The basal ganglia are known to influence action selection and modulation of movement vigor, but whether and how they contribute to specifying the kinematics of learned motor skills is not understood. Here, we probe this question by recording and manipulating basal ganglia activity in rats trained to generate complex task-specific movement patterns with rich kinematic structure. We find that the sensorimotor arm of the basal ganglia circuit is crucial for generating the detailed movement patterns underlying the acquired motor skills. Furthermore, the neural representations in the striatum, and the control function they subserve, do not depend on inputs from the motor cortex. Taken together, these results extend our understanding of the basal ganglia by showing that they can specify and control the fine-grained details of learned motor skills through their interactions with lower-level motor circuits.
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The generated datasets are available from the corresponding author upon reasonable request.
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We thank S. Escola, J. Murray and members of the Ölveczky Lab for advice on data analyses and for discussions and comments on the manuscript. We thank S. Turney and the Harvard Center for Biological Imaging for infrastructure and support. We thank A. Mathis and M. Mathis for help with setting up markerless tracking. This work was supported by NIH grants R01-NS099323-01 and R01-NS105349 to B.P.Ö., by a Life Sciences Research Foundation and Charles A. King Foundation postdoctoral fellowship to A.K.D., and by EMBO (ALTF1561-2013) and HFSP (LT 000514/2014) postdoctoral fellowships to S.B.E.W. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
The authors declare no competing interests.
Peer review information Nature Neuroscience thanks the anonymous reviewers for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Striatal subdivisions, recording sites and extent of lesions.
a, Virally-mediated fluorescent labeling of axons originating in either motor cortex (MC) or prefrontal cortex (PFC) to determine the outlines of the MC-recipient dorsolateral striatum (DLS) and of the PFC-recipient dorsomedial striatum (DMS), respectively. Based on the distinct projection patterns we estimated the extent of the DLS and DMS, respectively, along the anterior-posterior axis of the striatum. b, DLS/DMS outlines, recording sites and lesion extents. The outlines of the DLS and DMS determined in a along the anterior-posterior axis are indicated by red and green lines, respectively. Locations of recording electrode implantation sites in DLS and DMS are marked with arrowheads. Numbers indicate individual animals. For some animals several recording locations were determined, due to individual tetrode bundles of our recording arrays spreading apart during implantation. The extents of MC lesions in three recorded animals are marked in different shades of grey for individual animals and the dotted lines indicate the area in MC targeted for lesions. The extents of the DLS and DMS lesions are marked as shaded red and green areas, respectively. Lighter areas indicate the extent of the largest lesion across animals at a given anterior-posterior position, darker areas indicate the extent of the smallest lesion. Blue dotted lines indicate the target area for PFC tracing injections.
Extended Data Fig. 2 Classification of striatal units and statistics of task-aligned FSI activity in DLS and DMS.
a, Classification of single units recorded in striatum into putative spiny projection neurons (SPNs, maroon) and fast spiking interneurons (FSIs, blue). (Left) Spike waveform features such as peak-width and peak-to-valley interval, as well as average firing rates were used in combination to classify units as SPNs or FSIs. Grey dots indicate unclassified units (8.5%) that were excluded from further analysis. (Right) Population averaged spike waveforms for putative SPNs (top) and FSIs (bottom). Data presented as the mean ± s.d. across units. All waveforms were rescaled to unit amplitude prior to averaging. b, Average firing rate during the trial-period (P = 3 × 10−3), maximum modulation of Z-scored firing rate during the trial-period (P = 0.01), sparseness index (P = 0.13) and average trial-to-trial correlation of task-aligned spiking (P = 1 × 10−3) in putative FSIs recorded in the DLS (red, n = 171) and DMS (green, n = 138). Bars and error-bars represent mean and s.e.m., respectively, across units. P values measure the two-sided probability that two datasets have the same mean and are computed by bootstrapping difference in the means (n = 1 × 104 resamples).
Extended Data Fig. 3 Population-averaged activity in the DLS at the beginning and end of the skilled behavior.
a, Average Z-scored activity of putative SPN (top) or FSI (bottom) populations recorded in the DLS around the time of the 1st (solid line) and 2nd (dashed lined) lever-presses (n = 3 rats). Grey shading represents 95% confidence interval, corrected for multiple comparisons, of the distribution of Z-scored activity expected by chance if lever-presses occurred at random times (n = 1 × 104 randomizations). b, Trial-to-trial variability of an example rat’s task-aligned movement trajectories. (Top) Trajectories of the rat’s forelimb (vertical component) in an example session corresponding to a specific sequence mode (see Extended Data Fig. 4). Each line denotes a trial. (Bottom) Normalized trial-by-trial variability (see Methods) of movement trajectories of the rat’s forelimbs and head. Times at which this measure exceeds a value of 2 (dashed lines) are designated the start or stop time of the motor sequence. On average, starts occurred 0.42 ± 0.46 s prior to the first lever-press and stops occurred at 0.35 ± 0.02 s after the second lever-press (mean ± s.d., n = 3 rats). c, Average Z-scored activity for populations of SPNs (top) or FSIs (bottom) recorded in the DLS around the start (solid line) and stop (dashed lined) of the skilled behavior (n = 3 rats). Grey shading represents 95% confidence interval, corrected for multiple comparisons, of the distribution of Z-scored activity expected by chance if start/stop occurred at random times (n = 1 × 104 randomizations). d, Average Z-scored activity for populations of SPNs recorded in the DLS of three example rats during execution of a representative sequence mode (red lines). Superimposed are trial-averaged forelimb speed profiles (black, averaged over both contra- and ipsi-lateral forelimbs), from the same individuals. e, Non-uniformity of the average Z-scored activity profiles of DLS SPNs, measured by their s.d., was averaged across sequence modes and then across rats (red line, n = 3 rats). Grey histogram shows distribution expected by chance if SPNs showed independent activity (generated by randomly jittering the Z-scored PETHs of individual units prior to averaging, n = 1 × 104 randomizations), and P value quantifies the two-sided probability that this explains the data. h, Correlation coefficient between average speed profiles and average activity of DLS SPN populations (both shown in panel d), averaged across sequences modes and then across rats (red line, n = 3 rats). Grey histogram shows the statistic distribution under the null hypothesis (no relationship between the variables) computed by randomization (n = 1 × 104 permutations), and P value quantifies the two-sided probability that this explains the data.
Extended Data Fig. 4 Identification of sequence modes and population-averaged activity in the DLS at choice points between modes.
a, Two-dimensional t-distributed stochastic neighborhood embedding (tSNE) of task-aligned kinematic trajectories for a subset of trials from an example rat. Each point represents a trial and colors represent distinct modes identified by a semi-automated unsupervised clustering algorithm (see Methods). On average we identified 5 ± 2 modes (mean ± s.d.) per rat (n = 9 rats). b, Task-aligned horizontal and vertical components of the position and velocity of a single forelimb averaged across trials within each sequence mode shown in panel a. Shading represents s.d. across trials. c, Task-aligned kinematic variables including forelimb position (left) and velocity (right) for a random subset of 20,000 trials performed by the example rat, sorted by sequence mode (indicated by colors, as in panels a–b). Kinematics have been time-warped to account for trial-by-trial variability in the interval between the 1st and 2nd lever-presses. d, Pairwise correlations between the kinematics of the trials shown in c, sorted by sequence mode. e, Average Z-scored activity for populations of SPNs (top) or FSIs (bottom) recorded in the DLS around the time of choice-points (left) or at peak discriminability between the trajectories corresponding to pairs of modes (right). Z-scored activity is averaged across units and modes in a mode pair, then across all mode-pairs in each rat and then across rats (n = 3 rats). Grey shading represents 95% confidence interval, corrected for multiple comparisons, of the distribution of Z-scored activity expected by chance if these events occurred at random times (n = 1 × 104 randomizations).
Extended Data Fig. 5 Comparison between encoding of different kinematic features by striatal neurons.
a, Scatter plots comparing the goodness of fit, measured using the pseudo-R2 (see Methods), between encoding models that use a combination of all kinematic variables (position, velocity and acceleration) versus those that use only position (left), velocity (middle) or acceleration (right) variables to predict the activity of DLS SPNs (top) and FSIs (bottom). P < 1 × 10−4 for all SPN kinematic comparisons and P = 4 × 10−3, < 1 × 10−4, < 1 × 10−4 for FSI kinematic encoding comparisons to position, velocity and acceleration variables, respectively. P values are computed by bootstrapping the paired difference in means (n = 1 × 104 resamples) and quantify the likelihood that two distributions have the same mean. b, Goodness of fit, measured by pseudo-R2 (see Methods), for encoding models that use detailed kinematics (position, velocity and acceleration) of all tracked effectors and those that only use kinematics of the contralateral forelimb, ipsilateral forelimb, both forelimbs or the head to predict spiking activity of putative SPNs (left) and FSIs (right) in the DLS (red, n = 492 SPNs and 164 FSIs from 3 rats) and DMS (green, n = 213 SPNs and 123 FSIs from 3 rats). Boxes denote 1st, 2nd (median) and 3rd quartiles, while whiskers show the 5th and 95th percentile of the distribution. P < 1 × 10−4 for all encoding comparisons between SPNs in DLS and DMS, and P = 1 × 10−4, 6 × 10−3, 0.49, 4 × 10−3, 1 × 10−4 for comparisons between FSI encoding in the DLS and DMS of all effectors, contra-, ipsi-, both forelimbs and head, respectively. P values measure the probability that the two datasets have the same mean and are estimated by bootstrapping difference in means (n = 1 × 104 resamples).
Extended Data Fig. 6 Characterization of task performance and DLS representations after motor cortex lesion.
a, Comparison of performance measures before and after MC lesion (n = 3). IPI: Inter-Press Interval, CV of IPI: Coefficient of Variation of the IPI, IPI close to target: Fraction of trials close to target IPI (700 ms ± 20%), ITI: Inter-Trial Interval. Pre-Lesion: last 2,000 trials before lesion, post-Lesion: first 2,000 trials after lesion. Dots indicate individual animals and bars show means ± s.e.m. For statistical details see Supplementary Table 7. b, (Top) Comparing task-aligned activity statistics, including average firing rate during the trial-period (P = 0.09), maximum modulation of Z-scored firing rate during the trial-period (P < 1 × 10−4), sparseness index (P = 0.02) and average trial-to-trial correlation of task-aligned spiking (P < 1 × 10−4), between putative SPNs recorded in the intact (red, n = 683, replotted from Fig. 2c) and MC-lesioned (blue, n = 379) DLS. (Bottom) Average firing rate during the trial-period (P = 0.01), maximum modulation of Z-scored firing rate during the trial-period (P = 5 × 10−4), sparseness index (P = 0.08) and average trial-to-trial correlation of task-aligned spiking (P = 0.05) in putative FSIs recorded in the intact (red, n = 171, replotted from Extended Data Fig. 2b) and MC-lesioned (blue, n = 153) DLS. Bars and error-bars represent mean and s.e.m., respectively, across units. P values measure the probability that two datasets have the same mean and are computed by bootstrapping difference in means (n = 1 × 104 resamples). c, Goodness of fit, measured by pseudo-R2, for encoding models that use kinematics of all tracked effectors and those that only use kinematics of the contralateral forelimb, ipsilateral forelimb, both forelimbs or the head to predict spiking activity of putative SPNs (left) and FSIs (right) in the DLS of intact (red, n = 492 SPNs and 164 FSIs from 3 rats, replotted from Extended Data Fig. 5b) and MC-lesioned (blue, n = 279 SPNs and 169 FSIs from 3 rats) animals. Boxes denote 1st, 2nd (median) and 3rd quartiles, while whiskers show the 5th and 95th percentile of the distribution. P < 1 × 10−4, = 4 × 10−3, < 1 × 10−4, < 1 × 10−4 for comparisons between SPN encoding in the intact and MC-lesioned DLS of all effectors, contra-, ipsi-, both forelimbs and head, respectively. P = 0.04, 0.66, 0.04, 0.04 for comparisons between FSI encoding in the intact and MC-lesioned DLS of all effectors, contra-, ipsi-, both forelimbs and head, respectively. P values measure the probability that the two datasets have the same mean and are estimated by bootstrapping the difference in means (n = 1 × 104 resamples).
Extended Data Fig. 7 Task performance after DLS, but not DMS, lesions is impaired, resembles performance early in training, and does not recover.
Comparison of performance measures at different stages before and after lesions of DLS (n = 7 rats), DMS (n = 5), and control injections (n = 5). IPI: Inter-Press Interval, CV of IPI: Coefficient of Variation of the IPI, IPI close to target: Fraction of trials close to target IPI (700 ms ± 20%), ITI: Inter-Trial Interval. Early: first 2,000 trials in training, pre-lesion: last 2,000 trials before lesion, post-lesion: first 2,000 trials after lesion, late: trials 10,000 to 12,000 after lesion. Presses/session: Average number of lever-presses per session. Early: first 10 sessions in training, pre-lesion: last 20 sessions before lesion, post-lesion: first 20 sessions after lesion, late: sessions 50 to 70 after lesion. Dots indicate individual animals and bars show mean ± s.e.m. For statistical details see Supplementary Table 8. *P < 0.05, **P < 0.01, ***P < 0.001.
Extended Data Fig. 8 Lesions of the GPi affect task performance similarly to DLS lesions.
a, Representative example of the effect of a GPi lesion on task performance. Left: Example histological image of a unilateral GPi lesion, showing the comparison between the lesioned and the intact GPi. Experimental animals underwent bilateral GPi lesions (see Methods). Right: IPIs and ITIs for an example animal early in training, before and after bilateral GPi lesion. Population data shown in panel b. b, GPi lesions (n = 5 rats) have long-lasting effects on various measures of performance (cf. Extended Data Fig. 7). DLS performance as shown in Extended Data Fig. 7, here shown for comparison. Dots indicate individual animals and bars show the mean ± s.e.m. c, Left: Example distributions of IPI and ITI interval lengths early in training, and before and after GPi lesion. d, JS Divergence of IPI and ITI distributions for all GPi-lesioned animals (n = 5 rats). Dots indicate individual animals and bars show the mean ± s.e.m.. For statistical details see Supplementary Table 9. *P < 0.05, **P < 0.01.
Extended Data Fig. 9 DLS lesions do not affect lever-press vigor, but lead to regression to a common lever-pressing behavior.
a, Comparison of mean and peak lever-press speeds before and after DLS lesion (see Fig. 8). Speeds were averaged over 1st and 2nd lever-presses. Dots indicate individual animals and bars show mean ± s.e.m. No significant differences were detected. For statistical details see Methods. b, The comparison of 1st and 2nd lever-presses across animals early in training and after DLS lesion (see Fig. 8c) was extended to additional animals. The post-lesion lever-presses of the 2 DLS-lesioned animals which were not included in Fig. 8c (due to lack of trajectories for the early presses) were added. In addition, the trajectories of the early lever-presses of 2 of the DMS-lesioned animals (shown in Fig. 7) were added. The remaining animals were re-plotted from Fig. 8c. (Column 1) Forelimb movement trajectories for the 1st and 2nd presses early in training (green) and after DLS lesion (red), overlaid for all tracked animals (early in training: DLS-lesioned animals n = 4, DMS-lesioned animals n = 2; post-lesion: DLS-lesioned animals n = 6). (Column 2) Pairwise correlations between press trajectories of all animals early in training and after DLS lesion. Shown are average trial-to-trial correlations across individual presses (animal 1 press 1, animal 1 press 2, etc.). (Column 3) Averages of across animal correlations per condition. Shown are correlations between all presses early, all presses after DLS lesion and between all presses early and all presses after lesion (early-post). Mean ± s.e.m. For statistical details see Supplementary Table 10. ***P < 0.001.
Extended Data Fig. 10 Small lesions of the DLS affect performance and movement kinematics but do not, in contrast to large DLS lesions, cause animals to revert to species-typical lever-pressing behaviors.
a, Fraction of DLS lesioned. Red: Animals with large DLS lesions, included in Figs. 6–8. Yellow: Animals with small DLS lesions (excluded from prior analysis). b, Average performance across animals (large DLS lesions n = 7 rats; small DLS lesions n = 3, Control n = 5), normalized to pre-manipulation performance. Fraction of trials with IPIs close to target (700 ms ± 20%). Shading represents s.e.m.. Partially replotted from Fig. 6b. c, Comparison of average forelimb trajectories (vertical position) before and after small DLS lesions for all animals (from trials within a range of mean IPI ± 30 ms). The forelimb performing the 1st lever-press is regarded dominant (n = 3 rats). d, Forelimb vertical displacement in randomly selected trials (200 per animal) of all animals before and after small DLS lesions. Trials are sorted by IPI and normalized to minimum and maximum displacement for each animal. Black lines mark the 1st, grey lines the 2nd lever-press. e, Pairwise correlations between trials shown in d, averaged per animal. f, Averages of correlations shown in e by condition (averages of all pre-to-pre, post-to-post and pre-to-post correlations). Mean ± s.e.m. g, Distributions of correlation coefficients between individual forelimb trajectories before (blue) and after (black) small DLS lesion, and the animal’s pre-lesion modes (see Methods). Probability distributions were computed for each rat and then averaged (n = 3). Fraction of trials with correlations >0.85 (Mean ± s.e.m.): pre 0.53 ± 0.24, pre-post 0 ± 0. h, Comparison of forelimb trajectories associated with 1st and 2nd lever-presses across animals with large and small DLS lesions. Pairwise correlations between press trajectories of animals early in training, of animals after large (replotted from Extended Data Fig. 9b) and of animals after small DLS lesions. Shown are average trial-to-trial correlations across individual presses (animal 1 press 1, animal 1 press 2, etc.) (n = 6 rats early, n = 6 large DLS lesions (partially overlapping, see Extended Data Fig. 9b), n = 3 small DLS lesions). i, Averages of across animal correlations for selected conditions. Left: correlations between all presses early (dark green dotted square in h) and all presses after large DLS lesions (dark red dotted square in h) as in Extended Data Fig. 9b. Right: correlations between all presses early and all presses after small DLS lesions (small-early; light green dotted square in h) and between all presses after large DLS lesions and all presses after small DLS lesions (small-post; light red dotted square in h). All comparisons show statistically significant differences with P < 0.001, except the comparison small-early to small-post. Mean ± s.e.m. For statistical details see Supplementary Table 11.
Supplementary Tables 1–11.
Supplementary Video 1
Comparison of movement trajectories and neural representations in the DLS during execution of two sequence modes (the same example modes shown in Fig. 3) by an example rat. High-speed videos (at 120 Hz) and the position of the forelimb contralateral to the recording site are shown for two representative trials from two distinct modes. The neural representation is computed from trial-averaged activity of an ensemble of neurons compiled over multiple recording days.
Supplementary Video 2
Effects of DLS lesions on a learned task-specific movement pattern. Example trials from two animals in our timed lever-pressing task early in training, before DLS lesion, and after DLS lesion. Shown are videos and (vertical) trajectories of both forelimbs (marked with yellow and magenta dots in the videos). The forelimb trajectories of the two animals are overlaid when the second animal is shown.
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Dhawale, A.K., Wolff, S.B.E., Ko, R. et al. The basal ganglia control the detailed kinematics of learned motor skills. Nat Neurosci 24, 1256–1269 (2021). https://doi.org/10.1038/s41593-021-00889-3
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