Extended Data Fig. 5: Comparison between encoding of different kinematic features by striatal neurons.
From: The basal ganglia control the detailed kinematics of learned motor skills
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).
