Sex-dependent noradrenergic modulation of premotor cortex during decision-making

Article activity feed

1. 

   Version published to 10.7554/elife.85590 on eLife

   Aug 22, 2023
2. 

   eLife

   Jul 10, 2023

   Author Response

   Reviewer #1 (Public Review):

   Various parts of the premotor cortex have been implicated in choices underlying decisionmaking tasks. Further, norepinephrine has been implicated in modulating behavior during various decision-making tasks. Less work has been done on how noradrenergic modulation would affect M2 activity to alter decision-making, nor is it clear whether noradrenergic modulation effects on activity would differ between the male and female sexes.

   This manuscript addresses some of these questions.

   • In particular, clear sex differences in task engagement are seen.

   • May also show some interesting differences and distributions of β2 adrenergic receptors in M2 between males and females.

   We thank the reviewer for their summary of our findings and thoughtful critique of our manuscript. In our revised manuscript …

   Author Response

   Reviewer #1 (Public Review):

   Various parts of the premotor cortex have been implicated in choices underlying decisionmaking tasks. Further, norepinephrine has been implicated in modulating behavior during various decision-making tasks. Less work has been done on how noradrenergic modulation would affect M2 activity to alter decision-making, nor is it clear whether noradrenergic modulation effects on activity would differ between the male and female sexes.

   This manuscript addresses some of these questions.

   • In particular, clear sex differences in task engagement are seen.

   • May also show some interesting differences and distributions of β2 adrenergic receptors in M2 between males and females.

   We thank the reviewer for their summary of our findings and thoughtful critique of our manuscript. In our revised manuscript we have taken measures to address the reviewer’s comments in line (blue edits in text and revised figures) with direct responses outlined below. We believe these revisions improve the scientific rigor of our findings and provide relevant context for our studies. We hope that they have sufficiently addressed the reviewer’s concerns.

   Less clear is the specificity of systemic antagonism of β adrenergic receptors on the changes in M2 activity reported. As propranolol was given systemically, changes in M2 firing rates could also be due to broader circuit (indirect) activity changes. As it was not given locally, nor were local receptor populations manipulated, one is unable to make the conclusion that changes in neural activity are due to the direct effects of adrenergic receptors within M2 populations.

   We agree that propranolol driven changes in anterior M2 activity may arise via multiple mechanisms, including direct action on the adrenoreceptors within M2, and indirect action via other regions that project to M2. Although locally activating inhibitory interneurons within M2 is sufficient to disrupt cueguided action plans and behavior in a 2AFC task (Inagaki et al., 2018), our noradrenergic manipulation was not restricted to M2. We have clarified our conclusions and provided additional discussion to highlight that propranolol actions were multifaceted and that direct actions in M2 are likely working in concert with propranolol mediated actions in other regions.

   Also not clear, is the contribution of M2 to this task, and whether the changes in M2 activity patterns observed are directly responsible for the behavioral disruptions measured.

   We have revised our introduction and discussion to more clearly outline the critical role of cue-guided action plans in M2 for successful behavior in 2AFC tasks. Suppression of cue-guided activity in M2 results in behavioral performance at near chance levels, similar to what we saw in females after propranolol (Guo et al., 2017; Inagaki et al., 2018; Li et al., 2016). Furthermore, targeted photostimulation of action plan encoding neurons in M2 is sufficient to drive behavioral responses (Daie et al., 2021). In our investigations it is plausible to expect propranolol related disruptions in other cognitive, sensory or motor regions. Based on the strong foundational evidence for M2 activity in 2AFC, the propranolol driven changes in anterior M2 in females, whether direct or indirectly mediated, are likely sufficient to drive behavioral disruptions in accuracy and/or trial completion.

   Reviewer #2 (Public Review):

   This paper by Rodbarg et al describes an interesting study on the role of beta noradrenergic receptors in action-related activity in the premotor cortex of behaving rats. This work is precious because even if the action of neuromodulatory systems in the cortex is thought to be critical for cognition, there is very little data to actually substantiate the theories. The study is well conducted and the paper is well written. I think, however, that the paper could benefit from several modifications since I can see 3 major issues:

   We thank the reviewer for their generous comments on the potential impact of our manuscript as well as their suggestions to improve this work. Below we outline responses to specific comments raised by the reviewer in addition to adresing them in the revised manuscript. We hope these responses sufficiently address the reviewer’s concerns.

   Both from a theoretical and from a practical point of view, the emphasis on 'cue-related' activity and the potential influence of NA on sensory processing is problematic. First, recent studies in rodents and primates have clearly demonstrated that LC activation is more closely related to actions than to stimulus processing (see Poe et al, 2020 for review).

   Indeed during optimal performance the peaks of LC activity are larger when PETH are aligned to action initiation rather than the cue itself (Clayton et al., 2004). This alignment resolves variability in decision processing times and omitted cues. Although LC responses align with action they are evoked by, and occur after, cue presentation with LC responses to visual cues occurring ~ 60ms after presentation (Aston-Jones & Bloom, 1981). The same behavioral action without preceding task relevant cues does not evoke an LC response (Rajkowski et al., 2004)

   In our current study cues initiate activity in anterior M2, this is our primary interest and where our electrodes are placed. The window between cue delivery and action completion hones in on our goal of investigating the role for β noradrenergic signaling in target cortical processing, rather than LC explicitly. In both NHP and rodents NE signaling (and evoked LC) promotes sustained cortical representations between cue onset and actions across cortical regions (dlPFC, S1) (Ramos & Arnsten, 2007; Vazey et al., 2018; Wang et al., 2007). In the current study we aligned neural data to either cue presentation (Figure 3) or action (lever press; Figure 4). Both presentations support a critical role for β adrenoreceptor signaling in suppressing irrelevant information, resolving and maintaining action plans. A unique feature of aligning the data to cue onset is that it allows us to see how the neural activity changes not only on completed trials (that end with a lever press) but also on omitted trials (which strongly increase after propranolol). We propose the reason we are seeing large increases in omitted trials is because β adrenoreceptor blockade either directly or indirectly prevents anterior M2 from resolving an action plan.

   Second, the analysis of neural activity around cue onset should be examined with spikes aligned on the action, since M2 is a motor region and raster plots suggest that activity is strongly related to action (I'll be more specific below).

   We agree that M2 shows important action plan activity which we highlight throughout the manuscript. In cued tasks, M2 neurons have been shown to represent action plans starting at cue onset that continues up to behavioral execution. Neural data was examined and results presented aligned to cue onset (illustrated in Figure 3) and aligned to action - lever press (illustrated in Figure 4). The impact of propranolol in diminishing action plan selection was similar in both action, and cue-aligned analyses.

   The distinction between neural activity and behavior or cognition is not always clear. I understand that spike count can be related to motor preparation or decision, but it should not be taken for granted that neuronal activity is action planning. The analysis should be clarified and the relation between neural activity, behavior, and potential hidden cognitive operations should be explicated more clearly.

   We have worked to clarify in our revised introduction, results and discussion the specifics of the known roles of neural activity in M2 in both action planning and decision making. We further expand that the neuronal activity in our study may reflect potential changes in cognitive processing and thus alter resultant behavioral outcomes.

   The sex difference is interesting, but at the moment it seems anecdotal. From a theoretical point of view, is there any ecological/ biological reason for a sex dependency of noradrenergic modulation of the cortex? Is there any background literature on sex differences in motor functions in rats, or in terms of NA action? If not, why does it matter (how does it change the way we should interpret the data?) From a practical point of view, is there a functional sex difference in absence of treatment, or is it that the drug has a distinct effect on males vs females? This has very distinct consequences, I think.

   We did not find overt differences in behavior in the absence of treatment. Only when noradrenergic function was challenged using propranolol did we identify functional sex differences. We agree that this has very distinct consequences – specifically it supports sex differences that can be revealed by perturbations of normal function. These functional sex differences may be a result of differences in the anatomy of central noradrenergic systems, a hypothesis further supported by our mRNA expression findings and existing literature on LC anatomy across species (Bangasser et al., 2011, 2016; Luque et al., 1992; Mulvey et al., 2018; Ohm et al., 1997; Pinos et al., 2001). Collectively these results have potential ramifications for understanding sex differences in disease prevalence and targeted treatments.

   Background literature supports some innate sex differences in motor function and executive function in rodents and humans. Of particular relevance to our investigation is an established difference in behavioral strategy with females being more risk averse than males (Grissom & Reyes, 2019). Ethologically risk adverse strategies may support parental care roles, and increased inhibitory mechanisms may be selected for in females. Although this strategy was not directly tested in our study, the large increase in omissions after propranolol seen in females is in line with avoiding risk (incorrect choices) during uncertainty (disrupted neural signaling). As with other executive functions, the utilization of norepinephrine within the cortex along with other neuromodulators, and local microcircuit interactions would all contribute to promoting risk averse behavior.

   These issues could be clarified both in the introduction and in the discussion, but the authors might have a different view on what is theoretically relevant here. In the result section, however, I think that both the lack of specificity in the description of behavior and cognitive operation and the confusion between 'sensory' and 'motor' functions make it very difficult to figure out what is going on in these experiments, both at a behavioral and at a neurophysiological level. First, the description of the behavior in the task is clearly not sufficient, which makes the interpretation of the measures very difficult.

   We have made an effort to better specify the task and relevant behavioral operations in both the methods and results and have included a clearer task schematic (Figure 1A). We agree that the confusion between ‘sensory’ and ‘motor’ functions may make it more difficult to understand the findings in this study. Anterior M2 plays a unique role in representing motor/action plans that can be informed by sensory information. This integrative function creates difficulty in parsing the neural activity of anterior M2 as strictly motor, sensory or cognitive. In attempts to improve clarity we have expanded and highlighted relevant information on the known roles of M2 in the introduction and discussion.

   One possible interpretation of the effects of the drug is a decrease in motivation, for instance, due to a decrease in reward sensitivity or an increase in sensitivity to effort. But there are others. More importantly, none of these measures can be used to tease apart action preparation from action execution, even though the study is supposed to be about the former.

   Neural activity during action planning, prior to action execution is known to be an essential function of M2 (Barthas & Kwan, 2017; Gremel & Costa, 2013; Guo et al., 2017; Inagaki et al., 2018, 2022; Li et al., 2016; Siniscalchi et al., 2016; Sul et al., 2011; Wei et al., 2019) for optimal performance in 2AFC tasks. In all, we found that the representation/separation of opposing action plans (a well validated function of M2) prior to responses (lever press) is degraded after propranolol, especially in females. We have provided additional emphasis on these foundational studies throughout our revised manuscript.

   To minimize impact of motivational factors, effort and reward size remain consistent within our task, and all trials require a random initiation hold prior to cue delivery. As described in our general response to the editor above (Figure 1, above), we investigated whether motivational changes may be reflected in our M2 recordings. PETHs from the first and last 10 trials within saline sessions did not identify potential motivation related differences in anterior M2 activity. Similarly, across propranolol sessions the neural activity was consistent between early and late trials. We used early and late trials as there was a mild decrease in trial rate during saline sessions in both males and females, potentially indicative of motivation/reward sensitivity changes during these sessions. M2 neural responses consistently separate action plans (after saline) or failed to separate action plans (propranolol sessions).

   Also, but this is less critical: In Figures 2C and D, it looks like there is a bimodal distribution for the effect of propranolol in females. Is there something similar in the neuronal effects of the drug? And in the distribution of receptors? Can it be accounted for by hormonal cycles/ anything else?

   Although there is some clustering in behavioral outcomes all data passed normality assumption as appropriate. Propranolol treatments were not synchronized to hormonal cycles, and the data likely include animals at various hormonal stages. Similar clustering was not apparent in neuronal effects of propranolol, although propranolol increased variability in many measures.

   In a pilot experiment we did not see any difference in baseline performance on our 2AFC task across the hormonal cycle (diestrous, proestrous, estrous or metestrous) of females in any measure including accuracy (F(3,33)=0.59, p=0.63, one-way ANOVA) and omissions (F(3,33)=0.51, p=0.68).

   The description of neural activity is also very superficial. In general, it is not clear how spike count measures have been extracted. For example, legend and figure C are not clear, is the (long) period of cue presentation included in the 'decision time'?? "Cues were presented at a variable interval 200-700ms after initiation and until animals left the well, 'Well Exit'. The time from cue onset to well exit was identified as the decision time (yellow)." Yet on the figure only the period after cue presentation is in yellow. This is critical because, given the duration of the cue, the animals are probably capable of deciding (to exit the well) before the cue turns off. Indeed, as shown in fig 2D, the animals can decide within about 500 ms. So to what extent is the 'cue response' actually a 'decision response'?

   We have clarified the task and spike count measurements in methods and added a revised task schematic. It is correct that the cues are available throughout the decision time (for up to 5 seconds or until well exit), and an action plan is generated before well exit/cues turn off as reflected by the separation of neural action plans (Fig 3, saline). Anterior M2 neurons maintain action plan representation from cue onset until the lever press under normal conditions (Fig 4, saline). These action plans encapsulate “cue responses” and “decision responses”. We have aligned neural data to discrete timestamps at either end of the window in which M2 processing is known to be critical, specifically between cues and actions (lever press) and focus on neural activity relative to those points. We refer to this activity throughout the manuscript as an ‘action plan’ as action planning functions of M2 activity have been well established in prior studies.

   When looking at figure 3A, there is clearly a pattern on the raster, a line going from top left to bottom right. If the trials are sorted chronologically, something is happening over time. If, as I suspect, trials are sorted by ascending response time, this raster is showing that what authors are calling a 'response to cues' is actually a response around action. Basically, if propranolol slows down reaction time, the spikes will be delayed from cue onset only because they remain locked to the action. Then the whole analysis and interpretation need to be reconsidered. But it might be for the best: as I mentioned earlier, recent work on LC activity has clearly emphasized its influence on motor rather than sensory processing (Poe et al, 2020).

   Figure 3A is a single neuron example, and data analyses focus on population-wide activity. Neural data is presented both aligned to cues, for all trials in which a cue was received, and aligned to lever press (action), for all trials on which a lever press occurred. In both cases, aligned to cue or aligned to action, the impact of propranolol is the same. β adrenoreceptor blockade reduces the separation of action plans in M2, severely so in females. However, a major finding is that females receive a cue but omit a large number of trials after propranolol, for this outcome the action does not occur. We propose this is due to the lack of action plan separation in anterior M2 (either directly or indirectly). When no behavioral response occurs, these trials cannot be aligned to action, yet we are still interested in the neural activity during the critical window between cue delivery and actions. We are not assigning this neural activity to sensory processing but using this discrete sensory event within our trials (cue) to align the data as there is substantial evidence that action plans in M2 arise after cue presentation in tasks such as ours where performance is guided by external cues.

   Fig 2D-F: it is hard to believe that the increase in firing rate induced by propranolol in females is not significant. Presumably, because the range of the median firing rate is so high in the first place, distribution (2E) really indicates an increase in firing. Maybe some other test? e.g paired t.test, or standardized values (z.score) to get rid of variability in firing across neurons?

   We agree that the session wide firing rate appears rightward shifted in females after propranolol. As our recordings were taken on different days, several days apart we cannot assume they are the same neurons for paired analyses. In our revised manuscript we evaluated these distributions using a MannWhitney test to increase power and decrease the impact of variability within the population. Previously we had used a Kolmogorov-Smirnov test. Using our new analysis, we can confirm that the propranolol significantly increases session wide firing rates in anterior M2 of females (p=0.027) but not males. This finding increases evidence for direct actions of propranolol within M2 and supports our hypothesis that propranolol leads to local disinhibition by reducing β noradrenergic signaling in interneurons and that without this noradrenergic tone anterior M2 is less efficient at suppressing irrelevant action plans.

   Along those lines, would it be worth looking for effects on specific populations (interneurons) which are sometimes characterized by thinner spikes and higher mean firing rates? Given the distribution of beta receptors RNA on interneurons, one would actually expect an effect of propranolol on the firing rate irrespective of task events. Or what is it that prevents the influence of propranolol on interneurons from changing the firing rate? In any case, one of the strengths of this study is the localization of beta receptors on specific neuronal populations in the cortex, so I think that the authors should really try to build on it and find something related to the neurophysiological effects. Otherwise, one cannot exclude the possibility that the behavioral effects are not related to the influence of the drug on these receptors in that region.

   Data were collected using stainless steel electrode arrays and our sample population of task related neurons is likely biased to pyramidal neurons, with a small number of fast spiking interneurons. We used validated spike waveform parameters of interneurons in premotor cortex (peak-to-trough ratio and duration; Giordano et al., 2023) in an attempt to isolate putative interneurons and found only a very small number of these cells in our recordings (n=5-7 per group). This population is too small to make any inferences about specific impacts. We have focused on the collective population activity of M2 as this is most strongly related to optimal action planning.

   You are correct that from the given findings we cannot conclusively show that the results found here are a result of propranolol acting solely within anterior M2. We have made sure to clarify throughout our revised manuscript that the behavioral and physiological changes we identified are a result of collective direct and indirect actions of propranolol.

   The conclusion that neuronal discrimination decreases because the proportion of neurons showing no effect increases is confusing (negative results, basically). It would be clearer if they were reporting the number of neurons that do show an effect, and presumably that this number shows a significant decrease.

   The reviewer is correct that the number of neurons that do show an effect (task related activity) does significantly decrease with propranolol (from n=70 to 27 in females and n=71 to 48 in males). These n are now given adjacent to the proportions rather than at the end of the paragraph. Proportions were used for statistical analysis due to an overall decrease in the total number of units after propranolol. All PETH presented are from neurons that show some task related activity, these PETH confirm that neural activity no longer effectively discriminates/separates action plans in M2.

   Figs 3F-I: a good proportion of neurons (at least 20%) show a significant encoding before cue onset. How is it possible? This raises the issue of noise level/ null hypothesis for this kind of repeated analysis. How did the author correct for multiple comparison issues?

   In response to reviews, we have altered the manner in which we identify the significantly modulated neurons to increase rigor and no longer include these figures or analyses. The proportion of neurons showing action plan encoding prior to cue onset was likely an artifact of how the data was analyzed and an insufficient correction for multiple comparisons, allowing inclusion of internally generated action plans in some neurons.

   The description of the action-related activity is globally confusing. Again, how can the authors discriminate between activity related to planning vs action itself? What is significant and what is not, in males vs females? What is being measured here? For example, a very unclear statement on line 238: "Propranolol primarily disrupted active inhibition of irrelevant action selection in M2 activity, reducing the ability to maintain action plan representation in M2, delaying lever press responses (Figure 4L, 4M)." What is 'active inhibition? What is an irrelevant action plan? What is selection? All of that should be defined using objective behavioral criteria and tested formally.

   We have changed our wording to clarify what we are describing and why we have chosen the words we have, and to ensure consistency and objectivity throughout the manuscript. Much of the wording we have used – for example action planning or action plan selection, are the words used in the literature to describe M2 neural activity. We call the activity in M2 action planning (either externally/cue guided or internally guided) because that is what has been previously demonstrated. In our task design and analysis we are tracking cue guided actions, as opposed to internally guided.

   We also separate the electrophysiology data as preferred and nonpreferred because the literature has shown individual M2 neurons show specific directional tuning as noted in our results, using the term ‘preferred’ encapsulates that tuning regardless of left/right direction. An example M2 neuron that increases activity for left cues and responses (preferred direction), will show active inhibition (low/negative z scores) on trials with right cues and responses (nonpreferred), other neurons would show the inverse relationship with direction.

   A primary impact of propranolol was the loss of negative z-scores for nonpreferred trials ie neurons with a left preference that are usually inhibited on right trials were still firing and vice-versa. After propranolol neurons continue to fire for an irrelevant action plan (for the opposite direction), and the resulting population activity is not significantly different for opposing cues/responses. Behavioral responses normally occur after opposing action plans have significantly separated in M2, collapsing action plans by preventing relevant signaling (Guo et al., 2017; Inagaki et al., 2018; Li et al., 2016) or facilitating irrelevant signaling as we see here with propranolol leads impairments in 2AFC performance.

   Also, the description of the classifier analysis should be more thorough. Referencing the toolbox is not sufficient to understand what has been done.

   We have added additional explanation in both the methods and description of the results to clarify the functions of the neural decoding box and how we are using it to evaluate information encoding within M2. We have provided detail on how the algorithm was trained, how shuffled data was generated and how we determined significance of decoding accuracy.

   Measuring Beta adrenoceptors is a great idea, and the results are interesting, especially the difference between neuron types. But again, how does that fit with neurophysiological results? Note, that since this is RNA measures, it should not be phrased as 'receptors' but 'receptors RNA' throughout. One possible interpretation of these anatomical results that cannot be reconciled with physiology is that protein expression at the membrane shows a distinct pattern.

   We have changed the references to β receptor expression to β receptor mRNA expression throughout the manuscript. Although mRNA provides a valuable proxy for adrenoreceptor production, as noted by the reviewer protein expression at the membrane may differ. Reliable antibodies that allow quantitative analysis of membrane bound adrenoreceoptors in situ with co-labeling of specific cell types are limited. The goal of assessing mRNA expression within M2 was to determine if the functional sex differences we identified in M2 neurophysiology when manipulating β adrenoreceptor function could be mediated by basal differences in adrenoreceptors. The causal impact of differential mRNA expression in anterior M2 was not directly tested but our findings provide preliminary evidence that adrenoreceptor regulation may differ across sexes. Our results provide a plausible avenue for differential sensitivity to β adrenoreceptor manipulation across sexes, that may also be found in other brain regions.

   In conclusion, I think that this is a very interesting study and that the results are potentially relevant for a wide audience. But the paper would clearly benefit from revisions. If the authors could clearly identify a significant relationship between the action of NA on beta receptors on specific cortical neurons, at a physiological and behavioral level, that would be a seminal study. At the moment, the evidence is not convincing enough but the data suggest that it is the case.

   We thank the reviewer for the kind remarks. We have undertaken a number of new analyses, refined existing analysis and clarified our claims in the manuscript to improve rigor. Collectively our data reflect that the behavioral and neural deficits after systemic propranolol are likely due to both direct and indirect actions on M2. We believe this work is compelling and that it will inform future work investigating potential sex differences in central noradrenergic anatomy and functional sex differences after perturbations of noradrenergic signaling.

   Read the original source
3. 

   eLife

   Jul 9, 2023

   eLife assessment

   Rodberg et al. show systemic β adrenergic antagonism reduces engagement in decision-making, particularly in female rats, and reduces task-related encoding in neural activity. This is a valuable finding that addresses a gap in the field, however, the understanding of the direct contribution of β adrenergic receptors to the observed effects is incomplete. Further, the theoretical grounds, data analyses, and results could be improved in several ways.

   Read the original source
4. 

   eLife

   Jul 9, 2023

   Reviewer #1 (Public Review):

   Various parts of the premotor cortex have been implicated in choices underlying decision-making tasks. Further, norepinephrine has been implicated in modulating behavior during various decision-making tasks. Less work has been done on how noradrenergic modulation would affect M2 activity to alter decision-making, nor is it clear whether noradrenergic modulation effects on activity would differ between the male and female sexes.

   This manuscript addresses some of these questions.
   - In particular, clear sex differences in task engagement are seen.
   - May also show some interesting differences and distributions of β2 adrenergic receptors in M2 between males and females.

   Less clear is the specificity of systemic antagonism of β adrenergic receptors on the changes in M2 activity reported. As propranolol was given …

   Reviewer #1 (Public Review):

   Various parts of the premotor cortex have been implicated in choices underlying decision-making tasks. Further, norepinephrine has been implicated in modulating behavior during various decision-making tasks. Less work has been done on how noradrenergic modulation would affect M2 activity to alter decision-making, nor is it clear whether noradrenergic modulation effects on activity would differ between the male and female sexes.

   This manuscript addresses some of these questions.
   - In particular, clear sex differences in task engagement are seen.
   - May also show some interesting differences and distributions of β2 adrenergic receptors in M2 between males and females.

   Less clear is the specificity of systemic antagonism of β adrenergic receptors on the changes in M2 activity reported. As propranolol was given systemically, changes in M2 firing rates could also be due to broader circuit (indirect) activity changes. As it was not given locally, nor were local receptor populations manipulated, one is unable to make the conclusion that changes in neural activity are due to the direct effects of adrenergic receptors within M2 populations.

   Also not clear, is the contribution of M2 to this task, and whether the changes in M2 activity patterns observed are directly responsible for the behavioral disruptions measured.

   Read the original source
5. 

   eLife

   Jul 9, 2023

   Reviewer #2 (Public Review):

   This paper by Rodbarg et al describes an interesting study on the role of beta noradrenergic receptors in action-related activity in the premotor cortex of behaving rats. This work is precious because even if the action of neuromodulatory systems in the cortex is thought to be critical for cognition, there is very little data to actually substantiate the theories. The study is well conducted and the paper is well written. I think, however, that the paper could benefit from several modifications since I can see 3 major issues:

   Both from a theoretical and from a practical point of view, the emphasis on 'cue-related' activity and the potential influence of NA on sensory processing is problematic. First, recent studies in rodents and primates have clearly demonstrated that LC activation is more closely related …

   Reviewer #2 (Public Review):

   This paper by Rodbarg et al describes an interesting study on the role of beta noradrenergic receptors in action-related activity in the premotor cortex of behaving rats. This work is precious because even if the action of neuromodulatory systems in the cortex is thought to be critical for cognition, there is very little data to actually substantiate the theories. The study is well conducted and the paper is well written. I think, however, that the paper could benefit from several modifications since I can see 3 major issues:

   Both from a theoretical and from a practical point of view, the emphasis on 'cue-related' activity and the potential influence of NA on sensory processing is problematic. First, recent studies in rodents and primates have clearly demonstrated that LC activation is more closely related to actions than to stimulus processing (see Poe et al, 2020 for review). Second, the analysis of neural activity around cue onset should be examined with spikes aligned on the action, since M2 is a motor region and raster plots suggest that activity is strongly related to action (I'll be more specific below).

   The distinction between neural activity and behavior or cognition is not always clear. I understand that spike count can be related to motor preparation or decision, but it should not be taken for granted that neuronal activity is action planning. The analysis should be clarified and the relation between neural activity, behavior, and potential hidden cognitive operations should be explicated more clearly.
   The sex difference is interesting, but at the moment it seems anecdotal. From a theoretical point of view, is there any ecological/ biological reason for a sex dependency of noradrenergic modulation of the cortex? Is there any background literature on sex differences in motor functions in rats, or in terms of NA action? If not, why does it matter (how does it change the way we should interpret the data?) From a practical point of view, is there a functional sex difference in absence of treatment, or is it that the drug has a distinct effect on males vs females? This has very distinct consequences, I think.

   These issues could be clarified both in the introduction and in the discussion, but the authors might have a different view on what is theoretically relevant here. In the result section, however, I think that both the lack of specificity in the description of behavior and cognitive operation and the confusion between 'sensory' and 'motor' functions make it very difficult to figure out what is going on in these experiments, both at a behavioral and at a neurophysiological level.

   First, the description of the behavior in the task is clearly not sufficient, which makes the interpretation of the measures very difficult. One possible interpretation of the effects of the drug is a decrease in motivation, for instance, due to a decrease in reward sensitivity or an increase in sensitivity to effort. But there are others. More importantly, none of these measures can be used to tease apart action preparation from action execution, even though the study is supposed to be about the former.
   Also, but this is less critical: In Figures 2C and D, it looks like there is a bimodal distribution for the effect of propranolol in females. Is there something similar in the neuronal effects of the drug? And in the distribution of receptors? Can it be accounted for by hormonal cycles/ anything else?

   The description of neural activity is also very superficial.
   In general, it is not clear how spike count measures have been extracted. For example, legend and figure C are not clear, is the (long) period of cue presentation included in the 'decision time'?? "Cues were presented at a variable interval 200-700ms after initiation and until animals left the well, 'Well Exit'. The time from cue onset to well exit was identified as the decision time (yellow)." Yet on the figure only the period after cue presentation is in yellow. This is critical because, given the duration of the cue, the animals are probably capable of deciding (to exit the well) before the cue turns off. Indeed, as shown in fig 2D, the animals can decide within about 500 ms. So to what extent is the 'cue response' actually a 'decision response'? When looking at figure 3A, there is clearly a pattern on the raster, a line going from top left to bottom right. If the trials are sorted chronologically, something is happening over time. If, as I suspect, trials are sorted by ascending response time, this raster is showing that what authors are calling a 'response to cues' is actually a response around action. Basically, if propranolol slows down reaction time, the spikes will be delayed from cue onset only because they remain locked to the action. Then the whole analysis and interpretation need to be reconsidered. But it might be for the best: as I mentioned earlier, recent work on LC activity has clearly emphasized its influence on motor rather than sensory processing (Poe et al, 2020).

   Fig 2D-F: it is hard to believe that the increase in firing rate induced by propranolol in females is not significant. Presumably, because the range of the median firing rate is so high in the first place, distribution (2E) really indicates an increase in firing. Maybe some other test? e.g paired t.test, or standardized values (z.score) to get rid of variability in firing across neurons?

   Along those lines, would it be worth looking for effects on specific populations (interneurons) which are sometimes characterized by thinner spikes and higher mean firing rates? Given the distribution of beta receptors RNA on interneurons, one would actually expect an effect of propranolol on the firing rate irrespective of task events. Or what is it that prevents the influence of propranolol on interneurons from changing the firing rate? In any case, one of the strengths of this study is the localization of beta receptors on specific neuronal populations in the cortex, so I think that the authors should really try to build on it and find something related to the neurophysiological effects. Otherwise, one cannot exclude the possibility that the behavioral effects are not related to the influence of the drug on these receptors in that region.

   The conclusion that neuronal discrimination decreases because the proportion of neurons showing no effect increases is confusing (negative results, basically). It would be clearer if they were reporting the number of neurons that do show an effect, and presumably that this number shows a significant decrease.
   Figs 3F-I: a good proportion of neurons (at least 20%) show a significant encoding before cue onset. How is it possible? This raises the issue of noise level/ null hypothesis for this kind of repeated analysis. How did the author correct for multiple comparison issues?
   The description of the action-related activity is globally confusing. Again, how can the authors discriminate between activity related to planning vs action itself? What is significant and what is not, in males vs females? What is being measured here? For example, a very unclear statement on line 238: "Propranolol primarily disrupted active inhibition of irrelevant action selection in M2 activity, reducing the ability to maintain action plan representation in M2, delaying lever press responses (Figure 4L, 4M)." What is 'active inhibition? What is an irrelevant action plan? What is selection? All of that should be defined using objective behavioral criteria and tested formally.
   Also, the description of the classifier analysis should be more thorough. Referencing the toolbox is not sufficient to understand what has been done.
   Measuring Beta adrenoceptors is a great idea, and the results are interesting, especially the difference between neuron types. But again, how does that fit with neurophysiological results? Note, that since this is RNA measures, it should not be phrased as 'receptors' but 'receptors RNA' throughout. One possible interpretation of these anatomical results that cannot be reconciled with physiology is that protein expression at the membrane shows a distinct pattern.

   In conclusion, I think that this is a very interesting study and that the results are potentially relevant for a wide audience. But the paper would clearly benefit from revisions. If the authors could clearly identify a significant relationship between the action of NA on beta receptors on specific cortical neurons, at a physiological and behavioral level, that would be a seminal study. At the moment, the evidence is not convincing enough but the data suggest that it is the case.

   Read the original source
6. 

   Version published to 10.1101/2022.12.06.519304v1 on bioRxiv

   Dec 6, 2022