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.
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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]
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
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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-citation
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
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- Chklovskii, D. B., & Koulakov, A. A. (2004). MAPS IN THE BRAIN: What Can We Learn from Them? Annual Review of Neuroscience. https://doi.org/10.1146/annurev.neuro.27.070203.144226
