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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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Self-citationNeuronal structural remodeling: is it all about access?
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“The long term nature of structural changes make them particularly attractive as cellular substrates for persistent changes in connectivity, such as might be required for learning and memory [1] or changes in cortical map representation [2].”
BackgroundHeimler, B., & Amedi, A. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.06.034 · Cited by 70
“Specifically, accumulating evidence highlighted that the human adult brain still retains a considerable amount of plasticity (Buonomano and Merzenich, 1998; Draganski and May, 2008; Recanzone et al., 1992, 1993; Reetzke et al., 2018; Thomas and Baker, 2013).”
BackgroundIntrinsic excitability mechanisms of neuronal ensemble formation
Alejandre-García, T., Kim, S., Pérez-Ortega, J., & Yuste, R. (2022) · eLife · doi:10.7554/elife.77470 · Cited by 69
“…(Lisman et al., 2018; Marder and Goaillard, 2006; Pérez-Ortega et al., 2021; Pignatelli et al., 2019; Xu, 2005) and to the generation of intrinsic circuit states, such as for ensembles and circuit attractors (Buzsáki, 2010; Carrillo-Reid et al., 2019, 2016; Hopfield, 1982; Miller et al., 2014).”
BackgroundShort-term variations in response distribution to cortical stimulation
Lesser, R. P., Lee, H. W., Webber, W. R., Prince, B., Crone, N. E., & Miglioretti, D. L. (2008) · Brain · doi:10.1093/brain/awn044 · Cited by 69
“…patterns we found seem best explained by alterations in neuronal excitability or refractory periods, in synaptic strengths of existing connections (Buonomano and Merzenich, 1998; Abbott and Regehr, 2004; Chklovskii et al., 2004), or in the functional state of the network as a whole (Buonomano and…”
InfluentialPlasticity of the cochleotopic (frequency) map in specialized and nonspecialized auditory cortices
Sakai, M., & Suga, N. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.061021698 · Cited by 68
Effects of processing speed training on cognitive functions and neural systems
Takeuchi, H., & Kawashima, R. (2012) · Reviews in the Neurosciences · doi:10.1515/revneuro-2012-0035 · Cited by 67
Diniz, C. R. A. F., & Crestani, A. P. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01931-x · Cited by 77
“Similarly, based on Wilder Penfield works that showed a motor and sensory cortical representation of the body [6], Michael Merzenich noted that the adult brain is actually a dynamic structure, with the cortical body representations constantly shifting its boundaries [7].”
BackgroundDinse, H. R., Kalisch, T., Ragert, P., Pleger, B., Schwenkreis, P., & Tegenthoff, M. (2005) · ACM Transactions on Applied Perception · doi:10.1145/1060581.1060583 · Cited by 70
Presynaptic Gating of Postsynaptically Expressed Plasticity at Mature Thalamocortical Synapses
Blundon, J. A., Bayazitov, I. T., & Zakharenko, S. S. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3281-11.2011 · Cited by 69
“Cortical receptive fields (RFs) are formed by organized arrays of thalamocortical (TC) afferents projecting onto neurons in thalamorecipient layers of the cortex (Buonomano and Merzenich, 1998; Feldman and Brecht, 2005; Hensch, 2005; Liu et al., 2007).”
BackgroundLoss and recovery of voluntary hand movements in the macaque following a cervical dorsal rhizotomy
Darian‐Smith, C., & Ciferri, M. (2005) · The Journal of Comparative Neurology · doi:10.1002/cne.20686 · Cited by 67
Breton, J., & Stuart, G. J. (2009) · The Journal of Physiology · doi:10.1113/jphysiol.2009.180943 · Cited by 67
“…to investigate such experience-dependent changes in cortical development (Fox, 1992), with previous work indicating that somatosensory maps are highly malleable both during brain development (Van der Loos & Woolsey, 1973; Simons & Land, 1987) and in the adult animal (Buonomano & Merzenich, 1998).”
BackgroundToyoda, H., Zhao, M., Ulzhöfer, B., Wu, L., Xu, H., Seeburg, P. H., Sprengel, R., Kuner, R., & Zhuo, M. (2009) · Molecular Pain · doi:10.1186/1744-8069-5-46 · Cited by 69
“The SSC plays a central role in the processing of sensory inputs, and developmental- or pathology-associated activity-dependent changes in the SSC have been hypothesized to underlie plastic changes in sensory discrimination in vivo [33-35].”
BackgroundEffects of a spaceflight analog environment on brain connectivity and behavior
Cassady, K. E., Koppelmans, V., Reuter‐Lorenz, P. A., Dios, Y. E. D., Gadd, N. E., Wood, S. J., Riascos, R., Kofman, I. S., Bloomberg, J. J., Mulavara, A. P., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.029 · Cited by 74
Disturbance of neuronal plasticity is a critical pathogenetic event in Alzheimer's disease
Arendt, T. (2001) · International Journal of Developmental Neuroscience · doi:10.1016/s0736-5748(01)00007-7 · Cited by 66
Mierau, S. B., Meredith, R. M., Upton, A. L., & Paulsen, O. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402916101 · Cited by 67
Synaptic Plasticity and Filtering Emulated in Metal–Organic Frameworks Nanosheets Based Transistors
Ding, G., Yang, B., Zhou, K., Zhang, C., Wang, Y., Yang, J., Han, S., Zhai, Y., Roy, V. A. L., & Zhou, Y. (2019) · Advanced Electronic Materials · doi:10.1002/aelm.201900978 · Cited by 64
Culture and education: new frontiers in brain plasticity
Ansari, D. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.11.016 · Cited by 77
Evaluating dedicated and intrinsic models of temporal encoding by varying context
Spencer, R. M. C., Karmarkar, U. R., & Ivry, R. B. (2009) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2009.0024 · Cited by 68
“Temporal processing of intervals limited to just a few hundred milliseconds is certainly important for many tasks; for example, most of the critical temporal cues in speech perception are less than 100 ms (see Buonomano & Merzenich 1998).”
BackgroundNEUROBIOLOGY OF ANXIETY: FROM NEURAL CIRCUITS TO NOVEL SOLUTIONS?
Etkin, A. (2012) · Depression and Anxiety · doi:10.1002/da.21957 · Cited by 71
Perceptual Learning of Contrast Detection in the Human Lateral Geniculate Nucleus
Yu, Q., Zhang, P., Qiu, J., & Fang, F. (2016) · Current Biology · doi:10.1016/j.cub.2016.09.034 · Cited by 66
“In the visual system, adult plasticity is largely believed to be restricted to the cortex, with subcortical structures losing their capacity for change after a critical period of development [3, 4].”
Cortical processing of temporal modulations
Wang, X., Lu, T., & Li, L. (2003) · Speech Communication · doi:10.1016/s0167-6393(02)00097-3 · Cited by 66
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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