Fast-scan cyclic voltammetry demonstrates that L-DOPA produces dose-dependent, regionally selective bimodal effects on striatal dopamine kinetics in vivo

L-DOPA and oxytocin influence the neural correlates of performance monitoring for self and others

RATIONALE

The ability to monitor the consequences of our actions for others is imperative for flexible and adaptive behavior, and allows us to act in a (pro)social manner. Yet, little is known about the neurochemical mechanisms underlying alterations in (pro)social performance monitoring.

OBJECTIVE

The aim of this functional magnetic resonance imaging (fMRI) study was to improve our understanding of the role of dopamine and oxytocin and their potential overlap in the neural mechanisms underlying performance monitoring for own versus others' outcomes.

METHOD

Using a double-blind placebo-controlled cross-over design, 30 healthy male volunteers were administered oxytocin (24 international units), the dopamine precursor L-DOPA (100 mg + 25 mg carbidopa), or placebo in three sessions. Participants performed a computerized cannon shooting game in two recipient conditions where mistakes resulted in negative monetary consequences for (1) oneself or (2) an anonymous other participant.

RESULTS

Results indicated reduced error-correct differentiation in the ventral striatum after L-DOPA compared to placebo, independent of recipient. Hence, pharmacological manipulation of dopamine via L-DOPA modulated performance-monitoring activity in a brain region associated with reward prediction and processing in a domain-general manner. In contrast, oxytocin modulated the BOLD response in a recipient-specific manner, such that it specifically enhanced activity for errors that affected the other in the pregenual anterior cingulate cortex (pgACC), a region previously implicated in the processing of social rewards and prediction errors. Behaviorally, we also found reduced target sizes-indicative of better performance-after oxytocin, regardless of recipient. Moreover, after oxytocin lower target sizes specifically predicted higher pgACC activity when performing for others.

CONCLUSIONS

These different behavioral and neural patterns after oxytocin compared to L-DOPA administration highlight a divergent role of each neurochemical in modulating the neural mechanisms underlying social performance monitoring.

Striatal dopamine integrates cost, benefit, and motivation

Striatal dopamine (DA) release has long been linked to reward processing, but it remains controversial whether DA release reflects costs or benefits and how these signals vary with motivation. Here, we measure DA release in the nucleus accumbens (NAc) and dorsolateral striatum (DLS) while independently varying costs and benefits and apply behavioral economic principles to determine a mouse's level of motivation. We reveal that DA release in both structures incorporates both reward magnitude and sunk cost. Surprisingly, motivation was inversely correlated with reward-evoked DA release. Furthermore, optogenetically evoked DA release was also heavily dependent on sunk cost. Our results reconcile previous disparate findings by demonstrating that striatal DA release simultaneously encodes cost, benefit, and motivation but in distinct manners over different timescales. Future work will be necessary to determine whether the reduction in phasic DA release in highly motivated animals is due to changes in tonic DA levels.

l-DOPA and oxytocin influence the neurocomputational mechanisms of self-benefitting and prosocial reinforcement learning

Humans learn through reinforcement, particularly when outcomes are unexpected. Recent research suggests similar mechanisms drive how we learn to benefit other people, that is, how we learn to be prosocial. Yet the neurochemical mechanisms underlying such prosocial computations remain poorly understood. Here, we investigated whether pharmacological manipulation of oxytocin and dopamine influence the neurocomputational mechanisms underlying self-benefitting and prosocial reinforcement learning. Using a double-blind placebo-controlled cross-over design, we administered intranasal oxytocin (24 IU), dopamine precursor l-DOPA (100 mg + 25 mg carbidopa), or placebo over three sessions. Participants performed a probabilistic reinforcement learning task with potential rewards for themselves, another participant, or no one, during functional magnetic resonance imaging. Computational models of reinforcement learning were used to calculate prediction errors (PEs) and learning rates. Participants behavior was best explained by a model with different learning rates for each recipient, but these were unaffected by either drug. On the neural level, however, both drugs blunted PE signaling in the ventral striatum and led to negative signaling of PEs in the anterior mid-cingulate cortex, dorsolateral prefrontal cortex, inferior parietal gyrus, and precentral gyrus, compared to placebo, and regardless of recipient. Oxytocin (versus placebo) administration was additionally associated with opposing tracking of self-benefitting versus prosocial PEs in dorsal anterior cingulate cortex, insula and superior temporal gyrus. These findings suggest that both l-DOPA and oxytocin induce a context-independent shift from positive towards negative tracking of PEs during learning. Moreover, oxytocin may have opposing effects on PE signaling when learning to benefit oneself versus another.

The Straw That Broke the Camel's Back: Natural Variations in 17β-Estradiol and COMT-Val158Met Genotype Interact in the Modulation of Model-Free and Model-Based Control

The sex hormone estradiol has recently gained attention in human decision-making research. Animal studies have already shown that estradiol promotes dopaminergic transmission and thus supports reward-seeking behavior and aspects of addiction. In humans, natural variations of estradiol across the menstrual cycle modulate the ability to learn from direct performance feedback ("model-free" learning). However, it remains unclear whether estradiol also influences more complex "model-based" contributions to reinforcement learning. Here, 41 women were tested twice - in the low and high estradiol state of the follicular phase of their menstrual cycle - with a Two-Step decision task designed to separate model-free from model-based learning. The results showed that in the high estradiol state women relied more heavily on model-free learning, and accomplished reduced performance gains, particularly during the more volatile periods of the task that demanded increased learning effort. In contrast, model-based control remained unaltered by the influence of hormonal state across the group. Yet, when accounting for individual differences in the genetic proxy of the COMT-Val158Met polymorphism (rs4680), we observed that only the participants homozygote for the methionine allele (n = 12; with putatively higher prefrontal dopamine) experienced a decline in model-based control when facing volatile reward probabilities. This group also showed the increase in suboptimal model-free control, while the carriers of the valine allele remained unaffected by the rise in endogenous estradiol. Taken together, these preliminary findings suggest that endogenous estradiol may affect the balance between model-based and model-free control, and particularly so in women with a high prefrontal baseline dopamine capacity and in situations of increased environmental volatility.

Moving Fast-Scan Cyclic Voltammetry toward FDA Compliance with Capacitive Decoupling Patient Protection

Carbon-fiber microelectrodes allow for high spatial and temporal measurements of electroactive neurotransmitter measurements in vivo using fast-scan cyclic voltammetry (FSCV). However, common instrumentation for such measurements systems lack patient safety precautions. To add safety precautions as well as to overcome chemical and electrical noise, a two-electrode FSCV headstage was modified to introduce an active bandpass filter on the electrode side of the measurement amplifier. This modification reduced the measured noise and ac-coupled the voltammetric measurement and moved it from a classical direct current response measurement. ac-coupling not only reduces the measured noise, but also moves FSCV toward compliance with IEC-60601-1, enabling future human trials. Here, we develop a novel ac-coupled voltammetric measurement method of electroactive neurotransmitters. Our method allows for the modeling of a system to then calculate a waveform to compensate for added impedance and capacitance for the system. We describe how first by measuring the frequency response of the system and modeling the analogue response as a digital filter we can then calculate a predicted waveform. The predicted waveform, when applied to the bandpass filter, is modulated to create a desired voltage sweep at the electrode interface. Further, we describe how this modified FSCV waveform is stable, allowing for the measurement of electroactive neurotransmitters. We later describe a 32.7% sensitivity enhancement for dopamine with this new measurement as well as maintaining a calibration curve for dopamine, 3,4-dihydroxyphenylacetic acid, ascorbic acid, and serotonin in vitro. We then validate dopamine in vivo with stimulated release. Our developed measurement method overcame the added capacitance that would traditionally make a voltammetric measurement impossible, and it has wider applications in electrode sensor development, allowing for measurement with capacitive systems, which previously would not have been possible.

L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action

Dopamine is a key neurotransmitter in action control. However, influential theories of dopamine function make conflicting predictions about the effect of boosting dopamine neurotransmission. Here, we tested if increases in dopamine tone by administration of L-DOPA upregulate reward learning as predicted by reinforcement learning theories, and if increases are specific for deliberative "model-based" control or reflexive "model-free" control. Alternatively, L-DOPA may impair learning as suggested by "value" or "thrift" theories of dopamine. To this end, we employed a two-stage Markov decision-task to investigate the effect of L-DOPA (randomized cross-over) on behavioral control while brain activation was measured using fMRI. L-DOPA led to attenuated model-free control of behavior as indicated by the reduced impact of reward on choice. Increased model-based control was only observed in participants with high working memory capacity. Furthermore, L-DOPA facilitated exploratory behavior, particularly after a stream of wins in the task. Correspondingly, in the brain, L-DOPA decreased the effect of reward at the outcome stage and when the next decision had to be made. Critically, reward-learning rates and prediction error signals were unaffected by L-DOPA, indicating that differences in behavior and brain response to reward were not driven by differences in learning. Taken together, our results suggest that L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action. These findings provide support for the value and thrift accounts of dopamine and call for a refined integration of valuation and action signals in reinforcement learning models.

Assessing the role of dopamine in the differential neurotoxicity patterns of methamphetamine, mephedrone, methcathinone and 4-methylmethamphetamine

Methamphetamine and mephedrone are designer drugs with high abuse liability and they share extensive similarities in their chemical structures and neuropharmacological effects. However, these drugs differ in one significant regard: methamphetamine elicits dopamine neurotoxicity and mephedrone does not. From a structural perspective, mephedrone has a β-keto group and a 4-methyl ring addition, both of which are lacking in methamphetamine. Our previous studies found that methcathinone, which contains only the β-keto substituent, is neurotoxic, while 4-methylmethamphetamine, which contains only the 4-methyl ring substituent, elicits minimal neurotoxicity. In the present study, it was hypothesized that the varying neurotoxic potential associated with these compounds is mediated by the drug-releasable pool of dopamine, which may be accessed by methamphetamine more readily than mephedrone, methcathinone, and 4-methylmethamphetamine. To test this hypothesis, l-DOPA and pargyline, compounds known to increase both the releasable pool of dopamine and methamphetamine neurotoxicity, were combined with mephedrone, 4-methylmethamphetamine and methcathinone. Methamphetamine was also tested because of its ability to increase releasable dopamine. All three regimens significantly enhanced striatal neurotoxicity and glial reactivity for 4-methylmethamphetamine. Methcathinone neurotoxicity and glial reactivity were enhanced only by l-DOPA. Mephedrone remained non-neurotoxic when combined with either l-DOPA or pargyline. Body temperature effects of each designer drug were not altered by the combined treatments. These results support the conclusion that the neurotoxicity of 4-methylmethamphetamine, methcathinone and methamphetamine may be differentially regulated by the drug-releasable pool of dopamine due to β-keto and 4-methyl substituents, but that mephedrone remains non-neurotoxic despite large increases in this pool of dopamine. This article is part of the Special Issue entitled 'Designer Drugs and Legal Highs.'

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Central dopaminergic (DAergic) pathways have an important role in a wide range of functions, such as attention, motivation, and movement. Dopamine (DA) is implicated in diseases and disorders including attention deficit hyperactivity disorder, Parkinson's disease, and traumatic brain injury. Thus, DA neurotransmission and the methods to study it are of intense scientific interest. In vivo fast-scan cyclic voltammetry (FSCV) is a method that allows for selectively monitoring DA concentration changes with fine temporal and spatial resolution. This technique is commonly used in conjunction with electrical stimulations of ascending DAergic pathways to control the impulse flow of dopamine neurotransmission. Although the stimulated DA neurotransmission paradigm can produce robust DA responses with clear morphologies, making them amenable for kinetic analysis, there is still much debate on how to interpret the responses in terms of their DA release and clearance components. To address this concern, a quantitative neurobiological (QN) framework of stimulated DA neurotransmission was recently developed to realistically model the dynamics of DA release and reuptake over the course of a stimulated DA response. The foundations of this model are based on experimental data from stimulated DA neurotransmission and on principles of neurotransmission adopted from various lines of research. The QN model implements 12 parameters related to stimulated DA release and reuptake dynamics to model DA responses. This work describes how to simulate DA responses using QNsim1.0 and also details principles that have been implemented to systematically discern alterations in the stimulated dopamine release and reuptake dynamics.

Contrasting Regulation of Catecholamine Neurotransmission in the Behaving Brain: Pharmacological Insights from an Electrochemical Perspective

Catecholamine neurotransmission plays a key role in regulating a variety of behavioral and physiologic processes, and its dysregulation is implicated in both neurodegenerative and neuropsychiatric disorders. Over the last four decades, in vivo electrochemistry has enabled the discovery of contrasting catecholamine regulation in the brain. These rapid and spatially resolved measurements have been conducted in brain slices, and in anesthetized and freely behaving animals. In this review, we describe the methods enabling in vivo measurements of dopamine and norepinephrine, and subsequent findings regarding their release and regulation in intact animals. We thereafter discuss key studies in awake animals, demonstrating that these catecholamines are not only differentially regulated, but are released in opposition of each other during appetitive and aversive stimuli.

Ventricular fibrillation cardiac arrest produces a chronic striatal hyperdopaminergic state that is worsened by methylphenidate treatment

Cardiac arrest survival rates have improved with modern resuscitation techniques, but many survivors experience impairments associated with hypoxic-ischemic brain injury (HIBI). Currently, little is understood about chronic changes in striatal dopamine (DA) systems after HIBI. Given the common empiric clinical use of DA enhancing agents in neurorehabilitation, investigation evaluating dopaminergic alterations after cardiac arrest (CA) is necessary to optimize rehabilitation approaches. We hypothesized that striatal DA neurotransmission would be altered chronically after ventricular fibrillation cardiac arrest (VF-CA). Fast-scan cyclic voltammetry was used with median forebrain bundle (MFB) maximal electrical stimulations (60Hz, 10s) in rats to characterize presynaptic components of DA neurotransmission in the dorsal striatum (D-Str) and nucleus accumbens 14 days after a 5-min VF-CA when compared to Sham or Naïve. VF-CA increased D-Str-evoked overflow [DA], total [DA] released, and initial DA release rate versus controls, despite also increasing maximal velocity of DA reuptake (V_max ). Methylphenidate (10 mg/kg), a DA transporter inhibitor, was administered to VF-CA and Shams after establishing a baseline, pre-drug 60 Hz, 5 s stimulation response. Methylphenidate increased initial evoked overflow [DA] more-so in VF-CA versus Sham and reduced D-Str V_max in VF-CA but not Shams; these findings are consistent with upregulated striatal DA transporter in VF-CA versus Sham. Our work demonstrates that 5-min VF-CA increases electrically stimulated DA release with concomitant upregulation of DA reuptake 2 weeks after brief VF-CA insult. Future work should elucidate how CA insult duration, time after insult, and insult type influence striatal DA neurotransmission and related cognitive and motor functions.

Kinetic Diversity of Striatal Dopamine: Evidence from a Novel Protocol for Voltammetry

In vivo voltammetry reveals substantial diversity of dopamine kinetics in the rat striatum. To substantiate this kinetic diversity, we evaluate the temporal distortion of dopamine measurements arising from the diffusion-limited adsorption of dopamine to voltammetric microelectrodes. We validate two mathematical procedures for correcting adsorptive distortion, both of which substantiate that dopamine's apparent kinetic diversity is not an adsorption artifact.