Experience-related enhancements in striatal temporal encoding

Abstract

Temporal control of action is key for a broad range of behaviors and is disrupted in human diseases such as Parkinson's disease and schizophrenia. A brain structure that is critical for temporal control is the dorsal striatum. Experience and learning can influence dorsal striatal neuronal activity, but it is unknown how these neurons change with experience in contexts which require precise temporal control of movement. We investigated this question by recording from medium spiny neurons (MSNs) via dorsal striatal microelectrode arrays in mice as they gained experience controlling their actions in time. We leveraged an interval timing task optimized for mice which required them to "switch" response ports after enough time had passed without receiving a reward. We report three main results. First, we found that time-related ramping activity and response-related activity increased with task experience. Second, temporal decoding by MSN ensembles improved with experience and was predominantly driven by time-related ramping activity. Finally, we found that a subset of MSNs had differential modulation on error trials. These findings enhance our understanding of dorsal striatal temporal processing by demonstrating how MSN ensembles can evolve with experience. Our results can be linked to temporal habituation and illuminate striatal flexibility during interval timing, which may be relevant for human disease.

Figure 1:. Switch interval timing task and electrode locations.

A) We trained animals to perform a switch interval timing task in which mice initiate trials at a rear nosepoke. For 50% of the trials, mice were rewarded at the short nosepoke for the first nosepoke after six seconds; for the remaining trials (termed “switch trials”), mice were rewarded for the first nosepoke after 18 seconds at the long nosepoke. Nosepoke lights and a tone signified trial start; these stimuli are identical on short and long trials. The temporal decision to switch from short to long nosepokes is an explicit time-based decision as in other interval timing tasks. If the animal broke an infrared beam in each nosepoke, this was counted as a response. Our analysis was focused on switch trials. B) Electrode locations in the dorsal striatum from one animal (stained with Prussian Blue on the left) and all mice (electrode locations in green on the right). C) We identified medium-spiny neurons (MSNs) based on clustering of waveform peak-to-trough distance and waveform half-peak width. Data from six mice.

Figure 2:. Interval timing performance improves with experience.

A) Rasters of all responses; with each row representing a trial, and a block of trials from each mouse indicated by the numbers at far left. Short responses are gray; long responses are black; the last short response is in green and termed the ‘switch’, and first long response is in blue and termed the ‘arrival’. Only switch trials are plotted. B) Time-response histograms of short (gray) vs. long (black) nosepokes for early training vs. C) experienced animals. D) Distribution or E) cumulative probability of switch responses (when animals departed from the short nosepoke and subsequently responded at the long nosepoke) did not change with experience. F) Mean switch times or G) the coefficient of variability did not change with experience. H) The proportion of correct responses increased with experience. Gray lines in F-H are individual animals; black lines are mean±SEM.*=p<0.05 via Wilcoxon signed-rank. Data from 445 trials in six animals.

Figure 3:. Response-related and timing-related MSNs increase with experience.

A) Example of an MSN with time-related ramping activity; activity on all switch trials is included with each switch trial as one row. B) Example of an MSN with response-related activity; activity on all nosepoke responses is included with each nosepoke response as one row. C) Bar graphs illustrating the frequency of MSNs exhibiting significant response-related activity or time-related ramping activity during interval timing in early training (light green) vs. experienced sessions (dark green). * by ramping- and response-related activity indicates that they both increased in experienced sessions with p<0.05 as calculated by X²-test. Data from 77 MSNs in six mice during early training sessions and 79 MSNs in the same six mice during experienced sessions.

Figure 4:. Time-related ramping patterns are stable with experience.

Peri-event time histograms of all time-related ramping neurons in A) early training, and in B) experienced sessions. Histograms were calculated via kernel density estimates of firing rate on all switch trials, and z-scored. C) Principal component analyses (PCA), a data-driven technique to capture patterns of neural activity, revealed that a monotonic change over the entire interval was the most prominent pattern, explaining 48% of variance. A second component ramped until the approximate time of the switch, and explained 16% of variance. PCA was derived from both early training and experienced sessions; PC1 and PC2 did not reliably change with experience. Data from 57 time-related ramping neurons identified by GLMs from early training and experienced sessions in six mice.

Figure 5:. MSN ensembles improve temporal decoding with experience.

We trained naïve Bayesian classifiers to predict time from firing rate on a trial-by-trial basis. Temporal predictions from all trials for the entire neuronal ensemble from six mice in A) early training and B) experienced sessions; predicted time is on the y-axis and observed time is on the x-axis, with yellow representing the highest probability. Only the time during the trial (0–18 seconds; white box) is analyzed. C) Temporal decoding improved for early training vs. experienced sessions and was consistently stronger than shuffled data. *=p<0.05 via Wilcoxon signed-rank; single data points represent R² values from each trial; white circle represents the median; vertical gray lines represent the intraquartile range. D) Temporal decoding was higher for MSNs with both time-related and response-related modulations than for MSNs with response-related modulations. *=p<0.05 via Wilcoxon signed-rank vs. ramping & response neurons, and #=p<0.05 via Wilcoxon signed-rank vs. ramping neurons. Data from MSN ensembles in six mice during early training and experienced sessions.

Figure 6:. Neuronal activity on error trials.

A) An MSN with distinct activity during error-related trials, in which the animal made a terminal nosepoke at the incorrect port. B) An MSN with similar activity on error-related trials. C) Fraction of error-trial modulated neurons in early training vs. experienced sessions. Data from 98 neurons with >5 error trials in six mice during early training and experienced sessions.