Synchronized firing of fast-spiking interneurons is critical to maintain balanced firing between direct and indirect pathway neurons of the striatum

Simulating combined monoaminergic depletions in a PD animal model through a bio-constrained differential equations system

Introduction

Historically, Parkinson's Disease (PD) research has focused on the dysfunction of dopamine-producing cells in the substantia nigra pars compacta, which is linked to motor regulation in the basal ganglia. Therapies have mainly aimed at restoring dopamine (DA) levels, showing effectiveness but variable outcomes and side effects. Recent evidence indicates that PD complexity implicates disruptions in DA, noradrenaline (NA), and serotonin (5-HT) systems, which may underlie the variations in therapy effects.

Methods

We present a system-level bio-constrained computational model that comprehensively investigates the dynamic interactions between these neurotransmitter systems. The model was designed to replicate experimental data demonstrating the impact of NA and 5-HT depletion in a PD animal model, providing insights into the causal relationships between basal ganglia regions and neuromodulator release areas.

Results

The model successfully replicates experimental data and generates predictions regarding changes in unexplored brain regions, suggesting avenues for further investigation. It highlights the potential efficacy of alternative treatments targeting the locus coeruleus and dorsal raphe nucleus, though these preliminary findings require further validation. Sensitivity analysis identifies critical model parameters, offering insights into key factors influencing brain area activity. A stability analysis underscores the robustness of our mathematical formulation, bolstering the model validity.

Discussion

Our holistic approach emphasizes that PD is a multifactorial disorder and opens promising avenues for early diagnostic tools that harness the intricate interactions among monoaminergic systems. Investigating NA and 5-HT systems alongside the DA system may yield more effective, subtype-specific therapies. The exploration of multisystem dysregulation in PD is poised to revolutionize our understanding and management of this complex neurodegenerative disorder.

Striatal parvalbumin interneurons are activated in a mouse model of cerebellar dystonia

Dystonia is thought to arise from abnormalities in the motor loop of the basal ganglia; however, there is an ongoing debate regarding cerebellar involvement. We adopted an established cerebellar dystonia mouse model by injecting ouabain to examine the contribution of the cerebellum. Initially, we examined whether the entopeduncular nucleus (EPN), substantia nigra pars reticulata (SNr), globus pallidus externus (GPe) and striatal neurons were activated in the model. Next, we examined whether administration of a dopamine D1 receptor agonist and dopamine D2 receptor antagonist or selective ablation of striatal parvalbumin (PV, encoded by Pvalb)-expressing interneurons could modulate the involuntary movements of the mice. The cerebellar dystonia mice had a higher number of cells positive for c-fos (encoded by Fos) in the EPN, SNr and GPe, as well as a higher positive ratio of c-fos in striatal PV interneurons, than those in control mice. Furthermore, systemic administration of combined D1 receptor agonist and D2 receptor antagonist and selective ablation of striatal PV interneurons relieved the involuntary movements of the mice. Abnormalities in the motor loop of the basal ganglia could be crucially involved in cerebellar dystonia, and modulating PV interneurons might provide a novel treatment strategy.

Lateral Connections Improve Generalizability of Learning in a Simple Neural Network

To navigate the world around us, neural circuits rapidly adapt to their environment learning generalizable strategies to decode information. When modeling these learning strategies, network models find the optimal solution to satisfy one task condition but fail when introduced to a novel task or even a different stimulus in the same space. In the experiments described in this letter, I investigate the role of lateral gap junctions in learning generalizable strategies to process information. Lateral gap junctions are formed by connexin proteins creating an open pore that allows for direct electrical signaling between two neurons. During neural development, the rate of gap junctions is high, and daughter cells that share similar tuning properties are more likely to be connected by these junctions. Gap junctions are highly plastic and get heavily pruned throughout development. I hypothesize that they mediate generalized learning by imprinting the weighting structure within a layer to avoid overfitting to one task condition. To test this hypothesis, I implemented a feedforward probabilistic neural network mimicking a cortical fast spiking neuron circuit that is heavily involved in movement. Many of these cells are tuned to speeds that I used as the input stimulus for the network to estimate. When training this network using a delta learning rule, both a laterally connected network and an unconnected network can estimate a single speed. However, when asking the network to estimate two or more speeds, alternated in training, an unconnected network either cannot learn speed or optimizes to a singular speed, while the laterally connected network learns the generalizable strategy and can estimate both speeds. These results suggest that lateral gap junctions between neurons enable generalized learning, which may help explain learning differences across life span.

Involvement of brain cell phenotypes in stress-vulnerability and resilience

Stress-related disorders' prevalence is epidemically increasing in modern society, leading to a severe impact on individuals' well-being and a great economic burden on public resources. Based on this, it is critical to understand the mechanisms by which stress induces these disorders. The study of stress made great progress in the past decades, from deeper into the hypothalamic-pituitary-adrenal axis to the understanding of the involvement of a single cell subtype on stress outcomes. In fact, many studies have used state-of-the-art tools such as chemogenetic, optogenetic, genetic manipulation, electrophysiology, pharmacology, and immunohistochemistry to investigate the role of specific cell subtypes in the stress response. In this review, we aim to gather studies addressing the involvement of specific brain cell subtypes in stress-related responses, exploring possible mechanisms associated with stress vulnerability versus resilience in preclinical models. We particularly focus on the involvement of the astrocytes, microglia, medium spiny neurons, parvalbumin neurons, pyramidal neurons, serotonergic neurons, and interneurons of different brain areas in stress-induced outcomes, resilience, and vulnerability to stress. We believe that this review can shed light on how diverse molecular mechanisms, involving specific receptors, neurotrophic factors, epigenetic enzymes, and miRNAs, among others, within these brain cell subtypes, are associated with the expression of a stress-susceptible or resilient phenotype, advancing the understanding/knowledge on the specific machinery implicate in those events.

Basal ganglia network dynamics and function: Role of direct, indirect and hyper-direct pathways in action selection

Basal ganglia (BG) are a widely recognized neural basis for action selection, but its decision-making mechanism is still a difficult problem for researchers. Therefore, we constructed a spiking neural network inspired by the BG anatomical data. Simulation experiments were based on the principle of dis-inhibition and our functional hypothesis within the BG: the direct pathway, the indirect pathway, and the hyper-direct pathway of the BG jointly implement the initiation execution and termination of motor programs. Firstly, we studied the dynamic process of action selection with the network, which contained intra-group competition and inter-group competition. Secondly, we focused on the effects of the stimulus intensity and the proportion of excitation and inhibition on the GPi/SNr. The results suggested that inhibition and excitation shape action selection. They also explained why the firing rate of GPi/SNr did not continue to increase in the action-selection experiment. Finally, we discussed the experimental results with the functional hypothesis. Uniquely, this paper summarized the decision-making neural mechanism of action selection based on the direct pathway, the indirect pathway, and the hyper-direct pathway within BG.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.

Cortical control of striatal fast-spiking interneuron synchrony

KEY POINTS

Electrical synapses between striatal fast-spiking interneurons in adult mice occur in ∼8% of assayed pairs. Coincident, convergent cortical input onto fast-spiking interneurons significantly contributes to fast-spiking interneuron synchrony Electrical synapses between fast-spiking interneurons provide only minor enhancement of fast-spiking interneuron synchrony. These results suggest a mechanism by which adult mouse fast-spiking interneurons of the striatum synchronize in the face of declining expression of the electrical synapse-forming connexin-36 protein.

ABSTRACT

Inhibitory fast-spiking interneurons in the dorsal striatum regulate actions and action strategies, including habits. Fast-spiking interneurons are widely believed to synchronize their firing due to the electrical synapses formed between these neurons. However, neuronal modeling data suggest convergent cortical input may also drive synchrony in fast-spiking interneuron networks. To better understand how fast-spiking interneuron synchrony arises, we performed dual whole-cell patch clamp electrophysiology experiments to inform a simple Bayesian network modeling cortico-fast-spiking interneuron circuitry. Dual whole-cell patch clamp electrophysiology revealed that while responsivity to corticostriatal input activation was high in fast-spiking interneurons, few of these neurons exhibited electrical coupling in adult mice. In simulations of a cortico-fast-spiking interneuron network informed by these data, the degree of glutamatergic cortical convergence onto fast-spiking interneurons significantly increased fast-spiking interneuron synchronization while manipulations of electrical coupling between these neurons exerted relatively little impact. These results suggest that the primary source of functional coordination of fast-spiking interneuron activity in adulthood arises from convergent corticostriatal input activation. Abstract figure legend Dual whole-cell patch clamp recordings of dorsal striatal fast-spiking interneurons (FSIs; red circles) rarely (8 percentage) form electrical synapses with other FSIs in adult mouse. In a two-layer in silico model of cortical pyramidal neuron (gray triangles) input to FSIs using empirically defined cortico-FSI synaptic weights, synchronous FSI-FSI activity (in the absence of abundant electrical synapses) is achievable by convergent cortical pyramidal excitation of FSIs. This article is protected by copyright. All rights reserved.

Neuronal population models reveal specific linear conductance controllers sufficient to rescue preclinical disease phenotypes

Preclinical drug candidates are screened for their ability to ameliorate in vitro neuronal electrophysiology, and go/no-go decisions progress drugs to clinical trials based on population means across cells and animals. However, these measures do not mitigate clinical endpoint risk. Population-based modeling captures variability across multiple electrophysiological measures from healthy, disease, and drug phenotypes. We pursued optimizing therapeutic targets by identifying coherent sets of ion channel target modulations for recovering heterogeneous wild-type (WT) population excitability profiles from a heterogeneous Huntington's disease (HD) population. Our approach combines mechanistic simulations with population modeling of striatal neurons using evolutionary optimization algorithms to design 'virtual drugs'. We introduce efficacy metrics to score populations and rank virtual drug candidates. We found virtual drugs using heuristic approaches that performed better than single target modulators and standard classification methods. We compare a real drug to virtual candidates and demonstrate a novel in silico triaging method.

Computational neuronal correlation with enhanced synchronized activity in the basal ganglia and the slowing of thalamic theta and alpha rhythms in Parkinson's disease

The aim of this work is computationally to correlate the synchronized neuronal activity of basal ganglia and slowing in theta and alpha rhythms in electroencephalogram (EEG) signal in thalamic region in case of dopamine depletion and decrease of synaptic connections. The used network topology is a scale-free network with constant node degree. The dopamine-modulated type Izikhevich neuron model is used for modeling the striatal region, consisting of fast-spiking interneurons, D1 and D2 type dopamine expressing medium spiny neurons. On the other hand, the ordinary Izikhevich neuron model is used in the modeling of extrastriatal basal ganglia (BG) regions where globus pallidus (GP) subregion neurons have also dopamine-dependent parameters. The thalamic region of the network is mass modeled including inhibitory input from basal ganglia. Depending on the decrease of synaptic connections and dopamine level, the synchronization among basal ganglia neuron populations is investigated. The effect of synaptic delay on synchronization is also considered. It is observed that the decrease of dopamine neurotransmitter and decrease in the number of synaptic connections cause an increased synchronous activity in BG. Also, slowing in theta and alpha bands in thalamus EEG signals is observed. This shows the causal relation between synchronization and power shifting to lower frequency components in the case of neurodegenerative diseases such as Parkinson's disease (PD).

Modeling Neurotransmission: Computational Tools to Investigate Neurological Disorders

The investigation of synaptic functions remains one of the most fascinating challenges in the field of neuroscience and a large number of experimental methods have been tuned to dissect the mechanisms taking part in the neurotransmission process. Furthermore, the understanding of the insights of neurological disorders originating from alterations in neurotransmission often requires the development of (i) animal models of pathologies, (ii) invasive tools and (iii) targeted pharmacological approaches. In the last decades, additional tools to explore neurological diseases have been provided to the scientific community. A wide range of computational models in fact have been developed to explore the alterations of the mechanisms involved in neurotransmission following the emergence of neurological pathologies. Here, we review some of the advancements in the development of computational methods employed to investigate neuronal circuits with a particular focus on the application to the most diffuse neurological disorders.

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.

Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states

The basal ganglia (BG) is a collection of nuclei located deep beneath the cerebral cortex that is involved in learning and selection of rewarded actions. Here, we analyzed BG mechanisms that enable these functions. We implemented a rate model of a BG-thalamo-cortical loop and simulated its performance in a standard action selection task. We have shown that potentiation of corticostriatal synapses enables learning of a rewarded option. However, these synapses became redundant later as direct connections between prefrontal and premotor cortices (PFC-PMC) were potentiated by Hebbian learning. After we switched the reward to the previously unrewarded option (reversal), the BG was again responsible for switching to the new option. Due to the potentiated direct cortical connections, the system was biased to the previously rewarded choice, and establishing the new choice required a greater number of trials. Guided by physiological research, we then modified our model to reproduce pathological states of mild Parkinson's and Huntington's diseases. We found that in the Parkinsonian state PMC activity levels become extremely variable, which is caused by oscillations arising in the BG-thalamo-cortical loop. The model reproduced severe impairment of learning and predicted that this is caused by these oscillations as well as a reduced reward prediction signal. In the Huntington state, the potentiation of the PFC-PMC connections produced better learning, but altered BG output disrupted expression of the rewarded choices. This resulted in random switching between rewarded and unrewarded choices resembling an exploratory phase that never ended. Along with other computational studies, our results further reconcile the apparent contradiction between the critical involvement of the BG in execution of previously learned actions and yet no impairment of these actions after BG output is ablated by lesions or deep brain stimulation. We predict that the cortico-BG-thalamo-cortical loop conforms to previously learned choice in healthy conditions, but impedes those choices in disease states.

Parkin deficiency perturbs striatal circuit dynamics

Loss-of-function mutations in the parkin-encoding PARK2 gene are a frequent cause of young-onset, autosomal recessive Parkinson's disease (PD). Parkin knockout mice have no nigro-striatal neuronal loss but exhibit abnormalities of striatal dopamine transmission and cortico-striatal synaptic function. How these predegenerative changes observed in vitro affect neural dynamics at the intact circuit level, however, remains hitherto elusive. Here, we recorded from motor cortex, striatum and globus pallidus (GP) of anesthetized parkin-deficient mice to assess cortex-basal ganglia circuit dynamics and to dissect cell type-specific functional connectivity in the presymptomatic phase of genetic PD. While ongoing activity of presumed striatal spiny projection neurons and their downstream counterparts in the GP was not different from controls, parkin deficiency had a differential impact on striatal interneurons: In parkin-mutant mice, tonically active neurons displayed elevated activity levels. Baseline firing rates of transgenic striatal fast spiking interneurons (FSI), on the contrary, were reduced and the correlational structure of the FSI microcircuitry was disrupted. The entire transgenic striatal microcircuit showed enhanced and phase-shifted phase coupling to slow (1-3 Hz) cortical population oscillations. Unexpectedly, local field potentials recorded from striatum and GP of parkin-mutant mice robustly displayed amplified beta oscillations (~22 Hz), phase-coupled to cortex. Parkin deficiency selectively increased spike-field coupling of FSIs to beta oscillations. Our findings suggest that loss of parkin function leads to amplifications of synchronized cortico-striatal oscillations and an intrastriatal reconfiguration of interneuronal circuits. This presymptomatic disarrangement of dynamic functional connectivity may precede nigro-striatal neurodegeneration and predispose to imbalance of striatal outflow accompanying symptomatic PD.

A review of computational modeling and deep brain stimulation: applications to Parkinson's disease

Biophysical computational models are complementary to experiments and theories, providing powerful tools for the study of neurological diseases. The focus of this review is the dynamic modeling and control strategies of Parkinson's disease (PD). In previous studies, the development of parkinsonian network dynamics modeling has made great progress. Modeling mainly focuses on the cortex-thalamus-basal ganglia (CTBG) circuit and its sub-circuits, which helps to explore the dynamic behavior of the parkinsonian network, such as synchronization. Deep brain stimulation (DBS) is an effective strategy for the treatment of PD. At present, many studies are based on the side effects of the DBS. However, the translation from modeling results to clinical disease mitigation therapy still faces huge challenges. Here, we introduce the progress of DBS improvement. Its specific purpose is to develop novel DBS treatment methods, optimize the treatment effect of DBS for each patient, and focus on the study in closed-loop DBS. Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.

Aberrant features of in vivo striatal dynamics in Parkinson's disease

The striatum plays an important role in learning, selecting, and executing actions. As a major input hub of the basal ganglia, it receives and processes a diverse array of signals related to sensory, motor, and cognitive information. Aberrant neural activity in this area is implicated in a wide variety of neurological and psychiatric disorders. It is therefore important to understand the hallmarks of disrupted striatal signal processing. This review surveys literature examining how in vivo striatal microcircuit dynamics are impacted in animal models of one of the most widely studied movement disorders, Parkinson's disease. The review identifies four major features of aberrant striatal dynamics: altered relative levels of direct and indirect pathway activity, impaired information processing by projection neurons, altered information processing by interneurons, and increased synchrony.

Synchronized activation of striatal direct and indirect pathways underlies the behavior in unilateral dopamine-depleted mice

For more than three decades it has been known, that striatal neurons become hyperactive after the loss of dopamine input, but the involvement of dopamine (DA) D1‐ or D2‐receptor‐expressing neurons has only been demonstrated indirectly. By recording neuronal activity using fluorescent calcium indicators in D1 or D2 eGFP‐expressing mice, we showed that following dopamine depletion, both types of striatal output neurons are involved in the large increase in neuronal activity generating a characteristic cell assembly of particular neurons that dominate the pattern. When we expressed channelrhodopsin in all the output neurons, light activation in freely moving animals, caused turning like that following dopamine loss. However, if the light stimulation was patterned in pulses the animals circled in the other direction. To explore the neuronal participation during this stimulation we infected normal mice with channelrhodopsin and calcium indicator in striatal output neurons. In slices made from these animals, continuous light stimulation for 15 s induced many cells to be active together and a particular dominant group of neurons, whereas light in patterned pulses activated fewer cells in more variable groups. These results suggest that the simultaneous activity of a large dominant group of striatal output neurons is intimately associated with parkinsonian symptoms.

Insights into Parkinson's disease from computational models of the basal ganglia

Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson's disease as a case study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15-30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms and treatments for Parkinson's disease.

Calcium currents in striatal fast-spiking interneurons: dopaminergic modulation of CaV1 channels

BACKGROUND

Striatal fast-spiking interneurons (FSI) are a subset of GABAergic cells that express calcium-binding protein parvalbumin (PV). They provide feed-forward inhibition to striatal projection neurons (SPNs), receive cortical, thalamic and dopaminergic inputs and are coupled together by electrical and chemical synapses, being important components of the striatal circuitry. It is known that dopamine (DA) depolarizes FSI via D₁-class DA receptors, but no studies about the ionic mechanism of this action have been reported. Here we ask about the ion channels that are the effectors of DA actions. This work studies their Ca²⁺ currents.

RESULTS

Whole-cell recordings in acutely dissociated and identified FSI from PV-Cre transgenic mice were used to show that FSI express an array of voltage gated Ca²⁺ channel classes: Ca_V1, Ca_V2.1, Ca_V2.2, Ca_V2.3 and Ca_V3. However, Ca_V1 Ca²⁺ channel carries most of the whole-cell Ca²⁺ current in FSI. Activation of D₁-like class of DA receptors by the D₁-receptor selective agonist SKF-81297 (SKF) enhances whole-cell Ca²⁺ currents through Ca_V1 channels modulation. A previous block of Ca_V1 channels with nicardipine occludes the action of the DA-agonist, suggesting that no other Ca²⁺ channel is modulated by D₁-receptor activation. Bath application of SKF in brain slices increases the firing rate and activity of FSI as measured with both whole-cell and Ca²⁺ imaging recordings. These actions are reduced by nicardipine.

CONCLUSIONS

The present work discloses one final effector of DA modulation in FSI. We conclude that the facilitatory action of DA in FSI is in part due to Ca_V1 Ca²⁺ channels positive modulation.

A probabilistic, distributed, recursive mechanism for decision-making in the brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.

Decision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson’s and Huntington’s diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decision-making has, hitherto, remained elusive. Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decision-making in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

Effects of location and extent of spine clustering on synaptic integration in striatal medium spiny neurons-a computational study

The nucleus accumbens (NAc) is known widely for its role in the reward circuit, which is dysregulated in a number of psychological disorders. Recent evidence also suggests the contribution of this structure in spatial and gustatory memories. Because of its role in different types of memories, similar to the hippocampus, we assumed the formation of spine clusters, which are engrams of memory, to be present on dendrites of medium spiny neurons (MSNs). We found that the activation of clustered inputs resulted in sublinear summation when clusters were present on the same branch and also when inputs were distributed on different branches. The size, as well as the location of clusters, was found to affect the summation. With an increase in cluster size and distance from soma, the summation was increasingly sublinear. When the temporal integration window was measured for clustered spines, it was found to be narrower as compared to that for a single spine. Also, distally located clusters resulted in a wider temporal window, as compared to proximal clusters. Our results suggest that depending on the location of clusters, the modes of integration will differ in MSNs possessing clustered spines.

Modeling influences of dopamine on synchronization behavior of striatum

A network model of striatum that comprises medium spiny neurons (MSNs) and fast spiking interneurons (FSIs) is constructed following the work of Humphries et al. (2009). The dynamic behavior of striatum microcircuit is investigated using a dopamine-modulated modified Izhikevich neuron model. The influences of dopamine on the synchronization behavior of the striatal microcircuit and the dependence on receptor type are investigated with and without time delay. To investigate the role of two types of dopamine receptors, D1 and D2, on the overall activity of the striatum microcircuit, the activities of two groups are considered as disconnected and connected. When the connection exists between D1 and D2 sub-networks with zero dopamine and time delay, neuronal activity decreases because of an inhibitory effect of the connected neurons of the other sub-network. In the presence of dopamine, an increase in the activity of D1 type MSNs and quiescent behavior of D2 type MSNs are observed when the time delay is zero. However, the diversity in synchronization of D1 and D2 type MSNs is observed for different synaptic time delays and synaptic strengths in the case that dopamine is present.

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.

Npas1+ Pallidal Neurons Target Striatal Projection Neurons

Compelling evidence demonstrates that the external globus pallidus (GPe) plays a key role in processing sensorimotor information. An anatomical projection from the GPe to the dorsal striatum has been described for decades. However, the cellular target and functional impact of this projection remain unknown. Using cell-specific transgenic mice, modern monosynaptic tracing techniques, and optogenetics-based mapping, we discovered that GPe neurons provide inhibitory inputs to direct and indirect pathway striatal projection neurons (SPNs). Our results indicate that the GPe input to SPNs arises primarily from Npas1-expressing neurons and is strengthened in a chronic Parkinson's disease (PD) model. Alterations of the GPe-SPN input in a PD model argue for the critical position of this connection in regulating basal ganglia motor output and PD symptomatology. Finally, chemogenetic activation of Npas1-expressing GPe neurons suppresses motor output, arguing that strengthening of the GPe-SPN connection is maladaptive and may underlie the hypokinetic symptoms in PD.

SIGNIFICANCE STATEMENT

An anatomical projection from the pallidum to the striatum has been described for decades, but little is known about its connectivity pattern. The authors dissect the presynaptic and postsynaptic neurons involved in this projection, and show its cell-specific remodeling and strengthening in parkinsonian mice. Chemogenetic activation of Npas1(+) pallidal neurons that give rise to the principal pallidostriatal projection increases the time that the mice spend motionless. This argues that maladaptive strengthening of this connection underlies the paucity of volitional movements, which is a hallmark of Parkinson's disease.

Pallidostriatal Projections Promote β Oscillations in a Dopamine-Depleted Biophysical Network Model

In the basal ganglia, focused rhythmicity is an important feature of network activity at certain stages of motor processing. In disease, however, the basal ganglia develop amplified rhythmicity. Here, we demonstrate how the cellular architecture and network dynamics of an inhibitory loop in the basal ganglia yield exaggerated synchrony and locking to β oscillations, specifically in the dopamine-depleted state. A key component of this loop is the pallidostriatal pathway, a well-characterized anatomical projection whose function has long remained obscure. We present a synaptic characterization of this pathway in mice and incorporate these data into a computational model that we use to investigate its influence over striatal activity under simulated healthy and dopamine-depleted conditions. Our model predicts that the pallidostriatal pathway influences striatal output preferentially during periods of synchronized activity within GPe. We show that, under dopamine-depleted conditions, this effect becomes a key component of a positive feedback loop between the GPe and striatum that promotes synchronization and rhythmicity. Our results generate novel predictions about the role of the pallidostriatal pathway in shaping basal ganglia activity in health and disease.

SIGNIFICANCE STATEMENT

This work demonstrates that functional connections from the globus pallidus externa (GPe) to striatum are substantially stronger onto fast-spiking interneurons (FSIs) than onto medium spiny neurons. Our circuit model suggests that when GPe spikes are synchronous, this pallidostriatal pathway causes synchronous FSI activity pauses, which allow a transient window of disinhibition for medium spiny neurons. In simulated dopamine-depletion, this GPe-FSI activity is necessary for the emergence of strong synchronization and the amplification and propagation of β oscillations, which are a hallmark of parkinsonian circuit dysfunction. These results suggest that GPe may play a central role in propagating abnormal circuit activity to striatum, which in turn projects to downstream basal ganglia structures. These findings warrant further exploration of GPe as a target for interventions for Parkinson's disease.

Parvalbumin Interneurons Modulate Striatal Output and Enhance Performance during Associative Learning

The prevailing view is that striatal parvalbumin (PV)-positive interneurons primarily function to downregulate medium spiny projection neuron (MSN) activity via monosynaptic inhibitory signaling. Here, by combining in vivo neural recordings and optogenetics, we unexpectedly find that both suppressing and over-activating PV cells attenuates spontaneous MSN activity. To account for this, we find that, in addition to monosynaptic coupling, PV-MSN interactions are mediated by a competing disynaptic inhibitory circuit involving a variety of neuropeptide Y-expressing interneurons. Next we use optogenetic and chemogenetic approaches to show that dorsolateral striatal PV interneurons influence the initial expression of reward-conditioned responses but that their contribution to performance declines with experience. Consistent with this, we observe with large-scale recordings in behaving animals that the relative contribution of PV cells on MSN activity diminishes with training. Together, this work provides a possible mechanism by which PV interneurons modulate striatal output and selectively enhance performance early in learning.

Untangling Basal Ganglia Network Dynamics and Function: Role of Dopamine Depletion and Inhibition Investigated in a Spiking Network Model

The basal ganglia are a crucial brain system for behavioral selection, and their function is disturbed in Parkinson's disease (PD), where neurons exhibit inappropriate synchronization and oscillations. We present a spiking neural model of basal ganglia including plausible details on synaptic dynamics, connectivity patterns, neuron behavior, and dopamine effects. Recordings of neuronal activity in the subthalamic nucleus and Type A (TA; arkypallidal) and Type I (TI; prototypical) neurons in globus pallidus externa were used to validate the model. Simulation experiments predict that both local inhibition in striatum and the existence of an indirect pathway are important for basal ganglia to function properly over a large range of cortical drives. The dopamine depletion-induced increase of AMPA efficacy in corticostriatal synapses to medium spiny neurons (MSNs) with dopamine receptor D2 synapses (CTX-MSN D2) and the reduction of MSN lateral connectivity (MSN-MSN) were found to contribute significantly to the enhanced synchrony and oscillations seen in PD. Additionally, reversing the dopamine depletion-induced changes to CTX-MSN D1, CTX-MSN D2, TA-MSN, and MSN-MSN couplings could improve or restore basal ganglia action selection ability. In summary, we found multiple changes of parameters for synaptic efficacy and neural excitability that could improve action selection ability and at the same time reduce oscillations. Identification of such targets could potentially generate ideas for treatments of PD and increase our understanding of the relation between network dynamics and network function.

Parvalbumin+ Neurons and Npas1+ Neurons Are Distinct Neuron Classes in the Mouse External Globus Pallidus

Compelling evidence suggests that pathological activity of the external globus pallidus (GPe), a nucleus in the basal ganglia, contributes to the motor symptoms of a variety of movement disorders such as Parkinson's disease. Recent studies have challenged the idea that the GPe comprises a single, homogenous population of neurons that serves as a simple relay in the indirect pathway. However, we still lack a full understanding of the diversity of the neurons that make up the GPe. Specifically, a more precise classification scheme is needed to better describe the fundamental biology and function of different GPe neuron classes. To this end, we generated a novel multicistronic BAC (bacterial artificial chromosome) transgenic mouse line under the regulatory elements of the Npas1 gene. Using a combinatorial transgenic and immunohistochemical approach, we discovered that parvalbumin-expressing neurons and Npas1-expressing neurons in the GPe represent two nonoverlapping cell classes, amounting to 55% and 27% of the total GPe neuron population, respectively. These two genetically identified cell classes projected primarily to the subthalamic nucleus and to the striatum, respectively. Additionally, parvalbumin-expressing neurons and Npas1-expressing neurons were distinct in their autonomous and driven firing characteristics, their expression of intrinsic ion conductances, and their responsiveness to chronic 6-hydroxydopamine lesion. In summary, our data argue that parvalbumin-expressing neurons and Npas1-expressing neurons are two distinct functional classes of GPe neurons. This work revises our understanding of the GPe, and provides the foundation for future studies of its function and dysfunction.

SIGNIFICANCE STATEMENT

Until recently, the heterogeneity of the constituent neurons within the external globus pallidus (GPe) was not fully appreciated. We addressed this knowledge gap by discovering two principal GPe neuron classes, which were identified by their nonoverlapping expression of the markers parvalbumin and Npas1. Our study provides evidence that parvalbumin and Npas1 neurons have different topologies within the basal ganglia.

Optogenetic stimulation reveals distinct modulatory properties of thalamostriatal vs corticostriatal glutamatergic inputs to fast-spiking interneurons

Parvalbumin-containing fast-spiking interneurons (FSIs) exert a powerful feed-forward GABAergic inhibition on striatal medium spiny neurons (MSNs), playing a critical role in timing striatal output. However, how glutamatergic inputs modulate their firing activity is still unexplored. Here, by means of a combined optogenetic and electrophysiological approach, we provide evidence for a differential modulation of cortico- vs thalamo-striatal synaptic inputs to FSIs in transgenic mice carrying light-gated ion channels channelrhodopsin-2 (ChR2) in glutamatergic fibers. Corticostriatal synapses show a postsynaptic facilitation, whereas thalamostriatal synapses present a postsynaptic depression. Moreover, thalamostriatal synapses exhibit more prominent AMPA-mediated currents than corticostriatal synapses, and an increased release probability. Furthermore, during current-evoked firing activity, simultaneous corticostriatal stimulation increases bursting activity. Conversely, thalamostriatal fiber activation shifts the canonical burst-pause activity to a more prolonged, regular firing pattern. However, this change in firing pattern was accompanied by a significant rise in the frequency of membrane potential oscillations. Notably, the responses to thalamic stimulation were fully abolished by blocking metabotropic glutamate 1 (mGlu1) receptor subtype, whereas both acetylcholine and dopamine receptor antagonists were ineffective. Our findings demonstrate that cortical and thalamic glutamatergic input differently modulate FSIs firing activity through specific intrinsic and synaptic properties, exerting a powerful influence on striatal outputs.

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.

Desynchronization of fast-spiking interneurons reduces β-band oscillations and imbalance in firing in the dopamine-depleted striatum

Oscillations in the β-band (8-30 Hz) that emerge in the output nuclei of the basal ganglia during Parkinson's disease, along with an imbalanced activation of the direct and indirect pathways, have been linked to the hypokinetic motor output associated with the disease. Although dopamine depletion causes a change in cellular and network properties in the striatum, it is unclear whether abnormal activity measured in the globus pallidus and substantia nigra pars reticulata is caused by abnormal striatal activity. Here we use a computational network model of medium spiny neurons (MSNs)-fast-spiking interneurons (FSIs), based on data from several mammalian species, and find that robust β-band oscillations and imbalanced firing emerge from implementation of changes to cellular and circuit properties caused by dopamine depletion. These changes include a reduction in connections between MSNs, a doubling of FSI inhibition to D2 MSNs, an increase in D2 MSN dendritic excitability, and a reduction in D2 MSN somatic excitability. The model reveals that the reduced decorrelation between MSNs attributable to weakened lateral inhibition enables the strong influence of synchronous FSIs on MSN firing and oscillations. Weakened lateral inhibition also produces an increased sensitivity of MSN output to cortical correlation, a condition relevant to the parkinsonian striatum. The oscillations of FSIs, in turn, are strongly modulated by fast electrical transmission between FSIs through gap junctions. These results suggest that pharmaceuticals that desynchronize FSI activity may provide a novel treatment for the enhanced β-band oscillations, imbalanced firing, and motor dysfunction in Parkinson's disease.

Pallidal gap junctions-triggers of synchrony in Parkinson's disease?

Although increased synchrony of the neural activity in the basal ganglia may underlie the motor deficiencies exhibited in Parkinson's disease (PD), how this synchrony arises, propagates through the basal ganglia, and changes under dopamine replacement remains unknown. Gap junctions could play a major role in modifying this synchrony, because they show functional plasticity under the influence of dopamine and after neural injury. In this study, confocal imaging was used to detect connexin-36, the major neural gap junction protein, in postmortem tissues of PD patients and control subjects in the putamen, subthalamic nucleus (STN), and external and internal globus pallidus (GPe and GPi, respectively). Moreover, we quantified how gap junctions affect synchrony in an existing computational model of the basal ganglia. We detected connexin-36 in the human putamen, GPe, and GPi, but not in the STN. Furthermore, we found that the number of connexin-36 spots in PD tissues increased by 50% in the putamen, 43% in the GPe, and 109% in the GPi compared with controls. In the computational model, gap junctions in the GPe and GPi strongly influenced synchrony. The basal ganglia became especially susceptible to synchronize with input from the cortex when gap junctions were numerous and high in conductance. In conclusion, connexin-36 expression in the human GPe and GPi suggests that gap junctional coupling exists within these nuclei. In PD, neural injury and dopamine depletion could increase this coupling. Therefore, we propose that gap junctions act as a powerful modulator of synchrony in the basal ganglia.