Role of DARPP-32 and ARPP-21 in the Emergence of Temporal Constraints on Striatal Calcium and Dopamine Integration

Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network

Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular complexes, can be prohibitive. Contemporary modelling methods, such as rule- based (RB) modelling, have addressed these issues. The advantages of RB modelling over ODEs have been presented and discussed in numerous reviews. In this study, we conduct a direct comparison of the time courses of a molecular system founded on the same reaction network but encoded in the two frameworks. To make such a comparison, a set of reactions that underlie an ODE model was manually encoded in the Kappa language, one of the RB implementations. A comparison of the models was performed at the level of model specification and dynamics, acquired through model simulations. In line with previous reports, we confirm that the Kappa model recapitulates the general dynamics of its ODE counterpart with minor differences. These occur when molecules have multiple sites binding the same interactor. Furthermore, activation of these molecules in the RB model is slower than in the ODE one. As reported for other molecular systems, we find that, also for the DARPP-32 reaction network, the RB representation offers a more expressive and flexible syntax that facilitates access to fine details of the model, easing model reuse. In parallel with these analyses, we report a refactored model of the DARPP-32 interaction network that can serve as a canvas for the development of more complex dynamic models to study this important molecular system.

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Here we focus on the scale of biochemical pathways, which is one of the main objects of study in systems biology. While systems biology is among the more standardized fields, conversion between different model formats and interoperability between various tools is still somewhat problematic. To offer our take on tackling these shortcomings and by keeping in mind the FAIR (findability, accessibility, interoperability, reusability) data principles, we have developed a workflow for building and analyzing biochemical pathway models, using pre-existing tools that could be utilized for the storage and refinement of models in all phases of development. We have chosen the SBtab format which allows the storage of biochemical models and associated data in a single file and provides a human readable set of syntax rules. Next, we implemented custom-made MATLAB® scripts to perform parameter estimation and global sensitivity analysis used in model refinement. Additionally, we have developed a web-based application for biochemical models that allows simulations with either a network free solver or stochastic solvers and incorporating geometry. Finally, we illustrate convertibility and use of a biochemical model in a biophysically detailed single neuron model by running multiscale simulations in NEURON. Using this workflow, we can simulate the same model in three different simulators, with a smooth conversion between the different model formats, enhancing the characterization of different aspects of the model.

Personalized Medicine to Improve Treatment of Dopa-Responsive Dystonia-A Focus on Tyrosine Hydroxylase Deficiency

Dopa-responsive dystonia (DRD) is a rare movement disorder associated with defective dopamine synthesis. This impairment may be due to the fact of a deficiency in GTP cyclohydrolase I (GTPCHI, GCH1 gene), sepiapterin reductase (SR), tyrosine hydroxylase (TH), or 6-pyruvoyl tetrahydrobiopterin synthase (PTPS) enzyme functions. Mutations in GCH1 are most frequent, whereas fewer cases have been reported for individual SR-, PTP synthase-, and TH deficiencies. Although termed DRD, a subset of patients responds poorly to L-DOPA. As this is regularly observed in severe cases of TH deficiency (THD), there is an urgent demand for more adequate or personalized treatment options. TH is a key enzyme that catalyzes the rate-limiting step in catecholamine biosynthesis, and THD patients often present with complex and variable phenotypes, which results in frequent misdiagnosis and lack of appropriate treatment. In this expert opinion review, we focus on THD pathophysiology and ongoing efforts to develop novel therapeutics for this rare disorder. We also describe how different modeling approaches can be used to improve genotype to phenotype predictions and to develop in silico testing of treatment strategies. We further discuss the current status of mathematical modeling of catecholamine synthesis and how such models can be used together with biochemical data to improve treatment of DRD patients.

The critical balance between dopamine D2 receptor and RGS for the sensitive detection of a transient decay in dopamine signal

In behavioral learning, reward-related events are encoded into phasic dopamine (DA) signals in the brain. In particular, unexpected reward omission leads to a phasic decrease in DA (DA dip) in the striatum, which triggers long-term potentiation (LTP) in DA D2 receptor (D2R)-expressing spiny-projection neurons (D2 SPNs). While this LTP is required for reward discrimination, it is unclear how such a short DA-dip signal (0.5-2 s) is transferred through intracellular signaling to the coincidence detector, adenylate cyclase (AC). In the present study, we built a computational model of D2 signaling to determine conditions for the DA-dip detection. The DA dip can be detected only if the basal DA signal sufficiently inhibits AC, and the DA-dip signal sufficiently disinhibits AC. We found that those two requirements were simultaneously satisfied only if two key molecules, D2R and regulators of G protein signaling (RGS) were balanced within a certain range; this balance has indeed been observed in experimental studies. We also found that high level of RGS was required for the detection of a 0.5-s short DA dip, and the analytical solutions for these requirements confirmed their universality. The imbalance between D2R and RGS is associated with schizophrenia and DYT1 dystonia, both of which are accompanied by abnormal striatal LTP. Our simulations suggest that D2 SPNs in patients with schizophrenia and DYT1 dystonia cannot detect short DA dips. We finally discussed that such psychiatric and movement disorders can be understood in terms of the imbalance between D2R and RGS.

A computational model of dopaminergic modulation of hippocampal Schaffer collateral-CA1 long-term plasticity

Dopamine plays a critical role in modulating the long-term synaptic plasticity of the hippocampal Schaffer collateral-CA1 pyramidal neuron synapses (SC-CA1), a widely accepted cellular model of learning and memory. Limited results from hippocampal slice experiments over the last four decades have shown that the timing of the activation of dopamine D1/D5 receptors relative to a high/low-frequency stimulation (HFS/LFS) in SC-CA1 synapses regulates the modulation of HFS/LFS-induced long-term potentiation/depression (LTP/LTD) in these synapses. However, the existing literature lacks a complete picture of how various concentrations of D1/D5 agonists and the relative timing between the activation of D1/D5 receptors and LTP/LTD induction by HFS/LFS, affect the spatiotemporal modulation of SC-CA1 synaptic dynamics. In this paper, we have developed a computational model, a first of its kind, to make quantitative predictions of the temporal dose-dependent modulation of the HFS/LFS induced LTP/LTD in SC-CA1 synapses by various D1/D5 agonists. Our model combines the biochemical effects with the electrical effects at the electrophysiological level. We have estimated the model parameters from the published electrophysiological data, available from diverse hippocampal CA1 slice experiments, in a Bayesian framework. Our modeling results demonstrate the capability of our model in making quantitative predictions of the available experimental results under diverse HFS/LFS protocols. The predictions from our model show a strong nonlinear dependency of the modulated LTP/LTD by D1/D5 agonists on the relative timing between the activated D1/D5 receptors and the HFS/LFS protocol and the applied concentration of D1/D5 agonists.

Sex Differences in the Ventral Tegmental Area and Nucleus Accumbens Proteome at Baseline and Following Nicotine Exposure

Sex differences in behaviors relevant to nicotine addiction have been observed in rodent models and human subjects. Behavioral, imaging, and epidemiological studies also suggest underlying sex differences in mesolimbic dopamine signaling pathways. In this study we evaluated the proteome in the ventral tegmental area (VTA) and nucleus accumbens (NAc) shell in male and female mice. Experimental groups included two mouse strains (C3H/HeJ and C57BL/6J) at baseline, a sub-chronic, rewarding regimen of nicotine in C3H/HeJ mice, and chronic nicotine administration and withdrawal in C57BL/6J mice. Isobaric labeling with a TMT 10-plex system, sample fractionation, and tandem mass spectrometry were used to quantify changes in protein abundance. In C3H/HeJ mice, similar numbers of proteins were differentially regulated between sexes at baseline compared with within each sex after sub-chronic nicotine administration. In C57BL/6J mice, there were significantly greater numbers of proteins differentially regulated between sexes at baseline compared with within each sex after chronic nicotine administration and withdrawal. Despite differences by sex, strain, and nicotine exposure parameters, glial fibrillary acidic protein (GFAP) and dopamine and cAMP-regulated phosphoprotein of 32 kDa (DARPP-32, Ppp1r1b) were repeatedly identified as significantly altered proteins, especially in the VTA. Further, network analyses showed sex- and nicotine-dependent regulation of a number of signaling pathways, including dopaminergic signaling. Sub-chronic nicotine exposure in female mice increased proteins related to dopaminergic signaling in the NAc shell but decreased them in the VTA, whereas the opposite pattern was observed in male mice. In contrast, dopaminergic signaling pathways were similarly upregulated in both male and female VTA after chronic nicotine and withdrawal. Overall, this study identifies significant sex differences in the proteome of the mesolimbic system, at baseline and after nicotine reward or withdrawal, which may help explain differential trajectories and susceptibility to nicotine addiction in males and females.

Facilitating mGluR4 activity reverses the long-term deleterious consequences of chronic morphine exposure in male mice

Understanding the neurobiological underpinnings of abstinence from drugs of abuse is critical to allow better recovery and ensure relapse prevention in addicted subjects. By comparing the long-term transcriptional consequences of morphine and cocaine exposure, we identified the metabotropic glutamate receptor subtype 4 (mGluR4) as a promising pharmacological target in morphine abstinence. We evaluated the behavioral and molecular effects of facilitating mGluR4 activity in abstinent mice. Transcriptional regulation of marker genes of medium spiny neurons (MSNs) allowed best discriminating between 4-week morphine and cocaine abstinence in the nucleus accumbens (NAc). Among these markers, Grm4, encoding mGluR4, displayed down-regulated expression in the caudate putamen and NAc of morphine, but not cocaine, abstinent mice. Chronic administration of the mGluR4 positive allosteric modulator (PAM) VU0155041 (2.5 and 5 mg/kg) rescued social behavior, normalized stereotypies and anxiety and blunted locomotor sensitization in morphine abstinent mice. This treatment improved social preference but increased stereotypies in cocaine abstinent mice. Finally, the beneficial behavioral effects of VU0155041 treatment in morphine abstinent mice were correlated with restored expression of key MSN and neural activity marker genes in the NAc. This study reports that chronic administration of the mGluR4 PAM VU0155041 relieves long-term deleterious consequences of morphine exposure. It illustrates the neurobiological differences between opiate and psychostimulant abstinence and points to pharmacological repression of excessive activity of D2-MSNs in the NAc as a promising therapeutic lever in drug addiction.

Modeling the activity of the dopamine signaling pathway by combination of analog electrical circuit and mathematical approaches

This paper demonstrates the application of the system biology principles on the example of the dopamine signaling pathway in neurons. Presented model is based on two approaches - cytomorphic electronic circuits and mathematical modeling. Transcription and phosphorylation of DARPP-32 was modeled by analog circuit, based on well-known approaches presented in [1]. It was shown that application of circuit helps to receive signal oscillations that close to described ones in real biological systems. This combination on the one hand gives possibility to simplify calculations, on another to show this signaling pathway dynamics. The expected effect of changes in the functioning of calcium channels is considered, and the mathematical model of the interaction of system components is proposed. The average frequency of calcium current oscillations due to the presence of dopamine was 30 Hz in presented model, that is consistent with the literature, where the frequency of such oscillations is up to several tens of Hz. All presented results shows good correlation with known data, which already published today.

Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity

Animals remember temporal links between their actions and subsequent rewards. We previously discovered a synaptic mechanism underlying such reward learning in D1 receptor (D1R)-expressing spiny projection neurons (D1 SPN) of the striatum. Dopamine (DA) bursts promote dendritic spine enlargement in a time window of only a few seconds after paired pre- and post-synaptic spiking (pre-post pairing), which is termed as reinforcement plasticity (RP). The previous study has also identified underlying signaling pathways; however, it still remains unclear how the signaling dynamics results in RP. In the present study, we first developed a computational model of signaling dynamics of D1 SPNs. The D1 RP model successfully reproduced experimentally observed protein kinase A (PKA) activity, including its critical time window. In this model, adenylate cyclase type 1 (AC1) in the spines/thin dendrites played a pivotal role as a coincidence detector against pre-post pairing and DA burst. In particular, pre-post pairing (Ca2+ signal) stimulated AC1 with a delay, and the Ca2+-stimulated AC1 was activated by the DA burst for the asymmetric time window. Moreover, the smallness of the spines/thin dendrites is crucial to the short time window for the PKA activity. We then developed a RP model for D2 SPNs, which also predicted the critical time window for RP that depended on the timing of pre-post pairing and phasic DA dip. AC1 worked for the coincidence detector in the D2 RP model as well. We further simulated the signaling pathway leading to Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation and clarified the role of the downstream molecules of AC1 as the integrators that turn transient input signals into persistent spine enlargement. Finally, we discuss how such timing windows guide animals' reward learning.

Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator

Calmodulin-dependent kinase II (CaMKII) has long been known to play an important role in learning and memory as well as long term potentiation (LTP). More recently it has been suggested that it might be involved in the time averaging of synaptic signals, which can then lead to the high precision of information stored at a single synapse. However, the role of the scaffolding molecule, neurogranin (Ng), in governing the dynamics of CaMKII is not yet fully understood. In this work, we adopt a rule-based modeling approach through the Monte Carlo method to study the effect of Ca2+ signals on the dynamics of CaMKII phosphorylation in the postsynaptic density (PSD). Calcium surges are observed in synaptic spines during an EPSP and back-propagating action potential due to the opening of NMDA receptors and voltage dependent calcium channels. Using agent-based models, we computationally investigate the dynamics of phosphorylation of CaMKII monomers and dodecameric holoenzymes. The scaffolding molecule, Ng, when present in significant concentration, limits the availability of free calmodulin (CaM), the protein which activates CaMKII in the presence of calcium. We show that Ng plays an important modulatory role in CaMKII phosphorylation following a surge of high calcium concentration. We find a non-intuitive dependence of this effect on CaM concentration that results from the different affinities of CaM for CaMKII depending on the number of calcium ions bound to the former. It has been shown previously that in the absence of phosphatase, CaMKII monomers integrate over Ca2+ signals of certain frequencies through autophosphorylation (Pepke et al, Plos Comp. Bio., 2010). We also study the effect of multiple calcium spikes on CaMKII holoenzyme autophosphorylation, and show that in the presence of phosphatase, CaMKII behaves as a leaky integrator of calcium signals, a result that has been recently observed in vivo. Our models predict that the parameters of this leaky integrator are finely tuned through the interactions of Ng, CaM, CaMKII, and PP1, providing a mechanism to precisely control the sensitivity of synapses to calcium signals. Author Summary not valid for PLOS ONE submissions.

The microcircuits of striatum in silico

The basal ganglia play an important role in decision making and selection of action primarily based on input from cortex, thalamus, and the dopamine system. Their main input structure, striatum, is central to this process. It consists of two types of projection neurons, together representing 95% of the neurons, and 5% of interneurons, among which are the cholinergic, fast-spiking, and low threshold-spiking subtypes. The membrane properties, soma-dendritic shape, and intrastriatal and extrastriatal synaptic interactions of these neurons are quite well described in the mouse, and therefore they can be simulated in sufficient detail to capture their intrinsic properties, as well as the connectivity. We focus on simulation at the striatal cellular/microcircuit level, in which the molecular/subcellular and systems levels meet. We present a nearly full-scale model of the mouse striatum using available data on synaptic connectivity, cellular morphology, and electrophysiological properties to create a microcircuit mimicking the real network. A striatal volume is populated with reconstructed neuronal morphologies with appropriate cell densities, and then we connect neurons together based on appositions between neurites as possible synapses and constrain them further with available connectivity data. Moreover, we simulate a subset of the striatum involving 10,000 neurons, with input from cortex, thalamus, and the dopamine system, as a proof of principle. Simulation at this biological scale should serve as an invaluable tool to understand the mode of operation of this complex structure. This platform will be updated with new data and expanded to simulate the entire striatum.

The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation

The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.

Birdsong as a window into language origins and evolutionary neuroscience

Humans and songbirds share the key trait of vocal learning, manifested in speech and song, respectively. Striking analogies between these behaviours include that both are acquired during developmental critical periods when the brain's ability for vocal learning peaks. Both behaviours show similarities in the overall architecture of their underlying brain areas, characterized by cortico-striato-thalamic loops and direct projections from cortical neurons onto brainstem motor neurons that control the vocal organs. These neural analogies extend to the molecular level, with certain song control regions sharing convergent transcriptional profiles with speech-related regions in the human brain. This evolutionary convergence offers an unprecedented opportunity to decipher the shared neurogenetic underpinnings of vocal learning. A key strength of the songbird model is that it allows for the delineation of activity-dependent transcriptional changes in the brain that are driven by learned vocal behaviour. To capitalize on this advantage, we used previously published datasets from our laboratory that correlate gene co-expression networks to features of learned vocalization within and after critical period closure to probe the functional relevance of genes implicated in language. We interrogate specific genes and cellular processes through converging lines of evidence: human-specific evolutionary changes, intelligence-related phenotypes and relevance to vocal learning gene co-expression in songbirds. This article is part of the theme issue 'What can animal communication teach us about human language?'

The expression of DARPP-32 in adult male zebra finches (Taenopygia guttata)

Although the catecholaminergic circuitry in the zebra finch brain has been well studied, there is little information regarding the postsynaptic targets of dopamine. To answer this question, we looked at overall patterns of immunoreactivity for DARPP-32 (a dopamine and cAMP-regulated phosphoprotein, present mostly in dopaminoceptive neurons) in adult male zebra finches. Our results demonstrated that as in mammals and other avian species, DARPP-32 expression was highest in both medial and lateral striatum. Interestingly, a specific pattern of immunoreactivity was observed in the song control system, with 'core' song control regions, that is, LMANcore (lateral magnocellular nucleus of the anterior nidopallium), RA (nucleus robustus arcopallialis) and HVC being less immunoreactive for DARPP-32 than 'shell' areas such as LMANshell, RAcup, AId (intermediate arcopallium) and HVCshelf. Our results suggest that whereas dopamine may modulate the shell pathways at various levels of the AFP, dopaminergic modulation of the core pathway occurs mainly through Area X, a basal ganglia nucleus. Further, secondary sensory cortices including the perientopallial belt, Fields L1 and L3 had higher DARPP-32-immunoreactivity than primary sensory cortical areas such as the pallial basolateral nucleus, entopallium proper and Field L2, corresponding to somatosensory, visual and auditory systems, respectively. We also found DARPP-32-rich axon terminals surrounding dopaminergic neurons in the ventral tegmental area-substantia nigra complex which in turn project to the striatum, suggesting that there may be a reciprocal modulation between these regions. Overall, DARPP-32 expression appears to be higher in areas involved in integrating sensory information, which further supports the role of this protein as a molecular integrator of different signal processing pathways.

Mechanism suppressing H3K9 trimethylation in pluripotent stem cells and its demise by polyQ-expanded huntingtin mutations

Pluripotent stem cells are invaluable resources to study development and disease, holding a great promise for regenerative medicine. Here we use human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) from patients with Huntington's disease (HD-iPSCs) to shed light into the normal function of huntingtin (HTT) and its demise in disease. We find that HTT binds ATF7IP, a regulator of the histone H3 methyltransferase SETDB1. HTT inhibits the interaction of the ATF7IP-SETDB1 complex with other heterochromatin regulators and transcriptional repressors, maintaining low levels of H3K9 trimethylation (H3K9me3) in hESCs. Loss of HTT promotes global increased H3K9me3 levels and enrichment of H3K9me3 marks at distinct genes, including transcriptional regulators of neuronal differentiation. Although these genes are normally expressed at low amounts in hESCs, HTT knockdown (KD) reduces their induction during neural differentiation. Notably, mutant expanded polyglutamine repeats in HTT diminish its interaction with ATF7IP-SETDB1 complex and trigger H3K9me3 in HD-iPSCs. Conversely, KD of ATF7IP in HD-iPSCs reduces H3K9me3 alterations and ameliorates gene expression changes in their neural counterparts. Taken together, our results indicate ATF7IP as a potential target to correct aberrant H3K9me3 levels induced by mutant HTT.

A Dual Role Hypothesis of the Cortico-Basal-Ganglia Pathways: Opponency and Temporal Difference Through Dopamine and Adenosine

The hypothesis that the basal-ganglia direct and indirect pathways represent goodness (or benefit) and badness (or cost) of options, respectively, explains a wide range of phenomena. However, this hypothesis, named the Opponent Actor Learning (OpAL), still has limitations. Structurally, the OpAL model does not incorporate differentiation of the two types of cortical inputs to the basal-ganglia pathways received from intratelencephalic (IT) and pyramidal-tract (PT) neurons. Functionally, the OpAL model does not describe the temporal-difference (TD)-type reward-prediction-error (RPE), nor explains how RPE is calculated in the circuitry connecting to the DA neurons. In fact, there is a different hypothesis on the basal-ganglia pathways and DA, named the Cortico-Striatal-Temporal-Difference (CS-TD) model. The CS-TD model differentiates the IT and PT inputs, describes the TD-type RPE, and explains how TD-RPE is calculated. However, a critical difficulty in this model lies in its assumption that DA induces the same direction of plasticity in both direct and indirect pathways, which apparently contradicts the experimentally observed opposite effects of DA on these pathways. Here, we propose a new hypothesis that integrates the OpAL and CS-TD models. Specifically, we propose that the IT-basal-ganglia pathways represent goodness/badness of current options while the PT-indirect pathway represents the overall value of the previously chosen option, and both of these have influence on the DA neurons, through the basal-ganglia output, so that a variant of TD-RPE is calculated. A key assumption is that opposite directions of plasticity are induced upon phasic activation of DA neurons in the IT-indirect pathway and PT-indirect pathway because of different profiles of IT and PT inputs. Specifically, at PT→indirect-pathway-medium-spiny-neuron (iMSN) synapses, sustained glutamatergic inputs generate rich adenosine, which allosterically prevents DA-D2 receptor signaling and instead favors adenosine-A2A receptor signaling. Then, phasic DA-induced phasic adenosine, which reflects TD-RPE, causes long-term synaptic potentiation. In contrast, at IT→iMSN synapses where adenosine is scarce, phasic DA causes long-term synaptic depression via D2 receptor signaling. This new Opponency and Temporal-Difference (OTD) model provides unique predictions, part of which is potentially in line with recently reported activity patterns of neurons in the globus pallidus externus on the indirect pathway.

DARPP-32 in the orchestration of responses to positive natural stimuli

Dopamine- and cAMP-regulated phosphoprotein (M_r 32 kDa, DARPP-32) is an integrator of multiple neuronal signals and plays a crucial role particularly in mediating the dopaminergic component of the systems involved in the evaluation of stimuli and the ensuing elaboration of complex behavioral responses (e.g., responses to reinforcers and stressors). Dopamine neurons can fire tonically or phasically in distinct timescales and in specific brain regions to code different behaviorally relevant information. Dopamine signaling is mediated mainly through the regulation of adenylyl cyclase activity, stimulated by D1-like or inhibited by D2-like receptors, respectively, that modulates cAMP-dependent protein kinase (PKA) function. The activity of DARPP-32 is finely regulated by its phosphorylation at multiple sites. Phosphorylation at the threonine (Thr) 34 residue by PKA converts DARPP-32 into an inhibitor of protein phosphatase 1, while the phosphorylation at the Thr75 residue turns it into an inhibitor of PKA. Thus, DARPP-32 is critically implicated in regulating striatal output in response to the convergent pathways that influence signaling of the cAMP/PKA pathway. This review summarizes some of the landmark and recent studies of DARPP-32-mediated signaling in the attempt to clarify the role played by DARPP-32 in the response to rewarding natural stimuli. Particularly, the review deals with data derived from rodents studies and discusses the involvement of the cAMP/PKA/DARPP-32 pathway in: 1) appetitive food-sustained motivated behaviors, 2) motivated behaviors sustained by social reward, 3) sexual behavior, and 4) responses to environmental enrichment.

Molecular mechanisms underlying striatal synaptic plasticity: relevance to chronic alcohol consumption and seeking

The striatum, the input structure of the basal ganglia, is a major site of learning and memory for goal-directed actions and habit formation. Spiny projection neurons of the striatum integrate cortical, thalamic, and nigral inputs to learn associations, with cortico-striatal synaptic plasticity as a learning mechanism. Signaling molecules implicated in synaptic plasticity are altered in alcohol withdrawal, which may contribute to overly strong learning and increased alcohol seeking and consumption. To understand how interactions among signaling molecules produce synaptic plasticity, we implemented a mechanistic model of signaling pathways activated by dopamine D1 receptors, acetylcholine receptors, and glutamate. We use our novel, computationally efficient simulator, NeuroRD, to simulate stochastic interactions both within and between dendritic spines. Dopamine release during theta burst and 20-Hz stimulation was extrapolated from fast-scan cyclic voltammetry data collected in mouse striatal slices. Our results show that the combined activity of several key plasticity molecules correctly predicts the occurrence of either LTP, LTD, or no plasticity for numerous experimental protocols. To investigate spatial interactions, we stimulate two spines, either adjacent or separated on a 20-μm dendritic segment. Our results show that molecules underlying LTP exhibit spatial specificity, whereas 2-arachidonoylglycerol exhibits a spatially diffuse elevation. We also implement changes in NMDA receptors, adenylyl cyclase, and G protein signaling that have been measured following chronic alcohol treatment. Simulations under these conditions suggest that the molecular changes can predict changes in synaptic plasticity, thereby accounting for some aspects of alcohol use disorder.

Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2

The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.

Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons

KEY POINTS

Brief dopamine events are critical actors of reward-mediated learning in the striatum; the intracellular cAMP-protein kinase A (PKA) response of striatal medium spiny neurons to such events was studied dynamically using a combination of biosensor imaging in mouse brain slices and in silico simulations. Both D1 and D2 medium spiny neurons can sense brief dopamine transients in the sub-micromolar range. While dopamine transients profoundly change cAMP levels in both types of medium spiny neurons, the PKA-dependent phosphorylation level remains unaffected in D2 neurons. At the level of PKA-dependent phosphorylation, D2 unresponsiveness depends on protein phosphatase-1 (PP1) inhibition by DARPP-32. Simulations suggest that D2 medium spiny neurons could detect transient dips in dopamine level.

ABSTRACT

The phasic release of dopamine in the striatum determines various aspects of reward and action selection, but the dynamics of the dopamine effect on intracellular signalling remains poorly understood. We used genetically encoded FRET biosensors in striatal brain slices to quantify the effect of transient dopamine on cAMP or PKA-dependent phosphorylation levels, and computational modelling to further explore the dynamics of this signalling pathway. Medium-sized spiny neurons (MSNs), which express either D1 or D2 dopamine receptors, responded to dopamine by an increase or a decrease in cAMP, respectively. Transient dopamine showed similar sub-micromolar efficacies on cAMP in both D1 and D2 MSNs, thus challenging the commonly accepted notion that dopamine efficacy is much higher on D2 than on D1 receptors. However, in D2 MSNs, the large decrease in cAMP level triggered by transient dopamine did not translate to a decrease in PKA-dependent phosphorylation level, owing to the efficient inhibition of protein phosphatase 1 by DARPP-32. Simulations further suggested that D2 MSNs can also operate in a 'tone-sensing' mode, allowing them to detect transient dips in basal dopamine. Overall, our results show that D2 MSNs may sense much more complex patterns of dopamine than previously thought.

Reinforcement determines the timing dependence of corticostriatal synaptic plasticity in vivo

Plasticity at synapses between the cortex and striatum is considered critical for learning novel actions. However, investigations of spike-timing-dependent plasticity (STDP) at these synapses have been performed largely in brain slice preparations, without consideration of physiological reinforcement signals. This has led to conflicting findings, and hampered the ability to relate neural plasticity to behavior. Using intracellular striatal recordings in intact rats, we show here that pairing presynaptic and postsynaptic activity induces robust Hebbian bidirectional plasticity, dependent on dopamine and adenosine signaling. Such plasticity, however, requires the arrival of a reward-conditioned sensory reinforcement signal within 2 s of the STDP pairing, thus revealing a timing-dependent eligibility trace on which reinforcement operates. These observations are validated with both computational modeling and behavioral testing. Our results indicate that Hebbian corticostriatal plasticity can be induced by classical reinforcement learning mechanisms, and might be central to the acquisition of novel actions.

Spike timing dependent plasticity (STDP) has been studied extensively in slices but whether such pairings can induce plasticity in vivo is not known. Here the authors report an experimental paradigm that achieves bidirectional corticostriatal STDP in vivo through modulation by behaviourally relevant reinforcement signals, mediated by dopamine and adenosine signaling.