotype of temporal lobe epilepsy
Kaestner, E. J., Reyes, A., Macari, A. C., Chang, Y. A., Paul, B. M., Hermann, B. P., & McDonald, C. R. (2019) · Epilepsia · doi:10.1111/epi.16283 · Cited by 33
Preiß, D., Billette, O. V., Schneider, A., Spotorno, N., & Nestor, P. J. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101994 · Cited by 33
Kim, S., Kim, Y.-W., Shim, M., Jin, M. J., Im, C., & Lee, S. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00661 · Cited by 30
Morphometrical Brain Markers of Sex Difference
Brennan, D. J., Wu, T., & Fan, J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab037 · Cited by 32
Zhao, L., Matloff, W. J., Shi, Y., Cabeen, R. P., & Toga, A. W. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.11.002 · Cited by 32
Mild Traumatic Brain Injury Results in Significant and Lasting Cortical Demyelination
Mahoney, S., Chowdhury, N. F., Ngo, V., Imms, P. E., & Andrei Irimia, A. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.854396 · Cited by 34
Aller, M., Økland, H. S., MacGregor, L. J., Blank, H., & Davis, M. H. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.2476-21.2022 · Cited by 28
Chen, Y., Zhang, C., Xue, T., Song, Y., Makris, N., Yogesh Rathi, A., Cai, W., Zhang, F., & O’Donnell, L. J. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120086 · Cited by 34
FEMA : Fast and efficient mixed‐effects algorithm for large sample whole‐brain imaging data
Parekh, P., Fan, C. C., Frei, O., Palmer, C. E., Smith, D. M. Y., Makowski, C., Iversen, J. R., Pecheva, D., Holland, D., Loughnan, R. J., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.26579 · Cited by 33
Self-citationEarly Childhood Behavioral Inhibition Predicts Cortical Thickness in Adulthood
Sylvester, C. M., Barch, D. M., Harms, M. P., Belden, A. C., Oakberg, T. J., Gold, A. L., White, L. K., Benson, B. E., Troller‐Renfree, S. V., Degnan, K. A., et al. (2015) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2015.11.007 · Cited by 39
Language outcomes after resection of dominant inferior parietal lobule gliomas
Southwell, D. G., Riva, M., Jordan, K., Caverzasi, E., Li, J., Perry, D. W., Henry, R. G., & Berger, M. S. (2017) · Journal of neurosurgery · doi:10.3171/2016.8.jns16443 · Cited by 33
Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy
Chang, Y. A., Kemmotsu, N., Leyden, K. M., Kucukboyaci, N. E., Iragui, V. J., Tecoma, E. S., Kansal, L., Norman, M. A., Compton, R., Ehrlich, T. J., et al. (2017) · Brain and Language · doi:10.1016/j.bandl.2017.03.012 · Cited by 32
Zhuang, H., Liu, R., Wu, C., Meng, Z., Wang, D., Liu, D., Liu, M., & Li, Y. (2019) · Neuroscience Letters · doi:10.1016/j.neulet.2019.04.039 · Cited by 32
White and gray matter brain development in children and young adults with phenylketonuria
Hawks, Z., Hood, A., Lerman-Sinkoff, D. B., Shimony, J. S., Rutlin, J. R., Lagoni, D., Grange, D. K., & White, D. A. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101916 · 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
Welton, T., Constantinescu, C. S., Auer, D. P., & Dineen, R. A. (2020) · Brain Connectivity · doi:10.1089/brain.2019.0717 · Cited by 32
Vieira, B. H., Rondinoni, C., & Salmón, C. E. G. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116662 · Cited by 33
Schneider, N., Greenstreet, E., & Deoni, S. (2021) · Child Development · doi:10.1111/cdev.13649 · Cited by 31
Subthalamic–Cortical Network Reorganization during Parkinson's Tremor
Lauro, P. M., Lee, S., Akbar, U., & Asaad, W. F. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0854-21.2021 · Cited by 32
Ogawa, T., Shimobayashi, H., Hirayama, J.-I., & Kawanabe, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118794 · Cited by 32
Structural alterations of the insula in depression patients – A 7-Tesla-MRI study
Schnellbächer, G. J., Rajkumar, R., Veselinović, T., Ramkiran, S., Hagen, J., Shah, N. J., & Neuner, I. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103249 · Cited by 32
Predicting the development of mild cognitive impairment: A new use of pattern recognition
Cui, Y. J., Sachdev, P. S., Lipnicki, D. M., Jin, J. S., Luo, S., Zhu, W., Kochan, N. A., Reppermund, S., Liu, T., Trollor, J. N., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.084 · Cited by 32
Gray and white matter structural changes in corticobasal syndrome
Upadhyay, N., Suppa, A., Piattella, M. C., Stasio, F. D., Petsas, N., Colonnese, C., Colosimo, C., Berardelli, A., & Pantano, P. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.10.011 · Cited by 33
Haynes, W. I. A., Clair, A.-H., Fernandez-Vidal, S., Gholipour, B., Morgiève, M., & Mallet, L. (2018) · European Psychiatry · doi:10.1016/j.eurpsy.2018.01.005 · Cited by 29
Modulating limbic circuits in temporal lobe epilepsy: impacts on seizures, memory, mood and sleep
Křemen, V., Sladky, V., Mívalt, F., Gregg, N. M., Brinkmann, B. H., Balzekas, I., Marks, V. S., Kucewicz, M. T., Lundstrom, B. N., Cui, J., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf106 · Cited by 30
Default network correlations analyzed on native surfaces
Seibert, T. M., & Brewer, J. B. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2011.04.010 · Cited by 30
Arsenault, J. S., & Buchsbaum, B. R. (2015) · Psychonomic Bulletin & Review · doi:10.3758/s13423-015-0988-z · Cited by 39
Anatomical evidence for functional diversity in the mesencephalic locomotor region of primates
Sébille, S. B., Belaïd, H., Philippe, A.-C., André, A., Lau, B., François, C., Karachi, C., & Bardinet, É. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.011 · Cited by 39
Li, T., Xu, Y., Li, Y., Wang, J., Li, Q., Li, H., & Li, J. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00414 · Cited by 31
Deep Learning Models Unveiled Functional Difference Between Cortical Gyri and Sulci
Zhang, S., Liu, H., Huang, H., Zhao, Y., Jiang, X., Bowers, B., Guo, L., Hu, X. P., Sánchez, M. M., & Liu, T. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2872726 · Cited by 31
Clausen, A. N., Aupperle, R. L., Yeh, H., Waller, D. A., Payne, J., Kuplicki, R., Akeman, E., Paulus, M. P., Bodurka, J., Simmons, K., et al. (2019) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.03.001 · Cited by 30
Bridging the brain structure—brain function gap in prosodic speech processing in older adults
Giroud, N., Keller, M., Hirsiger, S., Dellwo, V., & Meyer, M. E. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.04.017 · Cited by 33
Multi-subject MEG/EEG source imaging with sparse multi-task regression
Janati, H., Bazeille, T., Thirion, B., Cuturi, M., & Gramfort, A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116847 · Cited by 31
Oros‐Peusquens, A., Loução, R., Abbas, Z., Gras, V., Zimmermann, M., & Shah, N. J. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.01333 · Cited by 31
Consonni, M., Bella, E. D., Contarino, V. E., Bersano, E., & Lauria, G. (2020) · Cortex · doi:10.1016/j.cortex.2020.07.007 · Cited by 31
Deep learning identifies morphological determinants of sex differences in the pre-adolescent brain
Adeli, E., Zhao, Q., Zahr, N. M., Goldstone, A., Adolf Pfefferbaum, A., Sullivan, E. V., & Pohl, K. M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117293 · Cited by 30
Kam, J. W. Y., Helfrich, R. F., Solbakk, A., Endestad, T., Larsson, P. G., Lin, J. J., & Knight, R. T. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa262 · Cited by 35
Meeker, T. J., Veldhuijzen, D. S., Keaser, M. L., Gullapalli, R. P., & Greenspan, J. D. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.594588 · Cited by 31
Structural neural correlates of individual differences in categorical perception
Fuhrmeister, P., & Myers, E. B. (2021) · Brain and Language · doi:10.1016/j.bandl.2021.104919 · Cited by 31
Bianciardi, M., Izzy, S., Rosen, B. R., Wald, L. L., & Edlow, B. L. (2021) · Neurology · doi:10.1212/wnl.0000000000012192 · Cited by 26
The Protective Performance of Modern Motorcycle Helmets Under Oblique Impacts
Yu, X., Logan, I., Sarasola, I. D. P., Dasaratha, A., & Ghajari, M. (2022) · Annals of Biomedical Engineering · doi:10.1007/s10439-022-02963-8 · Cited by 31
Han, K., Choi, K. W., Kim, A., Kang, W., Kang, Y., Tae, W., Han, M.-R., & Ham, B. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23105768 · Cited by 32
Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice
Cecchi, R., Vinckier, F., Hammer, J., Marusič, P., Nica, A., Rheims, S., Trébuchon, A., Barbeau, E. J., Denuelle, M., Maillard, L. G., et al. (2022) · eLife · doi:10.7554/elife.72440 · Cited by 32
Sulcal morphology of posteromedial cortex substantially differs between humans and chimpanzees
Willbrand, E. H., Maboudian, S. A., Kelly, J. P., Parker, B. J., Foster, B. L., & Weiner, K. S. (2023) · Communications Biology · doi:10.1038/s42003-023-04953-5 · Cited by 31
Mayer, A. R., Hanlon, F. M., Dodd, A. B., Ling, J. M., Klimaj, S. D., & Meier, T. B. (2015) · Human Brain Mapping · doi:10.1002/hbm.22930 · Cited by 31
Brodie, S. M., Borich, M. R., & Boyd, L. A. (2014) · European Journal of Neuroscience · doi:10.1111/ejn.12717 · Cited by 31
Jasińska, K. K., Molfese, P. J., Kornilov, S. A., Mencl, W. E., Frost, S. J., Lee, M., Pugh, K. R., Grigorenko, E. L., & Landi, N. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.03.014 · Cited by 30
Gray matter volume of the anterior insular cortex and social networking
Spagna, A., Dufford, A. J., Wu, Q., Wu, T., Zheng, W., Coons, E. E., Hof, P. R., Hu, B., Wu, Y., & Fan, J. (2018) · The Journal of Comparative Neurology · doi:10.1002/cne.24402 · Cited by 29
Sensitive Period for Cognitive Repurposing of Human Visual Cortex
Kanjlia, S., Pant, R., & Bedny, M. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy280 · Cited by 32
Sex differences in the influence of body mass index on anatomical architecture of brain networks
Gupta, A., Mayer, E. A., Hamadani, K., Bhatt, R., Fling, C., Alaverdyan, M., Torgerson, C., Ashe-McNalley, C., Van Horn, J. D., Naliboff, B., et al. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.86 · Cited by 30
Bedini, M., Olivetti, E., Avesani, P., & Baldauf, D. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02641-y · Cited by 35
Schwartzmann, B., Quilty, L. C., Dhami, P., Uher, R., Allen, T. A., Kloiber, S. M., Lam, R. W. M., Frey, B. N., Milev, R. V., Müller, D. J., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-35179-4 · Cited by 31
Aberra, A. S., Wang, R., Grill, W. M., & Peterchev, A. V. (2023) · Brain stimulation · doi:10.1016/j.brs.2023.11.018 · Cited by 37
Tesche, C. D., Kodituwakku, P. W., Garcia, C. M., & Houck, J. M. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.12.007 · Cited by 30
Barrès, V., Simons, A., & Arbib, M. A. (2012) · Neural Networks · doi:10.1016/j.neunet.2012.09.021 · Cited by 29
Vaughn, K. A., Ramos-Nuñez, A. I., Greene, M. R., Munson, B. A., Grigorenko, E. L., & Hernández, A. E. (2016) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2016.06.008 · Cited by 30
de Vries, C. F., Staff, R. T., Harris, S. E., Chapko, D., Williams, D. S., Reichert, P., Ahearn, T. S., McNeil, C. J., Whalley, L. J., & Murray, A. D. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.02.019 · Cited by 29
Behavioural Differences and Neural Substrates of Altruistic and Spiteful Punishment
Yamagishi, T., Li, Y., Fermin, A. S. R., Kanai, R., Takagishi, H., Matsumoto, Y., Kiyonari, T., & Sakagami, M. (2017) · Scientific Reports · doi:10.1038/s41598-017-15188-w · Cited by 30
Pellegrino, G., Maran, M., Turco, C., Weis, L., Pino, G. D., Piccione, F., & Arcara, G. (2018) · Neural Plasticity · doi:10.1155/2018/2782804 · Cited by 30
Zhang, L., Wang, L., & Zhu, D. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098638 · Cited by 30
Grinsvall, C., Ryu, H. J., Oudenhove, L. V., Labus, J. S., Gupta, A., Ljungberg, M., Törnblom, H., Mayer, E. A., & Simrén, M. (2020) · Neurogastroenterology & Motility · doi:10.1111/nmo.14027 · Cited by 29
Bérard, N., Landis, B. N., Legrand, L. B., Tyrand, R., Grouiller, F., Vulliémoz, S., Momjian, S., & Boëx, C. (2020) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2020.107559 · Cited by 30
Soshi, T., Andersson, M., Kawagoe, T., Nishiguchi, S., Yamada, M., Otsuka, Y., Nakai, R., Abe, N., Aslah, A., Igasaki, T., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab102 · Cited by 33
Yeater, T. D., Clark, D. J., Hoyos, L., Valdes-Hernandez, P. A., Peraza, J. A., Allen, K. D., & Cruz‐Almeida, Y. (2021) · Chronic Stress · doi:10.1177/24705470211030273 · Cited by 30
Schilling, K. G., Archer, D. B., Yeh, F.-C. F., Rheault, F., Cai, L. Y., Shafer, A. T., Resnick, S. M., Hohman, T. J., Jefferson, A. L., Anderson, A. W., et al. (2023) · Aging Brain · doi:10.1016/j.nbas.2023.100067 · Cited by 31
Visual callosal topography in the absence of retinal input
Bock, A. S., Sàenz, M., Tungaraza, R. F., Boynton, G. M., Bridge, H., & Fine, I. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.038 · Cited by 30
de Sousa, A. A., & Proulx, M. J. (2014) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2014.00051 · Cited by 30
Chamberland, M., Girard, G., Bernier, M., Fortin, D., Descoteaux, M., & Whittingstall, K. (2017) · Brain Connectivity · doi:10.1089/brain.2017.0539 · Cited by 30
Kang, Y., Shin, D., Kim, A., You, S., Kim, B., Han, K., & Ham, B. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.12.071 · Cited by 30
Gaiser, C., Berthet, P., Kia, S. M., Frens, M. A., Beckmann, C. F., Muetzel, R. L., & Marquand, A. F. (2024) · Human Brain Mapping · doi:10.1002/hbm.26565 · Cited by 28
Virtual brain twins for stimulation in epilepsy
Wang, H., Dollomaja, B., Triebkorn, P., Duma, G. M., Williamson, A., Makhalova, J., Lemaréchal, J.-D., Bartoloméi, F., & Jirsa, V. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00841-6 · Cited by 30
Lamar, M., Ajilore, O., Leow, A., Charlton, R. A., Cohen, J., GadElkarim, J., Yang, S., Zhang, A., Davis, R., Penney, D. L., et al. (2016) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2016.03.034 · Cited by 29
Thaler, A., Kliper, E., Maidan, I., Herman, T., Rosenberg‐Katz, K., Bregman, N., Gurevich, T., Shiner, T., Hausdorff, J. M., Orr‐Urtreger, A., et al. (2018) · Brain Topography · doi:10.1007/s10548-018-0653-8 · Cited by 29
Jo, H. J., Kenney‐Jung, D. L., Balzekas, I., Benarroch, E. E., Jones, D. T., Brinkmann, B. H., Stead, S. M., Gompel, J. J. V., Welker, K. M., & Worrell, G. A. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101671 · Cited by 29
Keller, M., Neuschwander, P., & Meyer, M. E. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.050 · Cited by 33
Primary motor cortical activity during unimanual movements with increasing demand on precision
Barany, D. A., Revill, K. P., Caliban, A., Vernon, I., Shukla, A., Sathian, K., & Buetefisch, C. M. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00546.2019 · Cited by 30
Comparison of Surface Area and Cortical Thickness Asymmetry in the Human and Chimpanzee Brain
Li, X., Crow, T. J., Hopkins, W. D., & Roberts, N. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa202 · Cited by 29
Kreilkamp, B. A. K., McKavanagh, A., Alonazi, B., Bryant, L., Das, K., Wieshmann, U. C., Marson, A. G., Taylor, P. N., & Keller, S. S. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102564 · Cited by 27
Quantitative Analysis of Synthetic Magnetic Resonance Imaging in Alzheimer’s Disease
Lou, B., Jiang, Y., Li, C., Wu, P., Li, S., Qin, B., Chen, H., Wang, R., Wu, B., & Chen, M. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.638731 · Cited by 29
Cole, M., Murray, K. D., St‐Onge, E., Risk, B. B., Zhong, J., Schifitto, G., Descoteaux, M., & Zhang, Z. (2021) · Human Brain Mapping · doi:10.1002/hbm.25447 · Cited by 30
Integrative Models of Brain Structure and Dynamics: Concepts, Challenges, and Methods
Venkadesh, S., & Horn, J. D. V. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.752332 · Cited by 25
Lai, H., Kong, X., Zhao, Y., Pan, N., Zhang, X., He, M., Wang, S., & Gong, Q. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119009 · Cited by 28
Magnetoencephalography can reveal deep brain network activities linked to memory processes
López‐Madrona, V. J., Villalon, S. M., Badier, J., Trébuchon, A., Velmurugan, J., Bartoloméi, F., Carron, R., Barborică, A., Vulliémoz, S., Alario, F. ‐., et al. (2022) · Human Brain Mapping · doi:10.1002/hbm.25987 · Cited by 26
Arutiunian, V., Arcara, G., Buyanova, I., Юрьевна, Д. Е., Станиславаовна, П. Д., Sorokin, A. B., Анатольевна, Т. С., Mamokhina, U. A., Касимовна, Д. К., & Dragoy, O. (2022) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2022.110690 · Cited by 31
Threat and Reward Imminence Processing in the Human Brain
Murty, D. V. P. S., Song, S., Surampudi, S. G., & Pessoa, L. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1778-22.2023 · Cited by 33
Single‐subject cortical morphological brain networks across the adult lifespan
Ruan, J., Wang, N., Li, J., Wang, J., Zou, Q., Lv, Y., Zhang, H., & Wang, J. (2023) · Human Brain Mapping · doi:10.1002/hbm.26450 · Cited by 28
Metadata
- Authors
- Destrieux, C., Fischl, B., Dale, A., & Halgren, E.
- Affiliations
- Université de Tours (FR)
- Harvard University (US)
- University of California San Diego (US)
- Corresponding author
- Destrieux, Christophe
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-10
- Volume
- 53
- Issue
- 1
- Pages
- 1-15
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2937159
- OpenAlex
- W2007581301
- Cited by
- 2,956
- References
- 41
- Citations by year
- 2026: 272 · 2025: 328 · 2024: 287 · 2023: 290 · 2022: 291 · 2021: 272 · 2020: 241 · 2019: 188 · 2018: 189 · 2017: 163 · 2016: 130 · 2015: 98 · 2014: 75 · 2013: 62 · 2012: 44
- FWCI
- 48.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- Funders
- Centre Hospitalier Régional et Universitaire de Tours
- National Institute for Neurological Disorders and Stroke (R01 NS18741, R01 NS052585)
- National Center for Research Resources (P41-RR14075, BIRN002, U24 RR021382)
- National Institute for Biomedical Imaging and Bioengineering (R01 EB001550, R01 EB006758, R01 EB009282)
- National Institute on Aging (R01 AG02238)
- Mental Illness and Neuroscience Discovery (MIND) Institute
- National Institutes of Health (U54 EB005149)
- Ellison Medical Foundation
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
- Keywords
- cortical parcellation, FreeSurfer, anatomical terminology, brain surface reconstruction
- MeSH terms
- Adolescent, Adult, Algorithms, Brain, Computer Simulation, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Anatomic, Terminology as Topic, Pattern Recognition, Automated, Sensitivity and Specificity, Reproducibility of Results, Imaging, Three-Dimensional, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
