Extended Data Fig. 1: Behavioral analysis, behavioral training, and experimental timeline.
From: A combinatorial neural code for long-term motor memory
a. Top left, representative video frame with automatically labeled tongue markers using DeepLabCut. Top middle, superimposed tongue tip trajectories and x and y velocities of individual lick events during lick left (red) and lick right (blue). Data from an example mouse across sessions within the same task context. Tongue tip trajectory scale bar, 4 pixels (x) and 6 pixels (y). X velocity scale bar, 12 ms and 2 pixels/s. Y velocity scale bar, 12 ms and 1.5 pixels/s. Top right, scatter of averaged pairwise similarity of single lick events (Pearson’s correlation) calculated within session versus across sessions. Data from two mice. Bottom, same as top but for data across task contexts 1 and 2. b. Same as a, but for jaw marker analysis. Jaw tip trajectory scale bar, 4 pixels (x) and 4 pixels (y). X velocity scale bar, 12 ms and 1 pixels/s. Y velocity scale bar, 12 ms and 1.5 pixels/s. c. Left, schematics of learning speed under two models. Context-specific saving effect (top): faster re-learning only for previously learned tasks. Context non-specific saving effect (bottom): faster learning each time. Right, faster reversal learning is consistent with a context-specific saving effect. Re-learning of task context 2’ is significantly faster than initial learning of task context 2 (top). P = 0.0487, paired t-test. Circles indicate individual mice (N = 13 mice). Crosses indicate mean ± s.e.m. We examine task context 2 because the initial learning of task context 1 is confounded by the exposure to home-cage training. To examine context non-specific saving effect, we compare the speed of re-learning task context 1’ versus re-learning task context 2’ (bottom). The two conditions have similar task-specific prior training. No significant difference is observed. P = 0.3425, two-tailed paired t-test. d. Same as Fig. 1i, but separately plotting photoinhibition results for task context 1 (left) and task context 2 (right). e. Experimental timeline of an example mouse imaged within the same task context over extended time. Black, behavior training in automated home-cage. Gray, habituation in two-photon setup. Red, calcium imaging in two-photon setup. All the trials are concatenated. Black triangle indicates the end of learning voluntary head-fixation and start of learning in tactile instructed licking task. Averaging window, 100 trials. f. Same as e, but for two mice imaged across different task contexts. g. Summary plot of experimental timeline from all GP4.3 mice used for imaging in this study. h-i. Behavior performance curves for the initial learning from GP4.3 mice (h, n = 15 mice, all were trained in automated home-cage) and Slc17a7-Cre x Ai148 mice (i, n = 11 mice, 7 mice were trained in automated home-cage and 4 mice were manually trained). Different colors represent individual mice. Circles indicate end of the learning curves for GP4.3 mice and termination of training for Slc17a7-Cre x Ai148 mice. j. Behavior performance within imaging sessions across 4 segments of trials. Thin gray lines indicate individual sessions. Thick black lines indicate mean ± s.e.m. Data from Fig. 2b.
