Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning (original) (raw)

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Acknowledgements

We thank C. Levelt (Netherlands Institute for Neuroscience) for the Gephyrin-GFP construct and B. Bloodgood, R. Malinow and members of the Komiyama laboratory for comments and discussions. This work was supported by grants from Japan Science and Technology Agency (PRESTO), Pew Charitable Trusts, Alfred P. Sloan Foundation, David & Lucile Packard Foundation, Human Frontier Science Program, McKnight Foundation, US National Institutes of Health (R01 NS091010A), University of California San Diego Center for Brain Activity Mapping and New York Stem Cell Foundation (NYSCF) to T.K. S.X.C. is a Human Frontier Science Program postdoctoral fellow. A.J.P. is supported by the Neuroplasticity of Aging Training Grant (AG000216). T.K. is a NYSCF-Robertson Investigator.

Author information

Authors and Affiliations

  1. Neurobiology Section, University of California, San Diego, La Jolla, California, USA
    Simon X Chen, An Na Kim, Andrew J Peters & Takaki Komiyama
  2. Center for Neural Circuits and Behavior, University of California, San Diego, La Jolla, California, USA
    Simon X Chen, An Na Kim, Andrew J Peters & Takaki Komiyama
  3. Department of Neurosciences, University of California, San Diego, La Jolla, California, USA
    Simon X Chen, An Na Kim, Andrew J Peters & Takaki Komiyama
  4. Japan Science and Technology Agency, PRESTO, University of California, San Diego, La Jolla, California, USA
    Takaki Komiyama

Authors

  1. Simon X Chen
  2. An Na Kim
  3. Andrew J Peters
  4. Takaki Komiyama

Contributions

S.X.C. and T.K. conceived the project. A.J.P. and T.K. developed the task. A.N.K. performed the PV-IN experiments. A.J.P. performed the in vivo cell-attached recordings. All other experiments were performed by S.X.C. with assistance by A.N.K. S.X.C. and T.K. analyzed the data with assistance from A.J.P. and wrote the manuscript with inputs from A.J.P. and A.N.K.

Corresponding author

Correspondence toTakaki Komiyama.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Low-magnification images of all representative images.

Low magnification images of the representative images for the L1 distal dendrites of L2/3 excitatory neurons in Fig. 2b (a), the L2/3 perisomatic dendrites of L2/3 excitatory neurons in Fig. 2b (b), the L1 distal dendrites in 'Control' in Fig. 7b (c), the L1 distal dendrites in 'ChR2' in Fig. 7b (d), the L1 distal dendrites in 'eNpHR' in Fig. 7b (e), and the L1 distal dendrites in Fig. 6b (red, tdTomato; green, Gephyrin-GFP) (f). The smaller panels are the same as those in the main figures.

Supplementary Figure 2 Dendritic spines and SOM-IN axonal boutons are stable in the hindlimb area during learning.

(a) Mean fractions of successful trials in sessions 7-11, showing that animals used for hindlimb area imaging learned the task similarly to the animals used for forelimb area imaging. (b) Mean of pairwise correlation of rewarded movements in sessions 7-11 in forelimb and hindlimb animals, indicating equivalent levels of learning. (c) Mean normalized density (top) and daily dynamics (bottom) of dendritic spines in distal dendrites in the hindlimb area during learning (n = 5 mice, 166 spines). (d) Mean normalized axonal bouton density (top) and daily dynamics (bottom) of SOM-INs in the hindlimb area during learning (n = 4 mice, 273 boutons). Both spine and bouton densities are stable during learning and do not show learning-related reorganization (spines, P = 0.52; SOM boutons, P = 0.07, 1-way ANOVA). Error bars indicate SEM.

Supplementary Figure 3 Validation of PV- and SOM-IN labeling.

(a) Representative images showing GFP expression in PV or SOM-Cre mouse (left, green) was confined to neurons immunoreactive for PV or SOM (middle, red), respectively. Right panels show merge of two channels. (b) Fractions of GFP cells that co-localized with PV (top, 29/32 cells, n = 3 sections from 3 PV-Cre animals) and SOM (bottom, 45/49 cells, n = 3 sections from 3 SOM-Cre animals).

Supplementary Figure 4 Validation of optogenetic stimulation in ChR2-expressing SOM-INs.

(a) Two-photon image of in vivo targeted cell-attached recording from a SOM-IN in the motor cortex expressing ChR2-tdTomato (red) and a targeting patch pipette (green). (b) Representative traces showing that blue light stimulation (3 Hz, 10 ms/pulse) reliably triggers action potentials in a SOM-IN for the duration of 10 min. (c) Latency to spike from light onset (colors represent cells recorded in different animals, n = 15 cells from 5 mice, Median ± SD). (d) SOM-INs expressing ChR2-tdTomato were imaged on Days 1, 5, and 11 while blue light stimulation was delivered every day for 11 days (3 Hz, 10 ms/pulse, 30 min/day). Arrows indicate tracked cells. (e) Most of SOM-INs were identified throughout the course of the experiment (77/80 neurons remained on Day 11, n = 4 imaging areas in 3 mice), indicating that optogenetic stimulation for 11 sessions does not kill ChR2-expressing SOM-INs. Grey, individual imaging area; black, mean. Error bars indicate SEM.

Supplementary Figure 5 Training-induced spine reorganizations are distributed across most branches.

(a) Length of individual dendritic branches analyzed in ‘No Training’ (n = 23 branches from 5 mice, data from Supplementary Fig. 6), ‘Control’ (n = 29 branches from 5 mice, data from Fig. 7), and ‘ChR2’ (n = 35 branches from 5 mice, data from Fig. 7). Branches analyzed in all 3 groups have similar length (P = 0.06, 1-way ANOVA). Box plot represents the median (dark line), quartiles (25% - 75% quantiles, white box), and data range (dashed lines). (b) Frequency of spine changes on separate dendritic branches. ‘Control’ and ‘ChR2’ groups showed more branches with spine changes (P<0.001, chi square test with Bonferroni correction) and more changes within each branch compared to ‘No Training’ (P<0.01, 1-way ANOVA with post hoc Tukey's test).

Supplementary Figure 6 Controls for the ChR2 and eNpHR experiments.

(a) Mean normalized spine density (top) and daily dynamics (bottom) of mice expressing ChR2 in SOM-INs. ‘(-) Training / (-) Stimulation) mice were water restricted and handled but not trained (n = 5 mice, 191 spines). ‘(+) Training / (-) Stimulation) mice were trained without blue light stimulation (n = 5 mice, 316 spines), ‘(+) Training / (+) Stimulation) mice received both training and blue light stimulation (n = 5 mice, 255 spines, same data as Fig. 7), and ‘(-) Training / (+) Stimulation) mice received blue light stimulation without training (n = 5 mice, 180 spines). ChR2 expression alone does not block learning-related spine density increase (P<0.001, ‘(+) Training / (-) Stimulation), 1-way ANOVA; P<0.001, ‘(+) Training / (-) Stimulation) vs. ‘(+) Training / (+) Stimulation); _P_=0.19, ‘(+) Training / (-) Stimulation) vs. (Control, data in Fig. 7), 2-way ANOVA with post hoc Tukey's test). SOM-IN activation alone does not affect spine density (P = 0.24, ‘(-) Training / (+) Stimulation) vs. ‘(-) Training / (-) Stimulation), 2-way ANOVA with post hoc Tukey's test). (b) Mean normalized spine density (top) and daily dynamics (bottom) of mice expressing ChR2 in PV-INs. ‘(+) Training / (+) Stimulation), n = 5 mice, 198 spines. ‘(-) Training / (+) Stimulation), n = 5 mice, 277 spines. Mild activation of PV-INs during learning with the same stimulation protocol as SOM-INs (3 Hz, 10 ms/pulse) does not block learning-related spine density increase (P<0.001, ‘PV-ChR2 (+) Training / (+) Stimulation), 1-way ANOVA; P<0.001, (PV-ChR2 (+) Training / (+) Stimulation) vs. (SOM-ChR2 (+) Training / (+) Stimulation); _P_=0.08, (PV-ChR2 ‘(+) Training / (+) Stimulation)( vs. (Control, data in Fig. 7), 2-way ANOVA with post hoc Tukey's test). (c) Mean normalized spine density (top) and daily dynamics (bottom) of mice expressing eNpHR in SOM-INs. ‘(+) Training / (+) Stimulation), n = 6 mice, 397 spines, same data as Fig. 7. ‘(-) Training / (+) Stimulation), n = 4 mice, 192 spines. Inactivating SOM-INs without training does not increase spine density (P = 0.97, ‘SOM-eNpHR (-) Training / (+) Stimulation), 1-way ANOVA; P = 0.77, ‘SOM-eNpHR (-) Training / (+) Stimulation) vs. ‘SOM-ChR2 (-) Training / (-) Stimulation), 2-way ANOVA with post hoc Tukey's test). (d) Training consistently induced spine formation in the first 3 sessions in all trained groups. ***P<0.001, 1-way ANOVA with post hoc Tukey's test compared to ‘SOM-ChR2 (-) Training / (-) Stimulation). (e) Behavioral performance showing that ‘SOM-ChR2 (+) Training / (-) Stimulation) and ‘PV-ChR2 (+) Training / (+) Stimulation) animals learned the task, achieving rewards in most trials and developing stereotyped movement. Left, mean fractions of successful trials in sessions 7-11. P = 0.63, 1-way ANOVA. Right, mean of pairwise correlation of rewarded movements in sessions 7-11. P = 0.14, 1-way ANOVA. The (Control) group is the same data as in Fig. 8. Error bars indicate SEM.

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Chen, S., Kim, A., Peters, A. et al. Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning.Nat Neurosci 18, 1109–1115 (2015). https://doi.org/10.1038/nn.4049

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