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. 2019 Jul;22(7):1122-1131.
doi: 10.1038/s41593-019-0407-2. Epub 2019 May 27.

Emergent Modular Neural Control Drives Coordinated Motor Actions

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Free PMC article

Emergent Modular Neural Control Drives Coordinated Motor Actions

Stefan M Lemke et al. Nat Neurosci. .
Free PMC article

Abstract

A remarkable feature of motor control is the ability to coordinate movements across distinct body parts into a consistent, skilled action. To reach and grasp an object, 'gross' arm and 'fine' dexterous movements must be coordinated as a single action. How the nervous system achieves this coordination is currently unknown. One possibility is that, with training, gross and fine movements are co-optimized to produce a coordinated action; alternatively, gross and fine movements may be modularly refined to function together. To address this question, we recorded neural activity in the primary motor cortex and dorsolateral striatum during reach-to-grasp skill learning in rats. During learning, the refinement of fine and gross movements was behaviorally and neurally dissociable. Furthermore, inactivation of the primary motor cortex and dorsolateral striatum had distinct effects on skilled fine and gross movements. Our results indicate that skilled movement coordination is achieved through emergent modular neural control.

Conflict of interest statement

Competing Interests

The authors declare no competing interests.

Figures

Figure 1.
Figure 1.. Refinement of skilled fine and gross movements is dissociable during reach-to-grasp skill learning.
a. Diagram of skilled reach-to-grasp task and measures of learning including duration from movement onset (MO) to pellet touch (PT), duration from movement onset to retract onset (RO), forearm trajectory correlation, and success rate. b. Example time course of learning (dots represent individual trials, lines are averaged over 30 trials; forearm trajectories are shown from day one and day eight, individual trial trajectories in grey and mean trajectory in yellow). c. Difference in reach duration, sub-movement timing variability, forearm trajectory correlation, and success rate between day one (D1) and day eight (D8) of training in learning cohort (n = 4 animals), and performance from an extended training cohort (EXT; n = 3 animals). Grey lines represent individual animals from learning cohort on day one and day eight, grey dots represent individual animals in extended training cohort, and black lines represent mean and SEM across animals. P values are from mixed-effects models. d. Differences in reach duration, sub-movement timing variability, and forearm trajectory correlation between successful (Suc.) and unsuccessful (Unsuc.) trials on days 5–8 (n = 4 animals). Grey lines represent mean values from each animal in learning cohort and black lines represent mean and SEM across animals. P values are from mixed-effects models.
Figure 2.
Figure 2.. Coordinated movement-related activity emerges across M1 and DLS during skill learning.
a. Diagram of emerging low-frequency dynamics across forearm speed profile, neural activity in M1 and DLS, and forearm muscle activity during reach-to-grasp skill learning. Top: Illustration of recoding scheme and example time course of learning for duration from movement onset to retract onset (gray) and movement onset to pellet touch (blue; dots represent individual trials, lines are averaged over 30 trials). Middle: Forearm speed profiles for all trials on day one and day eight with timing of pellet touch (blue dots) and retract onset (grey dots) overlaid for example animal. Bottom: neural activity and forearm muscle activity for representative successful trials from day one and day eight. b. Left: Spectrograms from example M1 and DLS LFP channels. Middle: Mean M1 and DLS LFP power spectrums across animals (n = 4 animals; width denotes mean ± SEM). Right: Difference in 3–6Hz M1 and DLS LFP power from day one to day eight. Grey lines represent mean power from individual animals (n = 4 animals) and black lines represent mean and SEM across animals. P values from mixed-effects models. c. Left: Coherograms from example M1-DLS LFP channel pair. Middle: Mean coherence spectrum across animals (n = 4 animals; width denotes mean ± SEM). Right: Difference in 3–6Hz M1-DLS LFP coherence from day one to day eight. Grey lines represent mean coherence from individual animals (n = 4 animals) and black lines represent mean and SEM across animals. P values from mixed-effects models. d. Top: 3–6Hz filtered LFP from example M1 and DLS channels time locked to sub-movements, individual trials with mean signal overlaid. Bottom: Changes in inter-trial coherence (ITC). Grey lines represent mean inter-trial coherence from individual animals (n = 4 animals) and black lines represent mean and SEM across animals. P values from mixed-effects models.
Figure 3.
Figure 3.. Coordinated spiking activity emerges across M1 and DLS during skill learning.
a. Example Peri-Event Time Histograms (PETH) from units in M1 (left) and DLS (right) displaying multiphasic activity locked to 3–6Hz LFP activity. b. Diagram of spike-LFP phase locking. Top: Raster plot of example M1 unit spiking activity during movement aligned to movement onset (MO). Middle: Example unit PETH with M1 LFP activity overlaid and extracted 3–6Hz LFP phase. Bottom: Polar histogram of LFP phases at which spikes occurred. c. Cumulative density functions of z-statistics for every unit-LFP pair across and within each region (vertical dotted lines denote significance threshold of z-statistic at p<0.05, % of respective unit-LFP pairs greater than threshold noted, lighter color is day one; n = 107 M1 unit-LFP pairs on day one, n = 80 M1 unit-LFP pairs on day eight, n = 54 DLS unit-LFP pairs on day one, n = 47 DLS unit-LFP pairs on day eight). P values from Kolmogorov-Smirnov test. d. Left: PETHs from example unit displaying multiphasic activity and example unit not displaying multiphasic activity and corresponding autocorrelations used for classifying multiphasic (MP; arrows denote “bumps” used for classification, see methods) and non-multiphasic units (Non-MP). Right: Percentage of units in M1 and DLS on day one and day eight that display multiphasic activity. e. Mean cross-correlation between all multiphasic M1 and DLS units on day one (grey; n = 46 cross-correlations) and day eight (blue; n = 104 cross-correlations). Grey and blue lines represent mean deviation across cross-correlations and width of shaded region depicts mean ± SEM).
Figure 4.
Figure 4.. Coordinated M1 and DLS activity is specifically linked to skilled gross movements.
a. Time course of movement-related 3–6Hz LFP coherence from example M1-DLS channel pair over training period overlaid with timing of sub-movements and forearm trajectories from day one and day eight. b. Scatterplots of each session’s mean movement-related 3–6Hz M1-DLS LFP coherence and mean reach duration, sub-movement timing variability, and forelimb trajectory correlation, each normalized per animal (n = 25 sessions across 4 animals; Pearson’s r). c. Filtered LFP (3–6Hz) signals from example M1 and DLS channels for successful and unsuccessful trials on days 5–8, individual trials overlaid with mean signal (left) and difference in M1-DLS LFP coherence for successful and unsuccessful trials on days 5–8 (right; n = 4 animals). Grey lines represent mean coherence from individual animals (n = 4 animals) and black lines represent mean and SEM across animals. P values from mixed-effects model.
Figure 5.
Figure 5.. M1 and DLS inactivation have differential effects on skilled fine and gross movements.
a. Illustration of M1 and DLS muscimol inactivation. b. Illustration of two-position reach-to-grasp task design with a “far” pellet and “close” pellet position. c. Differences in reach duration, sub-movement timing variability, and success rate between trials before muscimol infusion (Baseline), trials after muscimol infusion reaching to the far pellet position (Far), and trials after muscimol infusion reaching to the close pellet position (Close) for M1 infusions (n = 5 sessions across 3 animals; left) and DLS infusions (n = 6 sessions across 5 animals; right). Grey lines represent mean values from individual sessions and black lines represent mean and SEM across sessions. P values from mixed-effects models.
Figure 6.
Figure 6.. DLS inactivation decreases movement-related low-frequency M1 activity.
a. Illustration of DLS muscimol infusion and M1 recording. b. Left: 3–6Hz filtered LFP aligned to movement onset from example M1 channel for trials before and after DLS inactivation, individual trials overlaid with mean signal. Right: Difference in movement-related 3–6Hz LFP power in M1 before and after DLS inactivation (n = 5 sessions across 3 animals). Grey lines represent mean power values from individual sessions and black lines represent mean and SEM across sessions. P values from mixed-effects model. c. Left: PETH from example M1 unit for trials before and after DLS inactivation. Right: Difference in movement-related firing rate before and after DLS inactivation (n = 5 sessions across 4 animals). Grey lines represent mean firing rate across units from individual sessions and black lines represent mean and SEM across sessions. P values from mixed-effects model.
Figure 7.
Figure 7.. Persistent disruption of skilled fine movements after M1 lesion.
a. Illustration of photothrombotic M1 lesion. b. Differences in reach duration, sub-movement timing variability, and success rate between trials before M1 lesion (Pre Lesion), trials during the first reaching session post- lesion (Early Lesion), and trials once a performance plateau had been reached (Late Lesion; n = 5 animals). Grey lines represent mean values from individual animals and black lines represent mean and SEM across animals. P values from mixed-effects models.
Figure 8.
Figure 8.. Skilled fine movement representation in M1.
a. GPFA neural trajectories for trials on day eight for M1 (top) and DLS (bottom) from example animal. b. Illustration of method for calculating deviation from the mean successful template for successful and unsuccessful trials. c. Mean deviation from successful template for successful and unsuccessful trials from 250ms before movement onset to pellet touch, across animals (n = 10 sessions across 4 animals; width depicts mean deviation across sessions ± SEM; * = P<0.05, P value from mixed-effects model w/Bonferroni correction for multiple comparisons).

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