Positive and negative associations acquired through olfactory experience are thought to be especially strong and long-lasting. The conserved direct olfactory sensory input to the ventral striatal olfactory tubercle (OT) and its convergence with dense dopaminergic input to the OT could underlie this privileged form of associative memory, but how this process occurs is not well understood. We imaged the activity of the two canonical types of striatal neurons, expressing D1- or D2-type dopamine receptors, in the OT at cellular resolution while mice learned odor-outcome associations ranging from aversive to rewarding. D1 and D2 neurons both responded to rewarding and aversive odors. D1 neurons in the OT robustly and bidirectionally represented odor valence, responding similarly to odors predicting similar outcomes regardless of odor identity. This valence representation persisted even in the absence of a licking response to the odors and in the absence of the outcomes, indicating a true transformation of odor sensory information by D1 OT neurons. In contrast, D2 neuronal representation of the odor-outcome associations was weaker, contingent on a licking response by the mouse, and D2 neurons were more selective for odor identity than valence. Stimulus valence coding in the OT was modality-sensitive, with separate sets of D1 neurons responding to odors and sounds predicting the same outcomes, suggesting that integration of multimodal valence information happens downstream of the OT. Our results point to distinct representation of identity and valence of odor stimuli by D1 and D2 neurons in the OT. Assigning value to stimuli in the external environment and subsequently adjusting behavior on the basis of those learned values is a primary function of the nervous system. Understanding this process is especially important because certain associations result in maladaptive behaviors such as compulsions, binge eating, and drug addiction . OlfactiThe OT has been implicated in motivation as well as olfactory processing . As an eThis evidence establishes OT as a key region likely involved in learning odor-outcome associations and assigning emotional tags to odors. However, many questions remain unanswered regarding the nature of the information encoded by OT neurons and the role of the different neuronal types within the OT in this function. OT is a part of the ventral striatum and consists of spiny projection neurons (SPNs). Striatal SPNs are roughly divided into D1-type and D2-type dopamine receptor expressing SPNs, and these two groups of SPNs also have different output projection patterns . This diTo investigate the role of D1 and D2 receptor expressing neurons in the OT in odor valence learning, we imaged the activity of these neuronal populations in the OT using multiphoton microscopy, while mice learned to associate odors with aversive or rewarding outcomes. Adenoassociated virus that allows conditional expression of the calcium indicator GCaMP7s in the presence of Cre recombinase was injected into the right OT of Drd1-Cre and Adora2A-Cre mice and a 1 mm cannula was implanted targeting the OT  . After D1 neurons in six Drd1-Cre mice  and D2 neurons in six Adora2A-Cre mice  developed both excitatory and inhibitory responses to the task odors across days of training , with thTask-related activity of the population of D1 neurons we recorded was strikingly similar during the two aversive trial types . OverallBy using graded odor-outcome associations, we aimed to disambiguate neuronal coding for odor valence, odor motivational salience, and odor identity. We hypothesized that, in our task, idealized valence coding neurons would exhibit similar responses to odors of similar valence , row 3, We assigned each significantly responsive neuron a valence score by computing a normalized difference between the neuron’s activity in response to odors of opposite valence and odors of same valence  and otheIn the odor-outcome association task, both odors of positive valence were accompanied by licking responses and water drop delivery, and both odors of negative valence were accompanied by airpuff delivery. As such, these trial types shared licking responses and unconditioned stimuli that likely contributed to the shared outcome-related neuronal responses we observed. In order to test whether activity of OT neurons reflected true valence coding of the odor stimulus, we constructed a probe session with two distinct training blocks. Block 1 of the session proceeded as previously described. After this first block, a 2 min break was introduced in which mice received 2 mL of free water droplets and became sated on water. Block 2 of the imaging was then conducted where mice did not lick in response to odor presentations and all outcomes (water and airpuff) were omitted . We founIn Block 2, in the absence of licking and outcomes, D1 neuronal responses to odors of previously learned negative valence . The EucIndividual neuron valence coding scores of D1 neurons decreased significantly in Block 2 as compared to the full task condition . Odor vaTo further interrogate the stimulus valence coding property of OT neurons, the implanted Drd1-Cre mice (n=6) and Adora2A-Cre mice (n=4), which had been previously trained on the five-odor-outcome conditioning task, were then trained on a new task in which sound associations were introduced. The main motivation for these sound-odor association experiments was to determine whether sensory cues from a different modality known to activate OT neurons  could beA new task was introduced in which two odor-outcome associations and two sound-outcome associations were presented. Odors 1 and 5 were paired with strong airpuff and large water reward as previously, and two sound tones (5 and 12 kHz) were used, also paired with strong airpuff and large water reward . These sIn the stimulus-only condition in Block 2, we found that the same D1 neuronal populations which had previously strongly maintained similar activity patterns in response to odors of similar valence  did not Finally, we compared the principal components of D1 neuronal population activity in response to the five odors in Blocks 1 and 2 in the odor-odor task and activity in response to the odor-sound stimuli in Blocks 1 and 2 in the odor-sound task. Principal components of D1 neuronal populations were very similar in odors predicting similar outcomes in the typical task condition , top andThe results of these experiments offer key insights into the function of OT neuronal circuitry during odor association learning. We find some surprising similarities and some key differences in the neuronal responsivity of D1- and D2-type OT neurons, in the first single neuron imaging experiments of specific neuronal subtypes in the OT. We found that D1 neuronal populations clearly responded to both positive and negative odor valence. This is the first demonstration of bidirectional odor valence coding by OT neurons, as no previous real-time recordings of OT neurons in response to aversive valence odors have been reported. We therefore can conclude that the OT is likely to be involved in learning about both positive and negative odor associations, rather than the alternative possibilities that the OT is only involved in learning rewarded odor associations, or that it encodes odor salience rather than signed odor valence. We note that a higher proportion of neurons was active in response to the rewarded odors than the aversive odors; however, this may be an effect of possible high value of the water reward outcome in water restricted mice as compared to the aversiveness of a relatively harmless airpuff to the nose. Surprisingly, similar proportions of D1 and D2 neurons responded to the five task odors, challenging our initial hypothesis that D2 neurons may respond more strongly to negatively reinforced odors, based on immediate early gene expression results . This suWe then addressed a long-standing question about the factors driving the responses of OT activity in odor-outcome behavioral paradigms. In previous OT recording experiments, go/no-go tasks were used where licking in response to the rewarded odors was required. In our classical conditioning task, mice similarly exhibited anticipatory licking at the onset of the rewarded odors, although the water delivery was not contingent on this response. In all of these conditions, the odor presentation itself was in every case coupled with the motor licking action of the mouse. Thus, it was unclear whether the neuronal activity recorded occurred as a result of the odor stimulus or the licking response. Previously, it was reported that the onset of the recorded neuronal responses preceded the onset of the licking action by ~200 ms ; howeverWe also note that D1 neurons are heterogeneous in terms of their valence coding, and a sizable fraction loses its valence coding in the absence of licking and outcome (Block 2). We did not find distinct populations of neurons responding to licking and valence separately , indicatOur findings on the activity of OT D2 neurons provide an interesting contrast to the robust valence coding property of D1 neurons. While D2 neuronal populations differentiated between rewarded and aversive outcomes in the task condition involving licking and outcomes, this representation was significantly weaker than that of D1 neurons and disappeared in the stimulus-only condition when licking and outcomes were omitted. This result contrasts with photometry data in which reward contingency information was not observed in average D2 population activity in a go/no-go task , suggestHow D1 and D2 neuronal representations of learned odors diverge based on inputs to these neurons and the effect of dopamine onto them, and how they then subsequently shape behavior as they influence downstream targets are both important areas to investigate. Cre expressing neurons in the dorsal striatum from the Drd1-Cre and Adora2A-Cre mouse lines used in our imaging experiments have been previously shown to project via the distinct direct and indirect striatal output pathways , and as Informed by previous studies showing that sound cues can also activate OT neurons , we askeFirst, corroborating our previous result, we can conclude that the odor valence-related OT activity was not primarily a result of the licking response of the mouse. We demonstrate that behaviorally, the anticipatory licking rates of the mice in response to the rewarded odor stimulus and the rewarded sound stimulus are similarly high after training, yet stimulus-outcome representation in the OT during the odor-sound task is minimal in the period prior to outcome delivery even in the presence of matched anticipatory licking rates. Second, we can conclude that stimulus valence representation by D1 OT neurons does not automatically generalize to multimodal stimuli. Our previous study  demonstrAn unavoidable consequence of GRIN lens imaging of deep brain regions is tissue damage, but we are confident that our key conclusions are not affected by this issue. We made concerted efforts to minimize the damage caused by the implanted cannula. First, the cannula was constructed from highly biocompatible and thin-walled polyamide tubing and quartz floor which have previously been shown to minimize glial scar tissue . Second,The main comparisons we make in our study are likely not a function of the damage caused by the lens. First, the differences in the valence coding of D1 and D2 neurons are unlikely to be a result of lens damage, since there is no reason to suspect that damage caused by the lens will differentially affect D1 and D2 neuronal activity in the OT. D1- and D2-type neurons in the OT and the striatum typically receive inputs from similar upstream structures and their inputs were not generally altered by the lens damage. Second, there is no reason to suspect that the robust valence coding in the absence of the licking and outcomes by D1 neurons could be a result of the lens damage. Third, there is no particular reason to suggest that the distinction between the odor and sound responsive neurons in the last set of experiments would be a result of the damage caused by the lens as the possible auditory cortical projections to the OT arrived from the posterior direction. Finally, the nature of the valence-related responses we observe in the OT are similar to those observed by others using tetrode recordings  in whichIn summary, we find that D1 OT neurons are more likely to encode learned odor valence than D2 neurons, and conversely less likely to encode odor identity. We also demonstrate, for the first time, that even when the licking response to rewarded odors is eliminated, OT D1 neurons continue to robustly encode odor valence suggesting that this stimulus to valence transformation by the OT precedes the motor action itself. These results also suggest that OT odor valence representation could inform downstream brain regions of the value of odor stimuli. Finally, we find that stimulus valence representation by OT neurons is limited to olfactory stimuli suggesting a specialized role of the OT in assigning emotional tags to odors based on previous experience. Further investigation into the relative contributions of D1 and D2 OT neurons to odor association learning and the neural mechanisms that result in the differential responses of these neuronal types is required. These neuronal imaging results suggest a specialized role for the OT in odor valence memory, and further studies can be conducted to assess the causal contribution of the OT to the hypothesized unique emotional qualities of olfactory memory.Adult male and female heterozygous B6.FVB(Cg)-Tg(Drd1-Cre)EY262Gsat/Mmucd and B6.FVB(Cg)-Tg(Adora2A-Cre)KG139Gsat/Mmucd (MMRRC) mice were 2–6 months of age at the start of the experiments. Due to the highly consistent colocalization of A2A receptors and D2 dopamine receptors in the striatum, no colocalization of A2A receptors with D1 dopamine receptors , and preCustom-designed cannula were assembled in house. 6.2 mm length 1.1 mm diameter ultra-thin wall biocompatible polyimide tubing (MicroLumen) which was demonstrated to cause minimal inflammatory response in the brain  was usedNaïve mice underwent surgical virus injection, cannula implantation, and head fixation plate implantation, prior to any behavioral training. Mice were anesthetized with an intraperitoneal injection of a mixture of xylazine (10 mg/kg) and ketamine (80 mg/kg) and placed in a stereotaxic apparatus. A 1.4 mm craniotomy was performed at 1.5 mm AP, 1.3 mm ML in the right hemisphere. A 22 G needle was used to suction 2 mm below the brain surface prior to virus injection. A pulled glass micropipette attached to a nanoinjector  was used to inject 400 nL of pGP-AAV9-syn-FLEX-jGCaMP7s-WPRE (Addgene) virus at a depth of 4.8 mm DV at a rate of 100 nL/min. Five minutes after the injection was completed, the glass pipette was raised out of the brain over the course of another 5 min. The sanitized cannula was then held lightly with a dental paper point inserted into its center and attached to the stereotaxic arm. The cannula was lowered over the course of 10 min to a depth of 4.9 mm DV. The cannula was secured onto the skull with cyanoacrylate glue and a head fixation plate was also glued to the skull behind the cannula. Dental cement (MetaBond) was then used to cover the skull and headplate. The opening of the cannula was covered with a silicone sealant (KwikSil). Mice were single housed after surgery. After a period of 4 weeks to allow for virus expression and the reduction of the inflammatory response to the insertion of the cannula, a 1 mm diameter, 3.4 mm long 0.5NA GRIN lens (ThorLabs) was inserted into the cannula and behavioral training and imaging begun.Mice were water restricted to reach 85–90% of their initial body weight and provided approximately 1–1.5 mL water per day in order to maintain desired weight. Mice were habituated to head fixation and drinking from water spout prior to initial training session. In the pre-training (day 0), mice were provided large water drops (20 µL), small water drops (10 µL), strong airpuff (10 PSI), and weak airpuff (5 PSI) in identical trial structure as full five-odor conditioning task, but odors were not used. Each mouse was then assigned five odor-outcome contingencies with the monomolecular odorants hexanal, limonene, anisole, eucalyptol, and heptanal. Odors were delivered via a custom-built olfactometer as described previously  with a 1http://www.scopefoundry.org/) and National Instruments DAQ hardware.In days 1–4 of training, each of the five odors and associated outcomes were provided 30 times with 20 s inter-trial intervals. In 10% of trials , the outcomes were omitted; however, this number of trials was not later found to be sufficient for the analysis of neuronal activity. Trial types were interspersed randomly across the session, with the constraint that equal numbers of each trial type occurred in the first and second half of each session to ensure equal trial type representation for the duration of each imaging session. Licking of the water delivery spout was measured throughout training and imaging with the use of a capacitance sensing Arduino circuit. Behavioral events control and recording was conducted with Python with adapted use of the ScopeFoundry platform  of the sound stimuli and associated outcomes was identical to that of the odor stimuli. After 3 days of odor-sound task training, a probe session with two blocks was conducted as in the original five-odor task.A custom-built microscope was used for in vivo imaging as described previously . ImagingImaging data was motion corrected with Non-Rigid Motion Correction (NoRMCorre) . The actOdor valence coding scores and odor identity coding scores were computed for neurons which had significant mean activity deviations of >30% from pre-trial baseline as shown below. Due to the variability in the neutral odor responses which often tracked closely with either the aversive odors or the rewarded odors in neurons which clearly differentiated between the rewarded and aversive odors, the neutral odor responses were not included in the numerator of the valence score formula . A salience score was calculated analogous to the valence score using the formula noted above. Distributions of odor valence scores and odor identity scores across neuronal types and task conditions were compared with the non-parametric Wilcoxon rank sum test. We generated null distributions by shuffling the odor-valence pairing. Since the identity scores were calculated by comparing the best odor response to the next best one, the shuffling procedure does not affect the identity scores and was not done for those distributions. Matrix difference measures of neuronal population activity were obtained by taking the Euclidean norm of the difference between population activity in response to pairs of stimuli used in the task. The mean norm for stimuli pairs of opposite valence was then compared to the mean norm for stimuli pairs of the same valence. Neuronal population activity dimensionality reduction and trajectory analysis was conducted with the use of the DataHigh toolbox  with allAfter completion of imaging experiments, mice were transcardially perfused, and the brains were removed from the skull. Coronal floating sections were cut using a vibratome (Leica VT1000S). Brain sections were imaged using the Zeiss Axio Scan slide scanner at the Harvard Center for Biological Imaging to visualize the location of GCaMP expression and the location of cannula tip. Brain section images were matched and overlaid with the Paxinos and Franklin Mouse Brain Atlas cross-sections to identify imaging location. Six of eleven implanted Drd1-Cre mice had confirmed OT imaging locations, while in others the tip of the cannula was located in ventral pallidum or nucleus accumbens. Eight of eleven implanted Adora2A-Cre mice had confirmed OT imaging locations, but only six of eight produced satisfactory imaging results. Only mice with confirmed OT imaging locations and successful imaging results were used in later analysis.We primarily used the non-parametric Wilcoxon rank sum test (referred to simply as rank sum test in the main text) and Fisher’s exact test, since we could not assume normally distributed data in most cases. Comparisons involving t-tests were paired and two-tailed. Martiros et al. monitored the activity of dopamine D1 and D2-expressing neurons within the ventral striatum olfactory tubercle using 2-photon microscopy, as mice learned to associate odors and tones with either positive or aversive outcomes. Authors find differential roles for these neurons in the learning of odor valence and tone outcome associations. Overall, this study was deemed as an interesting and important contribution to our understanding of the neural basis of cue encoding. public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Michael Frank as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Daniel W Wesson (Reviewer #1).Thank you for submitting your article "Distinct representation of cue-outcome association by D1 and D2 neurons in the olfactory striatum" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Martiros et al. monitored the activity of dopamine D1 and D2-expressing neurons within the ventral striatum olfactory tubercule (OT) using 2-photon microscopy, as mice learned to associate odors and tones with either positive or aversive outcomes. D1 neurons robustly encoded learned odor valence, and D1 neurons maintained an odor valence representation even when appetitive or aversive unconditioned stimuli were removed. In contrast, D2 neurons were more selective to odor identity than D1 neurons, and odor valence coding in D2 neurons was dependent on odor outcome associations. Finally, authors show that in D1 neurons, odor and tone outcome associations recruit largely non-overlapping neuronal ensembles. Overall, this study was deemed by reviewers as an interesting and important contribution, however, they did identify a need for added details about data analyses and statistical comparisons for a clearer interpretation.Essential revisions:1) Authors should provide more details about the specific cell types being monitored in the D1 and A2A-cre mice since cre is present in neurons, not just medium spiny / striatal projection neurons. The authors did not exclude these other cells in their analysis or experimentally so any revision should be clear about inclusion of other types of neurons .2) The function of the different subpopulations of 'valence coding' D1 neurons should be clarified in both the Results and Discussion. Relatedly, it is unclear how neuronal responses to neutral odors are taken into consideration when calculating valence scores. It is suggested to include the distributions of valence scores with shuffled cell-odor pairs as reference points. Statistical tests for comparing odor valence and identity distributions should be described in more detail.3) It is unclear how odor identity (and sound frequency) is represented in neuronal response patterns. The authors should show neuronal responses grouped by mice / odorant-unconditioned stimulus combinations, in addition to showing neuronal responses grouped by the trial outcomes only.4) There was concern about a large portion of the brain damaged by the placement of the GRIN lens. The implication of this damage needs to be discussed.5) It is suggested to better link behavior to neural responses- specifically the timing of licking with the GCaMP response.6) Authors should provide a clearer rationale for the tone learning study. The motivation for the odor-tone association experiments is unclear. The main result is that different subpopulations of OT neurons encode odor and tone associations. However, this does not appear to be a question the authors set out to address a priori.Reviewer #1 (Recommendations for the authors):This study is a much needed addition to the field, and the manuscript is excellent and well done. I have a few number of major and a longer list of minor issues I'd appreciate being addressed.Figure 4F2 – the authors package these results that most D1 neurons maintain valence coding in absence of instrumental responding or conditioned outcomes, and while this is true, a good amount do not. It would be beneficial for the authors to elaborate upon what those two different subpopulations of D1 neurons are doing both in Results and Discussion.The authors do show that some cells display auditory valence coding, yet conclude across the population there is no such activity. It would be helpful for the authors to describe activity of the cells which do in fact show learned responses to the tones. Related to this, in some places the authors describe their results as "not modality invariant". Perhaps this could be rephrased to read, "modality variant" to avoid double negatives. Finally, isn't the finding that there are responses to multisensory stimuli and that these responses are dependent upon learning reason to reconsider titling this paper as originating from the "olfactory striatum"? These results show this is not simply an "olfactory" structure, and as described in Wesson 2020 (Tubular Striatum), the concept of calling the olfactory tubercle the "olfactory striatum" lost ground decades ago. Of course, I'm all for scholarly creativity of the authors and am not asking them to change the title, but more to think about what message this sends to readers.Overall, it would be helpful to see the timing of licking, even if on average, to help relate the gcamp response to behavior better. This is important since the authors used a fixed ITI of 20s and normalized each neuron's activity to a 1s pre-trial baseline. But can we be sure there was no anticipatory-related activity during that time? More specifically, it would be nice to show a new figure/inset of Figure 1C, day 1 and/or 4 in raster-format (similar to 4B perhaps) so readers can gain an appreciation for the timing of the licks specifically in this panel, if possible .I'd appreciate the authors elaborating upon the argument from their Discussion that tubercle neurons "encodes odor salience rather than signed odor valence". I'm not sure that I appreciate how the authors results directly disambiguate this, nor am I even clear how one could do in the context of like experiments.Reviewer #2 (Recommendations for the authors):1) It is unclear how neuronal responses to neutral odors are taken into consideration when calculating valence scores. For example, a neuron with a strong (positive) valence score would be expected to respond to the rewarded odor but not to the neutral odor or odors associated with the air puff. The current analysis appears to ignore neutral odors and should be expanded to include neutral odors.2) In figure 3, the authors claim that for D1 but not D2 neurons, the valence score increases with training. Valence scores in naive mice are expected to be zero – this should be reflected in the data. To help interpretability, the distributions of valence scores with shuffled cell-odor pairs should be included as reference points.Furthermore, figure 1 suggests that there is a rage of anticipatory lick numbers on day one, likely reflecting differences in learning during the first session. When analyzing imaging data over time, the authors should compare data from mice with similar behavioral performance.3) In figure 4, the authors state that the mean valence score of D1 neurons remains above zero for block 2 trials – the mean valence score should be indicated in the figure. Statistical tests for comparing odor valence and identity distributions should be described in more detail.4) The motivation for the odor-tone association experiments described in figure 5 is unclear. Without characterizing tone-outcome learning in OT neurons in the described experimental setting, the multimodal task is difficult to interpret. Furthermore, the response properties of neurons in the 'full task condition' are hardly analyzed (supplementary figure 4), instead, the analysis focuses on block 2 trials and is difficult to follow.The main result is that different subpopulations of OT neurons encode odor and tone associations. However, this does not appear to be a question the authors set out to address and may be a trivial result given the well-established differences in neuronal connectivity.5) It is unclear how odor identity (and sound frequency) is represented in neuronal response patterns in figures 2 and 4. The authors should show neuronal responses grouped by mice / odorant-unconditioned stimulus combinations, in addition to showing neuronal responses grouped by the trial outcomes only.Reviewer #3 (Recommendations for the authors):p. 2The term "addictive" is not appropriate to describe intracranial self-administration of cocaine. Use "reinforcing" or "rewarding", instead.Suppl. Figure 1AOT D1R neurons do not project to the substantia nigra or ventral tegmental area, or OT D2R neurons do not project to the globus pallidus. It is confusing to mention such projections that are most likely caused by viral diffusions to the nucleus accumbens and dorsal striatum. Clarify the points that the authors are making here.Figure 3ADotted circles used to describe their identifies are not shown on the actual diagram.p.3Licking response may not be labeled as "instrumental". Essentially, the study ued a Pavlovian conditioning procedure rather than operant conditioning procedure. Therefore, the conditioned licking response is a Pavlovian conditioned response.p. 4For clarity, rewrite the sentence that contains the phrase "non-zero licks were excluded."Rewrite the sentence "Odors 1 and 5, which... were combined with two sound tones". This sentence does not convey what the authors are trying to describe. The two modalities were combined in the new experiment; odors did not get combined with tones, which has a completely different meaning.p. 4 and Figure 5A,Avoid the phrases "odor and sound pairs" and "odor-sound pairs". In the psychology/behavior conditioning literature, they mean that odors are paired with sounds.Figure 5BThe plot suggests that by day 3, the mice may not have fully discriminated between sounds 1 and 2. The mice displayed anticipatory licks with sound 1 while they did not with odor 1.Figure 5F-5G and Suppl. Figure 5B-5CIt is more informative to show data separately between O and S for the plots of the OS experiment.Suppl. Figure 4Airpuff-paired sound triggered little or no conditioned response from the D1 neurons. What does this mean?Suppl. Figure 5B-5CThe Y-axis is not labeled.p. 6What do water- or airpuff-paired neural signals encode when they are present in the absence of behavior?The last full paragraph on p. 6The discussion is confusing. The authors mention that D1R neurons and D2R neurons have differential projections and that they have confirmed the fact in Fg. S1A. However, the authors do not discuss how projection patterns of the D1R and D2R neurons in the dorsal striatum and the nucleus accumbens are relevant to those of the OT. OT D1R and D2R neurons primarily project to the ventral pallidum ; it is not clear how these neurons differentially affect downstream circuits.Heimer L, Zaborszky L, Zahm DS, Alheid GF. 1987. The ventral striatopallidothalamic projection: I. The striatopallidal link originating in the striatal parts of the olfactory tubercle. J Comp Neurol 255: 571-91Zhou L, Furuta T, Kaneko T. 2003. Chemical organization of projection neurons in the rat accumbens nucleus and olfactory tubercle. Neuroscience 120: 783-98The paragraph starting from the bottom of p. 6 and ending at the top of p. andIt is not coherently written. It is hard to follow the arguments.p. 7The authors state "D1 OT neurons selectively and bidirectionally encode learned odor valence, unlike D2 neurons". This statement sounds too strong. The sub-heading in the result section on p. 3 characterizes the results more sensibly as follows: "Individual D1 neurons are more likely to encode odor valence and D2 neurons more likely to encode odor identity". Essential revisions:1) Authors should provide more details about the specific cell types being monitored in the D1 and A2A-cre mice since cre is present in neurons, not just medium spiny / striatal projection neurons. The authors did not exclude these other cells in their analysis or experimentally so any revision should be clear about inclusion of other types of neurons .We acknowledge the potential heterogeneity of the cells we monitored in these mice. Two concerns raised by Reviewer 3 are: (1) cells in the islands of Calleja (IC), which has been shown to express D1 in addition to D3 receptors may be included in the imaging and (2) we may have inadvertently imaged cells in the ventral pallidum, which is located just dorsal to the OT. We address these concerns in detail in the response to Reviewer 3 below . We add some text in the Discussion, acknowledging these points (Discussion third paragraph).2) The function of the different subpopulations of 'valence coding' D1 neurons should be clarified in both the Results and Discussion. Relatedly, it is unclear how neuronal responses to neutral odors are taken into consideration when calculating valence scores. It is suggested to include the distributions of valence scores with shuffled cell-odor pairs as reference points. Statistical tests for comparing odor valence and identity distributions should be described in more detail.We now discuss the different subpopulations (Discussion third paragraph), and we explain in detail in the Response to reviewer 1 (first point). We have also considered different metrics for describing valence that would include neutral odors, and discuss why we converged on the particular metric we use. We explain in detail our response below . We have now used shuffled distributions for comparison  – thanks for this important suggestion. Finally, we describe statistical tests in greater detail throughout the manuscript.3) It is unclear how odor identity (and sound frequency) is represented in neuronal response patterns. The authors should show neuronal responses grouped by mice / odorant-unconditioned stimulus combinations, in addition to showing neuronal responses grouped by the trial outcomes only.Thank you for this suggestion. To better illustrate the neuronal responses to specific odor-outcome pairings, we have added a supplementary figure with neurons grouped by mouse / odorant-outcome combination . The basic patterns of results hold for individual mice.4) There was concern about a large portion of the brain damaged by the placement of the GRIN lens. The implication of this damage needs to be discussed.We have added some text discussing this damage , which is an unfortunate outcome of the experimental procedure. We address the issue in two ways. First, we argue that the principal findings in our work on the OT neuronal activity are unlikely to be related to this damage. Second, we show that the behavior of the mice is not detectably affected by the damage . We discuss these issues in detail below in the response to reviewer 3.5) It is suggested to better link behavior to neural responses- specifically the timing of licking with the GCaMP response.We appreciate this suggestion and have compared the timing of licking and the neuronal  responses. Details are below in the response to Reviewer 1 (forth point). Data are now shown in Figure 1 figure supplement 3.6) Authors should provide a clearer rationale for the tone learning study. The motivation for the odor-tone association experiments is unclear. The main result is that different subpopulations of OT neurons encode odor and tone associations. However, this does not appear to be a question the authors set out to address a priori.The tone learning experiments were actually an integral part of the study design. We used tones to determine whether adding another stimulus of a different modality will recruit the same cells for valence coding. We have strong evidence from our earlier study  that adding new odors does indeed recruit same valence cells, so we wanted to see if adding a rewarding cue from a different modality will engage the same cells. Although the use 4 tones (2 for aversion and 2 for reward) might be even cleaner, nevertheless, our current data indicate that adding a new stimulus does NOT automatically recruit the same reward category cells. We present a detailed response below under Reviewer 2, point 4. We explain these points in the manuscript now , and also acknowledge the limitations.Reviewer #1 (Recommendations for the authors):This study is a much needed addition to the field, and the manuscript is excellent and well done. I have a few number of major and a longer list of minor issues I'd appreciate being addressed.Figure 4F2 – the authors package these results that most D1 neurons maintain valence coding in absence of instrumental responding or conditioned outcomes, and while this is true, a good amount do not. It would be beneficial for the authors to elaborate upon what those two different subpopulations of D1 neurons are doing both in Results and Discussion.This is a question of great interest to us. In response to the Reviewer’s comment, we conjectured that it may be possible that a subpopulation of licking-responsive D1 neurons with high valence scores in Block 1 may have stopped differentiating between rewarded and unrewarded odors in Block 2. In order to test this, we correlated the activity of each neuron on a trial-by-trial basis in the pre-outcome period to the number of anticipatory licks in the pre-outcome period in Block 1. Activity of individual neurons was considered to be significantly correlated to anticipatory licking if the absolute value of Pearson’s correlation coefficient was > 0.5 and the p value was < 0.05 in either odor 4 or odor 5 trial types . We then compared the distribution of the valence scores of Block 1 licking correlated and non-correlated neurons in Blocks 1 and 2 . In contrast to the hypothesis that licking correlated neurons may be less likely to encode valence in Block 2, in the absence of licking, we found that these neurons maintained high valence scores in Block 2. In both groups of neurons, the distribution of valence scores in Block 2 was significantly different from that of the shuffled distribution (Wilcoxon Rank sum test p < 0.01). Rather, the valence scores of the Block 1 licking correlated neurons were significantly higher in Block 2, in the absence of licking, than those of the non-licking correlated neurons in Block 2 (Wilcoxon Rank sum test p < 0.0001). This suggests that there is not a separate population of neurons responding to licking and valence separately, but rather that licking and valence responsivity are intertwined factors, such that even in the absence of licking the same neurons continue to encode odor valence.We continue to be interested in the factors that lead to the decrease in the valence coding in Block 2 and suggest that the animal’s low motivational state in Block 2  likely results in lower overall engagement of the OT neuronal circuitry. In addition, in almost all coding frameworks, not every cell has directly interpretable responses and many factors will clearly influence firing. It is also plausible that any cellular plasticity mechanisms involved in the generation of the firing patterns will have stochastic elements such that not all neurons (and connections) will be modified in the desired direction. Another way to interpret the data is that the particular task we have engages only a small part of the overall capacity of the OT neural circuit – so one can expect only a fraction of the neurons to be altered by this task, leaving many as reservoirs for other functions. We continue to be interested in this question, but more directed experimentation may be required to explain the changes in the neuronal activity levels and valence coding between Blocks 1 and 2 and contrast it with typical representational drift. We have added this data in Figure 4 figure supplement 2B, and discuss this issue in the Discussion section, paragraph 3.The authors do show that some cells display auditory valence coding, yet conclude across the population there is no such activity. It would be helpful for the authors to describe activity of the cells which do in fact show learned responses to the tones.In the present version of the study, we only used a single aversive tone and a single rewarding tone. While there were clearly strong neuronal responses to these sound tones, we don’t have multiple sound tones for outcomes of the same valence as we did for odors in the original five odor task. Therefore, we cannot be sure that a cell responding to a rewarding tone is simply because of sensory tuning, or because of valence coding. It is certainly possible that if we had used multiple sound tones of the same valence, we would observe valence coding for sounds as we observed for odors in the five odor task. The primary question we asked with the existing experiments was whether neurons responding to odor of the same valence also responded to auditory stimuli of the same valence, and we found that this was not common – hence the perhaps confusing phrasing of “not modality invariant” . We note that our earlier study (Millman and Murthy J Neurosci 2020) offered strong evidence that adding new rewarded odors will indeed recruit same valence cells that respond to familiar rewarded odors. Our current data indicate that adding a new stimulus of a different modality does NOT automatically recruit the same reward category cells.Related to this, in some places the authors describe their results as "not modality invariant". Perhaps this could be rephrased to read, "modality variant" to avoid double negatives. Finally, isn't the finding that there are responses to multisensory stimuli and that these responses are dependent upon learning reason to reconsider titling this paper as originating from the "olfactory striatum"? These results show this is not simply an "olfactory" structure, and as described in Wesson 2020 (Tubular Striatum), the concept of calling the olfactory tubercle the "olfactory striatum" lost ground decades ago. Of course, I'm all for scholarly creativity of the authors and am not asking them to change the title, but more to think about what message this sends to readers.”We have rephrased the relevant text as “modality-sensitive” (in the Abstract and in the main text). We appreciate the point made by this reviewer about the multisensory nature of this structure and the use of the term olfactory striatum. After considering all alternatives, we prefer to use the classical term olfactory tubercle and have titled the paper as “Distinct representation of cue-outcome association by D1 and D2 neurons in the ventral striatum’s olfactory tubercleOverall, it would be helpful to see the timing of licking, even if on average, to help relate the gcamp response to behavior better. This is important since the authors used a fixed ITI of 20s and normalized each neuron's activity to a 1s pre-trial baseline. But can we be sure there was no anticipatory-related activity during that time? More specifically, it would be nice to show a new figure/inset of Figure 1C, day 1 and/or 4 in raster-format (similar to 4B perhaps) so readers can gain an appreciation for the timing of the licks specifically in this panel, if possible .Thank you for this excellent suggestion. We have plotted the time of the first lick post-odor onset for each of the four training days in D1 and D2 mice, and the distribution of the times of the first lick . We find that the time of the first lick is on average 0.72s ± 0.3s (std dev) after odor onset. Rarely, the mice would lick immediately after the opening of the odor valve, but this was not in response to only the rewarding odors but occurred also in response to other odor types. The timing of the first lick we observe here is later than had been observed in previous studies  because in those studies a licking response was required to receive the water reward, whereas in our study the delivery of the water was not contingent on the licking response. Hence, the mice tended to start licking closer to the time of the water delivery, which occurred at 1.3s after the odor onset. The late onset of the licking response that we quantified further strengthens the argument that the valence-related activity we observed in the first 0.5s after odor onset is not a result of the licking response but rather in response to the positively reinforced odors instead. As displayed in Figure 2A and B, the activity of OT neurons often peaks by the 0.5s after odor onset well preceding the licking itself. Per the reviewer’s suggestion, we will place dashed lines in the neuronal population activity plots to indicate the average time of licking onset in the rewarded trials.I'd appreciate the authors elaborating upon the argument from their Discussion that tubercle neurons "encodes odor salience rather than signed odor valence". I'm not sure that I appreciate how the authors results directly disambiguate this, nor am I even clear how one could do in the context of like experiments.We propose that salience coding neurons would respond similarly to odors of high relevance (e.g. odors predicting strong airpuff or big water reward) whereas valence coding neurons would respond similarly to odors predicting outcomes of the same sign (e.g. two odors predicting water reward), as in the hypothetical responses illustrated in Figure 3A. Given the distinctly different population and individual neuronal activity to odors predicting positive and negative outcomes, we quickly concluded that it was rare for neurons to exhibit response patterns consistent with salience coding without regard to outcome direction. We quantify this in the following portion of the text “the prevalence of neuronal responses consistent with odor salience coding was very low .”In response to the Reviewer’s question, and to further elaborate the difference between valence and salience coding, we added a salience score calculated analogously to the valence score as follows:In this calculation, odor pairs 3-5 and odor pairs 3-1 were considered to have different salience . Odor pairs 1-5 and 2-4 were considered of more similar salience because they produced large and medium outcomes, respectively. According to this calculation, a neuron with salience-like responses  should receive a high positive salience score. In contrast, a neuron with very different responses to outcomes of opposite sign (rewarding v aversive) but similar magnitude, should receive a negative salience score inconsistent with salience coding. As expected, we find that there are very few D1 or D2 neurons in either Block 1 or 2 of the task with have positive salience scores. This indicates that the incidence of neurons with responses consistent with salience coding is highly rare in the OT. If anything, a comparison with the shuffle controls indicates that there is greater than chance occurrence of negative scores . We present this data in Figure 3 figure supplement 1 and Figure 4 figure supplement 2A now, and mention in the Results.Reviewer #2 (Recommendations for the authors):1) It is unclear how neuronal responses to neutral odors are taken into consideration when calculating valence scores. For example, a neuron with a strong (positive) valence score would be expected to respond to the rewarded odor but not to the neutral odor or odors associated with the air puff. The current analysis appears to ignore neutral odors and should be expanded to include neutral odors.Thank you for this clarifying point. We did not sufficiently address the responses of the neurons in neutral odors in the original manuscript and have added results to better demonstrate the neutral odor responses, which are interesting. Neuronal responses to neutral odor trials were not always intermediates between aversive and rewarding odor responses. Instead, neutral odor responses often tracked closely with the aversive odors, and more rarely tracked closely with the rewarded odors or fell between the two . In Block 1 of the last day of training, valence responsive neurons (those which clearly differentiated between rewarded and aversive odors) tended to respond to neutral odors similarly as to the aversive odors ; however, there appeared to be a second smaller group of neurons which responded to neutral odors similarly as they did to the rewarded odors. This was also true of D2 neurons in Block 1 which differentiated between the rewarded and aversive odors . In Block 2, when the licking and outcomes were omitted, this distribution shifted to the right indicating that neutral odor responses tended to be an intermediate between aversive and rewarding odor responses or track more closely with the rewarded odor responses . This suggests that the similarity in the responses to the aversive and neutral odors in Block 1 was likely in part due to the fact that the mice were not licking in response to the aversive and neutral odors, but were licking in response to the rewarding odors. The same trend is observed in the principal components of the D1 neuronal activity in Blocks 1 and 2 , where neutral odor responses trend with aversive odor responses in Block 1, but fall intermediate between rewarded and aversive odor responses in Block 2.In determining the formula for the valence score calculation, we aimed to identify neurons which clearly differentiated between the two aversive and the two rewarding odors.Due to the variability in the neutral odor responses which often tracked closely with either the aversive odors or the rewarded odors in neurons which clearly differentiated between the rewarded and aversive odors, the neutral odor responses were not included in the numerator of the valence score formula. However, while the numerator of the equation does not incorporate neutral odor responses, the denominator would take into account neutral odor responses if they were either the minimum or maximum of those observed. We have added these points in the Methods section when describing valence scores, and present the panels in Figure 4 figure supplement 3.2) In figure 3, the authors claim that for D1 but not D2 neurons, the valence score increases with training. Valence scores in naive mice are expected to be zero – this should be reflected in the data. To help interpretability, the distributions of valence scores with shuffled cell-odor pairs should be included as reference points.To provide a point of comparison, we have now incorporated the Reviewer’s great suggestion of the valence scores calculated with shuffled odors in all of the valence score distribution plots . As the identity scores were calculated on the basis of the best odor response as compared to the next best one, the shuffling procedure does not affect the identity scores and was not done for those distributions. These are now shown in Figures 3F, 4F and 5FG, and mentioned in the text.With regards to the naïve mice – we found that the mice learned the odor association task quickly, such that by the second half of the training session of the first day of training with the odors the mice had learned the associations . Due to the very small number of trials during which the mice were exposed to the odors but had not yet learned the odors associations , we are unfortunately unable to calculate neuronal valence coding in the naïve state .Furthermore, figure 1 suggests that there is a rage of anticipatory lick numbers on day one, likely reflecting differences in learning during the first session. When analyzing imaging data over time, the authors should compare data from mice with similar behavioral performance.The added variability in the day 1 licking rates is in part due to the learning process, but is likely also because in two of the six Drd1-Cre mice we imaged, in the first training day the lick detection did not pick up any licks due to a malfunction (thus those two mice were not included in the day 1 mean). This only occurred on the first day of two D1 mice and not on any other training days or mice. The individual licking rates of the four remaining D1 mice  all indicate that the mice began to learn the odor associations within the first day to varying degrees. While we would have liked to have imaging data to analyze at a stage when the mice have not yet learned the odor associations, they learned the task too quickly within < 10 trials of the first session in most cases.Based on the Reviewer’s suggestion, we plotted the anticipatory licking of each mouse separately across training days . We found that by day 2 all mice exhibited clear knowledge of the rewarded odors, and this was maintained through day 4. Note that the mice were not required to lick to receive the water reward, and there were no consequences for licking in response to the aversive and neutral odors. The absolute anticipatory licking rates varied slightly and were modulated by many factors beyond odor-outcome learning including the motivational level (thirst) of the mouse and overall tendency of the mouse to lick. We also confirmed that the mice differentiate between the small water reward predicting odor and the large water reward predicting odor. In day 4 of training, they did an average of 2.and anticipatory licks in response to odor 5 and an average of 2.0 anticipatory licks in response to odor 4 . This suggests that the mice learned the gradient of odor outcomes rather than simply categorizing odors into rewarding or aversive.Due to the quick learning and ceiling effect of the behavior, we only compare neuronal activity in days 1 and 4 in our analysis. The three main neuronal imaging results we report  are all from imaging experiments conducted at the end of the training. By day 4, all mice clearly differentiated between the rewarded and unrewarded odors  and we concluded that it is reasonable to combine the neuronal activity recorded from the mice. We show the individual mouse licking data in Figure 1 figure supplement 3.3) In figure 4, the authors state that the mean valence score of D1 neurons remains above zero for block 2 trials – the mean valence score should be indicated in the figure. Statistical tests for comparing odor valence and identity distributions should be described in more detail.Thank you for this suggestion. The mean valence score for D1 neurons in Block 1 is 0.39, the mean valence score for D1 neurons in Block 2 is 0.18 and there is a bimodal distribution of valence scores in Block 2 with one of the modes centered around zero and one of the modes centered around 0.4 similar to the mean in Block 1. The non-parametric two-tailed Wilcoxon rank sum test was used in all statistical comparisons of valence and identity score distributions. The Wilcoxon signed rank test indicates that the distribution of the overall valence scores of D1 neurons in Block 2 is significantly different from zero p = 2.8151e-13. Per the Reviewer’s suggestion, we also added the shuffled valence score distribution for the same neurons and find that the Block 2 D1 neuron valence score distribution is significantly different from the shuffled distribution . We have added this information in the main text in the Results section .4) The motivation for the odor-tone association experiments described in figure 5 is unclear. Without characterizing tone-outcome learning in OT neurons in the described experimental setting, the multimodal task is difficult to interpret. Furthermore, the response properties of neurons in the 'full task condition' are hardly analyzed (supplementary figure 4), instead, the analysis focuses on block 2 trials and is difficult to follow.The main result is that different subpopulations of OT neurons encode odor and tone associations. However, this does not appear to be a question the authors set out to address and may be a trivial result given the well-established differences in neuronal connectivity.Thank you for raising this point which was not previously explained well. We had three motivations for conducting the sound-odor association experiment. First, it has previously been demonstrated that neurons in the tubercle can become activated in response to auditory tones , so we wondered whether the valence related activation we observed in response to odors extended to auditory stimuli of the same valence as well. Second, as we learned that this was not the case, we found that the sound trials could serve as an additional control for checking whether the valence-related neuronal activity we observed was due to the instrumental licking response. The mice licked at similar rates in response to the rewarding odor and sound stimuli, and yet we did not observe the same similarity in neuronal responses to these odor and sound stimuli as we did to odors of the same valence in the five-odor task. This strengthens the argument that the odor valence-related activity we record in the original association task is not purely a result of the shared licking response to the two rewarded odors. Third, in the long term, we are interested in investigating the question of whether odor associations have unique qualities such as being more long-lived or more likely to elicit strong emotional responses due to the direct convergence of olfactory bulb input and dopaminergic input in limbic brain regions such as the olfactory tubercle. For this reason, we found it useful to use sound associations and related neuronal responses to gather evidence to begin to address this question. We clarify this in the manuscript in the Results section, when we first describe the odor-sound experiments and Figure 4.The reviewer has correctly pointed out that in the main text we selected to focus on the neuronal imaging results in the final blocked version of the sound-odor association task. This was done primarily for the sake of brevity, to focus on the most direct comparison of the neuronal responses to the stimulus-only condition to the sounds and odors. In doing so, we could directly compare valence coding in the stimulus only condition in the odor-odor task and in the odor-sound task and eliminate the effects of the licking responses and the water/airpuff outcomes which were shared in the two tasks. We do display the distribution of the valence scores in the full-task condition in the odor-odor and odor-sound tasks in Figure 5F, the Block 1 and Block 2 neuronal activity principal components in Figure 5I, and the full-task neuronal activity in Figure 5 figure supplement 1. We also show the cosine similarity for the O-O and O-S task in Blocks 1 and 2 in Figure 5J.5) It is unclear how odor identity (and sound frequency) is represented in neuronal response patterns in figures 2 and 4. The authors should show neuronal responses grouped by mice / odorant-unconditioned stimulus combinations, in addition to showing neuronal responses grouped by the trial outcomes only.Thank you for this suggestion. To better illustrate the neuronal responses to specific odor-outcome pairings, we have added a supplementary figure with neurons grouped by mouse / odorant-outcome combination. The basic patterns of results hold for individual mice. These are shown in Figure 2 figure supplement 1 and Figure 5 figure supplement 1.Reviewer #3 (Recommendations for the authors):p. 2The term "addictive" is not appropriate to describe intracranial self-administration of cocaine. Use "reinforcing" or "rewarding", instead.We have changed in to “reinforcing”.Suppl. Figure 1AOT D1R neurons do not project to the substantia nigra or ventral tegmental area, or OT D2R neurons do not project to the globus pallidus. It is confusing to mention such projections that are most likely caused by viral diffusions to the nucleus accumbens and dorsal striatum. Clarify the points that the authors are making here.We apologize for the confusion. The reviewer is correct in that the OT D1 and D2 neurons do not project to SNc/VTA and GP. This figure was included to validate the mouse models used – that the D1 and D2 mouse lines have differential projections, and the virus spillover in regions near the OT  will allow us to trace projections to the SNc and VTA. However, this is needlessly confusing, and these mouse lines have been extensively validated previously, therefore we have removed this figure panel.Figure 3ADotted circles used to describe their identifies are not shown on the actual diagram.Apologies – we have added these now.p.3Licking response may not be labeled as "instrumental". Essentially, the study ued a Pavlovian conditioning procedure rather than operant conditioning procedure. Therefore, the conditioned licking response is a Pavlovian conditioned response.We agree with this assessment – we have changed instances of the term “instrumental” to “licking” in the text.p. 4For clarity, rewrite the sentence that contains the phrase "non-zero licks were excluded."OK. We have changed this to “any trials in which the mice licked were excluded”.Rewrite the sentence "Odors 1 and 5, which... were combined with two sound tones". This sentence does not convey what the authors are trying to describe. The two modalities were combined in the new experiment; odors did not get combined with tones, which has a completely different meaning.OK, we have changed this to: A new task was introduced in which two odor-outcome associations and two sound-outcome associations were used. The odors 1 and 5 were paired with strong airpuff and large water reward as previously, and two sound tones were used (5kHz and 12kHz) also paired with strong airpuff and large water reward.p. 4 and Figure 5A,Avoid the phrases "odor and sound pairs" and "odor-sound pairs". In the psychology/behavior conditioning literature, they mean that odors are paired with sounds.This is a fair point. We have changed the text to remove pairs, and just refer to them as “odor and sound”.Figure 5BThe plot suggests that by day 3, the mice may not have fully discriminated between sounds 1 and 2. The mice displayed anticipatory licks with sound 1 while they did not with odor 1.We agree with the Reviewer that there is more anticipatory licking in response to the aversive sound 1 than to the aversive odor 1. However, the mice tend to lick marginally more both in response to the rewarded and aversive sounds – possibly due to the startling nature of the sound onset. In day 3, the mice clearly and strongly discriminated between sounds 1 and 2. They perform an average of 3.and anticipatory licks in response to sound 2 and 1.1 licks in response to sound 1 . The difference between the number of licks between sound 1 and sound 2 is ~2.6 licks. In comparison, the mean number of anticipatory licks for small rewarded odor 4 in the odor-odor task was 2.2 and the number of licks for aversive odor 1 was 0.08, for a smaller difference of 2.1 licks between the two stimuli. Therefore, we are sure that mice are indeed discriminating quite well between sounds 1 and 2. We present these numbers when describing the sound-odor experiments in the Results section.Figure 5F-5G and Suppl. Figure 5B-5CIt is more informative to show data separately between O and S for the plots of the OS experiment.We are not sure we understand the reviewer’s point. In the Odor-Sound experiment, there is no “O” valence score or “S” valence score, since there is only one odor and sound for each valence. The valence scores can only be calculated by comparing odors and sounds of the same vs opposite valence.Suppl. Figure 4Airpuff-paired sound triggered little or no conditioned response from the D1 neurons. What does this mean?We thank the Reviewer for this interesting observation. While we can only conjecture, we believe the reason for this may be that the activity in response to the sound stimuli in the “full task” condition as shown in Suppl. Figure 4 may be dominated by the response of the mice to the stimuli and the outcomes rather than the sound stimuli themselves. In the case of the airpuff-paired sound, the mice perform little anticipatory licking and likely the most salient event occurs at the onset of the airpuff. This is also supported by the fact that the airpuff-onset related neuronal activity is similar in the aversive odor and aversive sound trials. In the case of the water-paired sound, the mice begin anticipatory licking after the onset of the sound and continue to do so when the water outcome is delivered. However, we also note the presence of a significant number of sound 2 responsive neurons in Block 2 of the odor-sound task when there was no licking, indicating that the neuronal activity in response to the rewarded sound is not only due to licking. Indeed, there were very few (2.and%) of D1 neurons which were preferentially activated to aversive sound stimulus in Block 2. It remains to be explored whether D1 OT neurons are more likely to respond to reinforced sounds than aversive sounds, but our data indicates that this may be the case. We really don’t have anything informative to add in the manuscript, so have not done so.Suppl. Figure 5B-5CThe Y-axis is not labeled.Sorry for the oversight, and thanks for noting this. Corrected.p. 6What do water- or airpuff-paired neural signals encode when they are present in the absence of behavior?We are not sure what exactly the reviewer is asking, but here is an interpretation. Sensory signals are presumably converted/processed to allow motor outputs. In the earliest stages, the signals are likely to be largely sensory, and the latest stages signals will relate to motor acts . In the intermediate regions, signals are likely to be mixed. We suggest that signals in the OT are strongly sensory-related, but modified substantially to allow for categorical predictions. Therefore, while behavior can affect these signals, there will still be significant sensory component even in the absence of behavior .The last full paragraph on p. 6The discussion is confusing. The authors mention that D1R neurons and D2R neurons have differential projections and that they have confirmed the fact in Fg. S1A. However, the authors do not discuss how projection patterns of the D1R and D2R neurons in the dorsal striatum and the nucleus accumbens are relevant to those of the OT. OT D1R and D2R neurons primarily project to the ventral pallidum ; it is not clear how these neurons differentially affect downstream circuits.Heimer L, Zaborszky L, Zahm DS, Alheid GF. 1987. The ventral striatopallidothalamic projection: I. The striatopallidal link originating in the striatal parts of the olfactory tubercle. J Comp Neurol 255: 571-91Zhou L, Furuta T, Kaneko T. 2003. Chemical organization of projection neurons in the rat accumbens nucleus and olfactory tubercle. Neuroscience 120: 783-98Once again, we apologize for the confusing presentation. As noted in the response above to the reviewer’s earlier comment, we do not mean to imply that OT neurons project to VTA/SNc etc. We used Supp Figure 1A to validate the mouse lines used, and we realize that this is confusing/misleading. We have removed Supp Figure 1A and its reference – instead we use the references suggested by the reviewer to make our differential projections point in the Discussion (paragraph 5).The paragraph starting from the bottom of p. 6 and ending at the top of p. andIt is not coherently written. It is hard to follow the arguments.We have tried to clarify this part, in Discussion (paragraph 6) now.p. andThe authors state "D1 OT neurons selectively and bidirectionally encode learned odor valence, unlike D2 neurons". This statement sounds too strong. The sub-heading in the result section on p. 3 characterizes the results more sensibly as follows: "Individual D1 neurons are more likely to encode odor valence and D2 neurons more likely to encode odor identity".We have modified this sentence to “D1 OT neurons are more likely to encode learned odor valence than D2 neurons, and conversely less likely to encode odor identity”.References:Pharmacol Biochem Behav 60, 313-9.Barik, S. and de Beaurepaire, R. (1998). Hypothermic effects of dopamine D3 receptor agonists in the island of Calleja Magna. Potentiation by D1 activation. J Neural Eng 10, 066012.Cowley, B. R., Kaufman, M. T., Butler, Z. S., Churchland, M. M., Ryu, S. I., Shenoy, K. V. and Yu, B. M. (2013). DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity. J Neurosci 10, 2587-600.Mansour, A., Meador-Woodruff, J. H., Bunzow, J. R., Civelli, O., Akil, H. and Watson, S. J. (1990). Localization of dopamine D2 receptor mRNA and D1 and D2 receptor binding in the rat brain and pituitary: an in situ hybridization-receptor autoradiographic analysis. Neurochem Int 20 Suppl, 33S-43S.Mengod, G., Villaro, M. T., Landwehrmeyer, G. B., Martinez-Mir, M. I., Niznik, H. B., Sunahara, R. K., Seeman, P., O'Dowd, B. F., Probst, A. and Palacios, J. M. (1992). Visualization of dopamine D1, D2 and D3 receptor mRNAs in human and rat brain.


Multimodal analgesia that provides optimal pain treatment with minimal side effects is important for optimal recovery after open cardiac surgery. Regional anaesthesia can be used to block noxious nerve signals. Because sternotomy causes considerable pain that lasts several days, a continuous nerve block is advantageous. Previous studies on continuous sternal wound infusion or parasternal blocks with long-acting local anaesthetics have shown mixed results. This study aims to determine whether a continuous bilateral parasternal block with lidocaine, which is a short-acting local anaesthetic that has a favourable safety/toxicity profile, results in effective analgesia. We hypothesise that a 72-hour continuous parasternal block with 0.5% lidocaine at a rate of 7 ml/hour on each side provides effective analgesia and reduces opioid requirement. We will evaluate whether recovery is enhanced.In a prospective, randomised, double-blinded manner, 45 patients will receive a continuous parasternal block with either 0.5% lidocaine or saline. The primary endpoint is cumulated intravenous morphine by patient-controlled analgesia at 72 hours. Secondary end-points include the following: (1) the cumulated numerical rating scale (NRS) score recorded three times daily at 72 hours; (2) the cumulated NRS score after two deep breaths three times daily at 72 hours; (3) the NRS score at rest and after two deep breaths at 2, 4, 8 and 12 weeks after surgery; (4) oxycodone requirement at 2, 4, 8 and 12 weeks after surgery; (5) Quality of Recovery-15 score preoperatively compared with that at 24, 48 and 72 hours, and at 2, 4, 8 and 12 weeks after surgery; (6) preoperative peak expiratory flow compared with postoperative daily values for 3 days; and (7) serum concentrations of interleukin-6 and lidocaine at 1, 24, 48 and 72 hours postoperatively compared with preoperative values.Adequate analgesia is important for quality of care and vital to a rapid recovery after cardiac surgery. This study aims to determine whether a continuous parasternal block with a short-acting local anaesthetic improves analgesia and recovery after open cardiac procedures.The study was registered in the European Clinical Trials Database on 27/9/2019 (registration number: 2018-004672-35).The online version contains supplementary material available at 10.1186/s13063-022-06469-5. The order of the items has been modified to group similar items  pathways seek to attenuate the negative effect that surgery has on normal physiology, with the ultimate goal to allow a more rapid return to normal life , 12. A cTwo continuous peripheral blocks that have been described after sternotomy and are anatomically in proximity are sternal wound infiltration and a bilateral sternal block. In sternal wound infiltration, a catheter for continuous local anaesthetic infusion is placed centrally in the sternal wound. A bilateral sternal block is performed by bilaterally inserting a catheter over the costosternal margin. As described by Eljezi et al , the aimAn increased risk of infection has been raised as a possible issue for continuous regional anaesthesia in cardiac surgery. In a prematurely stopped trial reported by Agarwal et al , a contiWe consider that the above-mentioned studies show the potential of a continuous peripheral parasternal block after cardiac surgery, but its full effect has not been shown. In an attempt to further investigate this continuous block, we propose examining the use of a short-acting local anaesthetic of lidocaine, which will allow a dose increase for effect and simultaneously address the concern of an increased risk of infection.We plan to evaluate the analgesic efficacy of the least toxic local anaesthetic lidocaine in a continuous bilateral parasternal block after sternotomy for cardiac surgery. By using a relatively low 0.5% concentration at a total rate of 14 ml/hour (7 ml/hour on each side), our aim is to achieve a spread of local anaesthetic that will effectively block the distal endings of intercostal nerves. We will study whether this block offers effective analgesia and minimises the requirement for opioids. Additionally, we will evaluate if effects can be seen in quality of recovery in a broader perspective after this type of major surgery.This study will be conducted as a single-centre, randomised, double-blinded, clinical trial.The study population will consist of adult patients undergoing elective open cardiac surgery at the Karolinska University Hospital in Stockholm.The inclusion criteria are as follows: (1) male and non-pregnant female patients aged 20–80 years; (2) American Society of Anesthesiologists Physical Status Classification (ASA) II–II; (3) not undergoing emergency or planned redo surgery; not suffering from (4) severe left heart failure, (5) respiratory insufficiency, (6) advanced kidney failure or (7) pronounced hepatic disease; (8) no allergy to local anaesthetics; (9) no psychiatric disease or any psychoactive medication; (10) no cognitive disturbance and/or inability to understand written and/or oral instructions; (11) no history of chronic pain or chronic pain medication; and (12) informed consent.The exclusion criteria are as follows: (1) failure to be extubated within 4 hours after surgery; and (2) deep hypothermia during surgery.If study participants are subject to acute redo after the primary procedure and can be extubated within 4 hours thereafter, the study will continue per protocol.The principal investigator (ML) will obtain written informed consent from each study participant after oral and written information about the study has been provided to the participants.The study participant information form contains specific information on the collection, handling and analyses of blood samples taken during the trial. The consent form has specific boxes to tick for approval of the collection, handling and analyses of blood samples as explained in the information for the study participants.This trial is designed to compare a continuous parasternal block with the standard of care. Therefore, the comparator is saline. The standard treatment consists of paracetamol and a patient-controlled analgesia (PCA) pump with morphine.At the end of surgery, after sternal closure and wound closure, the skin surrounding the sternal wound will once again be swabbed with chlorhexidine. Thereafter, the surgeon who performed the procedure will insert a 19-cm multiply perforated catheter subpectorally on either side of the sternum over the costosternal margin. Patients will be randomised to receive either saline 9 mg/ml (0.9%) or lidocaine 5 mg/ml (0.5%). After a bolus from two pre-prepared 20-ml syringes with the allocated solution in each catheter, both catheters will be connected to the elastomeric pump for continuous infusion of the randomised treatment at a rate of 7 ml/hour in each catheter. The resulting lidocaine administration will be 70 mg/hour (1680 mg in 24 hours). The elastomeric single-use pump will be replaced by a new after 24 and 48 hours to attain 3 days of treatment.Preoperatively, patients will receive instructions on the assessment of perceived pain. The instructions are to score perceived pain from 0 to 10 according to the numerical rating scale (NRS), where an NRS score of 0 indicates no pain, and an NRS of 10 is the worst imaginable pain. Pain is further explained and categorised as mild (NRS scores of 1–3), moderate (NRS scores of 4–6) or severe (NRS scores of 7–10).Starting at the end of surgery, all patients will receive intravenous or oral paracetamol 1000 mg every 6 hours. After extubation, when the patient states a score greater than mild (an NRS score > 3), the attending ICU/recovery nurse will provide rescue analgesic as follows: (1) an intravenous bolus of morphine will be administered with 1-mg increments up to a total dose of 0.15 mg/kg; (2) if NSAID is tolerated and considered acceptable regarding chest tube flow, 15–30 mg of ketorolac will be administered intravenously; and (3) if tolerated and considered acceptable regarding alertness and blood pressure, 15–75 μg of clonidine will be administered intravenously. All rescue medication can be repeated as considered necessary to achieve an NRS score ≤ 3.After mild or no pain has been achieved (NRS score ≤ 3), a PCA pump will be connected to allow the patient to perform self-administration of intravenous morphine. The instructions for use will be to achieve an NRS score ≤ 3. On the patient’s demand, the PCA pump will deliver 1 mg of morphine, with a lockout time of 6 minutes and a maximal dose of 30 mg every 4 hours. Rescue analgesia consists of the same algorithm as the one described for rescue medication before starting the PCA pump.Analgesia after discharge from the ICU will consist of morphine by PCA and oral paracetamol 1000 mg every 6 hours. To treat break-through pain at the surgical ward that cannot be relieved with this regimen, additional intravenous morphine can be administered by the attending nurse. If required, rescue pain treatment will consist of an oral nonsteroidal anti-inflammatory drug (naproxen 250–500 mg) and/or oral clonidine (75 μg).After the 72-hour study period, the bilateral parasternal catheters will be removed and the PCA pump will be discontinued. If continued analgesia is required after the intervention, the patient will receive the following oral analgesia. (1) Slow-release oxycodone will be administered twice daily. An oral daily oxycodone dose will be approximated to the equivalent of the intravenous dose of morphine administered by the PCA pump during the last 24 hours of the intervention. (2) Paracetamol 1 g will be provided four times daily and rescue medication that consists of short-acting oral oxycodone will be provided.Parasternal infusion of the trial medication will be discontinued earlier than after 72 hours for the following reasons: (1) the trial subject retracts consent; (2) inadvertent removal of one or both parasternal catheter(s); (3) surgical complications requiring the removal of one or both parasternal catheter(s); (4) unforeseen medical occurrence caused by one or both parasternal catheter(s); and (5) unforeseen severe and potentially life-threatening medical event that is suspected to be the result of an allergy to or systemic toxicity of the infused study medication.Mild to moderate symptoms of lidocaine toxicity such as tinnitus, dizziness, blurred vision, metallic taste, peri-oral numbness and tongue paraesthesia may be managed with medication and are not necessarily reason for discontinuation of the intervention.Study participants who cannot engage in the follow-up owing to a prolonged ICU care will be considered dropouts. Further assessment will be discontinued.The intervention will last the first 72 hours after surgery. Study participants will be under continuous care at the ICU/surgical ward and will be visited daily by the study team.All study participants will receive standard postoperative care according to departmental practice.At the end of the intervention, the study participants will be cared for according to departmental practice. If required, analgesia will be provided as described above (“Intervention description” subsection). Open cardiac surgery and participating in this trial carry risks. In case any adverse event occurs, our department and the hospital will provide care, irrespective of the cause. The National Patient Safety Insurance will cover potential insurance claims.The primary endpoint is cumulated intravenous morphine administration by PCA at 72 hours. The secondary end points are as follows: (1) the cumulated NRS score three times daily at 72 hours; (2) the cumulated NRS score after two deep breaths three times daily at 72 hours; (3) the NRS score at rest and after two deep breaths at 2, 4, 8 and 12 weeks after surgery; (4) oxycodone requirement at 2, 4, 8 and 12 weeks after surgery; (5) Quality of Recovery (QoR)-15 score preoperatively and at 24, 48 and 72 hours, as well as at 2, 4, 8 and 12 weeks after surgery; (6) peak expiratory flow (PEF) preoperatively, postoperatively on the morning after surgery and in the evening from day after surgery until postoperative day 3; and (7) serum concentrations of interleukin-6 (IL-6) and lidocaine at 1, 24, 48 and 72 hours after starting the intervention compared with preoperative values.In addition to the primary and secondary endpoints, we will observe (1) the incidence of nausea and/or vomiting at any time during the initial 72 hours; (2) the incidence of sedation at any time during the initial 72 hours; (3) the incidence of arrhythmia, with more than single or solitary coupled supraventricular and ventricular extra beats at any time during the initial 72 hours; (4) NRS scores at rest at all time points during the initial 72 hours; (5) morphine consumption at 24, 48 and 72 hours; (6) NRS scores after two deep breaths three times daily during 72 hours; (7) the day of discharge and discharge time; and (8) the occurrence of sternal wound infection.See Appendix p < 0.05) with a power of 80%. This sample size calculation is based on the first 48-hour opioid requirement postoperatively. The study participants will be cared for in-hospital for at least 4 days postoperatively. Therefore, we expect a low drop-out for our primary endpoint of opioid requirement at 72 hours. To compensate for potential drop-out and/or incomplete collection of data, 45 patients will be included and randomised.Historical data at our institution show a mean (± standard deviation) intravenous morphine requirement of 67 (± 30 mg) after open cardiac surgery for the first 48 postoperative hours. We have previous experience of a continuous bilateral parasternal block after cardiac surgery. When infusing 8 mg ropivacaine/hour in each catheter , we found a mean morphine requirement of 53 mg the first 2 postoperative days, which equals to a decrease of 14 mg morphine. We believe that the use of a higher equivalent dose of lidocaine will increase efficacy, which we hypothesise will double the decrease in morphine requirement. If we assume a requirement for ≤ 40 mg morphine for the first 48 postoperative hours for patients receiving a bilateral parasternal block, 21 patients in each arm are required to identify a significant difference  will be determined by the randomisation as described above. The principal investigator (ML) will prepare the envelopes for allocation. Concealment of allocation will be achieved because an anaesthesia nurse who is not involved in the study will open the envelopes and prepare the study medication. ML will enrol all study participants.The study participants, investigators, participating research nurses, attending anaesthesiologist, anaesthesia nurse and ICU/recovery nurses and nurses on the ward will be blinded to the allocation.In case a serious adverse event occurs that requires knowledge of the allocated treatment, the label concealing the content of the elastomeric pump can be removed with some effort. The randomisation list is kept locked in our local thoracic anaesthesia pharmacy and can be made available in case of emergency at any time of the day by contacting the principal investigator.The analgesics administered during surgery and the initial time at the ICU/recovery will be recorded and added to the case record form (CRF). After starting the PCA pump according to the protocol, administered doses will be registered in the PCA pump. The number of provided doses for every 24 hours and the total 72-hour period will be retrieved and recorded in the CRF. If any other rescue medication is required for pain control, the type and dose will be retrieved from the charts.Push notices with a link to an online platform will be sent to the study participant’s mobile phone at pre-determined times. After two-step verification, access can be gained to the current questionnaire. Only the principal investigator and study nurses will - after two-way verification - have access to the completed questionnaires. For each questionnaire at a certain follow-up time, a separate push notice with a link will be sent. Questionnaires will be sent at specific times to determine the following: (1) QoR-15 score preoperatively and at 24, 48, 72 hours, as well as 2, 4, 8 and 12 weeks after surgery; (2) pain according to the NRS at rest and after two deep breaths, every 8 hours for 72 hours starting the evening after surgery; (3) pain in the evening according to the NRS at 2, 4, 8 and 12 weeks after surgery; (4) requirement of oral oxycodone in the morning and evening at 2, 4, 8 and 12 weeks after surgery; (5) whether any nausea is experienced, every 8 hours for 72 hours starting in the evening after surgery; and (6) whether the trial subject has experienced nausea and/or vomited in the last 8 hours (yes/no), every 8 hours for 72 hours starting in the evening after surgery.Blood samples will be drawn before starting surgery and at 1, 24, 48 and 72 hours after the administration of the study medication bolus dose and the initiation of parasternal infusion. At the specified times, two samples will be drawn. One sample will be sent for direct analysis of IL-6 concentration at the hospital laboratory. The other sample will be centrifuged at 2000 g for 10 minutes. The serum will be pipetted in micro tubes and stored at −70°C. After conclusion of the enrolment, lidocaine concentrations in the serum samples will be determined.PEF will be measured with a standard peak flow meter. To improve accuracy, we will record the results of three consecutive measurements. PEF will be recorded preoperatively and at each postoperative day until postoperative day 3.Information on weight, length, the discharge time and the length of stay will be obtained from the electronic patient dossier.The intervention will occur during the first 72 hours after surgery and will be monitored closely by the study team. We hope that our digital platform will facilitate completion and result in a high response rate of the follow-up questionnaires during the 3 months after surgery.All study data will be retrieved and documented in CRFs, which are only identifiable by a randomisation number.The randomisation key and CRFs will be stored separately. Data labelled with the randomisation number only will be gathered in a file for data management and analyses. These files will be stored at secure servers at the Karolinska Institute or in personal lap-tops provided by the Karolinska Institute and accessible only with personal passwords.Blood samples will be drawn as described above. The collected serum will be stored at −70°C, and will only be identifiable by a randomisation number. After conclusion of the enrolment, lidocaine concentrations will be measured in serum samples. No samples will be saved after this analysis.Effect variables will be analysed per protocol for efficacy. Per protocol is defined as fulfilment of the 72-hour parasternal infusion. The intention-to-treat population will also be analysed, mostly for safety and side effects, but also for efficacy. The safety population will include any patient who received parasternal catheters.The primary effect variable (cumulated intravenous morphine administered by a PCA pump at 72 hours) will be analysed as a continuous variable. Assessment for normal distribution will be performed by the Kolmogorov–Smirnoff test, Shapiro–Wilk test and Q-Q plot.Non-parametric statistics will be applied for the secondary effect variables comprising NRS scores, the oxycodone dose and QoR-15 scores. PEF and stress marker levels will be analysed as continuous variables.Data will be reported as the mean and standard deviation unless otherwise stated. The comparison of normally distributed variables will be performed by Student’s t-test and/or analysis of variance. Variables that do not follow a normal distribution will be analysed by the Wilcoxon test. Categorical data will be analysed with the chi-square test or contingency tables as appropriate. Appropriate statistical tests will be performed for repeated measures. Data management and statistical analysis will be performed using Stata  and R .No interim analyses are planned.No additional analyses are planned.Protocol non-adherence for opioid requirement will be handled by transforming any opioid other than morphine to a morphine-equivalent value. If there are missing NRS and QoR-15 scores, we will apply last observation carried forward analysis.This is an investigator-initiated trial. There are no publication restrictions. The funders have no role in the study design, data collection and analysis, preparation of the manuscript or decision to publish.This is a single-centre trial. No steering committee will be formed. The principal investigator (ML) will inform the sponsor (JJ) on a weekly basis on the progress of the trial.No data monitoring committee will be formed because the trial will only encompass 45 patients and is planned to be completed within 18 months from starting the enrolment.During the intervention, the principal investigator (ML) will actively seek and be informed on a daily basis of any adverse event occurring. During the follow-up time after discharge until 12 weeks after surgery, the QoR-15 questionnaire will provide information on adverse events. We will monitor for possible re-intake of study participants regarding adverse events. The sponsor (JJ) will be informed about all and any adverse events. Serious adverse events will be reported within 24 hours.All adverse events will be recorded in the CRF. A distinction will be made between expected and unexpected adverse events. Each adverse event will be assessed for the intensity , severity (serious vs non-serious) and relationship with the administered trial medication . Serious adverse events will be presented to and discussed with all investigators within 1 week of being identified.All adverse effects will be reported in accordance with the applicable local and European Union laws and regulations. The Swedish Medical Products Agency, Swedish Ethical Review authority and all participating investigators will be informed in accordance with the timelines set out in the applicable laws and regulations.We plan for an independent research nurse who is not involved in the trial and not working at the same site as the investigators to perform an audit during the trial. The audit will review good clinical practice adherence, enrolment, consent and data reporting in the CRF.No changes to the protocol and procedures stated will be undertaken unless the Swedish Ethical Review authority, and if applicable, the Swedish Medical Products Agency are informed and have approved the amendment.The results of the trial will be presented in a peer-reviewed publication. No later than 3 years after the completion of the last study participant’s 12-week follow-up, deidentified participant-level data will be made available in an appropriate data archive for the purpose of sharing.The objective of this trial is to determine if a continuous bilateral parasternal block with continuous infusion of lidocaine reduces intravenous morphine consumption after open heart surgery. This issue is clinically important because a decreased need for postoperative opioids is thought to enhance patients’ recovery following cardiac surgery.To enable a parasternal block to reach its full analgesic potential, we believe that the large area  that needs to be blocked requires a larger amount (dose) of local anaesthetic. Eljezi and D’Ostrevy showed a visually adequate spread of local anaesthetic when they injected a bolus of 20 ml in a parasternal catheter . A localThese findings suggest that uptake and potential systemic toxicity are reasons for caution when considering high doses of long-acting local anaesthetics to achieve the optimal analgesic effect. When infused over a longer period of time, accumulating long-acting local anaesthetics have an increased risk of toxic plasma concentrations.To address the risk of toxic plasma/serum concentrations when long-acting local anaesthetics are infused, especially when the dose is increased to improve efficacy, we suggest the use of lidocaine as an alternative. Lidocaine is a well-studied, frequently used, short-acting local anaesthetic, and it also has an established intravenous indication as an anti-arrhythmic. Additionally, intravenous infusion of lidocaine has been extensively studied. Several reviews have evaluated its postoperative analgesic effect, one has assessed the treatment of other acute pain –39. In tIn addition to the analgesic effect of lidocaine, it has an anti-inflammatory effect. Although the exact mechanisms of lidocaine are unknown, they affect multiple steps in the inflammatory response . ClinicaWe are aware that the analgesic regimen that we propose allows for several different analgesics with different routes of administration to be used as rescue medication. Despite the risk that this regimen might complicate our evaluation of the parasternal block, we believe that this multimodal approach is our clinical standard and should be offered as a possible treatment to our study participants.In conclusion, we hypothesise that a continuous bilateral parasternal block with infusion of lidocaine 5 mg/ml at a rate of 7 ml/hour on each side  will result in lower opioid requirement postoperatively and lower pain scores during the first 72 hours following open heart surgery. We aim to evaluate whether a potentially decreased opioid requirement and pain in addition to a possible anti-inflammatory effect of lidocaine in plasma will result in an enhanced quality of recovery. We recognise that a continuous infusion of lidocaine will result in its presence in plasma and have taken into consideration recommendations for intravenous dosing in our study design.The recruitment of this trial was initiated in June 2021, and we are currently enrolling patients. The protocol that we adhere to is the amended version v 3.1, June 2019. We expect to complete enrolment in April 2022. The follow-up will be finalised in July 2022.Additional file 1.Additional file 2.