Dorsal striatum coding for the timely execution of action sequences
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Evaluation Summary:
This manuscript investigates an important topic related to the initiation signals of actions sequences detected in the dorsal striatum. The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to the ability to wait for a reward. The study nicely bridges research on striatum's roles in reward-seeking actions and in time processing. Interesting activity patterns are detected that suggest a relationship to the premature versus the timely release of actions. These observations are potentially interesting, in particular, the possible difference between adult and adolescent rats. The functional significance of these activity patterns remain to be examined.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)
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Abstract
The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore–exploit balance.
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Author Resonse
Reviewer #1 (Public Review):
The authors trained rats to self-initiated a trial by poking into a nose poke, and to make a sequence of 8 licks in the nose poke after a visual cue. Trials were considered valid (called "timely") only if rats waited for more than 2.5 sec after the end of the previous trial. An attempt to initiate a trial (nose poking) before the 2.5 sec criterion was regarded as "premature". The authors recorded from the dorsal striatum while rats performed in this task. The authors first show that some neurons exhibited a phasic activation around the time of port entry detected using an infrared detector ("Entry cell"), as well as port exit ("Exit cell). Some neurons showed activation at both entry and exit ("Entry and Exit cell") or between these two events ("Inside-port cell"). Fractions of neurons that …
Author Resonse
Reviewer #1 (Public Review):
The authors trained rats to self-initiated a trial by poking into a nose poke, and to make a sequence of 8 licks in the nose poke after a visual cue. Trials were considered valid (called "timely") only if rats waited for more than 2.5 sec after the end of the previous trial. An attempt to initiate a trial (nose poking) before the 2.5 sec criterion was regarded as "premature". The authors recorded from the dorsal striatum while rats performed in this task. The authors first show that some neurons exhibited a phasic activation around the time of port entry detected using an infrared detector ("Entry cell"), as well as port exit ("Exit cell). Some neurons showed activation at both entry and exit ("Entry and Exit cell") or between these two events ("Inside-port cell"). Fractions of neurons that fall into these four categories are roughly the same (Fig. 3C). The main conclusions drawn from this study are that (1) the activity preceding a port entry was positively correlated with the latency to initiate a trial (or "waiting time"; Fig. 4E), which appear to reflect the value upcoming reward, and that (2) in adolescent rats, the activity rose more steeply with the latency to trial initiation (Fig. 7J).
These observations are potentially interesting, in particular, the possible difference between adult and adolescent rats is intriguing. However, this study does not examine whether this brain region actually plays a role in the task. Some of the conclusions appear to be premature.
- Previous studies have found correlations between the activity of neurons in the striatum and the latency to trial initiation (e.g. Wang et al., Nat. Neurosci., 2013) or action initiation more generally (e.g. Kunimatsu et al., eLife, 2018). In the former study, the trial initiation was self-generated, similar to the present study, and was modulated by the overall reward value (state value). In the latter study, the latency was instructed by a cue. Furthermore, there are many studies that showed correlations between striatal activity and future rewards (e.g. Samejima et al., Science, 2005; Lau and Glimcher, 2008). Many of these studies varied the value of upcoming reward (e.g. amount or probability). Although some details are different, the basic concepts have been demonstrated in previous studies.
Although there are other studies linking striatal activity to trial/action initiation and reward probability, here the striatal activity preceding the execution of a learned sequence is dependent on the internal representation of the time waited. Elapsed time is the only cue the animal has regarding the possible outcome until it is too late and the trial has already been initiated. Although a light cue then tells the rat if the timing was correct or not, providing an opportunity to stop the behavior, the behavior released during premature trials resembles very closely that observed during unrewarded timely trials. This remarkable similarity between premature trials and timely unrewarded trials allowed comparing very advantageously the effect of wait time-based modulation of anticipatory striatal activity. Moreover, we have compared striatal activity between adult and adolescent rats finding a steeper wait time-based modulation of striatal activity in adolescent animals that correlates with a more impulsive behavior in these animals.
- The authors conclude that "in this task, the firing rate modulation preceding trial initiation discriminates between premature and timely trials and does not predict the speed, regularity, structure, value or vigor of the subsequently released action sequence". This conclusion is based on the observation that premature and timely trials did not differ in terms of kinematic parameters as measured using accelerometer. Although the result supports that the difference in activity between premature and timely cannot be explained by the kinematic variables, it does not exclude the possibility that the activity is modulated by some kinematic variables in a way orthogonal to these trial types.
While our accelerometer data do not support that differences in movement initiation time or velocity could explain the differences in striatal activity between adolescent and adult rats, we can not rule out that kinematic variables not captured by the head accelerometer recordings could explain some of the results. This is acknowledged in the main text, results section, page 8, line 180.
- The firing rate plot shown in Figure 4D should be replotted by aligning trials by movement initiation (presumably available from accelometer or video recording). Is it possible that the activity rise similarly between trials types but the activity is cut off depending on when the animal enters the port at different latency from the movement initiation? In any case, the port entry is a little indirect measure of "trial initiation".
Unfortunately, we have not systematically obtained video recordings of the sessions and only have accelerometer recordings of a few of the animals that provided the neuronal data, which precludes replotting the data as suggested. Accelerometer recordings are available from two of adult and two adolescent rats. Latency from movement initiation to port entry do not differ between premature and timely trials at both ages. This is now reported on page 8 line 175 for adult rats, and page 15 line 341 for adolescent rats. These results appear to be at odds with the idea that decreased neuronal activity in premature trials is the result of a cut-off of the response.
- The difference between adult and adolescent rats are not particularly big, with the data from the adolescent rats showing a noisy trace.
New data from two adolescent rats reduced the variability and confirmed the behavioral and physiological differences with adult rats. All panels from figure 7 now include the data from 5 adolescent animals instead of 3. The number of neurons analyzed in the adolescent group passed from 552 to 876. The inclusion of these new data allowed us to perform new statistical comparisons. We adjusted a logistic function to accumulated trial initiation timing data (Fig.7N) and found that the rate of accumulation is higher in adolescent rats. Importantly, this is observed not only in the part of the curve corresponding to premature responding but also during timely responding, indicating that adolescent rats' premature responding is a manifestation of a more general behavioral trait that makes them self-initiate trials faster than adults (Fig. 7N). The noisy trace of curves showing the amplitude modulation of anticipatory activity as a function of waiting time was partly due to the relatively low number of premature trials that demanded using relatively long time bins. With more data available we have been able to replot these curves using a smaller bin size for the short waiting times (Fig. 7M). We have adjusted a logistic function to these data and observed a higher rate of increase of this activity modulation in adolescent rats, paralleling the behavioral data. Moreover, we report a significant correlation between the behavioral and neurophysiological data (a steeper rate of trial initiation times curve correlates with a steeper wait modulation of anticipatory activity, Fig. 7O). These new findings are reported in the results section, from page 17 line 405 to page 18 line 417.
Reviewer #2 (Public Review):
The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to how animals can wait to perform an action sequence for reward. There are a lot of interesting studies on striatal encoding of actions/skills, and additionally evidence that striatal activity can help control response timing and time-related response selection. The authors bridge these issues here in an impressive effort. Recordings were made in the dorsal striatum on several tasks, and activity was assessed with respect to action initiation, completion, and outcome processing with respect to whether animals could wait appropriately or could not wait and responded prematurely. Conducting recordings of this sort in this task, particularly in some adolescent animals, is technically advanced. I think there is a very timely and potentially very interesting set of results here. However, I have some concerns that I hope can be addressed:
It seems like the recordings were made throughout the dorsal striatum (histology map), including some recordings near/in the DLS. Is this accurate? The manuscript is written as though only the DMS was recorded.
We acknowledge that our recordings are spread along the medial and central regions of the dorsal striatum. Although we are not sure that there is a consensus regarding the limits of the DMS and DLS, we believe that none of our recordings are clearly located within the DLS. Following your suggestion, we have modified the text and refer to the location of our recordings as “dorsal striatum”. We believe that, as there is a lot of work on the roles of the DLS and DMS in reward learning, it is still important to refer to this work in the Introduction section and to discuss our findings in its context, particularly, since we find that most task-related activity is concentrated at the beginning and end of the task as shown in several studies focused in the DLS.
If I understand correctly, the rats must lick 8 times to get the water. If this is true, one strategy is to just keep licking until the water comes. Therefore, the rats may not have learned an 8-lick action sequence. The authors should clarify this possibility, and if it is, to consider avoiding using phrases like "automatized action sequence" since no real action sequence might have been learned. In short, I am not convinced the animals have learned an action pattern rather than to just keep licking once a waiting period has elapsed.
We acknowledge that the experiments do not allow us to establish if the rats know what the exact number of licks needed is; when the skill is acquired, licking becomes highly stereotyped and the rats might as well be learning a time after which continuous licking leads to reward. We still believe that the stereotyped performance, the inability to stop the behavior when the absence of the light cue unequivocally indicates that no reward will be obtained in premature trials, and the rapid decrease of lick rate after the eighth lick was emitted and no reward was obtained, support that the behavior is automatic until the time of expected reward delivery. A representative raster plot showing lick sequences during a whole session in a trained adult rat is presented in Fig. 1I and Figure 7 – supplement 1H shows an example of the licks of an adolescent rat.
The number of subjects per group is very low. This is fine for analysis of within-animal neural activity. However, comparing the behavior between these groups of animals does not seem appropriate unless the Ns are substantially increased.
The revised version of the manuscript includes a higher number of adolescent rats from which striatal activity and behavior were recorded, which allowed us to perform a more detailed statistical analysis of the correlations between these measures. In addition, we now include new behavioral data from an independent sample of non-implanted 6 adults and 6 adolescent rats that confirms the results obtained with the implanted animals (presented in Figure 7 – supplement 4).
I found the manuscript difficult to decipher. There are many groups. If I understand correctly, there are the following:
-ITI 2.5s experiment
-ITI 5 s experiment
-ITI2.5-5s experiment
-ITI 2.5 s experiment (adolescent)
-Two accelerometer animals (unclear which experiment)
-Two animals in ITI 2.5 sec without recordings (unclear how incorporated into analyses)
Within each group, there are multiple categories of behavioral performance. This produces a large list of variables. In some parts of the results, these groups are separated and compared, but not all groups are compared in those such sections. In other sections the different groups (all or just some?) appear to be combined for analysis, but it is not clearly described. Another consequence of mixing the groups and conditions together in analysis as they do is that some of the statements in the results are very hard to follow (E.g., line 305 "...similar behavior observed in 8-lick prematurely released and timely unrewarded trials...").
To clarify the experimental groups, we now include a table (Table 1) summarizing which tasks were used and how many animals were trained in each task.
Generally, it is difficult to understand the results without first understanding the details of the different tasks, the different groups of animals, and the different epochs of comparison for neural analysis. It took me a long time to work through the methods and I am still not sure I completely understand it. On this point, some sentences are very long and should be broken up into smaller, clearer sentences. There are a lot of phrases that only someone familiar with the cited articles might understand what they mean (e.g., even one paragraph starting with line 39 includes all of the following terms: automaticity in behavior; behavioral unit or chunk; reward expectancy; reward prediction errors and trial outcomes; explore-exploit; cost-benefit; speed-accuracy tradeoffs; tolerance to delayed rewards; internal urgency states). It is very hard to follow how each of these processes are to be understood in terms of behavioral measures used to study them and how they do or do not relate to the hypothesis of the present study. The discussion similarly uses a lot of different phrases to discuss the task and neural responses in a way that makes it hard to understand exactly what the author's interpretation of the data are. Is there maybe a 'most likely' interpretation that can be stated for some of the responses?
Our main aim is to disclose the mechanisms underlying differences between adult and adolescent rats relating to impulsivity. We hope that this will become clearer in this version of the manuscript after deepening the analysis of the differences between them. We believe that our data do not allow us to unequivocally determine what is the ultimate cognitive process producing the striatal activity differences between adult and adolescent rats, i.e., differences in internal urgency states, time perception, tolerance to delayed rewards, and tried to reflect that fairly in the Discussion.
The data set is extremely rich; there are lot of data here. As a result it can be hard to understand how all of the data relate to the main hypothesis of the article. It often reads as an exploratory set of results section rather than a series of hypothesis tests.
We have tried to improve the overall clarity of the text.
Reviewer #3 (Public Review):
Cecilia-Martinez et al., implement a task that allows the study of premature versus timely actions in rats. First, they show that rats can learn this task. Next, they record the activity in the DMS showing start/stop signals in the cells recorded, next they propose that the activity detected before the release of actions sequences discriminate the premature vs the timely initiations showing a relationship between the waiting time and the activity of cells recorded, furthermore they show that it could be the expectancy of reward what could be encoded in the activity before entering the port. Last they show that adolescent rats show more premature starts than adult rats documenting a difference in activity modulation of DMS cells in the relation between waiting time and firing rate (although above the premature threshold, see comments below).
Overall the paper is well presented describing a well-developed set of experiments and deserves publication attending only minor comments.
- I understand rats learn to execute sequences of <8licks or 8 licks, although diagrams are presented, no examples of the individual trials with 8 licks, neither distributions of bouts of these licks are presented.
Rats learn to execute a lick sequence to obtain the reward. The experiments do not allow us to establish if they know what the exact number of licks needed is; when the skill is acquired, licking becomes highly stereotyped and the rats might as well be learning a time after which continuous licking leads to reward. A representative raster plot showing lick sequences in a session in a trained adult rat is presented in Figure 1I and Figure 7 - supplement 1H shows an example of the licks of an adolescent rat.
- Relevant to the statement: "in this task, the firing rate modulation preceding trial initiation discriminates between premature and timely trials and does not predict the speed, regularity, structure, value or vigor of the subsequently released action sequence"... It is not clear if the latency to first lick (plot 2D) and the inter-lick interval (2E) is only from the 8Lick sequences or not. If that is not the case, it is important to compare only the ones with 8Licks.
The data are from 8 lick sequences, this is now indicated in the figure legend.
- Related to the implications of the previous statement, there seems to be a tendency for longer latency to first lick in timely vs premature trials in Figure 2D (timely-trials-Late vs premature-trials-late)? Again here it is important to compare the 8licks sequences only.
Only 8-lick sequences are compared and the two-way ANOVA showed a significant effect of the training stage without significant effects of trial timing (premature versus timely) and a non-significant interaction. The average ± SEM latencies to the first lick (of the eighth lick sequence) were 0.717 s ± 0.063 for timely trials late and 0.805 s ± 0.086 for premature trials late.
- I could not find in the main text whether the individual points in Fig.2 (e.g. 2B-E) are individual animals. Please specify that.
In this figure panels every individual point corresponds to the mean of a session, the data correspond to 5 adult animals (2-5 sessions per animal and timing condition). Whether the data correspond to animals or sessions is now clarified in all figure legends.
- Although very elegant the argument presented in Figure 4C and 6C, I wonder if the head acceleration may lose differences in movements outside the head in the two kinds of trials. If that is the case please acknowledge it.
We acknowledge in the main text, results section, page 8, line 180, that the accelerometer does not allow us to determine if the movements of other body parts differ between trial types.
- Also in 4C, small separations between timely vs premature signals are seen before 0. Is there a way to know if animals in timely vs premature trials approached the entry port in the same way? This request is pertinent in order to rule out motor contribution to the differences in Figure 4A-B.
Although it is not possible to completely rule out small movement differences between premature and timely trials, no evident behavioral differences can be detected by trained observers or by analyzing video recordings taken during some sessions. The available accelerometer recordings also suggest that a similar motor pattern is displayed in premature and timely trials (Figure 4C).
- when saying: "Similar results were obtained in rats trained with a longer waiting interval (Supplementary Figure 5)", "is hard to see the similarity in the premature range, while in the 2.5 seconds task there is a positive relationship in the 5 seconds task it is not.
Please note that a positive relationship is observed for the two bins preceding trial initiation, which are about 2.75s and 1s before port entry. The bin that seems to not fit is centered 4s before port entry (1s after exiting the port in the previous trial). Because of the longer waiting time, in the 5 s task behavior becomes less organized during the first seconds after port exit, however, the modulation of activity is still observed in the bins that are close to port entry.
- The data showing that the waiting modulation of reward anticipation grows at a faster rate in adolescent rats is clear, however, it is not clear how it could be related to the data showing that the adolescent rats were more impulsive.
We acknowledge that the data do not provide a causal link with behavior. After adding two new adolescent rats we have been able to study in more detail the relationship between the waiting modulation of neuronal activity and the accumulation of trial initiations (depicted in figures 7M and 7N respectively) by adjusting logistic functions to the data. The new results are explained on page 17,line 384. There is a striking parallel between the growth rate of both curves, and the curves of adolescent rats are significantly steeper than those of adult rats. Moreover, there is a significant correlation between the coefficients that mark the rate of growth of the behavioral and neurophysiological data (Fig. 7O).
- Related to the sentence: "the strength of anticipatory activity increased with the time waited before response release and was higher in the more impulsive adolescent rats"....One may expect to see a difference in the range of the premature time however the differences were observed in the range >2.5 seconds. Please explain how to reconcile this finding with the fact that the adolescent rats were more impulsive.
Please, note that the more impulsive behavior of adolescent rats (and the faster growth of the wait modulation of anticipatory activity) is observed along waiting times that exceed the 2.5s criterion wait time; we added a phrase in the Results section (page 18, lines 413) and in the Discussion section (page 19, line 443) to emphasize this point. Regarding the premature trials, a related issue was raised by reviewer #1, concern 4. The addition of new data from adolescent animals allowed us to used smaller bins to better discriminate what happens at short waiting times and included an inset in Figure 7M that allows to better appreciate what happens at these intervals.
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Evaluation Summary:
This manuscript investigates an important topic related to the initiation signals of actions sequences detected in the dorsal striatum. The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to the ability to wait for a reward. The study nicely bridges research on striatum's roles in reward-seeking actions and in time processing. Interesting activity patterns are detected that suggest a relationship to the premature versus the timely release of actions. These observations are potentially interesting, in particular, the possible difference between adult and adolescent rats. The functional significance of these activity patterns remain to be examined.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors …
Evaluation Summary:
This manuscript investigates an important topic related to the initiation signals of actions sequences detected in the dorsal striatum. The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to the ability to wait for a reward. The study nicely bridges research on striatum's roles in reward-seeking actions and in time processing. Interesting activity patterns are detected that suggest a relationship to the premature versus the timely release of actions. These observations are potentially interesting, in particular, the possible difference between adult and adolescent rats. The functional significance of these activity patterns remain to be examined.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
The authors trained rats to self-initiated a trial by poking into a nose poke, and to make a sequence of 8 licks in the nose poke after a visual cue. Trials were considered valid (called "timely") only if rats waited for more than 2.5 sec after the end of the previous trial. An attempt to initiate a trial (nose poking) before the 2.5 sec criterion was regarded as "premature". The authors recorded from the dorsal striatum while rats performed in this task. The authors first show that some neurons exhibited a phasic activation around the time of port entry detected using an infrared detector ("Entry cell"), as well as port exit ("Exit cell). Some neurons showed activation at both entry and exit ("Entry and Exit cell") or between these two events ("Inside-port cell"). Fractions of neurons that fall into these …
Reviewer #1 (Public Review):
The authors trained rats to self-initiated a trial by poking into a nose poke, and to make a sequence of 8 licks in the nose poke after a visual cue. Trials were considered valid (called "timely") only if rats waited for more than 2.5 sec after the end of the previous trial. An attempt to initiate a trial (nose poking) before the 2.5 sec criterion was regarded as "premature". The authors recorded from the dorsal striatum while rats performed in this task. The authors first show that some neurons exhibited a phasic activation around the time of port entry detected using an infrared detector ("Entry cell"), as well as port exit ("Exit cell). Some neurons showed activation at both entry and exit ("Entry and Exit cell") or between these two events ("Inside-port cell"). Fractions of neurons that fall into these four categories are roughly the same (Fig. 3C). The main conclusions drawn from this study are that (1) the activity preceding a port entry was positively correlated with the latency to initiate a trial (or "waiting time"; Fig. 4E), which appear to reflect the value upcoming reward, and that (2) in adolescent rats, the activity rose more steeply with the latency to trial initiation (Fig. 7J).
These observations are potentially interesting, in particular, the possible difference between adult and adolescent rats is intriguing. However, this study does not examine whether this brain region actually plays a role in the task. Some of the conclusions appear to be premature.
1. Previous studies have found correlations between the activity of neurons in the striatum and the latency to trial initiation (e.g. Wang et al., Nat. Neurosci., 2013) or action initiation more generally (e.g. Kunimatsu et al., eLife, 2018). In the former study, the trial initiation was self-generated, similar to the present study, and was modulated by the overall reward value (state value). In the latter study, the latency was instructed by a cue. Furthermore, there are many studies that showed correlations between striatal activity and future rewards (e.g. Samejima et al., Science, 2005; Lau and Glimcher, 2008). Many of these studies varied the value of upcoming reward (e.g. amount or probability). Although some details are different, the basic concepts have been demonstrated in previous studies.
2. The authors conclude that "in this task, the firing rate modulation preceding trial initiation discriminates between premature and timely trials and does not predict the speed, regularity, structure, value or vigor of the subsequently released action sequence". This conclusion is based on the observation that premature and timely trials did not differ in terms of kinematic parameters as measured using accelerometer. Although the result supports that the difference in activity between premature and timely cannot be explained by the kinematic variables, it does not exclude the possibility that the activity is modulated by some kinematic variables in a way orthogonal to these trial types.
3. The firing rate plot shown in Figure 4D should be replotted by aligning trials by movement initiation (presumably available from accelometer or video recording). Is it possible that the activity rise similarly between trials types but the activity is cut off depending on when the animal enters the port at different latency from the movement initiation? In any case, the port entry is a little indirect measure of "trial initiation".
4. The difference between adult and adolescent rats are not particularly big, with the data from the adolescent rats showing a noisy trace.
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Reviewer #2 (Public Review):
The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to how animals can wait to perform an action sequence for reward. There are a lot of interesting studies on striatal encoding of actions/skills, and additionally evidence that striatal activity can help control response timing and time-related response selection. The authors bridge these issues here in an impressive effort. Recordings were made in the dorsal striatum on several tasks, and activity was assessed with respect to action initiation, completion, and outcome processing with respect to whether animals could wait appropriately or could not wait and responded prematurely. Conducting recordings of this sort in this task, particularly in some adolescent animals, is technically advanced. I …
Reviewer #2 (Public Review):
The authors conduct an ambitious set of experiments to study how neural activity in the dorsal striatum relates to how animals can wait to perform an action sequence for reward. There are a lot of interesting studies on striatal encoding of actions/skills, and additionally evidence that striatal activity can help control response timing and time-related response selection. The authors bridge these issues here in an impressive effort. Recordings were made in the dorsal striatum on several tasks, and activity was assessed with respect to action initiation, completion, and outcome processing with respect to whether animals could wait appropriately or could not wait and responded prematurely. Conducting recordings of this sort in this task, particularly in some adolescent animals, is technically advanced. I think there is a very timely and potentially very interesting set of results here. However, I have some concerns that I hope can be addressed:
It seems like the recordings were made throughout the dorsal striatum (histology map), including some recordings near/in the DLS. Is this accurate? The manuscript is written as though only the DMS was recorded.
If I understand correctly, the rats must lick 8 times to get the water. If this is true, one strategy is to just keep licking until the water comes. Therefore, the rats may not have learned an 8-lick action sequence. The authors should clarify this possibility, and if it is, to consider avoiding using phrases like "automatized action sequence" since no real action sequence might have been learned. In short, I am not convinced the animals have learned an action pattern rather than to just keep licking once a waiting period has elapsed.
The number of subjects per group is very low. This is fine for analysis of within-animal neural activity. However, comparing the behavior between these groups of animals does not seem appropriate unless the Ns are substantially increased.
I found the manuscript difficult to decipher. There are many groups. If I understand correctly, there are the following:
-ITI 2.5s experiment
-ITI 5 s experiment
-ITI2.5-5s experiment
-ITI 2.5 s experiment (adolescent)
-Two accelerometer animals (unclear which experiment)
-Two animals in ITI 2.5 sec without recordings (unclear how incorporated into analyses)Within each group, there are multiple categories of behavioral performance. This produces a large list of variables. In some parts of the results, these groups are separated and compared, but not all groups are compared in those such sections. In other sections the different groups (all or just some?) appear to be combined for analysis, but it is not clearly described. Another consequence of mixing the groups and conditions together in analysis as they do is that some of the statements in the results are very hard to follow (E.g., line 305 "...similar behavior observed in 8-lick prematurely released and timely unrewarded trials...").
Generally, it is difficult to understand the results without first understanding the details of the different tasks, the different groups of animals, and the different epochs of comparison for neural analysis. It took me a long time to work through the methods and I am still not sure I completely understand it. On this point, some sentences are very long and should be broken up into smaller, clearer sentences. There are a lot of phrases that only someone familiar with the cited articles might understand what they mean (e.g., even one paragraph starting with line 39 includes all of the following terms: automaticity in behavior; behavioral unit or chunk; reward expectancy; reward prediction errors and trial outcomes; explore-exploit; cost-benefit; speed-accuracy tradeoffs; tolerance to delayed rewards; internal urgency states). It is very hard to follow how each of these processes are to be understood in terms of behavioral measures used to study them and how they do or do not relate to the hypothesis of the present study. The discussion similarly uses a lot of different phrases to discuss the task and neural responses in a way that makes it hard to understand exactly what the author's interpretation of the data are. Is there maybe a 'most likely' interpretation that can be stated for some of the responses?
The data set is extremely rich; there are lot of data here. As a result it can be hard to understand how all of the data relate to the main hypothesis of the article. It often reads as an exploratory set of results section rather than a series of hypothesis tests.
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Reviewer #3 (Public Review):
Cecilia-Martinez et al., implement a task that allows the study of premature versus timely actions in rats. First, they show that rats can learn this task. Next, they record the activity in the DMS showing start/stop signals in the cells recorded, next they propose that the activity detected before the release of actions sequences discriminate the premature vs the timely initiations showing a relationship between the waiting time and the activity of cells recorded, furthermore they show that it could be the expectancy of reward what could be encoded in the activity before entering the port. Last they show that adolescent rats show more premature starts than adult rats documenting a difference in activity modulation of DMS cells in the relation between waiting time and firing rate (although above the …
Reviewer #3 (Public Review):
Cecilia-Martinez et al., implement a task that allows the study of premature versus timely actions in rats. First, they show that rats can learn this task. Next, they record the activity in the DMS showing start/stop signals in the cells recorded, next they propose that the activity detected before the release of actions sequences discriminate the premature vs the timely initiations showing a relationship between the waiting time and the activity of cells recorded, furthermore they show that it could be the expectancy of reward what could be encoded in the activity before entering the port. Last they show that adolescent rats show more premature starts than adult rats documenting a difference in activity modulation of DMS cells in the relation between waiting time and firing rate (although above the premature threshold, see comments below).
Overall the paper is well presented describing a well-developed set of experiments.
I understand rats learn to execute sequences of <8licks or 8 licks, although diagrams are presented, no examples of the individual trials with 8 licks, neither distributions of bouts of these licks are presented.
Relevant to the statement: "in this task, the firing rate modulation preceding trial initiation discriminates between premature and timely trials and does not predict the speed, regularity, structure, value or vigor of the subsequently released action sequence"... It is not clear if the latency to first lick (plot 2D) and the inter-lick interval (2E) is only from the 8Lick sequences or not. If that is not the case, it is important to compare only the ones with 8Licks.
Related to the implications of the previous statement, there seems to be a tendency for longer latency to first lick in timely vs premature trials in Figure 2D (timely-trials-Late vs premature-trials-late)? Again here it is important to compare the 8licks sequences only.
I could not find in the main text whether the individual points in Fig.2 (e.g. 2B-E) are individual animals. Please specify that.
Although very elegant the argument presented in Figure 4C and 6C, I wonder if the head acceleration may lose differences in movements outside the head in the two kinds of trials. If that is the case please acknowledge it.
Also in 4C, small separations between timely vs premature signals are seen before 0. Is there a way to know if animals in timely vs premature trials approached the entry port in the same way? This request is pertinent in order to rule out motor contribution to the differences in Figure 4A-B.
when saying: "Similar results were obtained in rats trained with a longer waiting interval (Supplementary Figure 5)", "is hard to see the similarity in the premature range, while in the 2.5 seconds task there is a positive relationship in the 5 seconds task it is not.
The data showing that the waiting modulation of reward anticipation grows at a faster rate in adolescent rats is clear, however, it is not clear how it could be related to the data showing that the adolescent rats were more impulsive.
Related to the sentence: "the strength of anticipatory activity increased with the time waited before response release and was higher in the more impulsive adolescent rats"....One may expect to see a difference in the range of the premature time however the differences were observed in the range >2.5 seconds. Please explain how to reconcile this finding with the fact that the adolescent rats were more impulsive.
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