Mouse-optimized interval timing.

A) Mice to respond by switching nosepokes after a ∼6 second interval (see methods). Inset – screen captures from operant chambers. Responses to switch nosepokes are a timebased decision guided explicitly by temporal control of action (see Methods and Fig S1). Response times are defined as the moment mice exit the first nosepoke (on the left) to respond at the second nosepoke; nosepokes at a second port (on the right) after 18 seconds trigger reward delivery. B) Response probability distribution and C) cumulative density from 30 mice. D) We used optogenetic tagging to record from D2-MSNs or D1-MSNs trained to perform an interval timing task.

Summary of mice and MSNs

D2-MSNs and D1-MSNs have opposing dynamics during interval timing.

A) D2-MSNs in the indirect pathway, which project from the striatum to the globus pallidus external segment (GPe; sagittal section) and internal segment (GPi) and B) D1-MSNs, which project from the striatum to the GPe, GPi, and substantia nigra (SNr; sagittal section). Peri-event raster C) from a D2-MSN (red) and E) from a D1-MSN (blue). G) Peri-event time histograms from all D2-MSNs and H) from all D1-MSNs. Average activity revealed that G) D2-MSNs (red) tended to ramp up, whereas H) D1-MSNs (blue) tended to ramp down. Data from 32 tagged D2-MSNs in 4 D2-Cre mice and 41 tagged D1-MSNs in 5 D1-Cre mice.

Quantification of opposing D2-MSN and D1-MSN dynamics

A) Principal component analysis revealed that the first component (PC1) exhibited time-dependent ramping. B) The first principal component explained ∼56% of variance across tagged MSN ensembles. C) Differences between D2-MSNs (red) and D1-MSNs (blue) were captured by PC1 which exhibited time-dependent ramping. D) These differences were also apparent in the linear slope of firing rate vs time in the interval, with D1-MSNs (blue) having a more negative slope than D2-MSNs (red). The differences were unlikely to be driven by movement because most responses occur after 6 seconds, our GLMs included nosepokes as a regressor, and nosepoke GLM βs were similar between D2-MSNs and D1-MSNs. In C and D, each point represents data from a tagged MSN, and horizontal black lines represent group medians. * p < 0.05 via linear mixed effects models accounting individual mice. Data from 32 tagged D2-MSNs in 4 D2-Cre mice and 41 tagged D1-MSNs in 5 D1-Cre mice.

Four-parameter drift-diffusion computational model of striatal activity during interval timing.

A) We modeled interval timing with a low parameter diffusion process with a drift rate D, noise ξ(t), and a baseline firing rate b that drifts toward a threshold T indicated by dotted lines. With D2-MSNs disrupted (solid red curves), this drift process decreases in slope and takes longer to reach the threshold. B) The same model also accounted for D1-MSNs that had an opposite drift slope. With D1-MSNs disrupted (solid blue curves), the drift process again takes longer to reach the threshold. Because both D2-MSNs and D1-MSNs contribute to the accumulation of temporal evidence, this model predicted that C) disrupting D2-MSNs would increase response times during interval timing (dotted red line) and D) disrupting D1-MSNs would also increase response times (dotted blue line). Threshold T depends on b and target firing F.

Disrupting D2- or D1-MSNs increases response times.

A) As predicted by our DDM in Fig 4, optogenetic inhibition of D2-MSNs (red) shifted cumulative distributions of response times to the right, and B) increased response times; data from 10 D2-Cre mice expressing halorhodopsin (Halo). Also as predicted by our DDM, optogenetic inhibition of D1-MSNs C) shifted cumulative distribution functions to the right, and D) increased response times; data from 6 D1- Cre mice expressing Halo. Similarly, E) pharmacologically disrupting D2-dopamine receptors (red) with the D2 antagonist sulpiride shifted cumulative distribution functions to the right, and F) increased response times; data from 10 wild-type mice. Also, G) pharmacologically disrupting D1-dopamine receptors (blue) with the D1 antagonist SCH23390 shifted cumulative distribution functions to the right, and H) increased response times; data from the same 10 wild-type mice as in E-F. In B, D, F, and H connected points represent the mean response time from each animal in each session, and horizontal black lines represent group medians. *p = < 0.05, signed rank test.

D2 and D1 blockade shift temporal dynamics.

A) We recorded dorsomedial striatal medium spiny neuron (MSN) ensembles during interval timing in sessions with saline, D2 blockade with sulpiride, or D1 blockade with SCH23390. Made with BioRender.com. B) Peri-event raster from a single MSN in sessions with saline (black), D2-dopamine blockade (red), or D1-dopamine blockade (blue). D2 blockade or D1 blockade changed this MSN’s temporal dynamics. C) Neuronal ensemble recording from the same 11 animals with saline, D2 blockade, or D1 blockade; each row represents a peri-event time histogram. Colors indicate z-scored firing rate. D) Principal component analysis (PCA) identified MSN ensemble patterns of activity. The first principal component (PC1) exhibited time-dependent ramping. E) PC1 explained 55% of population variance among MSN ensembles; the second principal component (PC2) explained 31%; higher components explained <10% each and were not analyzed. F) PC1 scores were shifted and significantly different with D2 or D1 blockade, but G) PC2 scores were not. *p < 0.05 via linear mixed effect models; data from 11 mice.

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D2 and D1 blockade degrade MSN temporal encoding.

We used naïve Bayesian classifiers to decode time from MSN ensembles in A) saline sessions, B) D2 blockade sessions, and C) D1 blockade sessions. Color represents the temporal prediction across 20 trials with red representing stronger predictions. D) Temporal encoding was strong early in the interval, and D2 or D1 blockade degraded classification accuracy. Temporal encoding was decreased later in the interval. Each point represents the R2 for each trial of behavior for MSN ensembles from 11 mice. * p < 0.05 vs saline from 0-6 seconds. Horizontal black lines in (D) represent group medians.

Gamma distribution parameters

A) DeepLabCut tracking of position during the interval timing. B) Mice moved quickly after trial start and then velocity was relatively constant throughout the trial. C) Probability distribution of switch responses from 30 animals; each line is the average for one animal. D) Probability distribution of first nosepokes (grey), switch responses when mice depart the first nosepoke (in green; average of panel C), and second nosepokes (blue). Shaded bars represent standard error; data from the same 30 mice as from Figure 1B-C.

A) Recording locations in the dorsomedial striatum. Electrode reconstructions for D2-Cre (red), D1-Cre (blue), and wild-type mice (green). Only the left striatum was implanted with electrodes in all animals. B) MSN classification by waveform criteria for sessions with optogenetic tagging. C) Example of an optogenetically tagged MSN. This neuron expresses ChR2, and on trials when the 473 nm laser was pulsed (thin red line), this neuron fired action potentials within 5 milliseconds. Inset on bottom right – waveforms from laser trials (red) and trials without laser (blue). Across 73 tagged neurons, waveform correlation coefficients for laser trials vs. trials without laser was r = 0.97 (0.92-0.99). D) MSN classification by waveform criteria for pharmacology sessions.

D2- and D1-MSN activity over the whole 18-second interval. A) Peri-event time histograms from D2-MSNs and B) from D1-MSNs over the whole interval. C) We noticed that on average, D2-MSNs tended to ramp up (red), whereas D1-MSNs tended to ramp down (blue). D) Principal component analysis revealed that PC1 exhibited time-dependent ramping over the whole 18-second interval. This component explained ∼45% of variance across tagged MSN ensembles. E) Over the whole interval, differences between D2-MSNs and D1-MSNs were captured in PC1, which indicates opposing time-dependent ramping (rank sum p = 0.02). F) These differences were also captured via differences in a linear slope of firing rate vs time over the whole 18-second interval, with D1-MSNs having a more negative slope (rank sum p = 0.03). Data from 32 tagged D2-MSNs in 4 D2-Cre mice and 41 tagged D1-MSNs in 5 D1-Cre mice (see Figs. 1).

Fiber optic locations from A) an opsin-expressing mouse with mCherry-tagged halorhodopsin and bilateral fiber optics, and B) across 10 D2-Cre mice (red) and 6 D1-cre mice (blue) with fiber optics.

Experiments in D2-Cre mice injected with virus without opsins did not reliably affect A) cumulative density functions (CDFs) or B) response times (signed rank p = 0.44). Experiments in D1-Cre mice expressing virus without opsins did not reliably affect C) CDFs or D) response times (signed rank p = 0.81).

Model details. Histograms of behavioral data from D2-Cre mice with A) Laser Off and B) D2-MSN inhibition (red). Data from D1-Cre mice with C) Laser Off and with D) D1-MSN inhibition (blue). E-H) model predictions. I-J) Comparisons of empirical data vs model. All panels: fits for the gamma distribution with dotted circles; see Table S2 for the parameter values defining each gamma distribution. Behavioral data: from 10 D2-Cre mice and 6 D1-mice from Fig 1A-D. Model data: from numerical simulations of the DDM model shown in Fig 2.

Optogenetically inhibiting D2-MSNs or D1-MSNs does not affect task-specific motor control.

We measured nosepoke duration (time of nosepoke entry to exit) on switch responses. During interval timing there was no effect of optogenetic inhibition (red) of dorsomedial striatal D2-MSNs on A-B) nosepoke duration or C) the traversal time between the first and second nosepokes. There was also no effect of optogenetic inhibition (blue) of dorsomedial striatal D1-MSNs on response duration (D-E) or F) switch traversal time. Data from the same 10 D2-Cre mice and 6 D1-Cre mice, as in Fig 5. Horizontal black lines in B,C,E, and F represent group medians.

A) Standard deviation of interval timing performance for D2-MSN inhibition sessions (signed rank test, p = 0.19) and B) D1-MSN inhibition sessions (p = 0.84), and the number of total rewards for C) D2-MSN inhibition sessions (p = 0.07) and d) D1-MSN inhibition sessions (p = 0.24). Data from 10 D2-Cre mice and 6 D1-Cre mice as in Fig 5.

A) We sorted and identified the same 99 MSNs across saline sessions and sessions with D2 blockade or D1 blockade. Each row is a z-scored peri-event time histogram of MSN activity for all trials during interval timing. Each row is the same neuron identified by waveform and interspike-intervals across saline, D2 blockade, and D1 blockade sessions. B) We further explored early-interval dynamics by PCA. The matched sorting across sessions enabled paired signed rank analyses. C) The first component (PC1) explained 75% of variance among MSN ensemble dynamics between 3-6 seconds that showed maximal differences between sessions. D) As with dynamics between 0-6 seconds, PC1 was shifted relative to saline for D2 blockade (signed rank p = 0.000007) and D1 blockade (signed rank p = 0.002). We identified two clusters based on PC1, with cluster 1 (E) loading positively on PC1, and cluster 2 (F) loading negatively on PC1. For cluster 1 in (E), PCs were distinct from saline for D2 blockade (signed rank p = 3×10-12) and for D1 blockade (signed rank p = 10-7). For cluster 2 in panel (F), PC1 changes were also distinct for saline for D2 blockade (signed rank p = 0.00008) and for D1 blockade (signed rank p = 0.002). Data from the same mice as in Fig 6.