The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“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]
Citations
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
Items 201–300 of 365
An Optimized Structure-Function Design Principle Underlies Efficient Signaling Dynamics in Neurons
Puppo, F., George, V. K., & Silva, G. A. (2018) · Scientific Reports · doi:10.1038/s41598-018-28527-2 · Cited by 13
Sölter, J., Schumacher, J., Spors, H., & Schmuker, M. (2020) · Scientific Reports · doi:10.1038/s41598-019-56863-4 · Cited by 12
Alexander, D. M., Trengove, C., Sheridan, P., & van Leeuwen, C. (2010) · Cognitive Neurodynamics · doi:10.1007/s11571-010-9142-9 · Cited by 12
Visual Experience Modulates Spatio-Temporal Dynamics of Circuit Activation
Wang, L., Fontanini, A., & Maffei, A. (2011) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2011.00012 · Cited by 10
Weak universality in sensory tradeoffs
Marzen, S., & DeDeo, S. (2016) · Physical review. E · doi:10.1103/physreve.94.060101 · Cited by 9
Lusch, B., Weholt, J., Maia, P. D., & Kutz, J. N. (2018) · Brain and Cognition · doi:10.1016/j.bandc.2018.02.012 · Cited by 11
Clustering of heading selectivity and perception-related activity in the ventral intraparietal area
Shao, M., DeAngelis, G. C., Angelaki, D. E., & Chen, A. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00556.2017 · Cited by 11
Burkhalter, A., D’Souza, R. D., Ji, W., & Meier, A. M. (2023) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-083122-021241 · Cited by 13
Intra-hemispheric integration underlies perception of tilt illusion
Song, C., & Rees, G. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.073 · Cited by 11
Cho, M. W., & Choi, M. Y. (2012) · Neural Networks · doi:10.1016/j.neunet.2012.03.002 · Cited by 10
Optimal Information Storage: Nonsequential Sources and Neural Channels
Varshney, L. R. (2006) · Cited by 11
Barton, B., & Brewer, A. A. (2017) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2017.00004 · Cited by 10
Li, G., & Baker, C. L. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.4662-11.2012 · Cited by 9
On Palimpsests in Neural Memory: An Information Theory Viewpoint
Varshney, L. R., Kusuma, J., & Goyal, V. K. (2016) · IEEE Transactions on Molecular Biological and Multi-Scale Communications · doi:10.1109/tmbmc.2016.2640320 · Cited by 9
Ma, Z., Tu, W., & Zhang, N. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117463 · Cited by 9
Introduction to Dendritic Morphology
Torben-Nielsen, B., & Cuntz, H. (2013) · Springer series in computational neuroscience · doi:10.1007/978-1-4614-8094-5_1 · Cited by 9
Sentence Comprehension in Aphasia
Clark, D. G. (2011) · Language and Linguistics Compass · doi:10.1111/j.1749-818x.2011.00309.x · Cited by 9
The molecular basis for the development of neural maps
Wei, Y., Tsigankov, D., & Koulakov, A. A. (2013) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12324 · Cited by 9
Self-citationSurround suppression maps in the cat primary visual cortex
Vanni, M. P., & Casanova, C. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2013.00078 · Cited by 9
Sotero, R. C., & Shmuel, A. (2011) · Journal of Computational Neuroscience · doi:10.1007/s10827-011-0370-8 · Cited by 10
A Semantic Concept of Auditory Cortex Function and Learning
Scheich, H., & Ohl, F. W. (2010) · Springer eBooks · doi:10.1007/978-1-4419-0074-6_17 · Cited by 8
Barton, B., & Brewer, A. A. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-407794-2.00005-5 · Cited by 8
Positional information in neural map development: Lessons from the olfactory system
Imai, T. (2012) · Development Growth & Differentiation · doi:10.1111/j.1440-169x.2012.01334.x · Cited by 9
A Potential Role of Auditory Induced Modulations in Primary Visual Cortex
Azevedo, F. A. C., Azevedo, F. A. C., Ortiz-Rios, M., Azevedo, F. A. C., Ortiz-Rios, M., Li, Q., Azevedo, F. A. C., Ortiz-Rios, M., Li, Q., Logothetis, N. K., et al. (2015) · Multisensory Research · doi:10.1163/22134808-00002494 · Cited by 8
Chizhov, A. V., & Merkulyeva, N. S. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008333 · Cited by 8
Kleinschmidt, A. K. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.047 · Cited by 8
Structured learning in time‐dependent Cox models
Wang, G., Lian, Y., Yang, A. Y., Platt, R. W., Wang, R., Perreault, S., Dorais, M., & Schnitzer, M. E. (2024) · Statistics in Medicine · doi:10.1002/sim.10116 · Cited by 7
Distributed Representations for Cognitive Control in Frontal Medial Cortex
Colin, T. R., Ikink, I., & Holroyd, C. B. (2025) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02285 · Cited by 8
Neuroplasticity in the blind and sensory substitution for vision
Striem-Amit, E. (2014) · doi:10.13140/2.1.2640.2247 · Cited by 7
A Model of Brain Folding Based on Strong Local and Weak Long-Range Connectivity Requirements
Groden, M., Weigand, M., Triesch, J., Jedlička, P., & Cuntz, H. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz249 · Cited by 7
Development Via Information Self-structuring of Sensorimotor Experience and Interaction
Nehaniv, C. L., Mirza, N. A., & Olsson, L. (2007) · Springer eBooks · doi:10.1007/978-3-540-77296-5_9 · Cited by 7
Frequency Map Variations in Squirrel Monkey Primary Auditory Cortex
Cheung, S. W. (2005) · The Laryngoscope · doi:10.1097/01.mlg.0000165369.65046.cd · Cited by 7
Principles governing the topological organization of object selectivities in ventral temporal cortexPreprint
Zhang, Y., Zhou, K., Bao, P., & Jia Liu, B. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.15.460220 · Cited by 7
Neurons in cat V1 show significant clustering by degree of tuning
Ziskind, A. J., Emondi, A. A., Kurgansky, А. V., Rebrik, S. P., & Miller, K. D. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00646.2014 · Cited by 6
A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps
Mainetti, M., & Ascoli, G. A. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004155 · Cited by 5
Reconsidering Spatial Priors In EEG Source Estimation : Does White Matter Contribute to EEG Rhythms?
Douglas, P. K., & Douglas, D. (2019) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/iww-bci.2019.8737307 · Cited by 6
Brain networks: Graph theoretical analysis and development models
Cho, M. W., & Choi, M. Y. (2010) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.20229 · Cited by 7
Homotopy and heterotopy and the bilateral field advantage in the Dimond paradigm
Desjardins, S., & Braun, C. M. J. (2005) · Acta Psychologica · doi:10.1016/j.actpsy.2005.07.003 · Cited by 7
Baker, C. I. (2008) · Nature Neuroscience · doi:10.1038/nn0808-862 · Cited by 6
Seeing Natural Images through the Eye of a Fly with Remote Focusing Two-Photon Microscopy
Schützenberger, A., & Borst, A. (2020) · iScience · doi:10.1016/j.isci.2020.101170 · Cited by 5
Coding of low-level position and orientation information in human naturalistic vision
Christensen, J. H., Bex, P. J., & Fiser, J. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212141 · Cited by 5
Marzen, S., & Crutchfield, J. P. (2020) · Bulletin of Mathematical Biology · doi:10.1007/s11538-020-00694-2 · Cited by 4
Karkali, K., Vernon, S. W., Baines, R., Panayotou, G., & Martı́n-Blanco, E. (2023) · Nature Communications · doi:10.1038/s41467-023-43783-1 · Cited by 5
Gordon, N. S. (2007) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2007.10.007 · Cited by 5
A Pluralist Framework for the Philosophy of Social Neuroscience
Barberis, S. D., Branca, I., & Venturelli, A. N. (2017) · Springer eBooks · doi:10.1007/978-3-319-68421-5_21 · Cited by 5
Lundie, M. (2019) · Biology & Philosophy · doi:10.1007/s10539-019-9670-6 · Cited by 6
Information transfer and recovery for the sense of touch
Huang, C., Englitz, B., Reznik, A., Zeldenrust, F., & Celikel, T. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf073 · Cited by 5
Theoretical limitations on functional imaging resolution in auditory cortex
Chen, T. L., Watkins, P. V., & Barbour, D. L. (2010) · Brain Research · doi:10.1016/j.brainres.2010.01.012 · Cited by 5
A Comparison Study of the Vertical Bias of Pyramidal Cells in the Hippocampus and Neocortex
Casanova, M. F., Switala, A. E., & Trippe, J. (2006) · Developmental Neuroscience · doi:10.1159/000096223 · Cited by 5
Zhang, X., Braun, U., Harneit, A., Zang, Z., Geiger, L. S., Betzel, R. F., Chen, J., Schweiger, J. I., Schwarz, K., Reinwald, J., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/604322 · Cited by 5
Comprehension of computer code relies primarily on domain-general executive resourcesPreprint
Ivanova, A. A., Srikant, S., Sueoka, Y., Kean, H., Dhamala, R., O’Reilly, U.-M., Bers, M. U., & Fedorenko, E. G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.17605/osf.io/9jfn5 · Cited by 5
Puckered in pioneer neurons coordinates the motor activity of the Drosophila embryoPreprint
Karkali, K., Vernon, S. W., Baines, R., Panayotou, G., & Martín-Blanco, E. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/092486 · Cited by 5
A sinusoidal transform of the visual field in cortical area V2Preprint
Sedigh-Sarvestani, M., Lee, K.-S., Satterfield, R., Shultz, N., & Fitzpatrick, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.08.416651 · Cited by 5
Analytic Model for Feature Maps in the Primary Visual Cortex
Liu, X., & Robinson, P. A. (2022) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2022.659316 · Cited by 4
The global neuronal workspace as a broadcasting network
Paz, A. W. (2022) · Network Neuroscience · doi:10.1162/netn_a_00261 · Cited by 5
Kumar, B. S., Menon, S. C., Gayathri, S. R., & Chakravarthy, V. S. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.917196 · Cited by 3
Nine insights from internet engineering that help us understand brain network communication
Graham, D. J. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.976801 · Cited by 4
Framework for solving time-delayed Markov Decision Processes
Sawaya, Y., Issa, G., & Marzen, S. (2023) · Physical Review Research · doi:10.1103/physrevresearch.5.033034 · Cited by 4
Estimating the location and size of retinal injections from orthogonal images of an intact retina
Hjorth, J. J. J., Savier, E. L., Sterratt, D. C., Reber, M., & Eglen, S. J. (2015) · BMC Neuroscience · doi:10.1186/s12868-015-0217-8 · Cited by 4
Isabella, A. J., Barsh, G. R., Stonick, J. A., & Moens, C. B. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/826735 · Cited by 4
A semantotopic map in human hippocampusPreprint
Mickiewicz, E. A., Franch, M. C., Katlowitz, K. A., Chavez, A. G., Zhu, H., Chericoni, A., Yan, X., Belanger, J. L., Ismail, T., Paulo, D. L., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.31.685959 · Cited by 4
Differential clustering of visual and choice- and saccade-related activity in macaque V3A and CIP
Zhu, Z., Kim, B., Doudlah, R. C., Chang, T., & Rosenberg, A. (2024) · Journal of Neurophysiology · doi:10.1152/jn.00285.2023 · Cited by 3
Topographic Maps: Motor Axons Wait Their Turn
D’Elia, K. P., & Dasen, J. S. (2018) · Current Biology · doi:10.1016/j.cub.2017.11.047 · Cited by 3
Attention and Working Memory in Human Auditory Cortex
Barton, B., & Brewer, A. A. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.85537 · Cited by 3
The Wiring Economy Principle for Designing Inference Networks
Varshney, L. R. (2013) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2013.130611 · Cited by 3
Neural Maps: Their Function and Development
Bednar, J. A., & Williams, C. K. I. (2016) · Cited by 2
Cajal’s Law of Dynamic Polarization: Mechanism and Design
Barberis, S. (2018) · Philosophies · doi:10.3390/philosophies3020011 · Cited by 3
Enhanced representation of natural sound sequences in the ventral auditory midbrain
González‐Palomares, E., López‐Jury, L., García‐Rosales, F., & Hechavarría, J. C. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02188-2 · Cited by 3
Placement and routing optimization in the brain
Chen, B. L., & Chklovskii, D. B. (2006) · International Symposium on Physical Design · doi:10.1145/1123008.1123034 · Cited by 3
Self-citationSynaptic Rewiring in Neuromorphic VLSI for Topographic Map Formation
Bamford, S. A. (2009) · ERA · Cited by 3
Multi-scale Mining of fMRI data with Hierarchical Structured SparsityPreprint
Jenatton, R., Gramfort, A., Michel, V., Obozinski, G., Eger, E., Bach, F., & Thirion, B. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1105.0363 · Cited by 3
Wiring Principles, Optimization
Kaiser, M., & Hilgetag, C. C. (2015) · Springer eBooks · doi:10.1007/978-1-4614-6675-8_291 · Cited by 3
Neural network coding of natural images with applications to pure mathematics
Hillar, C. J., & Marzen, S. (2017) · Contemporary mathematics - American Mathematical Society · doi:10.1090/conm/685/13814 · Cited by 3
Zhao, A., Nern, A., Koskela, S., Dreher, M., Erginkaya, M., Laughland, C. W., Ludwigh, H., Thomson, A., Hoeller, J., Parekh, R., et al. (2024) · eLife · doi:10.7554/elife.93659 · Cited by 3
Øvsthus, M., van Swieten, M. M. H., Puchades, M. A., Tocco, C., Studer, M., Bjaalie, J. G., & Leergaard, T. B. (2024) · Scientific Data · doi:10.1038/s41597-024-04060-y · Cited by 3
Gao, L., Yang, Z., Zhou, Y., Yang, J., Luo, Q., Feng, R., Ou, K., Feng, R., & Lu, S. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121112 · Cited by 2
Kim, H., Xu, C., Washington, C., Shi, C., Lowman, M., & Kebschull, J. M. (2026) · Neuron · doi:10.1016/j.neuron.2026.05.005 · Cited by 6
Тонг, Л., Xie, Y., & Yu, H. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2016.10.014 · Cited by 2
Motifs, Small Worlds, and Network Economy
(2016) · Elsevier eBooks · doi:10.1016/b978-0-12-407908-3.00008-x · Cited by 2
No-reference Stereoscopic Image Quality Assessment Based on Parallel Multi-scale Perception
Zhang, Z., & Li, S. (2022) · IEEE International Conference on Visual Communications and Image Processing (VCIP) · doi:10.1109/vcip56404.2022.10008875 · Cited by 2
Cortical field maps across human sensory cortex
Brewer, A. A., & Barton, B. (2023) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2023.1232005 · Cited by 4
Marzen, S. (2025) · Interface Focus · doi:10.1098/rsfs.2024.0062 · Cited by 4
The invariance hypothesis and the ventral stream
Leibo, J. Z. (2014) · Cited by 2
Self-Organization of Object Categories in a Cortical Artificial Model
Plebe, A. (2011) · InTech eBooks · doi:10.5772/13291 · Cited by 2
Cohen, D., & Papliński, A. P. (2012) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2012.6252815 · Cited by 2
Temporal information as top-down context in binocular disparity detection
Solgi, M., & Weng, J. (2009) · IEEE International Conference on Development and Learning (ICDL) · doi:10.1109/devlrn.2009.5175533 · Cited by 2
Cloverleaf Clusters: A Common Macrostructural Organization across Human Visual and Auditory Cortex
Brewer, A. A., & Barton, B. (2018) · InTech eBooks · doi:10.5772/intechopen.77964 · Cited by 2
Wiring optimization explanation in neuroscience: What is special about it?
Barberis, S. D. (2019) · THEORIA An International Journal for Theory History and Foundations of Science · doi:10.1387/theoria.18148 · Cited by 2
Cortical communication and the comparison of colors
Mollon, J., & Danilova, M. (2019) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2019.10.002 · Cited by 3
Wiring Principles, Optimization
Kaiser, M., & Hilgetag, C. C. (2014) · Springer eBooks · doi:10.1007/978-1-4614-7320-6_291-2 · Cited by 2
Dynamic Adaptation in Fly Motion Vision
Flanagin, V. L. (2006) · Elektronische Hochschulschriften der LMU München (Ludwig-Maximilians-Universität München) · doi:10.5282/edoc.5980 · Cited by 2
Massé, I. O., Blanchet-Godbout, S., Bronchti, G., & Boire, D. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/514414 · Cited by 2
Pattern selection in the visual cortex
Kaschube, M. (2006) · doi:10.53846/goediss-2890 · Cited by 2
Functional organization of mouse auditory cortex in response to stimulus complexity and brain statePreprint
Afrashteh, N., Jafari, Z., Sun, J., Kyweriga, M., & Mohajerani, M. H. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.11.503675 · Cited by 2
The evolution of lossy compression
Marzen, S., & DeDeo, S. (2017) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0166 · Cited by 49
Self-Organizing Temporally Coded Representation Learning
Fois, A., & Girau, B. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-44207-0_35 · Cited by 1
Distinct Neural Mechanisms of Visual and Sound Adaptation in the Cat Visual Cortex
Belkacemi, Y. Y., Mokhtarinejad, E., Chanauria, N., Flouty, O. E., Molotchnikoff, S., & Bharmauria, V. (2025) · European Journal of Neuroscience · doi:10.1111/ejn.70253 · Cited by 1
A topographical organization in the primary olfactory cortex
Taragin, S., Bashan, O., Dalal, T., Belelovsky, K., & Haddad, R. (2026) · Nature Communications · doi:10.1038/s41467-026-70356-9 · Cited by 1
Multiagent Learning Through Indirect Encoding
D’Ambrosio, D. B. (2011) · Journal of International Crisis and Risk Communication Research · Cited by 1
Multimap formation in visual cortex
Jain, R., Millin, R., & Mel, B. W. (2015) · Journal of Vision · doi:10.1167/15.16.3 · Cited by 1
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 ›
Are you an author, or do you see a problem with this page? Request a review