The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning
Open accessAbstract
Motor skill learning induces long-lasting reorganization of dendritic spines, principal sites of excitatory synapses, in the motor cortex. However, mechanisms that regulate these excitatory synaptic changes remain poorly understood. Here, using in vivo two-photon imaging in awake mice, we found that learning-induced spine reorganization of layer (L) 2/3 excitatory neurons occurs in the distal branches of their apical dendrites in L1 but not in the perisomatic dendrites. This compartment-specific spine reorganization coincided with subtype-specific plasticity of local inhibitory circuits. Somatostatin-expressing inhibitory neurons (SOM-INs), which mainly inhibit distal dendrites of excitatory neurons, showed a decrease in axonal boutons immediately after the training began, whereas parvalbumin-expressing inhibitory neurons (PV-INs), which mainly inhibit perisomatic regions of excitatory neurons, exhibited a gradual increase in axonal boutons during training. Optogenetic enhancement and suppression of SOM-IN activity during training destabilized and hyperstabilized spines, respectively, and both manipulations impaired the learning of stereotyped movements. Our results identify SOM inhibition of distal dendrites as a key regulator of learning-related changes in excitatory synapses and the acquisition of motor skills.
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A pyramid approach to subpixel registration based on intensity
Thevenaz, P., Ruttimann, U. E., & Unser, M. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.650848 · Cited by 3,078
Imaging Neuronal Subsets in Transgenic Mice Expressing Multiple Spectral Variants of GFP
Feng, G., Mellor, R. H., Bernstein, M., Keller-Peck, C., Nguyen, Q. T., Wallace, M., Nerbonne, J. M., Lichtman, J. W., & Sanes, J. R. (2000) · Neuron · doi:10.1016/s0896-6273(00)00084-2 · Cited by 3,042
Interneurons of the neocortical inhibitory system
Markram, H., Toledo-Rodriguez, M., Wang, Y., Gupta, A., Silberberg, G., & Wu, C. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1519 · Cited by 2,954
Critical period plasticity in local cortical circuits
Hensch, T. K. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1787 · Cited by 2,323
Experience-dependent structural synaptic plasticity in the mammalian brain
Holtmaat, A., & Svoboda, K. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2699 · Cited by 1,934
A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex
Taniguchi, H., He, M., Wu, P., Kim, S., Paik, R., Sugino, K., Kvitsani, D., Fu, Y., Lu, J., Lin, Y., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.07.026 · Cited by 1,828
Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons
Rudy, B., Fishell, G., Lee, S., & Hjerling‐Leffler, J. (2011) · Developmental Neurobiology · doi:10.1002/dneu.20853 · Cited by 1,420
Nudo, R., Milliken, G., Jenkins, W., & Merzenich, M. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-02-00785.1996 · Cited by 1,413
Pfeffer, C. K., Xue, M., He, M., Huang, Z. J., & Scanziani, M. (2013) · Nature Neuroscience · doi:10.1038/nn.3446 · Cited by 1,353
Plasticity and Primary Motor Cortex
Sanes, J. N., & Donoghue, J. P. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.393 · Cited by 1,202
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Metadata
- Authors
- Chen, S. X., Kim, A. N., Peters, A. J., & Komiyama, T.
- Venue
- Nature Neuroscience
- Published
- 2015-06-22
- Volume
- 18
- Issue
- 8
- Pages
- 1109-1115
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W808307776
- Cited by
- 321
- References
- 47
- FWCI
- 12.10
- Type
- journal article
- Language
- en
- Open access
- green
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