Pathway Specific Activation of D1 And D2 Medium Spiny Neurons in a CRE Mouse Model Reveals Distinct Roles in Reinforcement Learning and Decision Making via Closed Loop Optogenetic Neuromodulation 

Pathway Specific Activation of D1 And D2 Medium Spiny Neurons in a CRE Mouse Model Reveals Distinct Roles in Reinforcement Learning and Decision Making via Closed Loop Optogenetic Neuromodulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pathway Specific Activation of D1 And D2 Medium Spiny Neurons in a CRE Mouse Model Reveals Distinct Roles in Reinforcement Learning and Decision Making via Closed Loop Optogenetic Neuromodulation Apaala Basak, Erica Goodin, Olivia Botonis, Shramik Sengupta, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7794302/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The basal ganglia integrate cortical and dopaminergic inputs to shape reinforcement learning, action selection, and motivation through the direct (D1) and indirect (D2) striatal pathways. While these pathways are thought to facilitate opposing behavioral outcomes, their causal roles in reinforcement-driven learning remain poorly defined. Methods: Pathway-specific optogenetic activation was used in D1-Cre and D2-Cre transgenic mice to examine the functional contributions of dorsomedial striatum (DMS) circuits. Animals were trained in an olfactory Go/No-Go discrimination task with closed-loop optogenetic stimulation, and complementary open-field and unilateral rotation assays were performed to assess motivational and motor effects. Results: In unilateral rotation tests, D1 stimulation induced contralateral turning, while D2 stimulation elicited ipsilateral rotations, validating effective pathway recruitment. Open-field assays showed that D1 stimulation drove strong preference for the stimulation zone, consistent with enhanced motivational salience, while D2 stimulation induced avoidance, reflecting behavioral inhibition. In the Go/No-Go task, pathway stimulation did not alter learning rates or accuracy. Instead, changes were observed in motivational dynamics: D1 stimulation reduced next-trial initiation times, particularly after errors, indicating increased persistence and approach drive, whereas D2 stimulation prolonged initiation times following errors, indicating reduced engagement and motivational suppression. Conclusion: These findings demonstrate that the optogenetic-driven activity in D1 and D2 pathways in the DMS do not directly encode reinforcement learning but instead modulate motivational vigor and behavioral engagement. Next-trial initiation latency and spatial preference emerge as sensitive behavioral markers of pathway-specific neuromodulation, offering translational value for disorders involving motivation and action control. Basal Ganglia Motivation Reward Operant Conditioning Striatum Dopaminergic Pathways Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction On a hot summer afternoon, Taylor is craving for an ice-cream. There is an ice cream store within a mile from her home that serves two flavors only, while there is another one five miles away that serves multiple flavors including her favorite one. If Taylor choses to go to the one near her home, she has to decide between either of the ones the store offers, while if Taylor choses to spend some time and drive a bit longer, she can get her favorite flavor. Based on the choices that she has; Taylor has to decide to go to the one that is most favorable to her maximizing the choices that she has. This simple scenario illustrates reinforcement learning—a goal-directed process in which an agent, like Taylor, evaluates options to maximize rewards or avoid undesirable outcomes by interacting with the environment, experiencing consequences, and adapting future actions based on positive or negative feedback (Botvinick et al., 2020 ; Dong et al., n.d.; Ghasemi & Ebrahimi, 2024 ; Sivamayil et al., 2023 ). The brain’s capacity for behavioral flexibility relies on feedback-based learning, where actions are evaluated against desired goals and adjusted accordingly. For reinforcement learning (Fig. 1), this adjustment is based on trial-and-error that are guided by their outcomes. Positive reinforcement strengthens behavior through rewards, while negative reinforcement strengthens behavior by avoiding an aversive stimulus. These work in a complementary fashion which together foster goal-directed behavior and adaptive responses that eventually facitate effective learning. At the center of this process is the basal ganglia (Fig. 1), a network of deep subcortical nuclei essential for inducing voluntary movement, reward-based learning and decision making, by integrating sensory, motivational, and contextual signals to guide behavioral outcomes (Bar-Gad et al., 2003 ; Baron & Galizio, n.d.; Fee & Goldberg, 2011 ; Innes & McBride, 2008 ; Magoon et al., 2017 ; Murray & Sarasota, n.d.; Reinschluessel & Mandryk, 2016 ; Singh et al., 2019 ). Within this circuit, the dorsomedial striatum (DMS) is the primary candidate for goal directed behavior, by receiving inputs from higher order cortical areas, like the prefrontal cortex, and dopaminergic projections from the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA). Integrating past experiences, motivational salience and present sensory data, the DMS supports action selection and value estimation – the core basis of reinforcement learning (Murray and Sarasota, n.d.; Yin et al., 2005 b, 2005 a; Ragozzino, 2007 ; Lex and Hauber, 2010 ; Sivamayil et al., 2023 ). Dopamine, the principal neuromodulator of the basal ganglia system regulates synaptic plasticity and updates the neural representations of reward value (Braunlich & Seger, 2013 ; Gu, 1994 ; Lanciego et al., 2012 ; Rice et al., 2011 ; Schultz, 2016 ; Yelnik, 2002 ). Within the striatum, the dopaminergic system is primarily composed of medium spiny neurons (MSNs) that form two output pathways: the direct (D1 receptor expressing) pathway and the indirect (D2 receptor expressing) pathway. The former facilitates movement initiation and reward seeking while the latter suppresses movement and is associated with inhibition by discarding non favorable actions (Freeze et al., 2013 ; Friend & Kravitz, 2014 ; Kravitz et al., 2015 ; Kravitz & Kreitzer, n.d.). This dynamic push-pull enables adaptive behavioral selection based on values assigned to previous outcomes (Fig. 1). Although D1 pathways are thought to encode rewarded actions while D2 pathways suppress negative actions, their precise causal role in reward based learning is still under ambiguity. It is essential to address this gap, as imbalanced D1–D2 pathway activity is implicated in several neuropsychological disorders, including Parkinson’s disease, schizophrenia, addiction, and depression, that are marked by impaired reward processing and poor decision-making. Present treatment options lack pathway specific precision, focusing on palliative care (Ding and Perkel, 2002 ; Williams et al., 2002 ; Yelnik, 2002 ; Magill et al., 2004 ; Graybiel, 2005 ; Monchi et al., 2006 ; Balleine et al., 2009 ; Leblois et al., 2010 ; Fee and Goldberg, 2011 ; Rice et al., 2011 ; Friend and Kravitz, 2014 ; Ikemoto et al., 2015 ; Schultz, 2016 ; Pouzzner, 2017 ; Stocco, 2018 ). In the context of the example above, if Taylor’s D1 pathway is more active, she would prioritize the distant store with her favorite flavor, valuing the higher reward despite the extra effort. In contrast, if her D2 pathway dominates, she would focus on minimizing effort and choose the nearer store with fewer options. In this way, striatal circuits weigh reward against cost—ice cream representing the D1-driven reward value and distance representing the D2-driven cost—so that the final decision may favor the closer ice cream shop. To identify the pathway specific contributions of the D1 and D2 dopaminergic circuits in reward based learning, we developed a closed loop optogenetic neuromodulation based olfactory discriminatory Go-NoGo task that combines reward-driven behavior with inhibitory demands, thereby providing an ideal framework parsing D1-D2 mediated behavior. By selectively activating D1 and D2 MSNs, during discreet behavioral epochs, we assessed the contribution of each pathway in action selection, learning performance and response inhibition in real time. Such targeted experiments hold promise for not only advancing our fundamental knowledge of neuroscience, but also the development of next-generation treatment strategies for dopamine related disorders. Ultimately, a deeper understanding of the role of the D1-D2 pathways in shaping learning and feedback processing, will open up avenues for the development of personalized neuromodulation strategies, bringing precision medicine closer to individuals with neuropsychiatric deficits. Methods Overview of Experimental Design To investigate the pathway specific contribution of the direct (D1) and indirect (D2) pathways within the DMS in reward based learning, we employed optogenetic neuromodulation in transgenic mouse models during an olfactory discriminatory Go-NoGo task (Table 1). The neuromodulation consists of pathway specific activation of the D1 or D2 expressing MSNs using channelrhodopsin (ChR2), delivered via CRE dependent viral vector constructs that are triggered through temporally precise light pulses synchronized with behavioral events. The olfactory task refers to a behavioral paradigm in which mice are trained to discriminate between odor cues that signal either a “Go” response (initiating a nose poke to receive a water reward), or a “No-Go” response (withholding a response to avoid negative consequences such as punishment). This enables us to monitor real-time decision making processes and creates a controlled framework for assessing how pathway specific activation or inhibition influences learning and action selection. Unlike traditional reward-based tasks, our modified Go-NoGo paradigm incorporates both positive reinforcement and negative inhibitory control, allowing us to functionally isolate and evaluate the distinct contributions of each striatal pathways in reinforcement learning. The hypothesis is that activating the D1 pathway enhances reward-based learning, while activating the D2 pathway suppresses it. In D1 animals (having CRE positive expression for D1-type dopamine receptor pathway), optogenetic stimulation during No-Go trials was expected to improve performance by enhancing accuracy, reducing reaction times, and shortening initiation times for subsequent trials. Increased accuracy would suggest improved learning of the discrimination rule, faster reaction times are typically interpreted as greater movement vigor, and shorter next-trial initiation times reflect heightened motivation and engagement with the task. Conversely, in D2 animals (having CRE positive expression for D2-type dopamine receptor pathway), stimulation is predicted to impair performance, increase reaction time and next trial initiation time, suggesting that D2 activation inhibits learning. If these hypotheses hold true, it will reveal opposing roles of D1 and D2 pathways in modulating feedback-driven learning. These findings could provide insight into the neural mechanisms underlying decision-making and behavioral flexibility, ultimately clarifying how distinct basal ganglia circuits contribute to adaptive behavior. Animals : Breeder pairs were obtained from the Mutant Mouse Resource and Research Centers ( https://www.mmrrc.org/ ) for breeding. Mice were housed in a temperature- and humidity-controlled facility on a 12-hour light/dark cycle, with ad libitum access to food and water. All efforts were made to minimize animal suffering and the number of animals used. To dissect the pathway-specific contributions of dopaminergic signaling in reinforcement learning, we utilized two well-characterized Cre-driver transgenic mouse lines that allow for selective targeting of striatal neurons involved in the direct and indirect pathways of the basal ganglia: 1. D1-Cre mice: B6.FVB(Cg)-Tg(Drd1-cre)EY262Gsat/Mmucd 2. D2-Cre mice: B6.FVB(Cg)-Tg(Adora2a-cre)KG139Gsat/Mmucd In D1-Cre mice, Cre recombinase is expressed under the dopamine D1 receptor promoter, resulting in selective Cre activity in neurons associated with the direct pathway. Similarly, in D2-Cre mice, Cre expression is driven by the adenosine A2A receptor promoter, which is co-expressed with the dopamine D2 receptor, targeting neurons of the indirect pathway. These models thus allow for high-fidelity pathway-specific manipulation when combined with CRE-dependent viral constructs. Breeding pairs for both lines were obtained from the Mutant Mouse Resource and Research Centers (MMRRC) ( https://www.mmrrc.org/ ) , and colonies were maintained in-house. Mice were weaned at postnatal day 21 and housed in same-sex groups of 2–5 animals per cage. Genotyping was performed via standard PCR protocols using tail biopsies collected at weaning ( Transnetyxx, Cordova, TN ). Only those animals verified to carry the CRE transgene were included in subsequent procedures. Experimental subjects included both male and female mice aged 6 to 24 weeks at the time of behavioral testing, with body weights ranging from 18 to 30 grams. To ensure balanced representation and reduce sex-based variability, we included both sexes across each genotype whenever possible. Injection Surgery To enable pathway-specific optogenetic control of striatal neurons, bilateral viral injections were performed in D1-Cre and D2-Cre mice. Animals were carefully screened for health, genotype, and age, and only those meeting strict criteria underwent surgery. Preoperative planning included sterilization of tools, preparation of viral constructs (AAV5-EF1a-DIO-hChR2-GFP or -mCherry), and setup of a fully aseptic surgical environment with stereotaxic apparatus, isoflurane anesthesia, and heating pads. Mice were anesthetized with isoflurane, mounted securely in a stereotaxic frame, and monitored for anesthetic depth. The scalp was depilated, sterilized, and incised to expose the skull, with bregma and lambda landmarks aligned for accurate targeting. Burr holes were drilled at AP + 0.5 mm, ML ± 1.5 mm relative to bregma, corresponding to the dorsal striatum. Using a Hamilton syringe, 1.0 µL of virus was infused per site at 0.1 µL/min after lowering the needle to 2.5 mm DV (Fig. 2). The needle was left in place before and after injection to minimize backflow and tissue disruption. Following injections, burr holes were sealed with Kwik-Cast, incisions closed with VetBond, and animals received saline and analgesia. Postoperatively, mice were monitored for recovery, hydration, and wound healing for at least 7 days. Opsin expression was later verified via fluorescence imaging. These procedures ensured reproducible, cell-type–specific ChR2 expression in D1- or D2-pathway neurons, enabling selective manipulation of basal ganglia circuits in subsequent behavioral experiments. Implantation Surgery To enable combined optogenetic stimulation and electrophysiological recording in freely moving mice, a bilateral implantation protocol using a custom optrode was developed. Each optrode integrates an optical fiber (105/125 µm) with a tungsten microelectrode (~ 500 kΩ) to allow simultaneous light delivery and neural recording from genetically defined striatal neurons. Fibers were fabricated in-house, stripped, sharpened, and bonded to electrodes with UV-cured epoxy, then terminated in ferrules for robust coupling to a 473 nm DPSS laser. Devices were validated for ≥ 70% light transmission and acceptable electrode impedance prior to implantation, sterilized, and prepared for surgery. Surgeries were conducted under aseptic conditions with ACUC approval. Mice were anesthetized with isoflurane, mounted in a stereotaxic frame, and maintained on heating pads. The scalp was shaved, sterilized, and incised to expose skull landmarks, which were carefully leveled. Burr holes were drilled at stereotaxic coordinates targeting the dorsomedial striatum at stereotaxic locations AP + 0.5 mm; ML ± 1.5 mm; DV 1.7 mm. Skull screws and a platinum reference wire provided anchorage. Optrodes were lowered into place, and light-evoked activity was used to confirm functional opsin expression before final fixation with Kwik-Sil and dental acrylic. Post-surgery, animals were warmed, given saline and analgesics, and monitored for 7–10 days. Implant stability, wound healing, and body weight were tracked daily. Optrode function was re-validated before behavioral testing (Fig. 3). This protocol enabled durable, high-quality bilateral recordings with concurrent optical stimulation in D1- and D2-pathway neurons. Task Environment and Olfactory System : Behavioral testing was performed in a custom-built operant chamber (7 × 7 × 7 inches) designed to minimize noise and light interference. The chamber contained two adjacent ports: an odor delivery port and a water reward port, allowing mice to transition quickly between odor sampling and reward retrieval. Odors were delivered via a multi-channel air-dilution olfactometer driven by compressed air. Airflow was split into clean and odorant streams, with the latter routed to five sealed glass vials—four containing essential oil odorants and one serving as a neutral air channel for flushing. Solenoid valves controlled odor delivery, ensuring precise timing and consistent stimulus concentration. Between trials, the neutral channel cleared residual odors to maintain baseline sensory conditions. Trial initiation was detected by an infrared sensor at the odor port, triggering random odor selection via an Arduino controller (Fig. 4). Mice were trained on an olfactory Go/NoGo task to assess discrimination and decision-making. Training followed a structured, multi-phase design that gradually shaped odor-guided decision-making and action control. The task began with (1) water port exploration and reward association, allowing mice to learn the link between port access and water reward. This was followed by (2) trial initiation at the odor port, reinforcing active engagement and consistent trial structure. In (3) sustained nose-poke engagement, dwell time requirements were incrementally increased to promote stable stimulus sampling and sustained attention. Finally, (4) full odor discrimination was introduced, where two odors signaled reward availability (Go) and two indicated no reward (NoGo). Correct responses produced both water and auditory reinforcement, while incorrect responses triggered brief time-outs to discourage impulsivity and strengthen learning. (Fig. 5). After mice reached stable baseline discrimination performance, bilateral optogenetic stimulation and simultaneous electrophysiological recordings were incorporated to examine how activation of D1 (direct) or D2 (indirect) medium spiny neuron (MSN) pathways modulated decision accuracy, action initiation, inhibition control, and reinforcement updating. This closed-loop design provided a powerful, reproducible framework to link neural activity and behavioral dynamics during sensory-guided, reward-based learning, enabling precise dissection of corticostriatal circuit contributions to motivated behavior and adaptive control (Fig. 6). Histology Postmortem histological analysis was performed to verify viral targeting and opsin expression in the dorsomedial striatum. After behavioral testing, mice were euthanized, and brains were cryoprotected in 30% sucrose until fully sunk. Trimmed brains were sectioned coronally on a microtome (40 µm), and slices containing the striatum were collected into PBS. Sections were mounted on glass slides, rinsed, dried, and cover slipped with DAPI mounting medium to visualize nuclei. Edges were sealed to prevent drying, and slides were imaged using fluorescence microscopy. Opsin expression patterns were cross-referenced with behavioral and stimulation data to validate accurate injection and implant placement. Data Analysis : Behavioral data from the open-field and odor discrimination tasks were analyzed using custom MATLAB pipelines developed for this study. Open-field recordings were processed to extract positional traces, velocity, and zone occupancy, allowing quantification of spatial preference and locomotor dynamics under optogenetic manipulation. Data were pooled across animals, and descriptive statistics (mean, SD, SEM) were computed for each experimental condition. Independent two-sample t -tests were performed to compare Reference vs. Stim, Stim vs. No Stim, and Reference vs. No Stim conditions, providing a quantitative measure of how optogenetic activation altered exploratory and approach–avoidance behavior. These comparisons revealed pathway-specific influences of D1 and D2 activation on exploratory drive and spatial bias during stimulation epochs. To evaluate how striatal neuromodulation shaped odor-guided learning, trial-by-trial data were parsed for odor identity, trial type (Go/NoGo), response outcome (correct/incorrect), stimulation status, and key timing parameters (odor onset, reaction latency, reward delivery). The following behavioral metrics were derived: (1) accuracy (percentage correct responses), (2) learning curves tracking trial-by-trial accuracy across sessions, (3) reaction time as a measure of decision latency, and (4) inter-trial interval (ITI) or next-trial initiation time (NTIT) as a proxy for motivational readiness. Data were further stratified by stimulation condition (D1-Stim, D2-Stim, or No-Stim), enabling within- and between-pathway comparisons. Analyses tested whether D1 activation enhanced correct No-Go performance or accelerated learning, and whether D2 activation impaired response inhibition or slowed acquisition. Aggregated data were visualized using smoothed learning trajectories and summary bar graphs. Statistical significance was assessed with paired and unpaired t -tests, as well as two-way ANOVA for factors such as odor and correctness, providing a comprehensive assessment of pathway-dependent effects on learning, motivation, and performance. Results Rotation Test Our results showed that D1-mice (n = 10) displayed clear contralateral rotations (opposite to the side of stimulation), while D2-mice (n = 9) showed ipsilateral rotations (toward the side of stimulation). Because the dorsomedial striatum receives dense sensorimotor projections from the motor cortex, stimulating this region reliably elicits motor behaviors such as rotation. During this screening, rotations were very clear and were visually verified by the experimenter. Only animals that exhibited a detectable and reproducible rotational bias in response to stimulation were included in the study, ensuring that pathway-specific activation was robust enough to support subsequent behavioral testing. This rotation test served the dual purpose of confirming functional targeting of the direct and indirect pathways and providing a basis to calibrate stimulation parameters. Specifically, the stimulation intensity that evoked consistent, repeatable rotations was identified for each animal and subsequently used as the baseline intensity during bilateral stimulation in the main behavioral experiments. Animals that failed to show detectable rotations under stimulation were excluded from further testing to avoid confounds arising from incomplete targeting or insufficient expression of opsins (Fig. 7). Open-Field Test : Mice explored a rectangular arena under video tracking while we alternated five 3 min blocks with 30 s rests: one Reference baseline (green), two STIM blocks with optogenetic ON (orange), and two NOSTIM blocks with stimulation OFF (blue). Reference, STIM, and NOSTIM conditions, with group summaries (mean ± SEM) and planned tests (e.g., t -tests/ANOVA) to assess pathway-specific modulation of spatial preference and locomotion (Table. 2). Closed-loop optogenetic stimulation of D1 MSNs in the DMS elicited a strong and reliable spatial preference in the open-field preference test. During stimulation epochs (R1 and R2), mice spent significantly more time in the stimulation-associated zone compared to the non-stimulated zone (paired t-test, p < 0.001), whereas no such bias was present during the baseline epoch. The lack of baseline preference confirms that the observed effect was specifically driven by optogenetic activation rather than inherent environmental bias or side preference. These findings suggest that D1 pathway stimulation has a motivational effect because stimulation drove animals to initiate and sustain approach behavior, reflecting greater willingness to engage with that area. Moreover, the repeated preference for the stimulation-paired location suggests that the stimulation itself acquired reinforcing properties, assigning positive value to that spatial zone. Thus, the observed occupancy likely reflects both enhanced motivational salience and value-based reinforcement linked to D1 activation. This reinforcement-like effect is consistent with the established role of D1 signaling in reward processing, where it facilitates value-based action selection, promotes approach toward rewarding cues, and supports persistence in goal-directed behavior. In this context, the rewarding cue is the stimulation itself, which animals repeatedly seek out as though it were a natural reward. While the behavior does not serve an external goal such as food or water retrieval, the consistent approach and sustained occupancy indicate a form of goal-directed engagement, with the goal being access to the stimulation-paired area that delivers the reinforcing signal (Fig. 8). In D2-expressing MSNs in the DMS induced a clear avoidance phenotype in the open-field preference test. During stimulation epochs (R1 and R2), mice spent significantly less time in the stimulation-associated zone compared to the non-stimulated zone (paired t-test, p = 0.002), while no side bias was observed during the baseline epoch. The absence of baseline side preference indicates that subsequent spatial bias arose from D2 pathway stimulation, not pre-existing tendencies. During stimulation epochs, animals reliably decreased entries and dwell time in the stimulation-paired zone relative to the non-stimulated side, despite no external punishment or reward being delivered there. We interpret this pattern as a motivational effect: D2 activation suppresses action initiation and approach, reducing the motivational salience of that location. Because the avoidance emerges specifically when stimulation is available—and is expressed as consistent withdrawal from the stimulation-paired side—the stimulation itself functions as a negative cue, effectively assigning negative value (negative valence) to that spatial context. This is consistent with the established role of the indirect (D2) pathway in action suppression and no-go signaling, whereby decreased occupancy reflects a bias in spatial decision-making away from contexts linked to D2 activation (Fig. 9). Olfactory Discriminatory Go-NoGo Task : Bilateral optogenetic stimulation of D1-expressing medium spiny neurons (dMSNs) in the dorsomedial striatum (DMS) had no significant effect on classical markers of learning performance. Mice receiving stimulation during rewarded Go trials (Odor 3) performed similarly to non-stimulated conditions across a range of behavioral metrics: pre-learning performance (p = 0.5), trials-to-criterion (p = 0.3), final accuracy (p = 0.3), and reaction time (p = 0.7). These findings indicate that D1 pathway activation does not directly facilitate associative learning or accelerate sensorimotor processing in this task context. To further evaluate the functional impact of stimulation, we analyzed next-trial initiation times (NTITs)—a proxy for motivational re-engagement—across odor-specific trial types. NTITs were not significantly different between correct Go trials with (Odor 3) and without stimulation (Odor 1) (p = 0.76), nor between correct NoGo trials with (Odor 4) and without stimulation (Odor 2) (p = 0.51). This suggests that D1 stimulation does not influence behavioral timing or vigor following successful outcomes, reinforcing the conclusion that temporal dynamics of action initiation remain unaffected by stimulation. However, a trend toward reduced NTITs was observed when comparing correct Go-Stim (Odor 3) to correct NoGo-Stim (Odor 4) trials (p = 0.0755), raising the possibility that D1 activation during rewarded actions may create a subtle motivational bias favoring action repetition over inhibition. More compellingly, a significant reduction in NTIT was found following incorrect Go-Stim (Odor 3) trials relative to incorrect NoGo-Stim (Odor 4) trials (p = 0.0059). This result is particularly informative, as it suggests that even in the absence of reinforcement, D1 pathway activation encourages rapid re-initiation, potentially reflecting a motivational persistence or decreased sensitivity to negative outcomes. A two-way ANOVA on session-averaged NTITs revealed significant main effects of both Odor (p = 0.0017, η² = 0.0180) and Correctness (p < 0.0001, η² = 0.1125), but no interaction between the two (p = 0.7667). While each session employed a unique set of four odors delivered in pseudorandom order, the fixed behavioral assignment of Go-NoGo to Stim-NoStim allowed controlled comparisons. The odor main effect may reflect stimulus-specific differences in salience, learned associations, or inherent valence rather than functional category per se. Meanwhile, the correctness effect supports the interpretation that animals re-engage more quickly after correct responses, possibly due to positive reinforcement signals enhancing motivational arousal. The absence of an interaction term suggests that these influences are independent and additive. Importantly, these behavioral findings are supported by open-field preference testing, in which D1-ChR2 animals spent significantly more time in the stimulated region during stimulation epochs (R1 and R2; paired t-test, p < 0.001), but not during baseline. This spatial preference indicates that D1 pathway activation is inherently reinforcing, consistent with its known role in encoding motivational salience, approach drive, and value-based decision making (Fig. 10). Bilateral optogenetic stimulation of D2-expressing medium spiny neurons (iMSNs) in the dorsomedial striatum (DMS) did not significantly alter classical measures of learning performance. Mice receiving D2 stimulation during rewarded Go trials (Odor 3) performed comparably to non-stimulated trials across all key behavioral metrics: pre-learning accuracy (p = 0.2), trials to reach learning criterion (p = 0.053), final task performance (p = 0.53), and reaction time (p = 0.87). These findings indicate that D2 pathway activation neither impaired nor enhanced associative learning, suggesting a limited role in shaping acquisition of cue-outcome contingencies or motor execution under these conditions. To assess the motivational and behavioral consequences of D2 stimulation, we analyzed next-trial initiation times (NTITs) across odor-specific trial types. NTITs following correct Go trials were statistically indistinguishable between stimulated (Odor 3) and non-stimulated conditions (Odor 1; p = 0.935), as were correct NoGo trials with (Odor 4) and without (Odor 2) stimulation (p = 0.561). Similarly, no differences were observed between incorrect Go (Odor 3) and incorrect NoGo (Odor 4) trials (p = 0.978), nor between incorrect trials with and without stimulation (p > 0.8). These results suggest that D2 activation does not influence re-engagement timing in a straightforward manner. However, a broader analysis using two-way ANOVA on session-averaged NTITs revealed no significant main effects of Odor (p = 0.9589, η² = 0.0005), Correctness (p = 0.4688, η² = 0.0009), or their interaction (p = 0.9460, η² = 0.0006). These small effect sizes indicate minimal impact of D2 stimulation on motivational vigor or trial structure. Notably, although a subtle trend toward prolonged NTITs following incorrect Go-Stim trials was observed, it did not reach statistical significance in this dataset. The absence of any facilitative effect, combined with hints of delayed task re-initiation, aligns with the idea that D2 activation may modestly reduce motivational drive or behavioral invigoration without disrupting learning per se (Fig. 11). Histology Representative histological section showing robust expression of AAV-DIO-mCherry in dopamine expressing medium spiny neurons (dMSNs) within the dorsomedial striatum (DMS). Robust mCherry fluorescence is clearly localized to the neuronal membrane, confirming successful, cell-type-specific viral transduction and proper targeting of the opsin construct. The optrode track is visible and precisely aligned with the injection site, verifying accurate placement for in vivo stimulation and recording. These anatomical validations confirm both the specificity of opsin expression and the precision of the stimulation protocol used in behavioral experiments, ensuring the reliability of the observed functional outcomes (Fig. 12). Discussion In this study, we examined the causal roles of dopaminergic direct (D1) and indirect (D2) pathways in the dorsomedial striatum (DMS) using pathway-specific optogenetic activation across multiple behavioral paradigms. Across rotation, open-field, and Go/NoGo tasks, D1 and D2 stimulation produced opposing effects on motivation and behavioral engagement, but neither directly altered associative learning. In the unilateral rotation assay, activation of D1 medium spiny neurons (MSNs) produced robust contralateral turning, consistent with the direct pathway’s facilitatory role in movement. In the open field, D1 stimulation produced strong preference for the stimulation-paired zone (p < 0.001), interpreted as enhanced motivational salience: animals repeatedly initiated and sustained approach behavior despite no external rewards. In the Go/NoGo task, D1 stimulation did not change pre-learning accuracy, trials-to-criterion, or reaction times, indicating it did not function as an intrinsic reward signal. If stimulation were rewarding, faster acquisition or impaired withholding on No-Go trials would be expected, but neither occurred. Instead, animals showed delayed acquisition of inhibitory associations, likely because stimulation interfered with task demands by reinforcing action. This supports the interpretation that D1 activity conveys a “Go” or response activation signal rather than acting as a primary reinforcer. Given that water reward carries high subjective value under restriction, it is possible that natural reward outweighed artificial stimulation in guiding learning. Future dual-choice paradigms pairing stimulation with variable rewards will help disentangle reward valuation from motor facilitation. Consistent with its role in behavioral suppression, D2 pathway stimulation induced ipsilateral rotations and reduced occupancy of the stimulation-paired zone (p < 0.01) in the open field. In the Go/NoGo task, D2 stimulation left learning performance intact but significantly increased latency to initiate the next trial after errors. Because accuracy and task rules were preserved, this delay reflects reduced motivational state rather than impaired cognition. In other words, D2 activation suppressed the propensity to initiate actions, consistent with its established role in inhibiting behavioral activation. Converging open-field data strengthen this view: animals systematically avoided the D2-stimulated side, even without external punishment, suggesting that stimulation reduced motivational salience and assigned negative valence to that spatial context. Together, these results delineate complementary motivational roles for the D1 and D2 pathways in the DMS: D1 activation promotes engagement and approach, while D2 activation reduces engagement and promotes withdrawal. Neither altered learning acquisition, implying these pathways modulate how animals express learned contingencies rather than how they acquire them. Conclusion In summary, we developed a reward-based Go/NoGo operant paradigm to interrogate how the direct (D1) and indirect (D2) pathways of the dorsomedial striatum (DMS) modulate behavior. Histological validation and optogenetic stimulation confirmed accurate targeting and effective recruitment of these circuits. Open-field assays reproduced canonical motivational effects, with D1 activation driving place preference and D2 activation producing spatial avoidance. Importantly, neither pathway altered learning rates or task accuracy, indicating that they do not function as primary reinforcement signals. Instead, their influence was most pronounced in motivational and engagement metrics. D1 activation reduced next-trial initiation times (NTIT), consistent with its role as a “Go” signal promoting approach and persistence, whereas D2 activation increased NTIT following errors, acting as a “brake” on re-engagement without disrupting accuracy or motor execution. Moreover, D1 stimulation interfered with No-Go acquisition by reinforcing action initiation, while simultaneously enhancing Go-trial engagement and exploration in stimulation-paired zones. Together, these findings indicate that D1 and D2 pathways primarily regulate motivational state and action initiation rather than associative learning. NTIT and spatial preference emerge as sensitive behavioral readouts of pathway-specific motivational modulation. This framework has translational implications for basal ganglia–related disorders such as Parkinson’s disease, addiction, and obsessive-compulsive disorder, where dysregulated motivation–action coupling is a central feature. Declarations Supplementary Material Detailed information on the methods section including the source of devices, implants and chemicals used is included in the supplementary materials. Declarations Clinical Trial Number Not Applicable. Ethics and Consent to Participate All animal research was conducted in accordance with the University of Missouri Animal Care and Use Committee (ACUC) guidelines. All procedures were approved by the institutional ACUC and conformed to NIH ethical standards for the care and use of laboratory animals. No human research was involved; therefore, consent to participate was not applicable. Consent for publication: Not Applicable. Competing Interests: The authors declare no competing interest. Funding Declaration : We would like to acknowledge University of Missouri at Columbia for supporting this study with the Dr. Ilker Ozden’s start up grants. Author Contribution A.B. and I.O conceptualized and designed the study. A.B performed optogenetic surgeries analyzed data using custom written MATLAB, interpreted results, and drafted the manuscript. A.B, O.B and E.G conducted behavioral experiments. A.B and S.S wrote the paper. I.O provided project supervision, methodological guidance, assisted in data analysis. S.S critically revised the manuscript. All authors reviewed the manuscript. Acknowledgement We would like to acknowledge University of Missouri at Columbia for supporting this study with the Dr. Ilker Ozden’s start up grants. We also extend our gratitude to past Ozden Lab students for their assistance. This manuscript contains the use of AI tools, including ChatGPT (OpenAI), Copilot (Microsoft) and Grammarly, used to help paraphrase, grammatical edits, and summarize portions of the text for increased readability and Biorender for creating figures and diagrams. All AI-assisted content was critically reviewed and verified by the authors to ensure accuracy, originality, and compliance with ethical standards. Data Availability Data are available on request to the authors. In that case, the corresponding author should be contacted. References Balleine BW, Liljeholm M, Ostlund SB. The integrative function of the basal ganglia in instrumental conditioning. Behav Brain Res. 2009;199(1):43–52. https://doi.org/10.1016/j.bbr.2008.10.034 . Bar-Gad I, Morris G, Bergman H. Information processing, dimensionality reduction and reinforcement learning in the basal ganglia. Progress in Neurobiology. Volume 71. Elsevier Ltd; 2003. pp. 439–73. https://doi.org/10.1016/j.pneurobio.2003.12.001 . Baron A, Galizio M. (n.d.). The Distinction Between Positive and Negative Reinforcement: Use With Care . Botvinick M, Wang JX, Dabney W, Miller KJ, Kurth-Nelson Z. Deep Reinforcement Learning and Its Neuroscientific Implications. Neuron. 2020;107(4):603–16. https://doi.org/10.1016/j.neuron.2020.06.014 . Braunlich K, Seger C. (2013). The basal ganglia. In Wiley Interdisciplinary Reviews: Cognitive Science (Vol. 4, Issue 2, pp. 135–148). https://doi.org/10.1002/wcs.1217 Ding L, Perkel DJ. (2002). Dopamine Modulates Excitability of Spiny Neurons in the Avian Basal Ganglia. In The Journal of Neuroscience (Vol. 22, Issue 12). Dong H, Ding Z, Zhang S, Fundamentals E, Research A. (n.d.). Deep Reinforcement Learning . Fee MS, Goldberg JH. (2011). A hypothesis for basal ganglia-dependent reinforcement learning in the songbird. In Neuroscience (Vol. 198, pp. 152–170). https://doi.org/10.1016/j.neuroscience.2011.09.069 Freeze BS, Kravitz AV, Hammack N, Berke JD, Kreitzer AC. Control of basal ganglia output by direct and indirect pathway projection neurons. J Neurosci. 2013;33(47):18531–9. https://doi.org/10.1523/JNEUROSCI.1278-13.2013 . Friend DM, Kravitz AV. Working together: Basal ganglia pathways in action selection. Trends in Neurosciences. Volume 37. Elsevier Ltd; 2014. pp. 301–3. 6 https://doi.org/10.1016/j.tins.2014.04.004 . Ghasemi M, Ebrahimi D. (2024). Introduction to Reinforcement Learning . http://arxiv.org/abs/2408.07712 Graybiel AM. (2005). The basal ganglia: Learning new tricks and loving it. In Current Opinion in Neurobiology (Vol. 15, Issue 6, pp. 638–644). https://doi.org/10.1016/j.conb.2005.10.006 Gu Z. (1994). The Basal Ganglia Structure to Signaling . Ikemoto S, Yang C, Tan A. (2015). Basal ganglia circuit loops, dopamine and motivation: A review and enquiry. In Behavioural Brain Research (Vol. 290, pp. 17–31). Elsevier B.V. https://doi.org/10.1016/j.bbr.2015.04.018 Innes L, McBride S. Negative versus positive reinforcement: An evaluation of training strategies for rehabilitated horses. Appl Anim Behav Sci. 2008;112(3–4):357–68. https://doi.org/10.1016/j.applanim.2007.08.011 . Kravitz AV, Kreitzer AC. (n.d.). Striatal Mechanisms Underlying Movement, Reinforcement, and Punishment . https://doi.org/10.1152/physiol.00004.2012 Kravitz AV, Tomasi D, Leblanc KH, Baler R, Volkow ND, Bonci A, Ferré S. (2015). Cortico-striatal circuits: Novel therapeutic targets for substance use disorders. In Brain Research (Vol. 1628, pp. 186–198). Elsevier B.V. https://doi.org/10.1016/j.brainres.2015.03.048 Lanciego JL, Luquin N, Obeso JA. Functional neuroanatomy of the basal ganglia. Cold Spring Harbor Perspect Med. 2012;2(12). https://doi.org/10.1101/cshperspect.a009621 . Leblois A, Wendel BJ, Perkel DJ. Striatal dopamine modulates basal ganglia output and regulates social context-dependent behavioral variability through D1 receptors. J Neurosci. 2010;30(16):5730–43. https://doi.org/10.1523/JNEUROSCI.5974-09.2010 . Lex B, Hauber W. The role of dopamine in the prelimbic cortex and the dorsomedial striatum in instrumental conditioning. Cereb Cortex. 2010;20(4):873–83. https://doi.org/10.1093/cercor/bhp151 . Magill PJ, Sharott A, Bolam JP, Brown P. Brain state-dependency of coherent oscillatory activity in the cerebral cortex and basal ganglia of the rat. J Neurophysiol. 2004;92(4):2122–36. https://doi.org/10.1152/jn.00333.2004 . Magoon MA, Critchfield TS, Merrill D, Newland MC, Schneider WJ. Are positive and negative reinforcement different? Insights from a free-operant differential outcomes effect. J Exp Anal Behav. 2017;107(1):39–64. https://doi.org/10.1002/jeab.243 . Monchi O, Petrides M, Strafella AP, Worsley KJ, Doyon J. Functional role of the basal ganglia in the planning and execution of actions. Ann Neurol. 2006;59(2):257–64. https://doi.org/10.1002/ana.20742 . Murray S, Sarasota F. (n.d.). The Distinction Between Positive and Negative Reinforcement: Some Additional Considerations . Pouzzner D. (2017). Control of Functional Connectivity in Cerebral Cortex by Basal Ganglia Mediated Synchronization . Ragozzino ME. The contribution of the medial prefrontal cortex, orbitofrontal cortex, and dorsomedial striatum to behavioral flexibility. Ann N Y Acad Sci. 2007;1121:355–75. https://doi.org/10.1196/annals.1401.013 . Reinschluessel AV, Mandryk RL. (2016). Using positive or negative reinforcement in Neurofeedback games for training self-regulation. CHI PLAY 2016 - Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play , 186–198. https://doi.org/10.1145/2967934.2968085 Rice ME, Patel JC, Cragg SJ. (2011). Dopamine release in the basal ganglia. In Neuroscience (Vol. 198, pp. 112–137). https://doi.org/10.1016/j.neuroscience.2011.08.066 Schultz W. (2016). Reward functions of the basal ganglia. In Journal of Neural Transmission (Vol. 123, Issue 7, pp. 679–693). Springer-Verlag Wien. https://doi.org/10.1007/s00702-016-1510-0 Singh P, Lenka A, Stezin A, Jhunjhunwala K, Pal PK, Ghosal A, Murthy A. Basal ganglia contributions during the learning of a visuomotor rotation: Effect of dopamine, deep brain stimulation and reinforcement. Eur J Neurosci. 2019;50(8):3349–64. https://doi.org/10.1111/ejn.14494 . Sivamayil K, Rajasekar E, Aljafari B, Nikolovski S, Vairavasundaram S, Vairavasundaram I. (2023). A Systematic Study on Reinforcement Learning Based Applications. In Energies (Vol. 16, Issue 3). MDPI. https://doi.org/10.3390/en16031512 Stocco A. A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision-Making Models. Cogn Sci. 2018;42(2):457–90. https://doi.org/10.1111/cogs.12506 . Williams D, Tijssen M, Van Bruggen G, Bosch A, Insola A, Di Lazzaro V, Mazzone P, Oliviero A, Quartarone A, Speelman H, Brown P. Dopamine-dependent changes in the functional connectivity between basal ganglia and cerebral cortex in humans. Brain. 2002;125(7):1558–69. https://doi.org/10.1093/brain/awf156 . Yelnik J. (2002). Functional anatomy of the basal ganglia. In Movement Disorders (Vol. 17, Issue SUPPL. 3). https://doi.org/10.1002/mds.10138 Yin HH, Knowlton BJ, Balleine BW. Blockade of NMDA receptors in the dorsomedial striatum prevents action-outcome learning in instrumental conditioning. Eur J Neurosci. 2005;22(2):505–12. https://doi.org/10.1111/j.1460-9568.2005.04219.x . Yin HH, Ostlund SB, Knowlton BJ, Balleine BW. The role of the dorsomedial striatum in instrumental conditioning. Eur J Neurosci. 2005;22(2):513–23. https://doi.org/10.1111/j.1460-9568.2005.04218.x . 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11","display":"","copyAsset":false,"role":"figure","size":118173,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-7794302/v1/a1f5562ac95c45ca6203b5fb.png"},{"id":97150531,"identity":"dd0e222c-8dc1-4b37-9436-924d3e0f2568","added_by":"auto","created_at":"2025-12-01 10:30:13","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":262942,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-7794302/v1/74a769e0093664e498e0e55e.png"},{"id":100050638,"identity":"edddbd77-7c17-4098-b266-458a035bb325","added_by":"auto","created_at":"2026-01-12 12:55:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2721413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7794302/v1/1c96d3d0-e64b-4990-a8f0-27bf9595b584.pdf"},{"id":97150527,"identity":"8c40d37a-71b7-4e09-8fcf-e308dd4b4215","added_by":"auto","created_at":"2025-12-01 10:30:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":34310,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialsDiscoverNeuroscience.docx","url":"https://assets-eu.researchsquare.com/files/rs-7794302/v1/aebf86ccb94aa10490fa006a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pathway Specific Activation of D1 And D2 Medium Spiny Neurons in a CRE Mouse Model Reveals Distinct Roles in Reinforcement Learning and Decision Making via Closed Loop Optogenetic Neuromodulation ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOn a hot summer afternoon, Taylor is craving for an ice-cream. There is an ice cream store within a mile from her home that serves two flavors only, while there is another one five miles away that serves multiple flavors including her favorite one. If Taylor choses to go to the one near her home, she has to decide between either of the ones the store offers, while if Taylor choses to spend some time and drive a bit longer, she can get her favorite flavor. Based on the choices that she has; Taylor has to decide to go to the one that is most favorable to her maximizing the choices that she has. This simple scenario illustrates reinforcement learning\u0026mdash;a goal-directed process in which an agent, like Taylor, evaluates options to maximize rewards or avoid undesirable outcomes by interacting with the environment, experiencing consequences, and adapting future actions based on positive or negative feedback (Botvinick et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dong et al., n.d.; Ghasemi \u0026amp; Ebrahimi, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sivamayil et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The brain\u0026rsquo;s capacity for behavioral flexibility relies on feedback-based learning, where actions are evaluated against desired goals and adjusted accordingly. For reinforcement learning (Fig.\u0026nbsp;1), this adjustment is based on trial-and-error that are guided by their outcomes. Positive reinforcement strengthens behavior through rewards, while negative reinforcement strengthens behavior by avoiding an aversive stimulus.\u003c/p\u003e\u003cp\u003eThese work in a complementary fashion which together foster goal-directed behavior and adaptive responses that eventually facitate effective learning. At the center of this process is the basal ganglia (Fig.\u0026nbsp;1), a network of deep subcortical nuclei essential for inducing voluntary movement, reward-based learning and decision making, by integrating sensory, motivational, and contextual signals to guide behavioral outcomes (Bar-Gad et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Baron \u0026amp; Galizio, n.d.; Fee \u0026amp; Goldberg, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Innes \u0026amp; McBride, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Magoon et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Murray \u0026amp; Sarasota, n.d.; Reinschluessel \u0026amp; Mandryk, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Within this circuit, the dorsomedial striatum (DMS) is the primary candidate for goal directed behavior, by receiving inputs from higher order cortical areas, like the prefrontal cortex, and dopaminergic projections from the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA). Integrating past experiences, motivational salience and present sensory data, the DMS supports action selection and value estimation \u0026ndash; the core basis of reinforcement learning (Murray and Sarasota, n.d.; Yin et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2005\u003c/span\u003eb, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2005\u003c/span\u003ea; Ragozzino, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lex and Hauber, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sivamayil et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDopamine, the principal neuromodulator of the basal ganglia system regulates synaptic plasticity and updates the neural representations of reward value (Braunlich \u0026amp; Seger, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gu, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Lanciego et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rice et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schultz, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yelnik, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Within the striatum, the dopaminergic system is primarily composed of medium spiny neurons (MSNs) that form two output pathways: the direct (D1 receptor expressing) pathway and the indirect (D2 receptor expressing) pathway. The former facilitates movement initiation and reward seeking while the latter suppresses movement and is associated with inhibition by discarding non favorable actions (Freeze et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Friend \u0026amp; Kravitz, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kravitz et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kravitz \u0026amp; Kreitzer, n.d.). This dynamic push-pull enables adaptive behavioral selection based on values assigned to previous outcomes (Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlthough D1 pathways are thought to encode rewarded actions while D2 pathways suppress negative actions, their precise causal role in reward based learning is still under ambiguity. It is essential to address this gap, as imbalanced D1\u0026ndash;D2 pathway activity is implicated in several neuropsychological disorders, including Parkinson\u0026rsquo;s disease, schizophrenia, addiction, and depression, that are marked by impaired reward processing and poor decision-making. Present treatment options lack pathway specific precision, focusing on palliative care (Ding and Perkel, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Williams et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Yelnik, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Magill et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Graybiel, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Monchi et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Balleine et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Leblois et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Fee and Goldberg, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rice et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Friend and Kravitz, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ikemoto et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Schultz, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pouzzner, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Stocco, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the context of the example above, if Taylor\u0026rsquo;s D1 pathway is more active, she would prioritize the distant store with her favorite flavor, valuing the higher reward despite the extra effort. In contrast, if her D2 pathway dominates, she would focus on minimizing effort and choose the nearer store with fewer options. In this way, striatal circuits weigh reward against cost\u0026mdash;ice cream representing the D1-driven reward value and distance representing the D2-driven cost\u0026mdash;so that the final decision may favor the closer ice cream shop.\u003c/p\u003e\u003cp\u003eTo identify the pathway specific contributions of the D1 and D2 dopaminergic circuits in reward based learning, we developed a closed loop optogenetic neuromodulation based olfactory discriminatory Go-NoGo task that combines reward-driven behavior with inhibitory demands, thereby providing an ideal framework parsing D1-D2 mediated behavior. By selectively activating D1 and D2 MSNs, during discreet behavioral epochs, we assessed the contribution of each pathway in action selection, learning performance and response inhibition in real time. Such targeted experiments hold promise for not only advancing our fundamental knowledge of neuroscience, but also the development of next-generation treatment strategies for dopamine related disorders. Ultimately, a deeper understanding of the role of the D1-D2 pathways in shaping learning and feedback processing, will open up avenues for the development of personalized neuromodulation strategies, bringing precision medicine closer to individuals with neuropsychiatric deficits.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eOverview of Experimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the pathway specific contribution of the direct (D1) and indirect (D2) pathways within the DMS in reward based learning, we employed optogenetic neuromodulation in transgenic mouse models during an olfactory discriminatory Go-NoGo task (Table 1). The neuromodulation consists of pathway specific activation of the D1 or D2 expressing MSNs using channelrhodopsin (ChR2), delivered via CRE dependent viral vector constructs that are triggered through temporally precise light pulses synchronized with behavioral events. The olfactory task refers to a behavioral paradigm in which mice are trained to discriminate between odor cues that signal either a \u0026ldquo;Go\u0026rdquo; response (initiating a nose poke to receive a water reward), or a \u0026ldquo;No-Go\u0026rdquo; response (withholding a response to avoid negative consequences such as punishment). This enables us to monitor real-time decision making processes and creates a controlled framework for assessing how pathway specific activation or inhibition influences learning and action selection. Unlike traditional reward-based tasks, our modified Go-NoGo paradigm incorporates both positive reinforcement and negative inhibitory control, allowing us to functionally isolate and evaluate the distinct contributions of each striatal pathways in reinforcement learning.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eThe hypothesis is that activating the D1 pathway enhances reward-based learning, while activating the D2 pathway suppresses it. In D1 animals (having CRE positive expression for D1-type dopamine receptor pathway), optogenetic stimulation during No-Go trials was expected to improve performance by enhancing accuracy, reducing reaction times, and shortening initiation times for subsequent trials. Increased accuracy would suggest improved learning of the discrimination rule, faster reaction times are typically interpreted as greater movement vigor, and shorter next-trial initiation times reflect heightened motivation and engagement with the task. Conversely, in D2 animals (having CRE positive expression for D2-type dopamine receptor pathway), stimulation is predicted to impair performance, increase reaction time and next trial initiation time, suggesting that D2 activation inhibits learning. If these hypotheses hold true, it will reveal opposing roles of D1 and D2 pathways in modulating feedback-driven learning. These findings could provide insight into the neural mechanisms underlying decision-making and behavioral flexibility, ultimately clarifying how distinct basal ganglia circuits contribute to adaptive behavior.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals\u003c/strong\u003e: Breeder pairs were obtained from the Mutant Mouse Resource and Research Centers (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mmrrc.org/\u003c/span\u003e\u003c/span\u003e) for breeding. Mice were housed in a temperature- and humidity-controlled facility on a 12-hour light/dark cycle, with \u003cem\u003ead libitum\u003c/em\u003e access to food and water. All efforts were made to minimize animal suffering and the number of animals used.\u003c/p\u003e\n\u003cp\u003eTo dissect the pathway-specific contributions of dopaminergic signaling in reinforcement learning, we utilized two well-characterized Cre-driver transgenic mouse lines that allow for selective targeting of striatal neurons involved in the direct and indirect pathways of the basal ganglia:\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e1. D1-Cre mice: \u003cem\u003eB6.FVB(Cg)-Tg(Drd1-cre)EY262Gsat/Mmucd\u003c/em\u003e\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e2. D2-Cre mice: \u003cem\u003eB6.FVB(Cg)-Tg(Adora2a-cre)KG139Gsat/Mmucd\u003c/em\u003e\u003c/p\u003e\n\u003c/span\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eIn D1-Cre mice, Cre recombinase is expressed under the dopamine D1 receptor promoter, resulting in selective Cre activity in neurons associated with the direct pathway. Similarly, in D2-Cre mice, Cre expression is driven by the adenosine A2A receptor promoter, which is co-expressed with the dopamine D2 receptor, targeting neurons of the indirect pathway. These models thus allow for high-fidelity pathway-specific manipulation when combined with CRE-dependent viral constructs. Breeding pairs for both lines were obtained from the \u003cem\u003eMutant Mouse Resource and Research Centers (MMRRC) (\u003c/em\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mmrrc.org/\u003c/span\u003e\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e, and colonies were maintained in-house. Mice were weaned at postnatal day 21 and housed in same-sex groups of 2\u0026ndash;5 animals per cage. Genotyping was performed via standard PCR protocols using tail biopsies collected at weaning (\u003cem\u003eTransnetyxx, Cordova, TN\u003c/em\u003e). Only those animals verified to carry the CRE transgene were included in subsequent procedures. Experimental subjects included both male and female mice aged 6 to 24 weeks at the time of behavioral testing, with body weights ranging from 18 to 30 grams. To ensure balanced representation and reduce sex-based variability, we included both sexes across each genotype whenever possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInjection Surgery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo enable pathway-specific optogenetic control of striatal neurons, bilateral viral injections were performed in D1-Cre and D2-Cre mice. Animals were carefully screened for health, genotype, and age, and only those meeting strict criteria underwent surgery. Preoperative planning included sterilization of tools, preparation of viral constructs (AAV5-EF1a-DIO-hChR2-GFP or -mCherry), and setup of a fully aseptic surgical environment with stereotaxic apparatus, isoflurane anesthesia, and heating pads. Mice were anesthetized with isoflurane, mounted securely in a stereotaxic frame, and monitored for anesthetic depth. The scalp was depilated, sterilized, and incised to expose the skull, with bregma and lambda landmarks aligned for accurate targeting. Burr holes were drilled at AP\u0026thinsp;+\u0026thinsp;0.5 mm, ML\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 mm relative to bregma, corresponding to the dorsal striatum. Using a Hamilton syringe, 1.0 \u0026micro;L of virus was infused per site at 0.1 \u0026micro;L/min after lowering the needle to 2.5 mm DV (Fig. 2). The needle was left in place before and after injection to minimize backflow and tissue disruption. Following injections, burr holes were sealed with Kwik-Cast, incisions closed with VetBond, and animals received saline and analgesia. Postoperatively, mice were monitored for recovery, hydration, and wound healing for at least 7 days. Opsin expression was later verified via fluorescence imaging. These procedures ensured reproducible, cell-type\u0026ndash;specific ChR2 expression in D1- or D2-pathway neurons, enabling selective manipulation of basal ganglia circuits in subsequent behavioral experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplantation Surgery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo enable combined optogenetic stimulation and electrophysiological recording in freely moving mice, a bilateral implantation protocol using a custom optrode was developed. Each optrode integrates an optical fiber (105/125 \u0026micro;m) with a tungsten microelectrode (~\u0026thinsp;500 kΩ) to allow simultaneous light delivery and neural recording from genetically defined striatal neurons. Fibers were fabricated in-house, stripped, sharpened, and bonded to electrodes with UV-cured epoxy, then terminated in ferrules for robust coupling to a 473 nm DPSS laser. Devices were validated for \u0026ge;\u0026thinsp;70% light transmission and acceptable electrode impedance prior to implantation, sterilized, and prepared for surgery. Surgeries were conducted under aseptic conditions with ACUC approval. Mice were anesthetized with isoflurane, mounted in a stereotaxic frame, and maintained on heating pads. The scalp was shaved, sterilized, and incised to expose skull landmarks, which were carefully leveled. Burr holes were drilled at stereotaxic coordinates targeting the dorsomedial striatum at stereotaxic locations AP\u0026thinsp;+\u0026thinsp;0.5 mm; ML\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 mm; DV 1.7 mm. Skull screws and a platinum reference wire provided anchorage. Optrodes were lowered into place, and light-evoked activity was used to confirm functional opsin expression before final fixation with Kwik-Sil and dental acrylic. Post-surgery, animals were warmed, given saline and analgesics, and monitored for 7\u0026ndash;10 days. Implant stability, wound healing, and body weight were tracked daily. Optrode function was re-validated before behavioral testing (Fig.\u0026nbsp;3). This protocol enabled durable, high-quality bilateral recordings with concurrent optical stimulation in D1- and D2-pathway neurons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTask Environment and Olfactory System\u003c/strong\u003e: Behavioral testing was performed in a custom-built operant chamber (7 \u0026times; 7 \u0026times; 7 inches) designed to minimize noise and light interference. The chamber contained two adjacent ports: an odor delivery port and a water reward port, allowing mice to transition quickly between odor sampling and reward retrieval. Odors were delivered via a multi-channel air-dilution olfactometer driven by compressed air. Airflow was split into clean and odorant streams, with the latter routed to five sealed glass vials\u0026mdash;four containing essential oil odorants and one serving as a neutral air channel for flushing. Solenoid valves controlled odor delivery, ensuring precise timing and consistent stimulus concentration. Between trials, the neutral channel cleared residual odors to maintain baseline sensory conditions. Trial initiation was detected by an infrared sensor at the odor port, triggering random odor selection via an Arduino controller (Fig.\u0026nbsp;4).\u003c/p\u003e\n\u003cp\u003eMice were trained on an olfactory Go/NoGo task to assess discrimination and decision-making. Training followed a structured, multi-phase design that gradually shaped odor-guided decision-making and action control. The task began with (1) water port exploration and reward association, allowing mice to learn the link between port access and water reward. This was followed by (2) trial initiation at the odor port, reinforcing active engagement and consistent trial structure. In (3) sustained nose-poke engagement, dwell time requirements were incrementally increased to promote stable stimulus sampling and sustained attention. Finally, (4) full odor discrimination was introduced, where two odors signaled reward availability (Go) and two indicated no reward (NoGo). Correct responses produced both water and auditory reinforcement, while incorrect responses triggered brief time-outs to discourage impulsivity and strengthen learning. (Fig. 5).\u003c/p\u003e\n\u003cp\u003eAfter mice reached stable baseline discrimination performance, bilateral optogenetic stimulation and simultaneous electrophysiological recordings were incorporated to examine how activation of D1 (direct) or D2 (indirect) medium spiny neuron (MSN) pathways modulated decision accuracy, action initiation, inhibition control, and reinforcement updating. This closed-loop design provided a powerful, reproducible framework to link neural activity and behavioral dynamics during sensory-guided, reward-based learning, enabling precise dissection of corticostriatal circuit contributions to motivated behavior and adaptive control (Fig. 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePostmortem histological analysis was performed to verify viral targeting and opsin expression in the dorsomedial striatum. After behavioral testing, mice were euthanized, and brains were cryoprotected in 30% sucrose until fully sunk. Trimmed brains were sectioned coronally on a microtome (40 \u0026micro;m), and slices containing the striatum were collected into PBS. Sections were mounted on glass slides, rinsed, dried, and cover slipped with DAPI mounting medium to visualize nuclei. Edges were sealed to prevent drying, and slides were imaged using fluorescence microscopy. Opsin expression patterns were cross-referenced with behavioral and stimulation data to validate accurate injection and implant placement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e: Behavioral data from the open-field and odor discrimination tasks were analyzed using custom MATLAB pipelines developed for this study. Open-field recordings were processed to extract positional traces, velocity, and zone occupancy, allowing quantification of spatial preference and locomotor dynamics under optogenetic manipulation. Data were pooled across animals, and descriptive statistics (mean, SD, SEM) were computed for each experimental condition. Independent two-sample \u003cem\u003et\u003c/em\u003e-tests were performed to compare Reference vs. Stim, Stim vs. No Stim, and Reference vs. No Stim conditions, providing a quantitative measure of how optogenetic activation altered exploratory and approach\u0026ndash;avoidance behavior. These comparisons revealed pathway-specific influences of D1 and D2 activation on exploratory drive and spatial bias during stimulation epochs. To evaluate how striatal neuromodulation shaped odor-guided learning, trial-by-trial data were parsed for odor identity, trial type (Go/NoGo), response outcome (correct/incorrect), stimulation status, and key timing parameters (odor onset, reaction latency, reward delivery). The following behavioral metrics were derived: (1) accuracy (percentage correct responses), (2) learning curves tracking trial-by-trial accuracy across sessions, (3) reaction time as a measure of decision latency, and (4) inter-trial interval (ITI) or next-trial initiation time (NTIT) as a proxy for motivational readiness. Data were further stratified by stimulation condition (D1-Stim, D2-Stim, or No-Stim), enabling within- and between-pathway comparisons. Analyses tested whether D1 activation enhanced correct No-Go performance or accelerated learning, and whether D2 activation impaired response inhibition or slowed acquisition. Aggregated data were visualized using smoothed learning trajectories and summary bar graphs. Statistical significance was assessed with paired and unpaired \u003cem\u003et\u003c/em\u003e-tests, as well as two-way ANOVA for factors such as odor and correctness, providing a comprehensive assessment of pathway-dependent effects on learning, motivation, and performance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eRotation Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur results showed that D1-mice (n\u0026thinsp;=\u0026thinsp;10) displayed clear contralateral rotations (opposite to the side of stimulation), while D2-mice (n\u0026thinsp;=\u0026thinsp;9) showed ipsilateral rotations (toward the side of stimulation). Because the dorsomedial striatum receives dense sensorimotor projections from the motor cortex, stimulating this region reliably elicits motor behaviors such as rotation. During this screening, rotations were very clear and were visually verified by the experimenter. Only animals that exhibited a detectable and reproducible rotational bias in response to stimulation were included in the study, ensuring that pathway-specific activation was robust enough to support subsequent behavioral testing. This rotation test served the dual purpose of confirming functional targeting of the direct and indirect pathways and providing a basis to calibrate stimulation parameters. Specifically, the stimulation intensity that evoked consistent, repeatable rotations was identified for each animal and subsequently used as the baseline intensity during bilateral stimulation in the main behavioral experiments. Animals that failed to show detectable rotations under stimulation were excluded from further testing to avoid confounds arising from incomplete targeting or insufficient expression of opsins (Fig. 7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen-Field Test\u003c/strong\u003e: Mice explored a rectangular arena under video tracking while we alternated five 3 min blocks with 30 s rests: one Reference baseline (green), two STIM blocks with optogenetic ON (orange), and two NOSTIM blocks with stimulation OFF (blue). Reference, STIM, and NOSTIM conditions, with group summaries (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM) and planned tests (e.g., \u003cem\u003et\u003c/em\u003e-tests/ANOVA) to assess pathway-specific modulation of spatial preference and locomotion (Table. 2).\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" style=\"width: 795px;\"\u003e\u003c/p\u003e\n\u003cp\u003eClosed-loop optogenetic stimulation of D1 MSNs in the DMS elicited a strong and reliable spatial preference in the open-field preference test. During stimulation epochs (R1 and R2), mice spent significantly more time in the stimulation-associated zone compared to the non-stimulated zone (paired t-test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas no such bias was present during the baseline epoch. The lack of baseline preference confirms that the observed effect was specifically driven by optogenetic activation rather than inherent environmental bias or side preference. These findings suggest that D1 pathway stimulation has a motivational effect because stimulation drove animals to initiate and sustain approach behavior, reflecting greater willingness to engage with that area. Moreover, the repeated preference for the stimulation-paired location suggests that the stimulation itself acquired reinforcing properties, assigning positive value to that spatial zone. Thus, the observed occupancy likely reflects both enhanced motivational salience and value-based reinforcement linked to D1 activation. This reinforcement-like effect is consistent with the established role of D1 signaling in reward processing, where it facilitates value-based action selection, promotes approach toward rewarding cues, and supports persistence in goal-directed behavior. In this context, the rewarding cue is the stimulation itself, which animals repeatedly seek out as though it were a natural reward. While the behavior does not serve an external goal such as food or water retrieval, the consistent approach and sustained occupancy indicate a form of goal-directed engagement, with the goal being access to the stimulation-paired area that delivers the reinforcing signal (Fig.\u0026nbsp;8).\u003c/p\u003e\n\u003cp\u003eIn D2-expressing MSNs in the DMS induced a clear avoidance phenotype in the open-field preference test. During stimulation epochs (R1 and R2), mice spent significantly less time in the stimulation-associated zone compared to the non-stimulated zone (paired t-test, p\u0026thinsp;=\u0026thinsp;0.002), while no side bias was observed during the baseline epoch. The absence of baseline side preference indicates that subsequent spatial bias arose from D2 pathway stimulation, not pre-existing tendencies. During stimulation epochs, animals reliably decreased entries and dwell time in the stimulation-paired zone relative to the non-stimulated side, despite no external punishment or reward being delivered there. We interpret this pattern as a motivational effect: D2 activation suppresses action initiation and approach, reducing the motivational salience of that location. Because the avoidance emerges specifically when stimulation is available\u0026mdash;and is expressed as consistent withdrawal from the stimulation-paired side\u0026mdash;the stimulation itself functions as a negative cue, effectively assigning negative value (negative valence) to that spatial context. This is consistent with the established role of the indirect (D2) pathway in action suppression and no-go signaling, whereby decreased occupancy reflects a bias in spatial decision-making away from contexts linked to D2 activation (Fig. 9).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOlfactory Discriminatory Go-NoGo Task\u003c/strong\u003e: Bilateral optogenetic stimulation of D1-expressing medium spiny neurons (dMSNs) in the dorsomedial striatum (DMS) had no significant effect on classical markers of learning performance. Mice receiving stimulation during rewarded Go trials (Odor 3) performed similarly to non-stimulated conditions across a range of behavioral metrics: pre-learning performance (p\u0026thinsp;=\u0026thinsp;0.5), trials-to-criterion (p\u0026thinsp;=\u0026thinsp;0.3), final accuracy (p\u0026thinsp;=\u0026thinsp;0.3), and reaction time (p\u0026thinsp;=\u0026thinsp;0.7). These findings indicate that D1 pathway activation does not directly facilitate associative learning or accelerate sensorimotor processing in this task context. To further evaluate the functional impact of stimulation, we analyzed next-trial initiation times (NTITs)\u0026mdash;a proxy for motivational re-engagement\u0026mdash;across odor-specific trial types. NTITs were not significantly different between correct Go trials with (Odor 3) and without stimulation (Odor 1) (p\u0026thinsp;=\u0026thinsp;0.76), nor between correct NoGo trials with (Odor 4) and without stimulation (Odor 2) (p\u0026thinsp;=\u0026thinsp;0.51). This suggests that D1 stimulation does not influence behavioral timing or vigor following successful outcomes, reinforcing the conclusion that temporal dynamics of action initiation remain unaffected by stimulation. However, a trend toward reduced NTITs was observed when comparing correct Go-Stim (Odor 3) to correct NoGo-Stim (Odor 4) trials (p\u0026thinsp;=\u0026thinsp;0.0755), raising the possibility that D1 activation during rewarded actions may create a subtle motivational bias favoring action repetition over inhibition. More compellingly, a significant reduction in NTIT was found following incorrect Go-Stim (Odor 3) trials relative to incorrect NoGo-Stim (Odor 4) trials (p\u0026thinsp;=\u0026thinsp;0.0059). This result is particularly informative, as it suggests that even in the absence of reinforcement, D1 pathway activation encourages rapid re-initiation, potentially reflecting a motivational persistence or decreased sensitivity to negative outcomes. A two-way ANOVA on session-averaged NTITs revealed significant main effects of both Odor (p\u0026thinsp;=\u0026thinsp;0.0017, \u0026eta;\u0026sup2; = 0.0180) and Correctness (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, \u0026eta;\u0026sup2; = 0.1125), but no interaction between the two (p\u0026thinsp;=\u0026thinsp;0.7667). While each session employed a unique set of four odors delivered in pseudorandom order, the fixed behavioral assignment of Go-NoGo to Stim-NoStim allowed controlled comparisons. The odor main effect may reflect stimulus-specific differences in salience, learned associations, or inherent valence rather than functional category per se. Meanwhile, the correctness effect supports the interpretation that animals re-engage more quickly after correct responses, possibly due to positive reinforcement signals enhancing motivational arousal. The absence of an interaction term suggests that these influences are independent and additive. Importantly, these behavioral findings are supported by open-field preference testing, in which D1-ChR2 animals spent significantly more time in the stimulated region during stimulation epochs (R1 and R2; paired t-test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not during baseline. This spatial preference indicates that D1 pathway activation is inherently reinforcing, consistent with its known role in encoding motivational salience, approach drive, and value-based decision making (Fig.\u0026nbsp;10).\u003c/p\u003e\n\u003cp\u003eBilateral optogenetic stimulation of D2-expressing medium spiny neurons (iMSNs) in the dorsomedial striatum (DMS) did not significantly alter classical measures of learning performance. Mice receiving D2 stimulation during rewarded Go trials (Odor 3) performed comparably to non-stimulated trials across all key behavioral metrics: pre-learning accuracy (p\u0026thinsp;=\u0026thinsp;0.2), trials to reach learning criterion (p\u0026thinsp;=\u0026thinsp;0.053), final task performance (p\u0026thinsp;=\u0026thinsp;0.53), and reaction time (p\u0026thinsp;=\u0026thinsp;0.87). These findings indicate that D2 pathway activation neither impaired nor enhanced associative learning, suggesting a limited role in shaping acquisition of cue-outcome contingencies or motor execution under these conditions. To assess the motivational and behavioral consequences of D2 stimulation, we analyzed next-trial initiation times (NTITs) across odor-specific trial types. NTITs following correct Go trials were statistically indistinguishable between stimulated (Odor 3) and non-stimulated conditions (Odor 1; p\u0026thinsp;=\u0026thinsp;0.935), as were correct NoGo trials with (Odor 4) and without (Odor 2) stimulation (p\u0026thinsp;=\u0026thinsp;0.561). Similarly, no differences were observed between incorrect Go (Odor 3) and incorrect NoGo (Odor 4) trials (p\u0026thinsp;=\u0026thinsp;0.978), nor between incorrect trials with and without stimulation (p\u0026thinsp;\u0026gt;\u0026thinsp;0.8). These results suggest that D2 activation does not influence re-engagement timing in a straightforward manner. However, a broader analysis using two-way ANOVA on session-averaged NTITs revealed no significant main effects of Odor (p\u0026thinsp;=\u0026thinsp;0.9589, \u0026eta;\u0026sup2; = 0.0005), Correctness (p\u0026thinsp;=\u0026thinsp;0.4688, \u0026eta;\u0026sup2; = 0.0009), or their interaction (p\u0026thinsp;=\u0026thinsp;0.9460, \u0026eta;\u0026sup2; = 0.0006). These small effect sizes indicate minimal impact of D2 stimulation on motivational vigor or trial structure. Notably, although a subtle trend toward prolonged NTITs following incorrect Go-Stim trials was observed, it did not reach statistical significance in this dataset. The absence of any facilitative effect, combined with hints of delayed task re-initiation, aligns with the idea that D2 activation may modestly reduce motivational drive or behavioral invigoration without disrupting learning per se (Fig. 11).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRepresentative histological section showing robust expression of AAV-DIO-mCherry in dopamine expressing medium spiny neurons (dMSNs) within the dorsomedial striatum (DMS). Robust mCherry fluorescence is clearly localized to the neuronal membrane, confirming successful, cell-type-specific viral transduction and proper targeting of the opsin construct. The optrode track is visible and precisely aligned with the injection site, verifying accurate placement for in vivo stimulation and recording. These anatomical validations confirm both the specificity of opsin expression and the precision of the stimulation protocol used in behavioral experiments, ensuring the reliability of the observed functional outcomes (Fig. 12).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we examined the causal roles of dopaminergic direct (D1) and indirect (D2) pathways in the dorsomedial striatum (DMS) using pathway-specific optogenetic activation across multiple behavioral paradigms. Across rotation, open-field, and Go/NoGo tasks, D1 and D2 stimulation produced opposing effects on motivation and behavioral engagement, but neither directly altered associative learning. In the unilateral rotation assay, activation of D1 medium spiny neurons (MSNs) produced robust contralateral turning, consistent with the direct pathway\u0026rsquo;s facilitatory role in movement. In the open field, D1 stimulation produced strong preference for the stimulation-paired zone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), interpreted as enhanced motivational salience: animals repeatedly initiated and sustained approach behavior despite no external rewards. In the Go/NoGo task, D1 stimulation did not change pre-learning accuracy, trials-to-criterion, or reaction times, indicating it did not function as an intrinsic reward signal. If stimulation were rewarding, faster acquisition or impaired withholding on No-Go trials would be expected, but neither occurred. Instead, animals showed delayed acquisition of inhibitory associations, likely because stimulation interfered with task demands by reinforcing action. This supports the interpretation that D1 activity conveys a \u0026ldquo;Go\u0026rdquo; or response activation signal rather than acting as a primary reinforcer. Given that water reward carries high subjective value under restriction, it is possible that natural reward outweighed artificial stimulation in guiding learning. Future dual-choice paradigms pairing stimulation with variable rewards will help disentangle reward valuation from motor facilitation.\u003c/p\u003e\u003cp\u003eConsistent with its role in behavioral suppression, D2 pathway stimulation induced ipsilateral rotations and reduced occupancy of the stimulation-paired zone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in the open field. In the Go/NoGo task, D2 stimulation left learning performance intact but significantly increased latency to initiate the next trial after errors. Because accuracy and task rules were preserved, this delay reflects reduced motivational state rather than impaired cognition. In other words, D2 activation suppressed the propensity to initiate actions, consistent with its established role in inhibiting behavioral activation. Converging open-field data strengthen this view: animals systematically avoided the D2-stimulated side, even without external punishment, suggesting that stimulation reduced motivational salience and assigned negative valence to that spatial context. Together, these results delineate complementary motivational roles for the D1 and D2 pathways in the DMS: D1 activation promotes engagement and approach, while D2 activation reduces engagement and promotes withdrawal. Neither altered learning acquisition, implying these pathways modulate how animals express learned contingencies rather than how they acquire them.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, we developed a reward-based Go/NoGo operant paradigm to interrogate how the direct (D1) and indirect (D2) pathways of the dorsomedial striatum (DMS) modulate behavior. Histological validation and optogenetic stimulation confirmed accurate targeting and effective recruitment of these circuits. Open-field assays reproduced canonical motivational effects, with D1 activation driving place preference and D2 activation producing spatial avoidance. Importantly, neither pathway altered learning rates or task accuracy, indicating that they do not function as primary reinforcement signals. Instead, their influence was most pronounced in motivational and engagement metrics. D1 activation reduced next-trial initiation times (NTIT), consistent with its role as a \u0026ldquo;Go\u0026rdquo; signal promoting approach and persistence, whereas D2 activation increased NTIT following errors, acting as a \u0026ldquo;brake\u0026rdquo; on re-engagement without disrupting accuracy or motor execution. Moreover, D1 stimulation interfered with No-Go acquisition by reinforcing action initiation, while simultaneously enhancing Go-trial engagement and exploration in stimulation-paired zones. Together, these findings indicate that D1 and D2 pathways primarily regulate motivational state and action initiation rather than associative learning. NTIT and spatial preference emerge as sensitive behavioral readouts of pathway-specific motivational modulation. This framework has translational implications for basal ganglia\u0026ndash;related disorders such as Parkinson\u0026rsquo;s disease, addiction, and obsessive-compulsive disorder, where dysregulated motivation\u0026ndash;action coupling is a central feature.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eSupplementary Material\u003c/h2\u003e\u003cp\u003e\u003cem\u003eDetailed information on the methods section including the source of devices, implants and chemicals used is included in the supplementary materials.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eDeclarations\u003c/h2\u003e\u003cp\u003e\u003ch2\u003eClinical Trial Number\u003c/h2\u003e\u003cp\u003e\u003cem\u003eNot Applicable.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate\u003c/strong\u003e\u003cp\u003e\u003cem\u003e All animal research was conducted in accordance with the University of Missouri Animal Care and Use Committee (ACUC) guidelines. All procedures were approved by the institutional ACUC and conformed to NIH ethical standards for the care and use of laboratory animals. No human research was involved; therefore, consent to participate was not applicable.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003cp\u003e\u003cem\u003eNot Applicable.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003cp\u003e\u003cem\u003eThe authors declare no competing interest.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003e\u003cb\u003eDeclaration\u003c/b\u003e: We would like to acknowledge University of Missouri at Columbia for supporting this study with the Dr. Ilker Ozden\u0026rsquo;s start up grants.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.B. and I.O conceptualized and designed the study. A.B performed optogenetic surgeries analyzed data using custom written MATLAB, interpreted results, and drafted the manuscript. A.B, O.B and E.G conducted behavioral experiments. A.B and S.S wrote the paper. I.O provided project supervision, methodological guidance, assisted in data analysis. S.S critically revised the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to acknowledge University of Missouri at Columbia for supporting this study with the Dr. Ilker Ozden\u0026rsquo;s start up grants. We also extend our gratitude to past Ozden Lab students for their assistance. This manuscript contains the use of AI tools, including ChatGPT (OpenAI), Copilot (Microsoft) and Grammarly, used to help paraphrase, grammatical edits, and summarize portions of the text for increased readability and Biorender for creating figures and diagrams. All AI-assisted content was critically reviewed and verified by the authors to ensure accuracy, originality, and compliance with ethical standards.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData are available on request to the authors. In that case, the corresponding author should be contacted.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBalleine BW, Liljeholm M, Ostlund SB. The integrative function of the basal ganglia in instrumental conditioning. Behav Brain Res. 2009;199(1):43\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bbr.2008.10.034\u003c/span\u003e\u003cspan address=\"10.1016/j.bbr.2008.10.034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBar-Gad I, Morris G, Bergman H. Information processing, dimensionality reduction and reinforcement learning in the basal ganglia. Progress in Neurobiology. Volume 71. Elsevier Ltd; 2003. pp. 439\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pneurobio.2003.12.001\u003c/span\u003e\u003cspan address=\"10.1016/j.pneurobio.2003.12.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaron A, Galizio M. (n.d.). \u003cem\u003eThe Distinction Between Positive and Negative Reinforcement: Use With Care\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBotvinick M, Wang JX, Dabney W, Miller KJ, Kurth-Nelson Z. Deep Reinforcement Learning and Its Neuroscientific Implications. Neuron. 2020;107(4):603\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuron.2020.06.014\u003c/span\u003e\u003cspan address=\"10.1016/j.neuron.2020.06.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBraunlich K, Seger C. (2013). The basal ganglia. In \u003cem\u003eWiley Interdisciplinary Reviews: Cognitive Science\u003c/em\u003e (Vol. 4, Issue 2, pp. 135\u0026ndash;148). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/wcs.1217\u003c/span\u003e\u003cspan address=\"10.1002/wcs.1217\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing L, Perkel DJ. (2002). Dopamine Modulates Excitability of Spiny Neurons in the Avian Basal Ganglia. In \u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e (Vol. 22, Issue 12).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDong H, Ding Z, Zhang S, Fundamentals E, Research A. (n.d.). \u003cem\u003eDeep Reinforcement Learning\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFee MS, Goldberg JH. (2011). A hypothesis for basal ganglia-dependent reinforcement learning in the songbird. In \u003cem\u003eNeuroscience\u003c/em\u003e (Vol. 198, pp. 152\u0026ndash;170). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroscience.2011.09.069\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroscience.2011.09.069\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFreeze BS, Kravitz AV, Hammack N, Berke JD, Kreitzer AC. Control of basal ganglia output by direct and indirect pathway projection neurons. J Neurosci. 2013;33(47):18531\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1523/JNEUROSCI.1278-13.2013\u003c/span\u003e\u003cspan address=\"10.1523/JNEUROSCI.1278-13.2013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFriend DM, Kravitz AV. Working together: Basal ganglia pathways in action selection. Trends in Neurosciences. Volume 37. Elsevier Ltd; 2014. pp. 301\u0026ndash;3. 6\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tins.2014.04.004\u003c/span\u003e\u003cspan address=\"10.1016/j.tins.2014.04.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhasemi M, Ebrahimi D. (2024). \u003cem\u003eIntroduction to Reinforcement Learning\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://arxiv.org/abs/2408.07712\u003c/span\u003e\u003cspan address=\"http://arxiv.org/abs/2408.07712\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGraybiel AM. (2005). The basal ganglia: Learning new tricks and loving it. In \u003cem\u003eCurrent Opinion in Neurobiology\u003c/em\u003e (Vol. 15, Issue 6, pp. 638\u0026ndash;644). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.conb.2005.10.006\u003c/span\u003e\u003cspan address=\"10.1016/j.conb.2005.10.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGu Z. (1994). \u003cem\u003eThe Basal Ganglia Structure to Signaling\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIkemoto S, Yang C, Tan A. (2015). Basal ganglia circuit loops, dopamine and motivation: A review and enquiry. In \u003cem\u003eBehavioural Brain Research\u003c/em\u003e (Vol. 290, pp. 17\u0026ndash;31). Elsevier B.V. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bbr.2015.04.018\u003c/span\u003e\u003cspan address=\"10.1016/j.bbr.2015.04.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInnes L, McBride S. Negative versus positive reinforcement: An evaluation of training strategies for rehabilitated horses. Appl Anim Behav Sci. 2008;112(3\u0026ndash;4):357\u0026ndash;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.applanim.2007.08.011\u003c/span\u003e\u003cspan address=\"10.1016/j.applanim.2007.08.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKravitz AV, Kreitzer AC. (n.d.). \u003cem\u003eStriatal Mechanisms Underlying Movement, Reinforcement, and Punishment\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/physiol.00004.2012\u003c/span\u003e\u003cspan address=\"10.1152/physiol.00004.2012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKravitz AV, Tomasi D, Leblanc KH, Baler R, Volkow ND, Bonci A, Ferr\u0026eacute; S. (2015). Cortico-striatal circuits: Novel therapeutic targets for substance use disorders. In \u003cem\u003eBrain Research\u003c/em\u003e (Vol. 1628, pp. 186\u0026ndash;198). Elsevier B.V. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.brainres.2015.03.048\u003c/span\u003e\u003cspan address=\"10.1016/j.brainres.2015.03.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLanciego JL, Luquin N, Obeso JA. Functional neuroanatomy of the basal ganglia. Cold Spring Harbor Perspect Med. 2012;2(12). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1101/cshperspect.a009621\u003c/span\u003e\u003cspan address=\"10.1101/cshperspect.a009621\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeblois A, Wendel BJ, Perkel DJ. Striatal dopamine modulates basal ganglia output and regulates social context-dependent behavioral variability through D1 receptors. J Neurosci. 2010;30(16):5730\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1523/JNEUROSCI.5974-09.2010\u003c/span\u003e\u003cspan address=\"10.1523/JNEUROSCI.5974-09.2010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLex B, Hauber W. The role of dopamine in the prelimbic cortex and the dorsomedial striatum in instrumental conditioning. Cereb Cortex. 2010;20(4):873\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/cercor/bhp151\u003c/span\u003e\u003cspan address=\"10.1093/cercor/bhp151\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagill PJ, Sharott A, Bolam JP, Brown P. Brain state-dependency of coherent oscillatory activity in the cerebral cortex and basal ganglia of the rat. J Neurophysiol. 2004;92(4):2122\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1152/jn.00333.2004\u003c/span\u003e\u003cspan address=\"10.1152/jn.00333.2004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagoon MA, Critchfield TS, Merrill D, Newland MC, Schneider WJ. Are positive and negative reinforcement different? Insights from a free-operant differential outcomes effect. J Exp Anal Behav. 2017;107(1):39\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jeab.243\u003c/span\u003e\u003cspan address=\"10.1002/jeab.243\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonchi O, Petrides M, Strafella AP, Worsley KJ, Doyon J. Functional role of the basal ganglia in the planning and execution of actions. Ann Neurol. 2006;59(2):257\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ana.20742\u003c/span\u003e\u003cspan address=\"10.1002/ana.20742\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurray S, Sarasota F. (n.d.). \u003cem\u003eThe Distinction Between Positive and Negative Reinforcement: Some Additional Considerations\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePouzzner D. (2017). \u003cem\u003eControl of Functional Connectivity in Cerebral Cortex by Basal Ganglia Mediated Synchronization\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRagozzino ME. The contribution of the medial prefrontal cortex, orbitofrontal cortex, and dorsomedial striatum to behavioral flexibility. Ann N Y Acad Sci. 2007;1121:355\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1196/annals.1401.013\u003c/span\u003e\u003cspan address=\"10.1196/annals.1401.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReinschluessel AV, Mandryk RL. (2016). Using positive or negative reinforcement in Neurofeedback games for training self-regulation. \u003cem\u003eCHI PLAY 2016 - Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play\u003c/em\u003e, 186\u0026ndash;198. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1145/2967934.2968085\u003c/span\u003e\u003cspan address=\"10.1145/2967934.2968085\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRice ME, Patel JC, Cragg SJ. (2011). Dopamine release in the basal ganglia. In \u003cem\u003eNeuroscience\u003c/em\u003e (Vol. 198, pp. 112\u0026ndash;137). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroscience.2011.08.066\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroscience.2011.08.066\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchultz W. (2016). Reward functions of the basal ganglia. In \u003cem\u003eJournal of Neural Transmission\u003c/em\u003e (Vol. 123, Issue 7, pp. 679\u0026ndash;693). Springer-Verlag Wien. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00702-016-1510-0\u003c/span\u003e\u003cspan address=\"10.1007/s00702-016-1510-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSingh P, Lenka A, Stezin A, Jhunjhunwala K, Pal PK, Ghosal A, Murthy A. Basal ganglia contributions during the learning of a visuomotor rotation: Effect of dopamine, deep brain stimulation and reinforcement. Eur J Neurosci. 2019;50(8):3349\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/ejn.14494\u003c/span\u003e\u003cspan address=\"10.1111/ejn.14494\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSivamayil K, Rajasekar E, Aljafari B, Nikolovski S, Vairavasundaram S, Vairavasundaram I. (2023). A Systematic Study on Reinforcement Learning Based Applications. In \u003cem\u003eEnergies\u003c/em\u003e (Vol. 16, Issue 3). MDPI. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/en16031512\u003c/span\u003e\u003cspan address=\"10.3390/en16031512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStocco A. A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision-Making Models. Cogn Sci. 2018;42(2):457\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/cogs.12506\u003c/span\u003e\u003cspan address=\"10.1111/cogs.12506\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilliams D, Tijssen M, Van Bruggen G, Bosch A, Insola A, Di Lazzaro V, Mazzone P, Oliviero A, Quartarone A, Speelman H, Brown P. Dopamine-dependent changes in the functional connectivity between basal ganglia and cerebral cortex in humans. Brain. 2002;125(7):1558\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/brain/awf156\u003c/span\u003e\u003cspan address=\"10.1093/brain/awf156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYelnik J. (2002). Functional anatomy of the basal ganglia. In \u003cem\u003eMovement Disorders\u003c/em\u003e (Vol. 17, Issue SUPPL. 3). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/mds.10138\u003c/span\u003e\u003cspan address=\"10.1002/mds.10138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYin HH, Knowlton BJ, Balleine BW. Blockade of NMDA receptors in the dorsomedial striatum prevents action-outcome learning in instrumental conditioning. Eur J Neurosci. 2005;22(2):505\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1460-9568.2005.04219.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1460-9568.2005.04219.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYin HH, Ostlund SB, Knowlton BJ, Balleine BW. The role of the dorsomedial striatum in instrumental conditioning. Eur J Neurosci. 2005;22(2):513\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1460-9568.2005.04218.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1460-9568.2005.04218.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThe supplementary material. for this article has been provided.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Basal Ganglia, Motivation, Reward, Operant Conditioning, Striatum, Dopaminergic Pathways","lastPublishedDoi":"10.21203/rs.3.rs-7794302/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7794302/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cu\u003eObjective:\u003c/u\u003e The basal ganglia integrate cortical and dopaminergic inputs to shape reinforcement learning, action selection, and motivation through the direct (D1) and indirect (D2) striatal pathways. While these pathways are thought to facilitate opposing behavioral outcomes, their causal roles in reinforcement-driven learning remain poorly defined.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMethods:\u003c/u\u003e Pathway-specific optogenetic activation was used in D1-Cre and D2-Cre transgenic mice to examine the functional contributions of dorsomedial striatum (DMS) circuits. Animals were trained in an olfactory Go/No-Go discrimination task with closed-loop optogenetic stimulation, and complementary open-field and unilateral rotation assays were performed to assess motivational and motor effects.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eResults:\u003c/u\u003e In unilateral rotation tests, D1 stimulation induced contralateral turning, while D2 stimulation elicited ipsilateral rotations, validating effective pathway recruitment. Open-field assays showed that D1 stimulation drove strong preference for the stimulation zone, consistent with enhanced motivational salience, while D2 stimulation induced avoidance, reflecting behavioral inhibition. In the Go/No-Go task, pathway stimulation did not alter learning rates or accuracy. Instead, changes were observed in motivational dynamics: D1 stimulation reduced next-trial initiation times, particularly after errors, indicating increased persistence and approach drive, whereas D2 stimulation prolonged initiation times following errors, indicating reduced engagement and motivational suppression.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConclusion:\u003c/u\u003e These findings demonstrate that the optogenetic-driven activity in D1 and D2 pathways in the DMS do not directly encode reinforcement learning but instead modulate motivational vigor and behavioral engagement. Next-trial initiation latency and spatial preference emerge as sensitive behavioral markers of pathway-specific neuromodulation, offering translational value for disorders involving motivation and action control.\u003c/p\u003e","manuscriptTitle":"Pathway Specific Activation of D1 And D2 Medium Spiny Neurons in a CRE Mouse Model Reveals Distinct Roles in Reinforcement Learning and Decision Making via Closed Loop Optogenetic Neuromodulation ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 10:30:08","doi":"10.21203/rs.3.rs-7794302/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff1b2186-235f-4163-975d-fb960cb7f455","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T12:54:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-01 10:30:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7794302","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7794302","identity":"rs-7794302","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}