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A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei
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Abstract
Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in vivo anatomical atlas of subcortical nuclei. In order to address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration of T 1 - and T 2 - weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineations of subcortical nuclei complement current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in vivo probabilistic anatomical atlas of the human brain.
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Cites
Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
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
Measures of the Amount of Ecologic Association Between Species
Dice, L. R. (1945) · Ecology · doi:10.2307/1932409 · Cited by 11,874
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.015 · Cited by 8,868
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Parallel organization of functionally segregated circuits linking basal ganglia and cortex
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.09.030186.002041 · Cited by 8,527
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304
AVANTS, B., EPSTEIN, C., GROSSMAN, M., & GEE, J. (2008) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,669
The WU-Minn Human Connectome Project: An overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.041 · Cited by 5,651
Dynamic mapping of human cortical development during childhood through early adulthood
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., Nugent, T. F., Herman, D. H., Clasen, L. S., Toga, A. W., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402680101 · Cited by 5,604
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253
Comparing images using the Hausdorff distance
Huttenlocher, D. P., Klanderman, G. A., & Rucklidge, W. J. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.232073 · Cited by 4,545
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data
Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.034 · Cited by 4,033
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083
THE BASAL GANGLIA: FOCUSED SELECTION AND INHIBITION OF COMPETING MOTOR PROGRAMS
MINK, J. W. (1996) · Progress in Neurobiology · doi:10.1016/s0301-0082(96)00042-1 · Cited by 2,486
Image matching as a diffusion process: an analogy with maxwell’s demons
Thirion, J.-P. (1998) · Medical Image Analysis · doi:10.1016/s1361-8415(98)80022-4 · Cited by 2,445
Within-subject template estimation for unbiased longitudinal image analysis
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.084 · Cited by 2,356
By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism
Frank, M. J., Seeberger, L. C., & O'Reilly, R. C. (2004) · Science · doi:10.1126/science.1102941 · Cited by 1,964
Basal ganglia and cerebellar loops: motor and cognitive circuits
Middleton, F. (2000) · Brain Research Reviews · doi:10.1016/s0165-0173(99)00040-5 · Cited by 1,940
Nonlinear spatial normalization using basis functions
Ashburner, J., & Friston, K. J. (1999) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1999)7:4<254::aid-hbm4>3.0.co;2-g · Cited by 1,884
Balleine, B. W., & O'Doherty, J. P. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.131 · Cited by 1,775
Haber, S. N., Fudge, J. L., & McFarland, N. R. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-06-02369.2000 · Cited by 1,610
The primate basal ganglia: Parallel and integrative networks
Haber, S. N. (2003) · Journal of Chemical Neuroanatomy · doi:10.1016/j.jchemneu.2003.10.003 · Cited by 1,479
Ikemoto, S. (2007) · Brain Research Reviews · doi:10.1016/j.brainresrev.2007.05.004 · Cited by 1,477
The neostriatal mosaic: multiple levels of compartmental organization
Gerfen, C. R. (1992) · Trends in Neurosciences · doi:10.1016/0166-2236(92)90355-c · Cited by 1,467
Jeurgen, K., Assheuer, J., & Paxinos, G. (1997) · Medical Entomology and Zoology · Cited by 1,403
Tractography-based connectomes are dominated by false-positive connections
Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,376
Input-specific control of reward and aversion in the ventral tegmental area
Lammel, S., Lim, B. K., Ran, C., Huang, K. W., Betley, M. J., Tye, K. M., Deisseroth, K., & Malenka, R. C. (2012) · Nature · doi:10.1038/nature11527 · Cited by 1,300
Lateral habenula as a source of negative reward signals in dopamine neurons
Matsumoto, M., & Hikosaka, O. (2007) · Nature · doi:10.1038/nature05860 · Cited by 1,292
Iglesias, J. E., Augustinack, J. C., Nguyen, K., Player, C. M., Player, A., Wright, M., Roy, N., Frosch, M. P., McKee, A. C., Wald, L. L., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.042 · Cited by 1,277
Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., Habel, U., Schneider, F., & Zilles, K. (2005) · Anatomy and Embryology · doi:10.1007/s00429-005-0025-5 · Cited by 1,264
Whole-Brain Mapping of Direct Inputs to Midbrain Dopamine Neurons
Watabe-Uchida, M., Zhu, L., Ogawa, S. K., Vamanrao, A., & Uchida, N. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.017 · Cited by 1,247
Dichotomous dopaminergic control of striatal synaptic plasticity
Shen, W., Flajolet, M., Greengard, P., & Surmeier, D. J. (2008) · Science · doi:10.1126/science.1160575 · Cited by 1,190
Hold Your Horses: Impulsivity, Deep Brain Stimulation, and Medication in Parkinsonism
Frank, M. J., Samanta, J., Moustafa, A. A., & Sherman, S. J. (2007) · Science · doi:10.1126/science.1146157 · Cited by 1,120
(2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-00937-3 · Cited by 1,048
BigBrain: An Ultrahigh-Resolution 3D Human Brain Model
Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-É., Bludau, S., Bazin, P.-L., Lewis, L. B., Oros-Peusquens, A.-M., et al. (2013) · Science · doi:10.1126/science.1235381 · Cited by 876
Disinhibition as a basic process in the expression of striatal functions
Chevalier, G., & Deniau, J. M. (1990) · Trends in Neurosciences · doi:10.1016/0166-2236(90)90109-n · Cited by 865
Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.11.018 · Cited by 809
Bullock, D., & Grossberg, S. (1988) · Psychological Review · doi:10.1037/0033-295x.95.1.49 · Cited by 801
Frazier, J. A., Chiu, S., Breeze, J. L., Makris, N., Lange, N., Kennedy, D. N., Herbert, M. R., Bent, E. K., Koneru, V. K., Dieterich, M. E., et al. (2005) · American Journal of Psychiatry · doi:10.1176/appi.ajp.162.7.1256 · Cited by 790
The organization of the human striatum estimated by intrinsic functional connectivity
Choi, E. Y., Yeo, B. T. T., & Buckner, R. L. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00270.2012 · Cited by 746
Thomas, C., Ye, F. Q., Irfanoglu, M. O., Modi, P., Saleem, K. S., Leopold, D. A., & Pierpaoli, C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405672111 · Cited by 725
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
Learning, reward, and decision making
O'Doherty, J. P., Cockburn, J., & Pauli, W. M. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-010416-044216 · Cited by 475
Self-citationBEaST: Brain extraction based on nonlocal segmentation technique
Eskildsen, S. F., Coupé, P., Fonov, V., Manjón, J. V., Leung, K. K., Guizard, N., Wassef, S. N., Østergaard, L. R., & Collins, D. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.012 · Cited by 472
Saygin, Z. M., Kliemann, D., Iglesias, J. E., van der Kouwe, A. J. W., Boyd, E., Reuter, M., Stevens, A., Van Leemput, K., McKee, A., Frosch, M. P., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.046 · Cited by 467
Biologically Based Computational Models of High-Level Cognition
O'Reilly, R. C. (2006) · Science · doi:10.1126/science.1127242 · Cited by 448
An unbiased iterative group registration template for cortical surface analysis
Lyttelton, O., Boucher, M., Robbins, S., & Evans, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.041 · Cited by 415
An Efficient Algorithm for Calculating the Exact Hausdorff Distance
Taha, A. A., & Hanbury, A. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2408351 · Cited by 411
Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI
Van Leemput, K., Bakkour, A., Benner, T., Wiggins, G., Wald, L. L., Augustinack, J., Dickerson, B. C., Golland, P., & Fischl, B. (2009) · Hippocampus · doi:10.1002/hipo.20615 · Cited by 405
Arithmetic and local circuitry underlying dopamine prediction errors
Eshel, N., Bukwich, M., Rao, V., Hemmelder, V., Tian, J., & Uchida, N. (2015) · Nature · doi:10.1038/nature14855 · Cited by 392
Ji, H., & Shepard, P. D. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.0958-07.2007 · Cited by 388
Banishing the homunculus: Making working memory work
Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2006) · Neuroscience · doi:10.1016/j.neuroscience.2005.04.067 · Cited by 385
A Physiologically Plausible Model of Action Selection and Oscillatory Activity in the Basal Ganglia
Humphries, M. D., Stewart, R. D., & Gurney, K. N. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3486-06.2006 · Cited by 370
From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure
Poldrack, R. A., & Yarkoni, T. (2016) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033729 · Cited by 365
3D brain mapping using a deformable neuroanatomy
Christensen, G. E., Rabbitt, R. D., & Miller, M. I. (1994) · Physics in Medicine and Biology · doi:10.1088/0031-9155/39/3/022 · Cited by 353
Deniau, J. M., & Chevalier, G. (1985) · Brain Research · doi:10.1016/0006-8993(85)90214-8 · Cited by 349
The globus pallidus sends reward-related signals to the lateral habenula
Hong, S., & Hikosaka, O. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.035 · Cited by 346
Yushkevich, P. A., Amaral, R. S. C., Augustinack, J. C., Bender, A. R., Bernstein, J. D., Boccardi, M., Bocchetta, M., Burggren, A. C., Carr, V. A., Chakravarty, M. M., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.004 · Cited by 345
A Three-dimensional MRI Atlas of the Mouse Brain with Estimates of the Average and Variability
Kovačević, N., Henderson, J. T., Chan, E., Lifshitz, N., Bishop, J., Evans, A. C., Henkelman, R. M., & Chen, X. J. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhh165 · Cited by 328
Metaanalytic connectivity modeling: Delineating the functional connectivity of the human amygdala
Robinson, J. L., Laird, A. R., Glahn, D. C., Lovallo, W. R., & Fox, P. T. (2010) · Human Brain Mapping · doi:10.1002/hbm.20854 · Cited by 327
Brown, J., Bullock, D., & Grossberg, S. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-23-10502.1999 · Cited by 298
Levy, R., Friedman, H. R., Davachi, L., & Goldman-Rakic, P. S. (1997) · The Journal of Neuroscience · doi:10.1523/jneurosci.17-10-03870.1997 · Cited by 279
Brown, J. W., Bullock, D., & Grossberg, S. (2004) · Neural Networks · doi:10.1016/j.neunet.2003.08.006 · Cited by 265
Persistently active neurons in human medial frontal and medial temporal lobe support working memory
Kamiński, J., Sullivan, S., Chung, J. M., Ross, I. B., Mamelak, A. N., & Rutishauser, U. (2017) · Nature Neuroscience · doi:10.1038/nn.4509 · Cited by 264
The neostriatal mosaic: multiple levels of compartmental organization
Gerfen, C. R. (1992) · Advances in Neuroscience and Schizophrenia · doi:10.1007/978-3-7091-9211-5_4 · Cited by 232
Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI
Keuken, M. C., Bazin, P.-L., Crown, L., Hootsmans, J., Laufer, A., Müller-Axt, C., Sier, R., van der Putten, E. J., Schäfer, A., Turner, R., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.032 · Cited by 223
Functional imaging of the human dopaminergic midbrain
Düzel, E., Bunzeck, N., Guitart-Masip, M., Wittmann, B., Schott, B. H., & Tobler, P. N. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2009.02.005 · Cited by 216
Regional specialization within the human striatum for diverse psychological functions
Pauli, W. M., O’Reilly, R. C., Yarkoni, T., & Wager, T. D. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507610113 · Cited by 199
Self-citationWiecki, T. V., Poland, J., & Frank, M. J. (2015) · Clinical Psychological Science · doi:10.1177/2167702614565359 · Cited by 182
Tyszka, J. M., & Pauli, W. M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23289 · Cited by 162
Self-citationWang, S., Yu, R., Tyszka, J. M., Zhen, S., Kovach, C., Sun, S., Huang, Y., Hurlemann, R., Ross, I. B., Chung, J. M., et al. (2017) · Nature Communications · doi:10.1038/ncomms14821 · Cited by 159
Self-citationMenke, R., Jbabdi, S., Miller, K. L., Matthews, P. M., & Zarei, M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.086 · Cited by 153
The central nucleus of the amygdala projection to dopamine subpopulations in primates
Fudge, J. L., & Haber, S. N. (2000) · Neuroscience · doi:10.1016/s0306-4522(00)00092-0 · Cited by 138
Defining the habenula in human neuroimaging studies
Lawson, R. P., Drevets, W. C., & Roiser, J. P. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.076 · Cited by 127
Multivariate Analysis of Structural and Diffusion Imaging in Traumatic Brain Injury
Avants, B., Duda, J., Kim, J., Zhang, H. G., Pluta, J. B., Gee, J. C., & Whyte, J. (2008) · Academic Radiology · doi:10.1016/j.acra.2008.07.007 · Cited by 113
Neural mechanisms of acquired phasic dopamine responses in learning
Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2009) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2009.11.019 · Cited by 107
de Hollander, G., Keuken, M. C., van der Zwaag, W., Forstmann, B. U., & Trampel, R. (2017) · Human Brain Mapping · doi:10.1002/hbm.23586 · Cited by 103
Preparation for movement in the cat. I. Unit activity in the cerebral cortex
Neafsey, E. J., Hull, C. D., & Buchwald, N. A. (1978) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(78)90205-5 · Cited by 101
Intrinsic functional connectivity of the central extended amygdala
Tillman, R. M., Stockbridge, M. D., Nacewicz, B. M., Torrisi, S., Fox, A. S., Smith, J. F., & Shackman, A. J. (2017) · Human Brain Mapping · doi:10.1002/hbm.23917 · Cited by 94
Hypothalamic neuron involvement in integration of reward, aversion, and cue signals
Ono, T., Nakamura, K., Nishijo, H., & Fukuda, M. (1986) · Journal of Neurophysiology · doi:10.1152/jn.1986.56.1.63 · Cited by 87
Basal ganglia: structure and computations
Wickens, J. R. (1997) · Network Computation in Neural Systems · doi:10.1088/0954-898x_8_4_001 · Cited by 82
Amygdala Volume Differences in Autism Spectrum Disorder Are Related to Anxiety
Herrington, J. D., Maddox, B. B., Kerns, C. M., Rump, K. M., Worley, J. A., Bush, J., McVey, A. J., Schultz, R. T., & Miller, J. S. (2017) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-017-3206-1 · Cited by 80
Erratum: Computational psychiatry
Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.04.003 · Cited by 65
Multivariate Normalization with Symmetric Diffeomorphisms for Multivariate Studies
Avants, B., Duda, J., Zhang, H. G., & Gee, J. C. (2007) · Springer eBooks · doi:10.1007/978-3-540-75757-3_44 · Cited by 52
Human habenula segmentation using myelin content
Kim, J.-W., Naidich, T. P., Ely, B. A., Yacoub, E. S., Martino, F. D., Fowkes, M. E., Goodman, W. K., & Xu, J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.048 · Cited by 45
Colas, J. T., Pauli, W. M., Larsen, T., Tyszka, J. M., & O’Doherty, J. P. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005810 · Cited by 30
Self-citation
Research works printed but not linked: 2
- Olszewski, J. & Baxter, D. Cytoarchitecture of the human brain stem 3rd edn (Karger Publishers 2013).
- Tyszka, J.M., Pauli, W., & Nili, A. Open Science Framework https://doi.org/10.17605/OSF.IO/JKZWP (2017) · doi:10.17605/osf.io/jkzwp
Cited by
SARS-CoV-2 is associated with changes in brain structure in UK Biobank
Douaud, G., Lee, S., Alfaro-Almagro, F., Arthofer, C., Wang, C., McCarthy, P., Lange, F., Andersson, J. L. R., Griffanti, L., Duff, E., et al. (2022) · Nature · doi:10.1038/s41586-022-04569-5 · Cited by 1,646
Topographic organization of the human subcortex unveiled with functional connectivity gradients
Tian, Y., Margulies, D. S., Breakspear, M., & Zalesky, A. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00711-6 · Cited by 784
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.-J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.068 · Cited by 739
A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder
Li, N., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Elias, G. J. B., Boutet, A., Lozano, A. M., Al-Fatly, B., Strange, B., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16734-3 · Cited by 316
Acute social isolation evokes midbrain craving responses similar to hunger
Tomova, L., Wang, K. L., Thompson, T., Matthews, G. A., Takahashi, A., Tye, K. M., & Saxe, R. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00742-z · Cited by 283
Metadata
- Authors
- Pauli, W. M., Nili, A. N., & Tyszka, J. M.
- Venue
- Scientific Data
- Published
- 2018-04-17
- Volume
- 5
- Issue
- 1
- Pages
- 180063-180063
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W2767027378
- Cited by
- 517
- References
- 88
- Type
- data paper
- Language
- en
- Open access
- gold
- Licence
- creativecommons.org/licenses/by/4.0 (tdm)
- creativecommons.org/licenses/by/4.0 (vor)
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