Reconstructing the three-dimensional GABAergic microcircuit of the striatum

Model of a striatal circuit exploring biological mechanisms underlying decision-making during normal and disordered states

Decision-making requires continuous adaptation to internal and external contexts. Changes in decision-making are reliable transdiagnostic symptoms of neuropsychiatric disorders. We created a computational model demonstrating how the striosome compartment of the striatum constructs a mathematical space for decision-making computations depending on context, and how the matrix compartment defines action value depending on the space. The model explains multiple experimental results and unifies other theories like reward prediction error, roles of the direct versus indirect pathways, and roles of the striosome versus matrix, under one framework. We also found, through new analyses, that striosome and matrix neurons increase their synchrony during difficult tasks, caused by a necessary increase in dimensionality of the space. The model makes testable predictions about individual differences in disorder susceptibility, decision-making symptoms shared among neuropsychiatric disorders, and differences in neuropsychiatric disorder symptom presentation. The model reframes the role of the striosomal circuit in neuroeconomic and disorder-affected decision-making.

Highlights

Striosomes prioritize decision-related data used by matrix to set action values. Striosomes and matrix have different roles in the direct and indirect pathways. Abnormal information organization/valuation alters disorder presentation. Variance in data prioritization may explain individual differences in disorders.

eTOC

Beck et al. developed a computational model of how a striatal circuit functions during decision-making. The model unifies and extends theories about the direct versus indirect pathways. It further suggests how aberrant circuit function underlies decision-making phenomena observed in neuropsychiatric disorders.

Coordinated reset stimulation of plastic neural networks with spatially dependent synaptic connections

Background

Abnormal neuronal synchrony is associated with several neurological disorders, including Parkinson's disease (PD), essential tremor, dystonia, and epilepsy. Coordinated reset (CR) stimulation was developed computationally to counteract abnormal neuronal synchrony. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites. Computational studies in plastic neural networks reported that CR stimulation drove the networks into an attractor of a stable desynchronized state by down-regulating synaptic connections, which led to long-lasting desynchronization effects that outlasted stimulation. Later, corresponding long-lasting desynchronization and therapeutic effects were found in animal models of PD and PD patients. To date, it is unclear how spatially dependent synaptic connections, as typically observed in the brain, shape CR-induced synaptic downregulation and long-lasting effects.

Methods

We performed numerical simulations of networks of leaky integrate-and-fire neurons with spike-timing-dependent plasticity and spatially dependent synaptic connections to study and further improve acute and long-term responses to CR stimulation.

Results

The characteristic length scale of synaptic connections relative to the distance between stimulation sites plays a key role in CR parameter adjustment. In networks with short synaptic length scales, a substantial synaptic downregulation can be achieved by selecting appropriate stimulus-related parameters, such as the stimulus amplitude and shape, regardless of the employed spatiotemporal pattern of stimulus deliveries. Complex stimulus shapes can induce local connectivity patterns in the vicinity of the stimulation sites. In contrast, in networks with longer synaptic length scales, the spatiotemporal sequence of stimulus deliveries is of major importance for synaptic downregulation. In particular, rapid shuffling of the stimulus sequence is advantageous for synaptic downregulation.

Conclusion

Our results suggest that CR stimulation parameters can be adjusted to synaptic connectivity to further improve the long-lasting effects. Furthermore, shuffling of CR sequences is advantageous for long-lasting desynchronization effects. Our work provides important hypotheses on CR parameter selection for future preclinical and clinical studies.

Neuronal glutamate transporters control reciprocal inhibition and gain modulation in D1 medium spiny neurons

Understanding the function of glutamate transporters has broad implications for explaining how neurons integrate information and relay it through complex neuronal circuits. Most of what is currently known about glutamate transporters, specifically their ability to maintain glutamate homeostasis and limit glutamate diffusion away from the synaptic cleft, is based on studies of glial glutamate transporters. By contrast, little is known about the functional implications of neuronal glutamate transporters. The neuronal glutamate transporter EAAC1 is widely expressed throughout the brain, particularly in the striatum, the primary input nucleus of the basal ganglia, a region implicated with movement execution and reward. Here, we show that EAAC1 limits synaptic excitation onto a population of striatal medium spiny neurons identified for their expression of D1 dopamine receptors (D1-MSNs). In these cells, EAAC1 also contributes to strengthen lateral inhibition from other D1-MSNs. Together, these effects contribute to reduce the gain of the input-output relationship and increase the offset at increasing levels of synaptic inhibition in D1-MSNs. By reducing the sensitivity and dynamic range of action potential firing in D1-MSNs, EAAC1 limits the propensity of mice to rapidly switch between behaviors associated with different reward probabilities. Together, these findings shed light on some important molecular and cellular mechanisms implicated with behavior flexibility in mice.

Dopamine D4 Receptor Is a Regulator of Morphine-Induced Plasticity in the Rat Dorsal Striatum

Long-term exposition to morphine elicits structural and synaptic plasticity in reward-related regions of the brain, playing a critical role in addiction. However, morphine-induced neuroadaptations in the dorsal striatum have been poorly studied despite its key function in drug-related habit learning. Here, we show that prolonged treatment with morphine triggered the retraction of the dendritic arbor and the loss of dendritic spines in the dorsal striatal projection neurons (MSNs). In an attempt to extend previous findings, we also explored whether the dopamine D4 receptor (D4R) could modulate striatal morphine-induced plasticity. The combined treatment of morphine with the D4R agonist PD168,077 produced an expansion of the MSNs dendritic arbors and restored dendritic spine density. At the electrophysiological level, PD168,077 in combination with morphine altered the electrical properties of the MSNs and decreased their excitability. Finally, results from the sustantia nigra showed that PD168,077 counteracted morphine-induced upregulation of μ opioid receptors (MOR) in striatonigral projections and downregulation of G protein-gated inward rectifier K+ channels (GIRK1 and GIRK2) in dopaminergic cells. The present results highlight the key function of D4R modulating morphine-induced plasticity in the dorsal striatum. Thus, D4R could represent a valuable pharmacological target for the safety use of morphine in pain management.

Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia

How does your brain decide what you will do next? Over the past few decades compelling evidence has emerged that the basal ganglia, a collection of nuclei in the fore- and mid-brain of all vertebrates, are vital to action selection. Gurney, Prescott, and Redgrave published an influential computational account of this idea in Biological Cybernetics in 2001. Here we take a look back at this pair of papers, outlining the "GPR" model contained therein, the context of that model's development, and the influence it has had over the past twenty years. Tracing its lineage into models and theories still emerging now, we are encouraged that the GPR model is that rare thing, a computational model of a brain circuit whose advances were directly built on by others.

A Basal Ganglia Computational Model to Explain the Paradoxical Sensorial Improvement in the Presence of Huntington's Disease

The basal ganglia (BG) represent a critical center of the nervous system for sensorial discrimination. Although it is known that Huntington's disease (HD) affects this brain area, it still remains unclear how HD patients achieve paradoxical improvement in sensorial discrimination tasks. This paper presents a computational model of the BG including the main nuclei and the typical firing properties of their neurons. The BG model has been embedded within an auditory signal detection task. We have emulated the effect that the altered levels of dopamine and the degree of HD affectation have in information processing at different layers of the BG, and how these aspects shape transient and steady states differently throughout the selection task. By extracting the independent components of the BG activity at different populations, it is evidenced that early and medium stages of HD affectation may enhance transient activity in the striatum and the substantia nigra pars reticulata. These results represent a possible explanation for the paradoxical improvement that HD patients present in discrimination task performance. Thus, this paper provides a novel understanding on how the fast dynamics of the BG network at different layers interact and enable transient states to emerge throughout the successive neuron populations.

A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection

Action selection has been hypothesized to be a key function of the basal ganglia, yet the nuclei involved, their interactions and the importance of the direct/indirect pathway segregation in such process remain debated. Here, we design a spiking computational model of the monkey basal ganglia derived from a previously published population model, initially parameterized to reproduce electrophysiological activity at rest and to embody as much quantitative anatomical data as possible. As a particular feature, both models exhibit the strong overlap between the direct and indirect pathways that has been documented in non-human primates. Here, we first show how the translation from a population to an individual neuron model was achieved, with the addition of a minimal number of parameters. We then show that our model performs action selection, even though it was built without any assumption on the activity carried out during behaviour. We investigate the mechanisms of this selection through circuit disruptions and found an instrumental role of the off-centre/on-surround structure of the MSN-STN-GPi circuit, as well as of the MSN-MSN and FSI-MSN projections. This validates their potency in enabling selection. We finally study the pervasive centromedian and parafascicular thalamic inputs that reach all basal ganglia nuclei and whose influence is therefore difficult to anticipate. Our model predicts that these inputs modulate the responsiveness of action selection, making them a candidate for the regulation of the speed-accuracy trade-off during decision-making.

Striatal network modeling in Huntington's Disease

Medium spiny neurons (MSNs) comprise over 90% of cells in the striatum. In vivo MSNs display coherent burst firing cell assembly activity patterns, even though isolated MSNs do not burst fire intrinsically. This activity is important for the learning and execution of action sequences and is characteristically dysregulated in Huntington's Disease (HD). However, how dysregulation is caused by the various neural pathologies affecting MSNs in HD is unknown. Previous modeling work using simple cell models has shown that cell assembly activity patterns can emerge as a result of MSN inhibitory network interactions. Here, by directly estimating MSN network model parameters from single unit spiking data, we show that a network composed of much more physiologically detailed MSNs provides an excellent quantitative fit to wild type (WT) mouse spiking data, but only when network parameters are appropriate for the striatum. We find the WT MSN network is situated in a regime close to a transition from stable to strongly fluctuating network dynamics. This regime facilitates the generation of low-dimensional slowly varying coherent activity patterns and confers high sensitivity to variations in cortical driving. By re-estimating the model on HD spiking data we discover network parameter modifications are consistent across three very different types of HD mutant mouse models (YAC128, Q175, R6/2). In striking agreement with the known pathophysiology we find feedforward excitatory drive is reduced in HD compared to WT mice, while recurrent inhibition also shows phenotype dependency. We show that these modifications shift the HD MSN network to a sub-optimal regime where higher dimensional incoherent rapidly fluctuating activity predominates. Our results provide insight into a diverse range of experimental findings in HD, including cognitive and motor symptoms, and may suggest new avenues for treatment.

Acute Alcohol Effects on Response Inhibition Depend on Response Automatization, but not on GABA or Glutamate Levels in the ACC and Striatum

Alcohol increases GABAergic signaling and decreases glutamatergic signaling in the brain. Variations in these neurotransmitter levels may modulate/predict executive functioning. Matching this, strong impairments of response inhibition are one of the most consistently reported cognitive/behavioral effects of acute alcohol intoxication. However, it has never been investigated whether baseline differences in these neurotransmitters allow to predict how much alcohol intoxication impairs response inhibition, and whether this is reflected in neurophysiological measures of cognitive control. We used MR spectroscopy to assess baseline (i.e., sober) GABA and glutamate levels in the anterior cingulate cortex (ACC) and striatum in n = 30 healthy young males, who were subsequently tested once sober and once intoxicated (1.01 permille). Inhibition was assessed with the sustained attention to response task (SART). This paradigm also allows to examine the effect of different degrees of response automatization, which is a known modulator for response inhibition, but does not seem to be substantially impaired during acute intoxication. As a neurophysiological correlate of response inhibition and control, we quantified EEG-derived theta band power and located its source using beamforming analyses. We found that alcohol-induced response inhibition deficits only occurred in the case of response automatization. This was reflected by decreased theta band activity in the left supplementary motor area (SMA), which may reflect modulations in the encoding of a surprise signal in response to inhibition cues. However, we did not find that differences in baseline (i.e., sober) GABA or glutamate levels significantly modulated differences in the size of alcohol-induced inhibition deficits.

Exploring the role of striatal D1 and D2 medium spiny neurons in action selection using a virtual robotic framework

The basal ganglia have been hypothesized to be involved in action selection, i.e. resolving competition between simultaneously activated motor programs. It has been shown that the direct pathway facilitates action execution whereas the indirect pathway inhibits it. However, as the pathways are both active during an action, it remains unclear whether their role is co-operative or competitive. In order to investigate this issue, we developed a striatal model consisting of D1 and D2 medium spiny neurons (MSNs) and interfaced it to a simulated robot moving in an environment. We demonstrate that this model is able to reproduce key behavioral features of several experiments involving optogenetic manipulation of the striatum, such as freezing and ambulation. We then investigate the interaction of D1- and D2-MSNs. We find that their fundamental relationship is co-operative within a channel and competitive between channels; this turns out to be crucial for action selection. However, individual pairs of D1- and D2-MSNs may exhibit predominantly competition or co-operation depending on their distance, and D1- and D2-MSNs population activity can alternate between co-operation and competition modes during a stimulation. Additionally, our results show that D2-D2 connectivity between channels is necessary for effective resolution of competition; in its absence, a conflict of two motor programs typically results in neither being selected.

Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics

Development of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation platform in this direction by adding extracellular modeling. The extracellular medium of neural tissue is an active medium of neuromodulators, ions, inflammatory cells, oxygen, NO and other gases, with additional physiological, pharmacological and pathological agents. These extracellular agents influence, and are influenced by, cellular electrophysiology, and cellular chemophysiology-the complex internal cellular milieu of second-messenger signaling and cascades. NEURON's extracellular reaction-diffusion is supported by an intuitive Python-based where/who/what command sequence, derived from that used for intracellular reaction diffusion, to support coarse-grained macroscopic extracellular models. This simulation specification separates the expression of the conceptual model and parameters from the underlying numerical methods. In the volume-averaging approach used, the macroscopic model of tissue is characterized by free volume fraction-the proportion of space in which species are able to diffuse, and tortuosity-the average increase in path length due to obstacles. These tissue characteristics can be defined within particular spatial regions, enabling the modeler to account for regional differences, due either to intrinsic organization, particularly gray vs. white matter, or to pathology such as edema. We illustrate simulation development using spreading depression, a pathological phenomenon thought to play roles in migraine, epilepsy and stroke. Simulation results were verified against analytic results and against the extracellular portion of the simulation run under FiPy. The creation of this NEURON interface provides a pathway for interoperability that can be used to automatically export this class of models into complex intracellular/extracellular simulations and future cross-simulator standardization.

The role of cortical oscillations in a spiking neural network model of the basal ganglia

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8–12Hz) and beta (13–30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus—globus pallidus loop. In contrast, gamma (30–90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders.

Striatal Local Circuitry: A New Framework for Lateral Inhibition

This Perspective will examine the organization of intrastriatal circuitry, review recent findings in this area, and discuss how the pattern of connectivity between striatal neurons might give rise to the behaviorally observed synergism between the direct/indirect pathway neurons. The emphasis of this Perspective is on the underappreciated role of lateral inhibition between striatal projection cells in controlling neuronal firing and shaping the output of this circuit. We review some classic studies in combination with more recent anatomical and functional findings to lay out a framework for an updated model of the intrastriatal lateral inhibition, where we explore its contribution to the formation of functional units of processing and the integration and filtering of inputs to generate motor patterns and learned behaviors.

SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models

There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming. We demonstrate the tool through the reproduction and visualisation of published models and show simulation results using code generation interfaced directly into SpineCreator. As a unique application for the graphical creation of neural networks, SpineCreator represents an important step forward for neuronal modelling.

Generation of low-gamma oscillations in a GABAergic network model of the striatum

Striatal oscillations in the low-gamma frequency range have been consistently recorded in a number of experimental studies. However, whether these rhythms are locally generated in the striatum circuit, which is mainly composed of GABAergic neurons, remains an open question. GABAergic medium spiny projection neurons represent the great majority of striatal neurons, but they fire at very low rates. GABAergic fast-spiking interneurons typically show firing rates that are approximately 10 times higher than those of principal neurons, but they are a very small minority of the total neuronal population. In this study, based on physiological constraints we developed a computational network model of these neurons and dissected the oscillations. Simulations showed that the population of medium spiny projection neurons, and not the GABAergic fast-spiking interneurons, determines the frequency range of the oscillations. D2-type dopamine receptor-expressing neurons dominate the generation of low-gamma rhythms. Feedforward inputs from GABAergic fast-spiking interneurons promote the oscillations by strengthening the inhibitory interactions between medium spiny projection neurons. The promotion effect is independent of the degree of synchronization in the fast-spiking interneuron population but affected by the strength of their feedforward inputs to medium spiny projection neurons. Our results provide a theoretical explanation for how firing properties and connections of the three types of GABAergic neurons, which are susceptible to on-going behaviors, experience, and dopamine disruptions, sculpt striatal oscillations.

Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity

The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action selection, initiation, and execution. Here, we studied the effects of spatial network connectivity on the spatiotemporal structure of striatal activity. We show that a striatal network with nonmonotonically changing distance-dependent connectivity (according to a gamma distribution) can exhibit a wide repertoire of spatiotemporal dynamics, ranging from spatially homogeneous, asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in “winner-take-all” (WTA) dynamics. Among these regimes, the unstable activity bumps [transition activity (TA)] regime closely resembles the experimentally observed spatiotemporal activity dynamics and neuronal assemblies in the striatum. In contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can exhibit only an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary nonmonotonically. In brain disorders such as Parkinson’s disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. In contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.

Striatal Neuropeptides Enhance Selection and Rejection of Sequential Actions

The striatum is the primary input nucleus for the basal ganglia, and receives glutamatergic afferents from the cortex. Under the hypothesis that basal ganglia perform action selection, these cortical afferents encode potential “action requests.” Previous studies have suggested the striatum may utilize a mutually inhibitory network of medium spiny neurons (MSNs) to filter these requests so that only those of high salience are selected. However, the mechanisms enabling the striatum to perform clean, rapid switching between distinct actions that form part of a learned action sequence are still poorly understood. Substance P (SP) and enkephalin are neuropeptides co-released with GABA in MSNs preferentially expressing D₁ or D₂ dopamine receptors respectively. SP has a facilitatory effect on subsequent glutamatergic inputs to target MSNs, while enkephalin has an inhibitory effect. Blocking the action of SP in the striatum is also known to affect behavioral transitions. We constructed phenomenological models of the effects of SP and enkephalin, and integrated these into a hybrid model of basal ganglia comprising a spiking striatal microcircuit and rate–coded populations representing other major structures. We demonstrated that diffuse neuropeptide connectivity enhanced the selection of unordered action requests, and that for true action sequences, where action semantics define a fixed structure, a patterning of the SP connectivity reflecting this ordering enhanced selection of actions presented in the correct sequential order and suppressed incorrect ordering. We also showed that selective pruning of SP connections allowed context–sensitive inhibition of specific undesirable requests that otherwise interfered with selection of an action group. Our model suggests that the interaction of SP and enkephalin enhances the contrast between selection and rejection of action requests, and that patterned SP connectivity in the striatum allows the “chunking” of actions and improves selection of sequences. Efficient execution of action sequences may therefore result from a combination of ordered cortical inputs and patterned neuropeptide connectivity within striatum.

Marked differences in the number and type of synapses innervating the somata and primary dendrites of midbrain dopaminergic neurons, striatal cholinergic interneurons, and striatal spiny projection neurons in the rat

Elucidating the link between cellular activity and goal-directed behavior requires a fuller understanding of the mechanisms underlying burst firing in midbrain dopaminergic neurons and those that suppress activity during aversive or non-rewarding events. We have characterized the afferent synaptic connections onto these neurons in the rat substantia nigra pars compacta (SNpc) and ventral tegmental area (VTA), and compared these findings with cholinergic interneurons and spiny projection neurons in the striatum. We found that the average absolute number of synapses was three to three and one-half times greater onto the somata of dorsal striatal spiny projection neurons than onto the somata of dopaminergic neurons in the SNpc or dorsal striatal cholinergic interneurons. A similar comparison between populations of dopamine neurons revealed a two times greater number of somatic synapses on VTA dopaminergic neurons than SNpc dopaminergic neurons. The percentage of symmetrical, presumably inhibitory, synaptic inputs on somata was significantly higher on spiny projection neurons and cholinergic interneurons compared with SNpc dopaminergic neurons. Synaptic data on the primary dendrites yielded similar significant differences for the percentage of symmetrical synapses for VTA dopaminergic vs. striatal neurons. No differences in the absolute number or type of somatic synapses were evident for dopaminergic neurons in the SNpc of Wistar vs. Sprague-Dawley rat strains. These data from identified neurons are pivotal for interpreting their electrophysiological responses to afferent activity and for generating realistic computer models of neuronal networks of striatal and midbrain dopaminergic function.

Dyadic social interaction inhibits cocaine-conditioned place preference and the associated activation of the accumbens corridor

Impaired social interaction is a hallmark symptom of many psychiatric disorders. In substance use disorders, impaired social interaction is triply harmful (a) because addicts increasingly prefer the drug of abuse to the natural reward of drug-free social interaction, thus worsening the progression of the disease by increasing their drug consumption, (b) because treatment adherence and, consequently, treatment success itself depends on the ability of the recovering addict to maintain social interaction and adhere to treatment, and (c) because socially interacting with an individual suffering from a substance use disorder may be harmful for others. Helping the addict reorient his/her behavior away from the drug of abuse toward social interaction would therefore be of considerable therapeutic benefit. This article reviews our work on the neural basis of such a reorientation from cocaine, as a prototypical drug of abuse, toward dyadic (i.e. one-to-one) social interaction and compares our findings with the effects of other potentially beneficial interventions, that is, environmental enrichment or paired housing, on the activation of the accumbens and other brain regions involved in behavior motivated by drugs of abuse or nondrug stimuli. Our experimental models are based on the conditioned place preference paradigm. As the therapeutically most promising finding, only four 15 min episodes of dyadic social interaction were able to inhibit both the subsequent reacquisition/re-expression of preference for cocaine and the neural activation associated with this behavior, that is, an increase in the expression of the immediate early gene Early Growth Response protein 1 (EGR1, Zif268) in the nucleus accumbens, basolateral and central amygdala, and the ventral tegmental area. The time spent in the cocaine-associated conditioning compartment was correlated with the density of EGR1-activated neurons not only in the medial core (AcbCm) and medial shell (AcbShm) of the nucleus accumbens, but was observed in all regions medial to the anterior commissure ('accumbens corridor'), including (from medial to lateral), the vertical limb of the diagonal band and the medial septum (VDB+MS), the major island of Calleja and the intermediate nucleus of the lateral septum (ICjM+LSI), the AcbShm, and the AcbCm. All effects were limited to GABAergic projection neurons (called 'medium spiny neurons', in the accumbens), encompassing both dopamine D1 receptor-expressing and D2 receptor-expressing medium spiny neuron subtypes. Our EGR1 expression findings were mirrored in multielectrode array recordings. Finally, we have validated our paradigm in C57BL/6 mice to make use of the plethora of transgenic models available in this genus.

Existence and control of Go/No-Go decision transition threshold in the striatum

A typical Go/No-Go decision is suggested to be implemented in the brain via the activation of the direct or indirect pathway in the basal ganglia. Medium spiny neurons (MSNs) in the striatum, receiving input from cortex and projecting to the direct and indirect pathways express D1 and D2 type dopamine receptors, respectively. Recently, it has become clear that the two types of MSNs markedly differ in their mutual and recurrent connectivities as well as feedforward inhibition from FSIs. Therefore, to understand striatal function in action selection, it is of key importance to identify the role of the distinct connectivities within and between the two types of MSNs on the balance of their activity. Here, we used both a reduced firing rate model and numerical simulations of a spiking network model of the striatum to analyze the dynamic balance of spiking activities in D1 and D2 MSNs. We show that the asymmetric connectivity of the two types of MSNs renders the striatum into a threshold device, indicating the state of cortical input rates and correlations by the relative activity rates of D1 and D2 MSNs. Next, we describe how this striatal threshold can be effectively modulated by the activity of fast spiking interneurons, by the dopamine level, and by the activity of the GPe via pallidostriatal backprojections. We show that multiple mechanisms exist in the basal ganglia for biasing striatal output in favour of either the `Go' or the `No-Go' pathway. This new understanding of striatal network dynamics provides novel insights into the putative role of the striatum in various behavioral deficits in patients with Parkinson's disease, including increased reaction times, L-Dopa-induced dyskinesia, and deep brain stimulation-induced impulsivity.

From model specification to simulation of biologically constrained networks of spiking neurons

A declarative extensible markup language (SpineML) for describing the dynamics, network and experiments of large-scale spiking neural network simulations is described which builds upon the NineML standard. It utilises a level of abstraction which targets point neuron representation but addresses the limitations of existing tools by allowing arbitrary dynamics to be expressed. The use of XML promotes model sharing, is human readable and allows collaborative working. The syntax uses a high-level self explanatory format which allows straight forward code generation or translation of a model description to a native simulator format. This paper demonstrates the use of code generation in order to translate, simulate and reproduce the results of a benchmark model across a range of simulators. The flexibility of the SpineML syntax is highlighted by reproducing a pre-existing, biologically constrained model of a neural microcircuit (the striatum). The SpineML code is open source and is available at http://bimpa.group.shef.ac.uk/SpineML .

Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network

Striatal medium spiny neurons (MSNs) receive lateral inhibitory projections from other MSNs and feedforward inhibitory projections from fast-spiking, parvalbumin-containing striatal interneurons (FSIs). The functional roles of these connections are unknown, and difficult to study in an experimental preparation. We therefore investigated the functionality of both lateral (MSN-MSN) and feedforward (FSI-MSN) inhibition using a large-scale computational model of the striatal network. The model consists of 2744 MSNs comprised of 189 compartments each and 121 FSIs comprised of 148 compartments each, with dendrites explicitly represented and almost all known ionic currents included and strictly constrained by biological data as appropriate. Our analysis of the model indicates that both lateral inhibition and feedforward inhibition function at the population level to limit non-ensemble MSN spiking while preserving ensemble MSN spiking. Specifically, lateral inhibition enables large ensembles of MSNs firing synchronously to strongly suppress non-ensemble MSNs over a short time-scale (10–30 ms). Feedforward inhibition enables FSIs to strongly inhibit weakly activated, non-ensemble MSNs while moderately inhibiting activated ensemble MSNs. Importantly, FSIs appear to more effectively inhibit MSNs when FSIs fire asynchronously. Both types of inhibition would increase the signal-to-noise ratio of responding MSN ensembles and contribute to the formation and dissolution of MSN ensembles in the striatal network.

Reacquisition of cocaine conditioned place preference and its inhibition by previous social interaction preferentially affect D1-medium spiny neurons in the accumbens corridor

We investigated if counterconditioning with dyadic (i.e., one-to-one) social interaction, a strong inhibitor of the subsequent reacquisition of cocaine conditioned place preference (CPP), differentially modulates the activity of the diverse brain regions oriented along a mediolateral corridor reaching from the interhemispheric sulcus to the anterior commissure, i.e., the nucleus of the vertical limb of the diagonal band, the medial septal nucleus, the major island of Calleja, the intermediate part of the lateral septal nucleus, and the medial accumbens shell and core. We also investigated the involvement of the lateral accumbens core and the dorsal caudate putamen. The anterior cingulate 1 (Cg1) region served as a negative control. Contrary to our expectations, we found that all regions of the accumbens corridor showed increased expression of the early growth response protein 1 (EGR1, Zif268) in rats 2 h after reacquisition of CPP for cocaine after a history of cocaine CPP acquisition and extinction. Previous counterconditioning with dyadic social interaction inhibited both the reacquisition of cocaine CPP and the activation of the whole accumbens corridor. EGR1 activation was predominantly found in dynorphin-labeled cells, i.e., presumably D1 receptor-expressing medium spiny neurons (D1-MSNs), with D2-MSNs (immunolabeled with an anti-DRD2 antibody) being less affected. Cholinergic interneurons or GABAergic interneurons positive for parvalbumin, neuropeptide Y or calretinin were not involved in these CPP-related EGR1 changes. Glial cells did not show any EGR1 expression either. The present findings could be of relevance for the therapy of impaired social interaction in substance use disorders, depression, psychosis, and autism spectrum disorders.

Striatal GABA-MRS predicts response inhibition performance and its cortical electrophysiological correlates

Response inhibition processes are important for performance monitoring and are mediated via a network constituted by different cortical areas and basal ganglia nuclei. At the basal ganglia level, striatal GABAergic medium spiny neurons are known to be important for response selection, but the importance of the striatal GABAergic system for response inhibition processes remains elusive. Using a novel combination of behavior al, EEG and magnetic resonance spectroscopy (MRS) data, we examine the relevance of the striatal GABAergic system for response inhibition processes. The study shows that striatal GABA levels modulate the efficacy of response inhibition processes. Higher striatal GABA levels were related to better response inhibition performance. We show that striatal GABA modulate specific subprocesses of response inhibition related to pre-motor inhibitory processes through the modulation of neuronal synchronization processes. To our knowledge, this is the first study providing direct evidence for the relevance of the striatal GABAergic system for response inhibition functions and their cortical electrophysiological correlates in humans.

Striatal disorders dissociate mechanisms of enhanced and impaired response selection - Evidence from cognitive neurophysiology and computational modelling

Paradoxically enhanced cognitive processes in neurological disorders provide vital clues to understanding neural function. However, what determines whether the neurological damage is impairing or enhancing is unclear. Here we use the performance of patients with two disorders of the striatum to dissociate mechanisms underlying cognitive enhancement and impairment resulting from damage to the same system. In a two-choice decision task, Huntington's disease patients were faster and less error prone than controls, yet a patient with the rare condition of benign hereditary chorea (BHC) was both slower and more error prone. EEG recordings confirmed significant differences in neural processing between the groups. Analysis of a computational model revealed that the common loss of connectivity between striatal neurons in BHC and Huntington's disease impairs response selection, but the increased sensitivity of NMDA receptors in Huntington's disease potentially enhances response selection. Crucially the model shows that there is a critical threshold for increased sensitivity: below that threshold, impaired response selection results. Our data and model thus predict that specific striatal malfunctions can contribute to either impaired or enhanced selection, and provide clues to solving the paradox of how Huntington's disease can lead to both impaired and enhanced cognitive processes.

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Comparative study on well-defined neurological disorders

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Striatal disorders dissociate mechanisms of enhanced and impaired cognition.

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Neurophysiological data in patients is combined with computational modelling.

Timing control by redundant inhibitory neuronal circuits

Rhythms and timing control of sequential activity in the brain is fundamental to cognition and behavior. Although experimental and theoretical studies support the understanding that neuronal circuits are intrinsically capable of generating different time intervals, the dynamical origin of the phenomenon of functionally dependent timing control is still unclear. Here, we consider a new mechanism that is related to the multi-neuronal cooperative dynamics in inhibitory brain motifs consisting of a few clusters. It is shown that redundancy and diversity of neurons within each cluster enhances the sensitivity of the timing control with the level of neuronal excitation of the whole network. The generality of the mechanism is shown to work on two different neuronal models: a conductance-based model and a map-based model.

Transient and steady-state selection in the striatal microcircuit

Although the basal ganglia have been widely studied and implicated in signal processing and action selection, little information is known about the active role the striatal microcircuit plays in action selection in the basal ganglia-thalamo-cortical loops. To address this knowledge gap we use a large scale three dimensional spiking model of the striatum, combined with a rate coded model of the basal ganglia-thalamo-cortical loop, to asses the computational role the striatum plays in action selection. We identify a robust transient phenomena generated by the striatal microcircuit, which temporarily enhances the difference between two competing cortical inputs. We show that this transient is sufficient to modulate decision making in the basal ganglia-thalamo-cortical circuit. We also find that the transient selection originates from a novel adaptation effect in single striatal projection neurons, which is amenable to experimental testing. Finally, we compared transient selection with models implementing classical steady-state selection. We challenged both forms of model to account for recent reports of paradoxically enhanced response selection in Huntington's disease patients. We found that steady-state selection was uniformly impaired under all simulated Huntington's conditions, but transient selection was enhanced given a sufficient Huntington's-like increase in NMDA receptor sensitivity. Thus our models provide an intriguing hypothesis for the mechanisms underlying the paradoxical cognitive improvements in manifest Huntington's patients.

Inhibitory synapses between striatal projection neurons support efficient enhancement of cortical signals: a computational model

The function of lateral inhibitory synapses between striatal projection neurons is currently poorly understood. This paper puts forward a model suggesting that inhibitory collaterals can be used to enhance the incoming cortical signals. In particular, we propose that lateral inhibition between projection neurons performs a signal-enhancing process that resembles the image processing technique of "unsharp masking", where a blurred copy is used to enhance and sharpen an input image. The paper also presents the results of computer simulations deomsntrating that the proposed mechanisms is compatible with known properties of striatal projection neurons, and outperforms alternative models of lateral inhibition. Finally, this paper illustrates the advantages of the proposed model and discusses the relevance of these conclusions for existing computational models of the basal ganglia and their role in cognition.

Neural dynamics of attentional cross-modality control

Attentional networks that integrate many cortical and subcortical elements dynamically control mental processes to focus on specific events and make a decision. The resources of attentional processing are finite. Nevertheless, we often face situations in which it is necessary to simultaneously process several modalities, for example, to switch attention between players in a soccer field. Here we use a global brain mode description to build a model of attentional control dynamics. This model is based on sequential information processing stability conditions that are realized through nonsymmetric inhibition in cortical circuits. In particular, we analyze the dynamics of attentional switching and focus in the case of parallel processing of three interacting mental modalities. Using an excitatory-inhibitory network, we investigate how the bifurcations between different attentional control strategies depend on the stimuli and analyze the relationship between the time of attention focus and the strength of the stimuli. We discuss the interplay between attention and decision-making: in this context, a decision-making process is a controllable bifurcation of the attention strategy. We also suggest the dynamical evaluation of attentional resources in neural sequence processing.

Acetylcholine-based entropy in response selection: a model of how striatal interneurons modulate exploration, exploitation, and response variability in decision-making

The basal ganglia play a fundamental role in decision-making. Their contribution is typically modeled within a reinforcement learning framework, with the basal ganglia learning to select the options associated with highest value and their dopamine inputs conveying performance feedback. This basic framework, however, does not account for the role of cholinergic interneurons in the striatum, and does not easily explain certain dynamic aspects of decision-making and skill acquisition like the generation of exploratory actions. This paper describes basal ganglia acetylcholine-based entropy (BABE), a model of the acetylcholine system in the striatum that provides a unified explanation for these phenomena. According to this model, cholinergic interneurons in the striatum control the level of variability in behavior by modulating the number of possible responses that are considered by the basal ganglia, as well as the level of competition between them. This mechanism provides a natural way to account for the role of basal ganglia in generating behavioral variability during the acquisition of certain cognitive skills, as well as for modulating exploration and exploitation in decision-making. Compared to a typical reinforcement learning model, BABE showed a greater modulation of response variability in the face of changes in the reward contingences, allowing for faster learning (and re-learning) of option values. Finally, the paper discusses the possible applications of the model to other domains.

Origin and properties of striatal local field potential responses to cortical stimulation: temporal regulation by fast inhibitory connections

Evoked striatal field potentials are seldom used to study corticostriatal communication in vivo because little is known about their origin and significance. Here we show that striatal field responses evoked by stimulating the prelimbic cortex in mice are reduced by more than 90% after infusing the AMPA receptor antagonist CNQX close to the recording electrode. Moreover, the amplitude of local field responses and dPSPs recorded in striatal medium spiny neurons increase in parallel with increasing stimulating current intensity. Finally, the evoked striatal fields show several of the basic known properties of corticostriatal transmission, including paired pulse facilitation and topographical organization. As a case study, we characterized the effect of local GABA_A receptor blockade on striatal field and multiunitary action potential responses to prelimbic cortex stimulation. Striatal activity was recorded through a 24 channel silicon probe at about 600 µm from a microdialysis probe. Intrastriatal administration of the GABA_A receptor antagonist bicuculline increased by 65±7% the duration of the evoked field responses. Moreover, the associated action potential responses were markedly enhanced during bicuculline infusion. Bicuculline enhancement took place at all the striatal sites that showed a response to cortical stimulation before drug infusion, but sites showing no field response before bicuculline remained unresponsive during GABA_A receptor blockade. Thus, the data demonstrate that fast inhibitory connections exert a marked temporal regulation of input-output transformations within spatially delimited striatal networks responding to a cortical input. Overall, we propose that evoked striatal fields may be a useful tool to study corticostriatal synaptic connectivity in relation to behavior.

Spatial and temporal properties of tic-related neuronal activity in the cortico-basal ganglia loop

Motor tics are involuntary brief muscle contractions that interfere with ongoing behavior and appear as a symptom in several human disorders. While the pathophysiology of tics is still largely unknown, multiple lines of evidence suggest the involvement of the corticobasal ganglia loop in tic disorders. We administered local microinjections of bicuculline into the putamen of Macaca fascicularis monkeys to induce motor tics, while simultaneously recording neuronal activity from the primary motor cortex, putamen, and globus pallidus. These data were used to explore the spatial and temporal properties of tic-related neuronal activity within the cortico-basal ganglia system. In the putamen, tics were associated with brief bursts of activity of phasically active neurons (presumably the projection neurons) and complex excitation-inhibition patterns of tonically active neurons. Tic-related activity within the putamen was spatially focused and somatotopically organized. In the globus pallidus, tic-related activity was diffusely distributed throughout the motor territory. Tic-related activity in the putamen usually preceded the tic-related activations in the cortex, but in the globus pallidus, tic-related activity was mostly later than the cortex. These findings shed new light on the role of the different basal ganglia nuclei in the generation of motor tics. Despite the early and somatotopically focused nature of tic-related activity in the input stage of the basal ganglia, tic-related activity in the output nucleus is temporally late and diffusely distributed, making it incompatible with a role in tic initiation. Instead, abnormal basal ganglia activity may serve to modulate motor patterns or activate learning mechanisms, thus augmenting further tic expression.