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MAPS IN THE BRAIN: What Can We Learn from Them?
Abstract
▪ Abstract In mammalian visual cortex, neurons are organized according to their functional properties into multiple maps such as retinotopic, ocular dominance, orientation preference, direction of motion, and others. What determines the organization of cortical maps? We argue that cortical maps reflect neuronal connectivity in intracortical circuits. Because connecting distant neurons requires costly wiring (i.e., axons and dendrites), there is an evolutionary pressure to place connected neurons as close to each other as possible. Then, cortical maps may be viewed as solutions that minimize wiring cost for given intracortical connectivity. These solutions can help us in inferring intracortical connectivity and, ultimately, in understanding the function of the visual system.
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“We expect regions that need to interact at high bandwidth and short latency to be placed close together9.”
From Cognitive computational neuroscience (2018) · cites this paper as [9]
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Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen, B. A., & Field, D. J. (1996) · Nature · doi:10.1038/381607a0 · Cited by 5,694
An Energy Budget for Signaling in the Grey Matter of the Brain
Attwell, D., & Laughlin, S. B. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200110000-00001 · Cited by 3,543
Preface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,537
The Molecular Biology of Axon Guidance
Tessier‐Lavigne, M., & Goodman, C. S. (1996) · Science · doi:10.1126/science.274.5290.1123 · Cited by 3,311
The “independent components” of natural scenes are edge filters
Bell, A. J., & Sejnowski, T. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00121-1 · Cited by 2,201
A tension-based theory of morphogenesis and compact wiring in the central nervous system
Essen, D. C. V. (1997) · Nature · doi:10.1038/385313a0 · Cited by 1,668
Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex
Gilbert, C., & Wiesel, T. (1989) · Journal of Neuroscience · doi:10.1523/jneurosci.09-07-02432.1989 · Cited by 1,166
The representation of the visual field on the cerebral cortex in monkeys
Daniel, P. M., & Whitteridge, D. (1961) · The Journal of Physiology · doi:10.1113/jphysiol.1961.sp006803 · Cited by 1,147
Research works printed but not linked: 2
- Allman JM, 1999, Evolving Brains
- 10.1088/0954-898X/1/1/004 · DOI
Cited by
Sorted by citations
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284
The ventral visual pathway: an expanded neural framework for the processing of object quality
Kravitz, D. J., Saleem, K. S., Baker, C. I., Ungerleider, L. G., & Mishkin, M. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.10.011 · Cited by 1,204
Energy limitation as a selective pressure on the evolution of sensory systems
Niven, J. E., & Laughlin, S. B. (2008) · Journal of Experimental Biology · doi:10.1242/jeb.017574 · Cited by 1,056
A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks
Stanley, K. O., D'Ambrosio, D. B., & Gauci, J. (2009) · Artificial Life · doi:10.1162/artl.2009.15.2.15202 · Cited by 895
Cortical rewiring and information storage
Chklovskii, D. B., Mel, B. W., & Svoboda, K. (2004) · Nature · doi:10.1038/nature03012 · Cited by 717
Self-citationWiring optimization can relate neuronal structure and function
Chen, B. L., Hall, D. H., & Chklovskii, D. B. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506806103 · Cited by 650
Self-citationKaiser, M., & Hilgetag, C. C. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020095 · Cited by 653
Cognitive computational neuroscience
Kriegeskorte, N., & Douglas, P. K. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0210-5 · Cited by 535
Minicolumnar abnormalities in autism
Casanova, M. F., van Kooten, I. A. J., Switala, A. E., van Engeland, H., Heinsen, H., Steinbusch, H. W. M., Hof, P. R., Trippe, J., Stone, J., & Schmitz, C. (2006) · Acta Neuropathologica · doi:10.1007/s00401-006-0085-5 · Cited by 499
Area map of mouse visual cortex
Wang, Q., & Burkhalter, A. (2007) · The Journal of Comparative Neurology · doi:10.1002/cne.21286 · Cited by 498
A Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule
Ercsey-Ravasz, M., Markov, N. T., Lamy, C., Van Essen, D. C., Knoblauch, K., Toroczkai, Z., & Kennedy, H. (2013) · Neuron · doi:10.1016/j.neuron.2013.07.036 · Cited by 487
Chomiak, T., & Hu, B. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007754 · Cited by 465
Bayesian just-so stories in psychology and neuroscience.
Bowers, J. S., & Davis, C. J. (2012) · Psychological Bulletin · doi:10.1037/a0026450 · Cited by 436
Sterling, P., & Laughlin, S. (2015) · doi:10.7551/mitpress/9780262028707.001.0001 · Cited by 482
Exploring the network dynamics underlying brain activity during rest
Cabral, J., Kringelbach, M. L., & Deco, G. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.12.005 · Cited by 351
One Rule to Grow Them All: A General Theory of Neuronal Branching and Its Practical Application
Cuntz, H., Förstner, F., Borst, A., & Häusser, M. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000877 · Cited by 383
Imaging retinotopic maps in the human brain
Wandell, B. A., & Winawer, J. A. (2010) · Vision Research · doi:10.1016/j.visres.2010.08.004 · Cited by 403
The Cortical Organization of Syntax
Matchin, W., & Hickok, G. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhz180 · Cited by 370
Representation in Cognitive Science
Shea, N. (2018) · doi:10.1093/oso/9780198812883.001.0001 · Cited by 676
Precision and diversity in an odor map on the olfactory bulb
Soucy, E. R., Albeanu, D. F., Fantana, A. L., Murthy, V. N., & Meister, M. (2009) · Nature Neuroscience · doi:10.1038/nn.2262 · Cited by 344
Decision theory: what “should” the nervous system do?
Körding, K. (2007) · Science · doi:10.1126/science.1142998 · Cited by 313
The heterogeneity of mental representation: Ending the imagery debate
Pearson, J., & Kosslyn, S. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1504933112 · Cited by 317
Developmental mechanisms of topographic map formation and alignment
Cang, J., & Feldheim, D. A. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062012-170341 · Cited by 275
Action Potential Energy Efficiency Varies Among Neuron Types in Vertebrates and Invertebrates
Sengupta, B., Stemmler, M., Laughlin, S. B., & Niven, J. E. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000840 · Cited by 285
Metabolic cost as a unifying principle governing neuronal biophysics.
Hasenstaub, A., Otte, S., Callaway, E., & Sejnowski, T. J. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914886107 · Cited by 246
The Medium of Haptic Perception: A Tensegrity Hypothesis
Turvey, M. T., & Fonseca, S. T. (2014) · Journal of Motor Behavior · doi:10.1080/00222895.2013.798252 · Cited by 239
Synaptic Connectivity and Neuronal Morphology
Chklovskii, D. B. (2004) · Neuron · doi:10.1016/s0896-6273(04)00498-2 · Cited by 263
Self-citationA transcriptional signature of hub connectivity in the mouse connectome
Fulcher, B., & Fornito, A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1513302113 · Cited by 217
Wiring Economy and Volume Exclusion Determine Neuronal Placement in the Drosophila Brain
Rivera-Alba, M., Vitaladevuni, S. N., Mishchenko, Y., Lu, Z., Takemura, S.-Y., Scheffer, L., Meinertzhagen, I. A., Chklovskii, D. B., & de Polavieja, G. G. (2011) · Current Biology · doi:10.1016/j.cub.2011.10.022 · Cited by 223
Self-citationMixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods
Gramfort, A., Kowalski, M., & Hämäläinen, M. (2012) · Physics in Medicine and Biology · doi:10.1088/0031-9155/57/7/1937 · Cited by 251
Ion-channel noise places limits on the miniaturization of the brain's wiring
Faisal, A. A., White, J. A., & Laughlin, S. B. (2005) · Current Biology · doi:10.1016/j.cub.2005.05.056 · Cited by 216
Auditory Cortex Mapmaking: Principles, Projections, and Plasticity
Schreiner, C. E., & Winer, J. A. (2007) · Neuron · doi:10.1016/j.neuron.2007.10.013 · Cited by 218
Information and efficiency in the nervous system-a synthesis.
Sengupta, B., Stemmler, M. B., & Friston, K. J. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003157 · Cited by 212
Horvát, S., Gămănuț, R., Ercsey-Ravasz, M., Magrou, L., Gămănuț, B., Van Essen, D. C., Burkhalter, A., Knoblauch, K., Toroczkai, Z., & Kennedy, H. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002512 · Cited by 198
Murthy, V. N. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113738 · Cited by 175
A brainstem map for visceral sensations
Chen, R., Boettcher, J. C., Kaye, J. A., Gallori, C. E., & Liberles, S. D. (2022) · Nature · doi:10.1038/s41586-022-05139-5 · Cited by 180
Vision and Cortical Map Development
WHITE, L. E., & Fitzpatrick, D. (2007) · Neuron · doi:10.1016/j.neuron.2007.10.011 · Cited by 169
Visual Field Map Clusters in Macaque Extrastriate Visual Cortex
Kolster, H., Mandeville, J. B., Arsenault, J. T., Ekstrom, L. B., Wald, L. L., & Vanduffel, W. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.0518-09.2009 · Cited by 168
Parametric Functional Maps of Visual Inputs to the Tectum
Nikolaou, N., Lowe, A., Walker, A., Abbas, F. H., Hunter, P. R., Thompson, I. D., & Meyer, M. P. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.040 · Cited by 162
Coding of visual objects in the ventral stream
Reddy, L., & Kanwisher, N. (2006) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2006.06.004 · Cited by 167
Peeling the Onion of Brain Representations
Kriegeskorte, N., & Diedrichsen, J. (2019) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-080317-061906 · Cited by 173
Silson, E. H., Chan, A. W.-Y., Reynolds, R. C., Kravitz, D. J., & Baker, C. I. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0137-15.2015 · Cited by 156
Comparing Bayesian and non-Bayesian accounts of human confidence reports
Adler, W. T., & Ma, W. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006572 · Cited by 118
Optimization principles of dendritic structure
Cuntz, H., Borst, A., & Segev, I. (2007) · Theoretical Biology and Medical Modelling · doi:10.1186/1742-4682-4-21 · Cited by 142
Total Variation Regularization for fMRI-Based Prediction of Behavior
Michel, V., Gramfort, A., Varoquaux, G. P., Eger, E., & Thirion, B. (2011) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2011.2113378 · Cited by 146
Spatial clustering of tuning in mouse primary visual cortex
Ringach, D. L., Mineault, P., Tring, E., Olivas, N. D., García‐Junco‐Clemente, P., & Trachtenberg, J. T. (2016) · Nature Communications · doi:10.1038/ncomms12270 · Cited by 138
Hanganu‐Opatz, I. L. (2010) · Brain Research Reviews · doi:10.1016/j.brainresrev.2010.03.005 · Cited by 132
Generating large-scale neural networks through discovering geometric regularities
Gauci, J., & Stanley, K. O. (2007) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1276958.1277158 · Cited by 130
Retinal input instructs alignment of visual topographic maps
Triplett, J. W., Owens, M. T., Yamada, J., Lemke, G., Cang, J., Stryker, M. P., & Feldheim, D. A. (2009) · Cell · doi:10.1016/j.cell.2009.08.028 · Cited by 123
Receptive fields and functional architecture in the retina
Balasubramanian, V., & Sterling, P. (2009) · The Journal of Physiology · doi:10.1113/jphysiol.2009.170704 · Cited by 126
Micro-connectomics: probing the organization of neuronal networks at the cellular scale
Schröter, M. S., Paulsen, O., & Bullmore, E. T. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2016.182 · Cited by 128
Chen, Y., Chen, X., Başerdem, B., Zhan, H., Li, Y., Davis, M. B., Kebschull, J. M., Zador, A. M., Koulakov, A. A., & Albeanu, D. F. (2022) · Cell · doi:10.1016/j.cell.2022.09.038 · Cited by 119
Self-citationAutonomous Evolution of Topographic Regularities in Artificial Neural Networks
Gauci, J., & Stanley, K. O. (2010) · Neural Computation · doi:10.1162/neco.2010.06-09-1042 · Cited by 121
Energy‐efficient neural information processing in individual neurons and neuronal networks
Yu, L., & Yu, Y. (2017) · Journal of Neuroscience Research · doi:10.1002/jnr.24131 · Cited by 125
Chen, Y., Wang, S.-J., Hilgetag, C. C., & Zhou, C. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002937 · Cited by 119
Extensive Cochleotopic Mapping of Human Auditory Cortical Fields Obtained with Phase-Encoding fMRI
Striem-Amit, E., Hertz, U., & Amedi, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017832 · Cited by 118
Comprehension of computer code relies primarily on domain-general executive brain regions
Ivanova, A. A., Srikant, S., Sueoka, Y., Kean, H., Dhamala, R., O’Reilly, U.-M., Bers, M. U., & Fedorenko, E. G. (2020) · eLife · doi:10.7554/elife.58906 · Cited by 120
Balasubramanian, V. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2107022118 · Cited by 113
Exploring Spatiotemporal Organization of SCN CircuitsPreprint
Yan, L., Karatsoreos, I. N., LeSauter, J., Welsh, D. K., Kay, S. A., Foley, D. K., & Silver, R. (2007) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2007.72.037 · Cited by 112
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Casanova, M. F. (2006) · The Neuroscientist · doi:10.1177/1073858406290375 · Cited by 109
A functionally ordered visual feature map in the Drosophila brain
Klapoetke, N. C., Nern, A., Rogers, E. M., Rubin, G. M., Reiser, M. B., & Card, G. M. (2022) · Neuron · doi:10.1016/j.neuron.2022.02.013 · Cited by 98
The optic tectum of birds: Mapping our way to understanding visual processing.
Wylie, D. R. W., Gutierrez-Ibanez, C., Pakan, J. M. P., & Iwaniuk, A. N. (2009) · Canadian Journal of Experimental Psychology / Revue canadienne de psychologie expérimentale · doi:10.1037/a0016826 · Cited by 107
Understanding Human Object Vision: A Picture Is Worth a Thousand Representations
Bracci, S., & de Beeck, H. O. (2022) · Annual Review of Psychology · doi:10.1146/annurev-psych-032720-041031 · Cited by 105
The Morphological Identity of Insect Dendrites
Cuntz, H., Förstner, F., Haag, J., & Borst, A. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000251 · Cited by 96
Jetti, S. K., Vendrell-Llopis, N., & Yaksi, E. (2014) · Current Biology · doi:10.1016/j.cub.2014.01.015 · Cited by 94
Contributions of Theoretical Modeling to the Understanding of Neural Map Development
Goodhill, G. J. (2007) · Neuron · doi:10.1016/j.neuron.2007.09.027 · Cited by 93
Cang, J., Niell, C. M., Liu, X., Pfeiffenberger, C., Feldheim, D. A., & Stryker, M. P. (2008) · Neuron · doi:10.1016/j.neuron.2007.12.025 · Cited by 89
Neural representation for object recognition in inferotemporal cortex
Lehky, S. R., & Tanaka, K. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.12.001 · Cited by 95
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Kaschube, M. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.08.017 · Cited by 93
A novel generative encoding for exploiting neural network sensor and output geometry
D’Ambrosio, D. B., & Stanley, K. O. (2007) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1276958.1277155 · Cited by 87
Topographic organization in the brain: searching for general principles
Patel, G. H., Kaplan, D. M., & Snyder, L. H. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.03.008 · Cited by 85
Visuospatial coding as ubiquitous scaffolding for human cognition
Groen, I. I. A., Dekker, T. M., Knapen, T. H. J., & Silson, E. H. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.10.011 · Cited by 93
Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity
Jenatton, R., Gramfort, A., Michel, V., Obozinski, G., Eger, E., Bach, F., & Thirion, B. (2012) · SIAM Journal on Imaging Sciences · doi:10.1137/110832380 · Cited by 83
Cortical tonotopic map plasticity and behavior
Pienkowski, M., & Eggermont, J. J. (2011) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.02.002 · Cited by 85
Abnormalities of cortical minicolumnar organization in the prefrontal lobes of autistic patients
Casanova, M. F., van Kooten, I. A. J., Switala, A. E., van Engeland, H., Heinsen, H., Steinbusch, H. W. M., Hof, P. R., & Schmitz, C. (2006) · Clinical Neuroscience Research · doi:10.1016/j.cnr.2006.06.003 · Cited by 80
Nienborg, H., & Cumming, B. G. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.2340-13.2014 · Cited by 76
The Wiring Economy Principle: Connectivity Determines Anatomy in the Human Brain
Raj, A., & Chen, Y.-H. (2011) · PLoS ONE · doi:10.1371/journal.pone.0014832 · Cited by 78
Recording of brain activity across spatial scales
Lewis, C., Bosman, C. A., & Fries, P. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.12.007 · Cited by 78
Phenomenology and neurophysiological correlations: Two approaches to perception research
Spillmann, L. (2009) · Vision Research · doi:10.1016/j.visres.2009.02.022 · Cited by 81
On the Origin of the Functional Architecture of the Cortex
Ringach, D. L. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000251 · Cited by 73
Cortical Representation of Medial Axis Structure
Lescroart, M. D., & Biederman, I. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs046 · Cited by 78
Brewer, A. A., & Barton, B. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-014045 · Cited by 76
How our body influences our perception of the world
Harris, L. R., Carnevale, M. J., Dâ€TMAmour, S., Fraser, L. E., Harrar, V., Hoover, A. E. N., Mander, C. M., & Pritchett, L. M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00819 · Cited by 82
Song, C., Schwarzkopf, D. S., & Rees, G. E. (2013) · Nature Communications · doi:10.1038/ncomms3201 · Cited by 74
Topographic organization of macaque area LIP
Patel, G. H., Shulman, G. L., Baker, J. T., Akbudak, E., Snyder, A. Z., Snyder, L. H., & Corbetta, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908092107 · Cited by 73
Harding-Forrester, S., & Feldman, D. E. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63622-5.00004-8 · Cited by 77
A Motion Direction Preference Map in Monkey V4
Li, P., Zhu, S., Chen, M., Han, C., Xu, H., Hu, J., Fang, Y., & Lu, H. D. (2013) · Neuron · doi:10.1016/j.neuron.2013.02.024 · Cited by 70
Communication and wiring in the cortical connectome
Budd, J. M. L., & Kisvárday, Z. F. (2012) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2012.00042 · Cited by 71
Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation
Budd, J. M. L., Kovács, K., Ferecskó, A. S., Buzás, P., Eysel, U. T., & Kisvárday, Z. F. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000711 · Cited by 67
Quality Time: Representation of a Multidimensional Sensory Domain through Temporal Coding
Lorenzo, P. M. D., Chen, J.-Y., & Victor, J. D. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.5995-08.2009 · Cited by 67
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Goodhill, G. J., & Xu, J. (2005) · Network Computation in Neural Systems · doi:10.1080/09548980500254654 · Cited by 67
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Nauhaus, I., Nielsen, K. J., & Callaway, E. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.015 · Cited by 67
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Carreira-Perpiñán, M. Á., Lister, R. J., & Goodhill, G. J. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhi004 · Cited by 65
Wang, L., Rangarajan, K. V., Lawhn-Heath, C. A., Sarnaik, R., Wang, B.-S., Liu, X., & Cang, J. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2128-09.2009 · Cited by 62
Martin, K. A. C., & Schröder, S. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.4071-12.2013 · Cited by 66
Functional maps within a single neuron
Narayanan, R., & Johnston, D. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00530.2012 · Cited by 64
Knösche, T. R., & Tittgemeyer, M. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00058 · Cited by 66
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Baier, H. (2013) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-101011-155748 · Cited by 64
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Casanova, M. F., & Tillquist, C. R. (2007) · The Neuroscientist · doi:10.1177/1073858407309091 · Cited by 59
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Metadata
- Authors
- Chklovskii, D. B., & Koulakov, A. A.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2004-07-21
- Volume
- 27
- Issue
- 1
- Pages
- 369-392
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2144662207
- Cited by
- 366
- References
- 86
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 7 · 2023: 12 · 2022: 20 · 2021: 11 · 2020: 27 · 2019: 20 · 2018: 18 · 2017: 13 · 2016: 21 · 2015: 21 · 2014: 15 · 2013: 28 · 2012: 23
- FWCI
- 1.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- Funders
- David and Lucile Packard Foundation
- Annenberg Foundation
- Lita Annenberg Hazen Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- cortical maps, visual cortex, retinotopic map, ocular dominance, orientation preference, movement direction, intracortical connectivity, wiring cost, neuronal connectivity, brain organization
- MeSH terms
- Animals, Axons, Brain Mapping, Dendrites, Humans, Nerve Net, Neural Pathways, Visual Cortex, Visual Fields, Visual Pathways
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 ›
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