Article Figures & Data
Figures
- Figure 1.
Mice achieve expert status on the TPSD task (n = 8). A, Schematic of mouse on polystyrene ball. B, Experimental paradigm is a go/no-go task composed of synchronous audiovisual stimuli. C, d′ shows mice learn to discriminate temporal patterns (one-way ANOVA: F(1,16) = 5.45, p = 1.23 × 10−7). D, Hrs and CRrs do not significantly change with learning (Hr: Kruskal–Wallis test: H(16) = 21.74. p = 0.1515; CRr one-way ANOVA: F(1,16) = 1.23, p = 0.26). E, Hr and CRr in naive and learned sessions are significantly different (Hr: two-tailed t test: t(14) = 4.42, p = 5.85 × 10−4; CRr: two-tailed t test: t(14) = 4.46, p = 5.3 × 10−4). Refer to Extended Data Figures 1-1, 1-2, 1-3, 1-4, which show no dependence on trial ratios or training paradigm. The Extended Data also show dependence on the stimulus for learning.
- Figure 2.
Licking profiles index learning (n = 8). A, Raster plots of licking in naive and learned sessions, using the best 150 trials of all mice, as determined by the best d′ for that session. B, Probability of a lick event by stimulus type and session. C, Probability of a lick event by trial outcome in naive sessions. D, Probability of a lick event by trial outcome in learned sessions. Miss trials are excluded as there were exceedingly few miss trials for each mouse. E, Accuracy of bootstrapped SVM as a function of time. Licking events per 0.067 s were the predictors, and stimulus type is the outcome. Learned session accuracy confirms learning as predictability rises above chance before the water reward at 1.2 s.
- Figure 3.
V1 neural activity changes with learning and represents stimuli and trial outcomes (n = 5). A, Schematic of a mouse on a polystyrene ball with microscope objective over V1. B, Example craniotomy window showing binocular V1. C, Example frame of video taken from binocular V1 during behavior with imaging. D, Raw florescence traces of 10 representative cells in one mouse over 3 trial outcomes in learned session. E, Spike-sorted mean activity of all non-lick-modulated cells, in all trials, in naive sessions. Shaded areas represent 95% confidence intervals. F, Mean spiking activity in naive sessions. G, Spike-sorted mean activity of all non-lick-modulated cells, in all trials, in learned sessions. H, Mean spiking activity in learned sessions. Shaded areas represent 95% confidence intervals. Refer to Extended Data Figures 3-1 and 3-2 for extended analysis on neural activity from V1 during learning. Extended Data Figures 3-3 and 3-4 show the analysis of lick-modulated cells. Refer to Extended Data Figure 3-5 for learned neural dynamics during the flipped paradigm.
- Figure 4.
V1 neural activity ramps earlier in learned sessions (n = 5). A, Cumulative Distribution Function (CDF) of maximum spiking in naive sessions by trial outcome in preferred stimulus period (KS tests with Bonferroni correction: α = 0.0083; Hit vs Miss: D(0.1609), p = 2.58 × 10−6; Hit vs CR: D(0.2035), p = 7.49 × 10−10; Hit vs FA: D(0.062), p = 0. 2658; Miss vs CR: D(0.064), p = 0.234; Miss vs FA: D(0.1434), p = 4.16 × 10−5; CR vs FA: D(0.1899), p =1.23 × 10−8). B, CDF of maximum spiking in learned sessions by trial outcome in preferred stimulus period (KS tests with Bonferroni correction: α = 0.0167; Hit vs CR: D(0.1274), p = 9.57 × 10−4; Hit vs FA: D(0.1339), p = 4.31 × 10−4; CR vs FA: D(0.0518), p = 0.5518). C, CDF of maximum spiking in naive and learned sessions by trial outcome in nonpreferred stimulus period (KS tests with Bonferroni correction: α = 0.0083; Naive CR vs Naive FA: D(0.124), p = 6.29 × 10−4; Naive CR vs Learned CR: D(0.2612), p = 4.01 × 10−15; Naive CR vs Learned FA: D(0.1873), p = 5.57 × 10−8; Naive FA vs Learned CR: D(0.3369), p = 7.16 × 10−25; Naive FA vs Learned FA: D(0.2478), p = 1.19 × 10−13; Learned CR vs Learned FA: D(0.1058), p = 0.01).
- Figure 5.
Neural trajectories diverge only in correct trials in learned sessions (n = 5). A, Neural trajectories of Hit and Miss trials, naive sessions. B, Neural trajectories of Hit and CR trials, naive sessions. C, Neural trajectories of Hit and FA trials, naive sessions. D, Neural trajectories of Hit and CR trials, learned sessions. E, Neural trajectories of Hit and FA trials, learned sessions. Vertical bar at bottom right shows color coding of time through trials.
- Figure 6.
SVM performance as a function of time (n = 5). A, Spiking activities per mouse per trial in naive and learned sessions were predictors, and outcome was the stimulus type. B, Spiking activity per mouse per trial in naive sessions was the predictor, and outcome was the trial outcome (Hit, Miss, CR, FA). C, Spiking activity per mouse per trial in learned sessions was the predictor, and outcome was the trial outcome (Hit, CR, FA). Miss trials were again omitted because of their small sample size. D, Control for A. Spiking activities per mouse per trial in naive and learned sessions were predictors, and outcome was the randomly shuffled stimulus type. E, Control for B. Spiking activities per mouse per trial in naive sessions was the predictor, outcome was the randomly shuffled trial outcome. F, Control for C. Spiking activities per mouse per trial in learned sessions were predictors, and outcome was the randomly shuffled trial outcome. G, SVM decoding accuracy of spiking activity in naive sessions with varying numbers of cells selected. A forward sequential feature selection algorithm was used to select predictive cells (see Materials and Methods). H, Same as G, but in learned sessions. Extended Data Figure 6-1 provides evidence for cell selectivity during learning.
Extended Data
Figure 1-1
Learning is sustained regardless of the preferred to nonpreferred trial ratio (n = 8). A, Discriminability index (two-tailed t test: t(14) = 1.4175, p = 0.1782), Hit rate (two-tailed t test: t(14) = 2.099, p = 0.0544), and CR rate (two-sided Wilcoxon rank-sum test: p = 0.6454) do not significantly differ between learned sessions in main trials (P/NP stimulus ratio, 7:3) and 6:4 P/NP stimulus ratio sessions, indicating nonbiased learning. B, Rasters of licking in learned main sessions and 6:4 P/NP stimulus ratio sessions. C, Probability of a licking event as a function of time by stimulus type and session. D, Accuracy of bootstrapped SVM as a function of time. Licking events per 0.067 s were the predictors, and stimulus type was the outcome. Comparable predictability between learned and P/NP stimulus ratio 6:4 sessions indicate nonbiased learning. Download Figure 1-1, EPS file.
Figure 1-2
Learning is stimulus dependent (n = 7). A, Discriminability index (two-tailed t test: t(13) = 11.0036, p = 5.86 × 10−8), Hit rate (two-tailed t test: t(13) = 24.2266, p = 3.34 × 10−12), and CR rate (two-tailed t test: t(13) = 4.0389, p = 0.0014) significantly differ between learned sessions in main trials and control sessions in which both monitor and speaker are turned off, indicating that learning is stimulus dependent. B, Rasters of licking in learned main sessions and control sessions. C, Probability of licking event as a function of time by stimulus type and session. D, Accuracy of bootstrapped SVM as a function of time. Licking events per 0.067 s were the predictors, and stimulus type is the outcome. Predictability at chance level in control sessions indicates that learning is stimulus dependent. Download Figure 1-2, EPS file.
Figure 1-3
Mice achieve expert status on the TPSDmod paradigm. A, Schematic of flipped paradigm. Synchronous audiovisual stimuli are presented as before in the original paradigm. The preferred stimulus has the longer intratrial stimulus of 0.73 s; the nonpreferred is composed of 0.2 s intratrial stimuli. The total time between stimuli is now equal at 2.6 s. B, Raster plot of licking between naive and learned sessions (n = 2). C, Discriminability index across days shows learning in mice. D, CR and Hit rates change with sessions. E, Change in performance is driven primarily by changes in CR rates. F, Probabilities of licking by stimulus type and session day. G, Probabilities of licking in naive sessions. H, Probabilities of licking in learned sessions. Miss trials are removed as there were exceedingly few. I, SVM accurately predicts stimuli from licking data as a function of time in learned sessions. Naive predictability remains at chance level until after the period at which the water reward is delivered. Download Figure 1-3, EPS file.
Figure 1-4
Learning on the TPSDmod paradigm is not an artifact of experimental design. A, Discriminability index, Hit rates, and CR rates in learned and P/NP stimulus ratio 6:4 sessions (n = 2). B, Raster plot of licking between learned and P/NP stimulus ratio 6:4 sessions. C, Probabilities of licking by stimulus type and session day. D, SVM accuracy in P/NP stimulus ratio 6:4 session mirrors SVM accuracy using licking to predict stimulus type in learned sessions, confirming that the main task P/NP stimulus ratio 7:3 is not a confound. E, Discriminability index, Hit rates, and CR rates in learned and control (monitor and speakers turned off) sessions (n = 2). B, Raster plot of licking between learned and control sessions. C, Probabilities of licking by stimulus type and session day. D, SVM accuracy using licking to predict stimulus type in control sessions remains at chance level throughout the trial period confirming that learning is stimulus dependent. Download Figure 1-4, EPS file.
Figure 3-1
V1 neural activity changes with learning (n = 5). A, Mean spiking activity in naive and learned sessions by stimulus type in preferred period. Shaded areas represent 95% confidence intervals. B, Calcium-dependent facilitation (CDF) of maximum spiking in naive and learned sessions by stimulus type in preferred stimulus period [KS tests with Bonferroni correction: α = 0.0083; preferred naive (PN) vs preferred learned (PL): D(0.1197), p = 0.0016; PN vs nonpreferred naive (NPN): D(0.0795), p = 0.0731; PN vs nonpreferred learned (NPL): D(0.1186), p = 6.36 × 10−8; PL vs NPN: D(0.1376), p = 1.68 × 10−4; PL vs NPL: D(0.1469), p = 7.79 × 10−5; NPN vs NPL: D(0.225), p = 2.49 × 10−11). C, Mean spiking activity in naive and learned sessions by stimulus type in nonpreferred period. Shaded areas represent 95% confidence intervals. D, CDF of maximum spiking in naive and learned sessions by stimulus type in nonpreferred stimulus period (KS test: D(0.3766), p = 5.68 × 10−31). Download Figure 3-1, EPS file.
Figure 3-2
V1 neural activity is successively suppressed in learned sessions (n = 5). A, Mean spiking activity in naive session by trial outcome in nonpreferred period. Shaded areas represent 95% confidence intervals. B, Mean spiking activity in learned session by trial outcome in nonpreferred period. Shaded areas represent 95% confidence intervals. Download Figure 3-2, EPS file.
Figure 3-3
Lick-modulated cells show differential activity based on trial outcome (n = 4). A, Spike-sorted mean activity of all lick-modulated cells, all trials, in learned sessions. B, Mean spiking activity of lick-modulated cells in learned sessions by trial outcome in preferred period. C, CDF of maximum spiking of lick-modulated cells in learned sessions by trial outcome in preferred stimulus period (KS tests with Bonferroni correction: α = 0.0167; Hit vs CR: D(0.169), p = 0.2388; Hit vs FA: D(0.169), p = 0.2388; CR vs FA: D(0.0704), p = 0.9928). D, Mean spiking activity of lick-modulated cells in learned sessions by trial outcome in nonpreferred period. E, CDF of maximum spiking of lick-modulated cells in learned sessions by trial outcome in nonpreferred stimulus period (KS test: D(0.1831), p = 0.1654). F, SVM predictability between licking and neural activity of lick-modulated cells is comparable, indicating successful extraction of lick-modulated cells. Predictor is, respectively, licking per 0.067s bins and lick-modulated cell neural activity per 0.067 s bins in learned sessions. Outcome is stimulus type. Download Figure 3-3, EPS file.
Figure 3-4
SVM performance as a function of time comparing licking, lick-modulated cell neural activity, and non-lick-modulated cell neural activity in learned sessions (n = 5). A, SVM predictability comparing Hit and CR trials. B, SVM predictability comparing Hit and FA trials. C, SVM predictability comparing CR and FA trials. D, Control for A. E, Control for B. F, Control for C. Download Figure 3-4, EPS file.
Figure 3-5
SVM cell selectivity is time and stimulus dependent. A, Heatmaps of sorted cell selectivity as a function of time in small number cell selection groups. Bars represent how many times a given cell was selected at a given time as a proportion of the total number of possible selections (e.g., when 2 cells were selected, in a given time bin 2000 total selections could be made due to 1000 bootstrap iterations; therefore, if a cell were selected in every iteration, it would account for 50% of the total selections for that time bin). B, Heatmaps of sorted cell selectivity as a function of time in large number cell selection groups. Due to more cells being selected in larger number cell groups, some cells may be selected whether they are or are not predictive (e.g., in “Learned: 100 cells,” one mouse had exactly 100 cells, therefore, each cell was selected in each iteration regardless of how informative it was). Download Figure 3-5, EPS file.
Figure 6-1
V1 L-2/3 encodes temporal information in flipped paradigm in learned sessions (n = 2). A, Heatmaps of spike-sorted activity in mice in naive sessions based on trial outcome. Lick cells were removed prior to the analysis of neural activity in both sessions as was done in the original TPSD paradigm analysis. B, Heatmaps of spike-sorted activity in mice in learned sessions based on trial outcome. C, Mean network spiking activity based on stimulus or trial outcome and session day. CR trials in the naive sessions and Miss trials in the learned session were removed due to exceedingly small samples. D, Cumulative distributions of maximum spiking activity based on stimulus or trial outcome and session day. CR trials in the naive session and Miss trials in the learned session were removed due to exceedingly small samples. E, SVM predicts stimulus from neural activity in learned sessions but remains at chance level in naive sessions. Download Figure 6-1, EPS file.
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