Dopamine and serotonin neurotransmissions exert complementary control over primate approach and avoidance

Abstract

Efficient selection of appropriate responses to emotionally valenced stimuli is crucial for adaptive behavior, and disruptions in such approach-avoidance processes are common in various psychopathological disorders. While the dopamine and serotonin systems are primary targets for psychiatric medications, their precise roles in approach-avoidance behaviors remain unclear. To address this, we compared the effects of acute administration of methylphenidate (MPH) and fluoxetine, which respectively block dopamine and serotonin transporters (DAT and SERT), in four monkeys trained to perform an approach-avoidance task involving responses to valenced stimuli. We conducted PET scans to assess and localize drug binding levels at behaviorally effective doses. The two pharmacological agents improved task performance through distinct yet complementary mechanisms. MPH selectively enhanced the reward-based approach while concurrently binding to striatal DAT, whereas fluoxetine promoted the active avoidance of aversive stimuli through widespread SERT binding within limbic cortico-subcortical circuits. Rather than directly antagonizing each other, MPH and fluoxetine regulated distinct adaptive responses to emotional stimuli in a complementary fashion. Contrary to traditional models that pit dopamine and serotonin functions against each other, these results suggest a more segmented and independent framework for regulating distinct adaptive responses. From a clinical perspective, these findings highlight the potential of combining MPH and fluoxetine to target distinct symptomatic dimensions in psychopathological disorders marked by imbalances in approach-avoidance tendencies.

Introduction

Efficiently selecting appropriate responses to emotional stimuli is vital for survival, emotional well-being, and successful social interaction. Positive stimuli, such as rewards or happy facial expressions, typically elicit and facilitate approach behaviors, while negative stimuli, such as threats, tend to trigger avoidance responses [1]. Many psychopathological disorders are characterized by imbalances in approach-avoidance tendencies and difficulties in regulating them [2]. For example, individuals with depression often exhibit reduced approach tendencies [3], while those with anxiety disorders engage in heightened avoidance behaviors [4]. Similarly, individuals with attention-deficit/hyperactivity disorder (ADHD) or addictions may display excessive approach behaviors without fully considering potential negative consequences [5, 6]. Although numerous studies have identified these maladaptive response tendencies across various mental disorders [2], the precise brain mechanisms underlying and regulating approach-avoidance behavior patterns remain elusive.

Approach and avoidance are intricate reactions shaped by valence-dependent processes and guided by appetitive or aversive motivations [7]. Human and preclinical studies have indicated that the assignment of positive and negative emotional valence to specific cues or outcomes is tightly regulated by the dopamine and serotonin systems [8–10]. However, the exact roles played by dopamine and serotonin neurotransmissions in controlling approach-avoidance behavior remain debated. Despite many inconsistencies, partly due to the complex nature of dopamine-serotonin interactions, two main models have been proposed regarding the involvement of these neuromodulators in adaptive behavior. The first model suggests an opponent-process model, wherein dopamine primarily mediates active reward-seeking behaviors, while serotonin predominantly regulates behavioral inhibition when anticipating threats [11–13]. Evidence somewhat supports this dopamine-serotonin opposition, highlighting the distinct functions of these neurotransmitters in promoting reward or avoiding punishment [14–17]. Corresponding with this dichotomous perspective and an antagonistic relationship between monoaminergic functions, reciprocal inhibitory mechanisms that exert opposing control over the dopamine and serotonin systems have been identified [18–20]. However, a strict opponency between systems fails to explain some aspects of research on aversion processing, particularly the role of serotonin in avoidance [12, 21]. Alternatively, the second model proposes intertwined, rather than purely opposing, roles of the two neurotransmitters in controlling active and passive responses to affective stimuli [21, 22]. Given documented synergistic interactions between dopamine and serotonin functions [23–26], this model hypothesizes that the two monoaminergic systems may cooperate and co-adjust the balance between approach and avoidance, without strict functional segregation between appetitive and aversive contexts. However, the detailed processes governing these complex co-adjustments remain to be more thoroughly characterized.

Because the dopamine and serotonin systems are primary targets of psychopharmacotherapy, gaining a deeper understanding of their opposing or cooperative roles in regulating affective processing and adaptive behavior has significant implications for psychiatric treatment. Notably, medications like methylphenidate (MPH, Ritalin) and selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine (Prozac), are commonly prescribed for individuals with disorders characterized by emotional dysfunctions, as they preferentially potentiate dopamine and serotonin neurotransmissions, respectively [27, 28]. In addition to blocking the norepinephrine transporter (NET), MPH acts as a psychostimulant primarily by inhibiting the dopamine transporter (DAT) in conditions like ADHD or apathetic elderly patients [29], while fluoxetine selectively blocks the serotonin transporter (SERT) to manage mood disorders such as depression and anxiety [8]. Interestingly, there have been descriptions of differences as well as overlap in the therapeutic effects of these two reuptake inhibitors, with potential synergistic effects observed when they are used in combination [30–32]. Despite the widespread clinical use of these monoaminergic agents to boost dopamine or serotonin neurotransmission, their specific effects on approach-avoidance behaviors remain incompletely understood, as there have been limited direct comparisons of the effects of these two drugs.

To investigate the mutual roles of dopamine and serotonin neurotransmission in governing approach-avoidance tendencies and to discern whether they act in a segregated or integrated manner, we first trained four monkeys to perform an approach-avoidance task in which animals adjusted their responses based on the emotional valence of visual stimuli [33–35]. Subsequently, we conducted two series of acute administrations of MPH or fluoxetine, which increase dopamine or serotonin levels in the extracellular compartment [36, 37], to examine and compare drug-induced effects on affective processing and adaptive functioning while the monkeys performed the task. To investigate the extent to which these dopamine and serotonin agents achieved significant DAT/SERT occupancy in the whole brain, we employed positron emission tomography (PET) scans to assess and localize drug binding levels at behaviorally effective doses.

Materials and methods

Animals

The effects of the drugs on approach-avoidance behavior were tested in four male Macaca fascicularis monkeys (C, S, M and L; 6.5-9 kg), aged between 5 and 7 years. When the monkeys were not in active use, they were paired in large cages where the animals had free access to food and were maintained under a water regulation schedule individually optimized to maintain stable motivation for task performance across days (20-40 ml/kg/day). To improve the resolution of PET images concerning serotonin neurotransmission, we scanned two additional macaques (2 males; 4-6 years; 5.8-7 kg). Animal care and housing complied with NIH guidelines (1996) and the 2010 European Council Directive (2010/63/UE). The procedures were approved by the French National Ethics Committee (#990-2015063017055778).

Apparatus

Each monkey was seated on a chair in front of a touch-screen on which they executed the task with the left arm. To initiate the task, the monkeys placed their left-hand on an infrared-sensitive resting key installed on the chair. Presentation (Neurobehavioral Systems, CA, USA) and Scenario Manager (ISCJM, France) controlled the presentation of visual cues on the screen, monitored behavioral responses, and regulated solenoid valves for both reward delivery and airpuff systems. Single drops of apple juice (0.2 mL) or single puffs of air directed to the face (between the cheek and eye; 25–35 psi) were delivered depending on the task conditions. A detailed description of the apparatus and setup can be found in our previous work [33–35].

Approach-avoidance task

The monkeys were trained to perform an approach-avoidance task that manipulated the valence of visual stimuli that potentially induced motivated responses (Fig. 1A). The attribution of valence to visual information presented on the screen guided monkeys’ decisions to approach rewards and avoid punishments. Each trial began with a white central dot when the monkey placed its hand on the resting key. After 1.3 s, a conditioned stimulus was presented on the screen (for 1 s). The location of the cue alternated randomly between the left and the right sides of the monitor. We used two sets of images as conditioned stimuli: the first set of images signaled the possibility of obtaining a juice reward at the end of the trial (defined as events with a positive valence), while the second set signaled the possibility of a punishing airpuff (defined as events with a negative valence). Images of abstract or concrete objects, including fractals and food items, served as conditioned stimuli. After a random delay period (1.5–2 s after cue offset), two green squares appeared on both sides of the screen, cueing the animal to touch one of the targets (within 2 s). When the monkey chose the green target at the location where the conditioned stimulus had appeared, it approached the stimulus. In that case, the juice reward or airpuff was delivered after a random delay (1.5–2 s). Alternatively, the monkey could avoid the anticipated outcome by selecting the contralateral green target. In that case, nothing happened at the end of the trial, i.e., the animal erroneously forfeited a reward or successfully prevented an airpuff. Trials were separated by 0.8–1.5 s intertrial intervals during which the screen was black.

Fig. 1. Approach-avoidance task and behavior.

A Temporal sequence of events in trials of the two conditions. After the animal initiated a trial by positioning its hand on the resting key, a conditioned stimulus was presented briefly (left or right position, determined randomly). Depending on the condition, visual stimuli predicted liquid reward (green) or airpuff punishment (red). The animal could then approach or avoid the location of the presented cue and thereby the anticipated outcome by selecting the ipsi- or contralateral target. B Basal performance of the four monkeys. Behavioral measures were averaged (mean ± SEM) separately for each trial type (appetitive vs. aversive) and animal (monkey C, S, M and L) across all control sessions. The rates of approach and of avoidance, reaction times, movement durations, and error rates (including early escapes, response omissions, and imprecise touches) were overall affected by the valence of trials (two-way ANOVA, trial types x animals, ** P < 0.01, *** P < 0.001). The bar plots show the population-averaged values, while black lines reflect individual differences per animal (t-test with permutations, P < 0.05 and P < 0.001 indicated by different line thicknesses).

Errors in ongoing task performance corresponded to failures to fulfill specific requirements. In particular, (1) the monkey was required to hold its hand in the start position until the presentation of the green targets; (2) the response times (reaction time [RT] + movement duration [MD]) had to be faster than 2 s; and (3) the touch of the screen was required to be in one of the target zones (5 cm2). If any one of these rules was broken, an error was registered, a blank screen appeared (1 s), followed by an intertrial interval, and the trial was repeated. Hence, by intentionally provoking errors, the animal had alternative ways to temporarily prevent the anticipated outcome until the next trial. Early escape (premature release) from the resting key could be interpreted as an active avoidance strategy, while response omission (noninitiated action) could be viewed as passive avoidance behavior. Since error trials were repeated, however, the most effective way to actively avoid the anticipated outcome and minimize repetitions was to prioritize pressing the contralateral target without making an error. But the animal could freely choose among these different task strategies based on its sensitivity to the expected outcome.

Prior to the experiment, the animals learned the valence associated with each conditioned stimulus (positive vs. negative) during a training period (>8 months) and were then free to choose any behavioral response (approach vs. avoidance) to complete trials. To maintain a sufficient level of motivation for performance across trials and to minimize task disengagement, the aversiveness of the airpuff was limited (<36 psi), and blocks of 50 trials without negative cues were interleaved between blocks of 50 trials in which both negative and positive cues were displayed randomly. The total number of trials was adjusted daily, depending on performance (250-980 complete trials). Task execution was aborted when the monkey stopped repositioning its hand on the resting key for 5 consecutive minutes or after 25 consecutive response omissions (in the behavioral analysis, these last 5 min or 25 omitted trials were removed from the collected data).

Pharmacological procedure

Once the animals reached a stable day-to-day performance, the acute behavioral effects of two pharmacological agents (dopamine vs. serotonin reuptake inhibitors) were tested across two series of 4-week periods separated by a wash-out period of >4 weeks. In one set of sessions, intramuscular injections of MPH (0.1 mg/kg) were administered 5 min before the task was performed. We previously reported that this dosage most effectively reduces impulsivity in macaques during a delay discounting task, whereas higher doses of MPH induce sedative-like effects [38]. In another set of sessions, fluoxetine (4 mg/kg) was intramuscularly injected 4 h before testing. This dosage has been shown to be effective for treating anxiety-related symptoms such as self-injuries and stereotypic behaviors in monkeys [39, 40]. The drug concentrations and metabolic profiles are consistent with those of other studies in humans [41]. Acute administration of MPH or fluoxetine occurred once a week. Control days (without any injection) were defined as behavioral sessions conducted 1 day before and 2 days after an injection day (except when it was a day off). The type of drug and its administration were not randomized, and the investigators were not blinded during the analysis. Because we previously observed that saline injections do not alter monkeys’ performance on the approach-avoidance task [34] and with respect to animal welfare, we did not reproduce this control condition.

Imaging

After acquiring an anatomical MRI (Siemens 1.5 T, voxel size of 0.6 mm), we performed several PET scans on each animal under anesthesia (Atropine 0.05 mg/kg IM followed by Zoletil 15 mg/kg IM) to localize brain regions where MPH and fluoxetine block dopamine and serotonin transporters (DAT and SERT). PETs were acquired with a Siemens Biograph mCT/S64 scanner at CERMEP (Imaging Centre, Lyon) at a spatial transverse resolution of 4.4 mm. We used two selective radioligands: ¹¹C-N-(3-iodoprop-2E-enyl)-2β-carbomethoxy-3β-(4-methylphenyl)nortropane ([¹¹C]-PE2I) for DAT binding and ¹¹C-N,N-dimethyl-2-(-2 amino-4-cyanophenylthio)benzylamine ([¹¹C]-DASB) for SERT binding. Unlike many other DAT ligands, [¹¹C]-PE2I is highly selective for DAT, and has a negligible affinity for NET and SERT [42]. A 90-min dynamic acquisition was required after the [¹¹C]PE2I intravenous injection, while 70-min were adequate for the [¹¹C]-DASB. PET acquisitions were coupled with (test) or without (control) an injection of MPH (0.1 mg/kg IM, 5 min before acquisition) or fluoxetine (4 mg/kg IM, 4 h before acquisition) on the same animals. The average radioactivity (mean ± SEM) injected was 3.96 ± 0.22 mCi and 3.79 ± 0.21 mCi in control sessions, and 3.64 ± 0.3 mCi and 3.92 ± 0.1 mCi in drug challenge sessions for [¹¹C]-PE2I and [¹¹C]-DASB, respectively. The specific radioactivity was 1.64 ± 0.62 Ci/µmol and 1.12 ± 0.41 Ci/µmol in control sessions, and 1.14 ± 0.25 Ci/µmol and 1.37 ± 0.62 Ci/µmol in drug challenge sessions for [¹¹C]-PE2I and [¹¹C]-DASB, respectively. PET data were corrected for attenuation using a transmission scan. They were then reconstructed with the Siemens ultraHD PET algorithm (12 iterations, 8 subsets, zoom factor 21) on a 256 × 256 × 109 matrix (voxel size: 0.398 × 0.398 × 2.027 mm) in series of 30 frames (4x30s, 6x60s, 9x180s, 11x300s) for [¹¹C]PE2I and in series of 24 frames (4x30s, 4x60s, 8x180s, 8x300s) for [¹¹C]DASB. As reported previously [35, 38], the non-displaceable binding potential (BP) of the radiotracer with (test) and without (control) drug injection was calculated for each animal. Parametric images of BP were calculated using a simplified tissue model with the cerebellum gray matter (excluding the vermis) as a reference. Images were transformed into a common space using a brain Macaca fascicularis MRI template [43], and the values for the regions of interest (ROIs) were compared between conditions (control–test) using paired Wilcoxon tests with Benjamini-Hochberg correction for multiple comparisons.

Analysis of behavioral data

Before testing whether the psychoactive drugs (MPH and fluoxetine) changed performance, we analyzed how behavior varied according to the valence assigned to distinct conditioned stimuli. In control sessions, rates of approach (selection of the ipsilateral target), rates of avoidance (selection of the contralateral target), RT (the interval between target appearance and key release), MD (the interval between key release and target capture), and error rates (early escape, response omission, and imprecise touch) were calculated per block of trials and tested across task conditions (appetitive vs aversive trials) and animals (monkey C, S, M and L) using two-way ANOVAs. Only blocks of trials involving both positive and negative cues were included in this study. All error trials were included in the analysis because the animals were similarly exposed to cues at the start of each trial (excluding repeated error trials from the dataset does not impact the main results concerning selective drug effects; Supplemental Fig. 1). Individual effects on each animal were also tested using a series of two-sample t-tests with permutations. We measured the generalized action of each drug on behavior by comparing behavioral parameters between drug conditions (test vs. control) according to the different monkeys via ANOVAs. Interactions between drug condition (test vs. control) and task condition (appetitive vs. aversive) were investigated with three-way ANOVAs (drug condition x task condition x animal) in order to determine whether the drug effects were context-dependent (Supplemental Fig. 2).

Results

Reward- and punishment-associated cues differentially affect approach and avoidance

After an extensive training phase, the four monkeys were familiar with the task and differentiated appetitive trials from aversive trials. The conditioned stimuli presented during the task effectively acquired distinct valences as evidenced by consistent effects on the animals’ task performance during the control sessions (n = 67 daily sessions of >355 trials; Fig. 1B). As a whole, the monkeys preferentially approached reward-predictive cues (two-way ANOVA, task conditions x monkeys, F_(1,1078) = 4142 P < 0.001) with shorter RTs (F_(1,1078) = 559 P < 0.001), faster movements (F_(1,1078) = 50 P < 0.001) and more precise responses (F_(1,1087) = 8.8 P = 0.003) compared to trials with a negative valence. In contrast, punishment-predictive cues were often avoided by selecting the contralateral target more frequently than chance (Chi-square test, Χ² > 3.99 P < 0.04) or by making more errors than in appetitive trials (F_(1,1087) = 133 P < 0.001). In aversive trials, animals showed higher rates of early escape (F_(1,1087) = 57 P < 0.001) and response omission (F_(1,1087) = 130 P < 0.001), enabling them to actively and passively prevent airpuffs. Task conditions affected performance similarly and consistently in all individual analyses (two-sample t-test with permutations, P < 0.05), suggesting that the differential responses to valenced cues were similar in all four animals. Overall, the monkeys adaptively adjusted their approach-avoidance behavior, successfully obtaining rewards in 86% of the appetitive trials and (actively or passively) avoiding air-puffs in 71% of the aversive trials.

Methylphenidate facilitates the reward approach

To investigate whether and how dopamine regulates approach-avoidance behavior, we intramuscularly and acutely injected MPH in 16 testing sessions (4 monkeys x 4 tests). Compared to 32 control sessions, MPH administration drastically improved task engagement, as evidenced by a 50% increase in the number of trials completed per session (F_(1,40) = 19.21 P < 0.001; Fig. 2A). This drug effect was coupled with the selective action of MPH in appetitive trials, in which monkeys more often approached reward-predictive cues (F_(1,416) = 6.79 P = 0.009; Fig. 2B) while making fewer errors (F_(1,416) = 7.82, P = 0.005; Fig. 2E), particularly early escapes (F_(1,416) = 15.59, P < 0.001; Fig. 2F). Thus, animals exposed to MPH not only showed increased motivation to continue working actively within sessions, but also earned more rewards (+7%) in appetitive trials by behaving more optimally in individual trials (i.e., by reducing errors and choosing reward-predictive cues more often). In contrast to the MPH effects in trials with a positive valence, the active avoidance of airpuffs in aversive trials remained unchanged. Apart from an effect on the omission rate (F_(1,416) = 6.79 P = 0.009; Fig. 2G) driven largely by a single animal (i.e, monkey C; Permutation test P = 0.018), MPH affected neither the rate of avoiding negatively valenced cues (F_(1,407) = 0.02 P = 0.88; Fig. 2B) nor that of escaping punishments (F_(1,146) = 1.94 P = 0.16; Fig. 2F). Consistent with this asymmetrical effect of MPH on task performance, we found that the monkeys’ approaches at the population level were differentially modulated by drug administration depending on the task condition (drug condition × task condition; F_(1,416) = 7.12, P = 0.007; Fig. 2B; Supplemental Fig. 2). Furthermore, the drug’s impact on error rates also varied with trial type, but this effect emerged when accounting for inter-individual variability (drug condition × task condition × monkey; F > 4.34, P < 0.001; Fig. 2E, F). MPH injection did not result in consistent changes in motor performance (RT: F < 0.77 P > 0.38, Fig. 2C; MD: F < 1.47 P > 0.23, Fig. 2D; imprecise touch: F < 2.71 P > 0.10, Fig. 2H), indicating that the administered dose of MPH affected cognitive/limbic functions more than motor abilities. Likely because the animals rarely responded prematurely in the control condition (i.e., before target appearance; Supplemental Fig. 3), we found no evidence that MPH improved motor impulsivity in our task (Mann-Whitney U-test, U > 71 P > 0.21). Together, acute MPH administration improved a single dimension of adaptive behavior by selectively enhancing reward-seeking behavior, without impacting the avoidance of or escape from punishment.

Fig. 2. Methylphenidate effects on approach-avoidance behavior.

Behavioral measures were averaged (mean ± SEM) separately for each drug condition (control vs. test) and animal. Black lines reflect individual differences per animal (t-test with permutations, P < 0.05 and P < 0.001 indicated by different line thickness), while bar plots show the population-averaged values (A-H). Compared to control sessions, at the population level, methylphenidate primarily improved performance in the appetitive context by facilitating reward-seeking behavior in terms of increased complete trials (A) and percentage of approaches (B), and of reduced errors (E-F) (two-way ANOVA, drug conditions x animals; ** P < 0.01, *** P < 0.001).

Fluoxetine facilitates punishment avoidance

After a wash-out period (4-12 weeks), we investigated whether and how fluoxetine modulates approach-avoidance behavior in the same four animals. We again performed acute intramuscular injections in a total of 19 testing sessions (4 monkeys x 4-5 tests). Compared to 35 control sessions, fluoxetine considerably improved task engagement as evidenced by a 42% increase in the number of trials completed per session (F_(1,46) = 18.53 P < 0.001; Fig. 3A). Contrasting with MPH, however, this enhanced willingness to work was coupled to a selective action of fluoxetine on aversive trials, in which monkeys preferentially avoided punishment-predictive cues more often by selecting the contralateral target (F_(1,508) = 12.2 P = 0.0005; Fig. 3B). Moreover, the animals also reduced their errors (F_(1,513) = 12.80 P = 0.0004; Fig. 3E), including early escapes (F_(1,513) = 9.88 P = 0.0017; Fig. 3F) and response omissions (F_(1,513) = 4.78 P = 0.03; Fig. 3G). Consequently, animals exposed to fluoxetine prevented airpuffs more efficiently by more frequently completing trials with an active choice (+11%), which reduced the number of aversive trials they had to repeat due to errors (all trials with an error were repeated). In appetitive trials, on the other hand, no evidence supported a fluoxetine effect on reward-seeking and how animals experienced the positively valenced cues (% approach: F_(1,511) = 3.41 P = 0.07, Fig. 3B; error rate: F_(1,513) = 0.29 P = 0.59, Fig. 3E; % early escape: F_(1,513) = 0.02 P = 0.873, Fig. 3F; % omission: F_(1,513) = 1.33 P = 0.248, Fig. 3G). Consistent with a context-dependent effect of fluoxetine, monkeys’ errors at the population level were significantly influenced by drug administration depending on the task condition (drug condition × task condition; F > 10.4, P < 0.0012; Fig. 3E, F; Supplemental Fig. 2), and its effect on avoidance behavior also varied with trial type when taking individual differences into account (drug condition × task condition × monkey; F_(9,508) = 12.3, P < 0.001; Fig. 3B). While movement execution remained broadly unchanged following fluoxetine administration (MD: F < 2.98 P > 0.08, Fig. 3D; imprecise touch: F < 3.11 P > 0.08, Fig. 3H), the initiation of approach-avoidance responses took longer overall (RT in appetitive trials: F_(1,511) = 41.1 P < 0.001; RT in aversive trials: F_(1,508) = 14.42 P = 0.0002, Fig. 3C). Thus, fluoxetine appeared to render animals more cautious in both conditions. Fluoxetine had no consistent effect on motor impulsivity, as measured by premature responses before target appearance (U > 52 P > 0.06; Supplemental Fig. 3). Together, these findings suggest that acute fluoxetine administration improved adaptive behavior primarily in the aversive domain by promoting more efficient avoidance behavior. Notably, the effects of fluoxetine in the aversive domain complement those of MPH in the appetitive domain.

Fig. 3. Fluoxetine effects on approach-avoidance behavior.

This figure (A-H) follows the conventions of Fig. 2. Compared to control sessions, at the population level, fluoxetine primarily improved performance in the aversive context by increasing the willingness to work (A) with a higher percentage of active avoidance of punishment-predictive cues (B) and fewer errors (E). Both early escapes (F) and response omissions (G) were reduced (two-way ANOVA, drug conditions x animals; * P < 0.05, ** P < 0.01, *** P < 0.001).

Effects of the MPH and fluoxetine on DAT and SERT availability

To determine binding levels on transporters through which MPH and fluoxetine promote distinct aspects of approach-avoidance behavior, we compared a series of PET images acquired with (test) or without (control) drug administration (Fig. 4). We used [¹¹C]-PE2I or [¹¹C]-DASB as selective radioligands to assess DAT or SERT availabilities, and determine the population-averaged BP_ND values for each radiotracer under control and test conditions (Fig. 4B and D). The differential BP_ND values (controls-tests) indicated where the transporters were occupied by MHP or fluoxetine in the primate brain. Co-administration of MPH at the dose it affected approach behavior reduced PE2I-BP_ND values in the striatum (n = 4 animals x 2 hemispheres; paired Wilcoxon test with Benjamini-Hochberg correction for multiple comparisons P < 0.01, Fig. 4C). This finding is consistent with direct MPH binding to striatal DAT, including the ventral striatum, caudate nucleus and putamen. The other subcortical and cortical regions did not have any MPH effect on the PE2I-BP_ND values (P > 0.078, Fig. 4C). In comparison, co-administration of fluoxetine at the dose it affected avoidance behavior showed more widespread binding to SERT (n = 6 animals x 2 hemispheres; P < 0.001, Fig. 4D, E). The brain regions with the most reduced DASB-BP_ND after fluoxetine administration formed part of the limbic cortico-striato-thalamic circuits. Specifically, fluoxetine effects on SERT availability were primarily detected within the striatum, the thalamus, the amygdala, and the insula. Hence, the two psychoactive substances regulated approach and avoidance behaviors by blocking DAT and SERT in various subcortical and cortical regions, primarily within the limbic cortico-subcortical circuits.

Fig. 4. Localization of methylphenidate and fluoxetine binding sites in the monkey brain.

A MRI template with example ROIs delineated by color areas, (B-C) [¹¹C]-PE2I PET imaging results and (D-E) [¹¹C]-DASB PET imaging results. B, D Population-averaged PET images superimposed on an MRI template (n = 4 animals for PE2I, and n = 6 for DASB). The non-displaceable binding potential (BP_ND) of the tracers with (test) or without (control) drug co-injection was calculated for each hemisphere before comparison. Differences in BP_ND (ΔBP = BP_control - BP_test) indicate where DAT and SERT were the most occupied by MPH and fluoxetine, respectively. C, E MPH reduced PE2I-BP_ND values only in the striatal regions, while fluoxetine affected DASB-BP_ND values in a broader limbic network including subcortical and cortical regions (paired Wilcoxon test with Benjamini-Hochberg correction for multiple comparisons **P < 0.01 *** P < 0.001). VS: ventral striatum, CdN: caudate nucleus, Pu: putamen, GP: globus pallidus, Thal: thalamus, Hipp: hippocampus, Amy: amygdala, Ins: insula, OFC: orbitofrontal cortex, and ACC: anterior cingulate cortex.

Discussion

Our findings clarify the contributions of dopamine and serotonin neurotransmission to the approach and avoidance of emotionally valenced cues. MPH and fluoxetine, which increase dopamine and serotonin levels, respectively, in the extracellular space [27, 37] improved overall performance and task engagement. However, they achieved these beneficial effects by different means. The MPH specifically enhanced the appetitive motivational processes responsible for reward-seeking behaviors without affecting aversive responses (Fig. 2), consistent with a preferential action of dopamine on reward-mediating circuits [44]. In contrast, fluoxetine improved active avoidance in response to aversive stimuli while leaving approach behavior largely unchanged (Fig. 3), in line with a preferential influence of serotonin on neuronal networks associated with threat avoidance [45, 46]. Our neuroimaging data further support the notion of direct drug actions on transporters in various limbic cortico-subcortical regions, facilitating distinct aspects of approach-avoidance behavior (Fig. 4). PET scans revealed that MPH, at the dose affecting approach behavior, reduced PE2I-BP_ND values in the striatum, whereas fluoxetine, at the dose affecting avoidance behavior, decreased DASB-BP_ND not only in the striatum but also in the limbic cortico-subcortical circuits, including the thalamus, amygdala, and insula. Although MPH and fluoxetine primarily occupy monoaminergic transporters in distinct brain regions, we found that their binding co-localized exclusively in the striatum, which may hypothetically reflect a spatially restricted shared neural substrate for balancing approach and avoidance. Together, our findings demonstrate that MPH and fluoxetine primarily act in a complementary manner, without significant functional antagonism, to regulate approach and avoidance behaviors.

Our results contribute to the ongoing debate on the roles of dopamine and serotonin in affective control and adaptive behavior. Both monoaminergic systems can be activated in response to appetitive and aversive events [47–50], yet their specific functions and interactions remain largely unclear. Traditionally, dopamine has been associated with positive valence, encoding reward prediction error signals [51]. Conversely, serotonin is hypothesized to primarily contribute to negative valence and aversive processing [17, 21, 22], although findings concerning drugs affecting serotonin signaling have been inconsistent [26, 52, 53]. The concept, now considered outdated, that these two systems have strictly opposing functions partially arises from behavioral studies in which serotonin manipulations suppressed dopamine-related effects [54]. For example, serotonin can antagonize dopamine-enhanced appetitive behaviors such as feeding [55], sexual behavior [56], movement vigor [57], reward-seeking behavior [58], and the reinforcing effects of drugs [59]. However, neurochemical studies using microdialysis or voltammetry provide more nuanced evidence of the interplay between serotonin and dopamine systems, suggesting multifaceted interactions rather than pure opposition [60, 61]. Specifically, in rodents, systemic dopamine receptor agonists increase serotonin release [62], while acute and chronic SSRI administration reduces dopamine in the striatum [37] but increases it in the prefrontal cortex [63]. Contrary to a straightforward model, a growing body of clinical and preclinical evidence indicates that the interaction between monoamines depends on various complex factors, including the subtypes of postsynaptic receptors, the cellular heterogeneity of brain regions, and the basal activity of neuronal networks [64, 65]. Hence, depending on pathological states involving up- or down-regulation of monoamine systems, psychotropic drugs such as MPH and fluoxetine may promote distinct mechanisms.

Because monoaminergic drugs can rapidly modulate emotional processing in patients [66–68], potentially predicting later clinical outcomes even before detectable changes in symptoms [69], we administered acute doses of MPH and fluoxetine to our animals. The doses were previously defined based on their efficacy in improving primate impulsivity in the appetitive domain [38] and anxiety-related symptoms in the aversive domain [35, 39, 40]. Rather than directly antagonizing each other, for instance, the effects of the two drugs in our study were domain-specific. The actions of the two drugs were well-separated into specific clusters, suggesting that at the chosen doses, MPH and fluoxetine did not induce strong interactions between the dopamine and serotonin systems. While traditional models propose opposing or intertwined roles for these neurotransmitters in regulating approach and avoidance behaviors, our results suggest a more segmented and independent perspective. Dopamine and serotonin agents seem to act primarily in a complementary fashion, each regulating distinct adaptive responses to emotional stimuli.

SSRIs, including fluoxetine, are frequently combined with MPH for the treatment of ADHD and depression comorbidity [70, 71]. MPH can also be used in combination with SSRIs as an augmentation therapy for major depressive disorder (MDD) [72]. Although some patients have reported synergistic effects from these drug combinations [30], clinical trials generally show that each medication type is effective at reducing distinct symptomatic dimensions. For instance, in MDD patients, the combined use of MPH and SSRIs does not affect depression severity compared to SSRI monotherapy, but can significantly improve fatigue and apathy [73, 74]. Consistent with our findings, at therapeutic doses, MPH and SSRIs produce non-interactive and complementary clinical effects in patients with comorbidities. This suggests that co-exposure may be particularly effective in simultaneously addressing distinct abnormalities in the processing of both positive and negative affective information. Further research is needed to determine the extent to which this co-treatment can benefit individuals with various mental disorders characterized by imbalances in approach-avoidance tendencies and difficulties in controlling them.

Consistent with PET studies in humans [27, 75–77], our findings suggest that the beneficial effects on approach behavior may be linked to MPH’s binding to DAT in the striatum, while improvements in avoidance performance could be attributed to fluoxetine’s binding to SERT in various limbic regions. Our results also align with the effects of MPH and SSRIs on BOLD signaling, where cortical and striatal activities related to assigning emotional valence to specific events were retuned as function of dopamine or serotonin levels [52, 78, 79]. Among the brain regions identified as supporting behavioral responses to emotional stimuli [80, 81], the striatum was the only region in our study influenced by both the MPH and fluoxetine binding. This suggests that the striatum may potentially play a particular role in regulating both appetitive and aversive circuits through dopamine- and serotonin-dependent mechanisms. The striatum, which is strongly innervated by dopaminergic and serotonergic inputs [82, 83], has traditionally been associated with the control of goal-directed actions toward appetitive events, with a key role in motivational drive and reward processing [84]. However, growing evidence suggests that the same neural circuits also participate in avoidance behaviors and aversive processing [33, 34, 85–87]. Using intracerebral interventions during our approach-avoidance task, we previously showed that both the motivation to achieve rewards and the motivation to avoid aversive stimuli are mediated by neurons in the striatum [33, 35]. Thus, the valence-dependent processes performed in the striatum appear to be crucial for affective control and adaptive behavior [88, 89], making this brain region a potential target for treating biases in approach-avoidance behaviors. Although our previous work suggested that the therapeutic effect of MPH on impulsive decisions may be mainly due to its action in the striatum [38], the evidence is more equivocal for fluoxetine. Further research is needed to determine whether causal relationships exist between SERT occupancy in the striatum and adaptive avoidance. One experimental approach would be intra-striatal injections of fluoxetine in animal models. While we showed that fluoxetine binds within the striatum at a therapeutic dose (Fig. 4), actions from other brain territories cannot be excluded so far.

While our results align with findings in ADHD and depressed patients, our monkey model did not present the same pathophysiological underpinnings, our drug administrations were not equivalent to chronic medications in human patients, and our results were collected without a control group. However, our experimental approach allows for repetitive investigations of the consequences of transiently enhanced dopamine or serotonin transmission, as regularly performed in human studies [79, 90–94]. Although the effects of MPH on the dopamine system are much greater than those on the NE system (10 times greater affinity for DAT than for NET [95]), we cannot completely rule out the possibility that the NE system contributes to MPH effects on task performance. In addition, depending on pathological states and the mode of drug administration, psychotropic agents like MPH and fluoxetine may promote pharmacological mechanisms distinct from those observed in our healthy animals. Despite these limitations, our study provides valuable insights into the complex interplay between the dopamine and serotonin systems in regulating approach-avoidance behaviors, highlighting their distinct and complementary roles in adaptive responses to emotional stimuli. This could explain why co-treatment with MPH and SSRIs is particularly effective in simultaneously addressing distinct imbalances in approach-avoidance tendencies.

Author contributions

LT and BP designed the study and provided supervision. GD, YS, MM, EM, and KP collected the data. LG, JD, EM, and BP analyzed the data. LT and PNT contributed project funding and reviewed the manuscript. LG and BP wrote the manuscript.

Data availability

Data and codes are available upon request.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Supplementary information

The online version contains supplementary material available at 10.1038/s41398-025-03794-6.