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CORTICAL PLASTICITY: From Synapses to Maps
Abstract
It has been clear for almost two decades that cortical representations in adult animals are not fixed entities, but rather, are dynamic and are continuously modified by experience. The cortex can preferentially allocate area to represent the particular peripheral input sources that are proportionally most used. Alterations in cortical representations appear to underlie learning tasks dependent on the use of the behaviorally important peripheral inputs that they represent. The rules governing this cortical representational plasticity following manipulations of inputs, including learning, are increasingly well understood. In parallel with developments in the field of cortical map plasticity, studies of synaptic plasticity have characterized specific elementary forms of plasticity, including associative long-term potentiation and long-term depression of excitatory postsynaptic potentials. Investigators have made many important strides toward understanding the molecular underpinnings of these fundamental plasticity processes and toward defining the learning rules that govern their induction. The fields of cortical synaptic plasticity and cortical map plasticity have been implicitly linked by the hypothesis that synaptic plasticity underlies cortical map reorganization. Recent experimental and theoretical work has provided increasingly stronger support for this hypothesis. The goal of the current paper is to review the fields of both synaptic and cortical map plasticity with an em…
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“These theoretical predictions are entirely consistent with empirical and computational characterisations of plasticity [56],[57].”
From Hierarchical Models in the Brain (2008) · cites this paper as [56]
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Fushiki, A., Kohsaka, H., & Nose, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0062199 · Cited by 45
“Does sensory feedback also play a role in the development of the motor system? Sensory experience plays critical roles in the development of the sensory systems [4].”
Reports of intimate touch: Erogenous zones and somatosensory cortical organization
Turnbull, O. H., Lovett, V. E., Chaldecott, J., & Lucas, M. (2013) · Cortex · doi:10.1016/j.cortex.2013.07.010 · Cited by 42
“…in S1 can be dynamic and even ‘fuzzy’, with many reports of plasticity in S1, including changes following practise or sensory restriction (e.g., Buonomano & Merzenich, 1998; Candia, Wienbruch, Elbert, Rockstroh, & Ray, 2003; Donoghue, 1995), or changes as part of the phantom limb phenomenon…”
From cortical modules to memories
Rowland, D. C., & Moser, M. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.08.012 · Cited by 40
Wehman, P., Gentry, T., West, M. D., & Arango‐Lasprilla, J. C. (2009) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2008.08.0105 · Cited by 41
Multiscale mapping of frequency sweep rate in mouse auditory cortex
Issa, J. B., Haeffele, B. D., Young, E. D., & Yue, D. T. (2016) · Hearing Research · doi:10.1016/j.heares.2016.11.018 · Cited by 41
Visual illusion of tool use recalibrates tactile perception
Miller, L. E., Longo, M. R., & Saygın, A. P. (2017) · Cognition · doi:10.1016/j.cognition.2017.01.022 · Cited by 41
“…underlie the observed recalibration of body representation, perhaps by modulating receptive field properties of SI neurons through changes in intracortical inhibition (Cardini, Longo, & Haggard, 2011), a mechanism that commonly drives experiencedependent plasticity (Buonomano & Merzenich, 1998).”
BackgroundNeurorepair versus Neuroprotection in Stroke
Hurtado, O., Pradillo, J. M., Alonso‐Escolano, D., Lorenzo, P., Sobrino, T., Castillo, J., Lizasoaín, I., & Moro, M. Á. (2006) · Cerebrovascular Diseases · doi:10.1159/000091704 · Cited by 41
Forming classes by stimulus frequency: Behavior and theory
Rosenthal, O., Fusi, S., & Hochstein, S. (2001) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.071525998 · Cited by 44
Garraghty, P. E., Arnold, L. L., Wellman, C. L., & Mowery, T. M. (2006) · The Journal of Comparative Neurology · doi:10.1002/cne.21018 · Cited by 41
Palagina, G., Eysel, U. T., & Jancke, D. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900068106 · Cited by 41
Angulo, M. C., Staiger, J. F., Rossier, J., & Audinat, É. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00750.2002 · Cited by 41
Rapid emergence of latent knowledge in the sensory cortex drives learning
Drieu, C., Zhu, Z., Wang, Z., Fuller, K., Wang, A., Elnozahy, S., & Kuchibhotla, K. V. (2025) · Nature · doi:10.1038/s41586-025-08730-8 · Cited by 45
“This model posits that individual neurons, via changes in sensory tuning, and neural populations, via cortical map expansion, enhance the representation of behaviourally relevant cues for use by downstream regions 27,28 .”
Carpenter‐Hyland, E. P., Plummer, T. K., Vazdarjanova, A. I., & Blake, D. T. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1008604107 · Cited by 39
“Dominant models of this plasticity are activity-dependent (2, 7, 8), and associated learning is presumed to be a function of endogenous processes reliant on gene activation, because long-term plasticity and long-termmemory require protein synthesis (9) following expression of immediate-early genes such as Arc (10, 11).”
BackgroundUnifying practice schedules in the timescales of motor learning and performance
Verhoeven, F. M., & Newell, K. M. (2018) · Human Movement Science · doi:10.1016/j.humov.2018.04.004 · Cited by 42
Role of Insulin-Like Growth Factors in Neuronal Plasticity and Neuroprotection
Torres‐Alemán, I. (2005) · Advances in experimental medicine and biology · doi:10.1007/0-387-26274-1_10 · Cited by 40
Representations of odors in the rat orbitofrontal cortex change during and after learning.
Alvarez, P., & Eichenbaum, H. (2002) · Behavioral Neuroscience · doi:10.1037/0735-7044.116.3.421 · Cited by 40
Metadata
- Authors
- Buonomano, D. V., & Merzenich, M. M.
- Affiliations
- University of California, Los Angeles (US)
- University of California, San Francisco (US)
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 1998-03
- Volume
- 21
- Issue
- 1
- Pages
- 149-186
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2158935809
- Cited by
- 2,083
- References
- 192
- Citations by year
- 2026: 21 · 2025: 27 · 2024: 43 · 2023: 40 · 2022: 45 · 2021: 58 · 2020: 49 · 2019: 73 · 2018: 67 · 2017: 61 · 2016: 61 · 2015: 78 · 2014: 72 · 2013: 95 · 2012: 98
- FWCI
- 8.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Public Health Service (10414)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- cortical plasticity, synaptic plasticity, long-term potentiation, long-term depression, excitatory postsynaptic potentials, learning rules
- MeSH terms
- Animals, Brain Mapping, Cerebral Cortex, Neuronal Plasticity, Synapses
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