Corticostriatal combinatorics: the implications of corticostriatal axonal arborizations

Break-up and recovery of harmony between direct and indirect pathways in the basal ganglia: Huntington's disease and treatment

The basal ganglia (BG) in the brain exhibit diverse functions for motor, cognition, and emotion. Such BG functions could be made via competitive harmony between the two competing pathways, direct pathway (DP) (facilitating movement) and indirect pathway (IP) (suppressing movement). As a result of break-up of harmony between DP and IP, there appear pathological states with disorder for movement, cognition, and psychiatry. In this paper, we are concerned about the Huntington's disease (HD), which is a genetic neurodegenerative disorder causing involuntary movement and severe cognitive and psychiatric symptoms. For the HD, the number of D2 SPNs ( N D 2 ) is decreased due to degenerative loss, and hence, by decreasing x D 2 (fraction of N D 2 ), we investigate break-up of harmony between DP and IP in terms of their competition degree C d , given by the ratio of strength of DP ( S DP ) to strength of IP ( S IP ) (i.e.,C d = S DP / S IP ). In the case of HD, the IP is under-active, in contrast to the case of Parkinson's disease with over-active IP, which results in increase in C d (from the normal value). Thus, hyperkinetic dyskinesia such as chorea (involuntary jerky movement) occurs. We also investigate treatment of HD, based on optogenetics and GP ablation, by increasing strength of IP, resulting in recovery of harmony between DP and IP. Finally, we study effect of loss of healthy synapses of all the BG cells on HD. Due to loss of healthy synapses, disharmony between DP and IP increases, leading to worsen symptoms of the HD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10125-w.

Quantifying harmony between direct and indirect pathways in the basal ganglia: healthy and Parkinsonian states

The basal ganglia (BG) show a variety of functions for motor and cognition. There are two competitive pathways in the BG; direct pathway (DP) which facilitates movement and indirect pathway (IP) which suppresses movement. It is well known that diverse functions of the BG may be made through "balance" between DP and IP. But, to the best of our knowledge, so far no quantitative analysis for such balance was done. In this paper, as a first time, we introduce the competition degree C d between DP and IP. Then, by employing C d , we quantify their competitive harmony (i.e., competition and cooperative interplay), which could lead to improving our understanding of the traditional "balance" so clearly and quantitatively. We first consider the case of normal dopamine (DA) level ofϕ ∗ = 0.3 . In the case of phasic cortical input (10 Hz), a healthy state withC d ∗ = 2.82 (i.e., DP is 2.82 times stronger than IP) appears. In this case, normal movement occurs via harmony between DP and IP. Next, we consider the case of decreased DA level, ϕ = ϕ ∗ ( = 0.3 ) x DA ( 1 > x DA ≥ 0 ). With decreasing x DA from 1, the competition degree C d between DP and IP decreases monotonically from C d ∗ , which results in appearance of a pathological Parkinsonian state with reduced C d . In this Parkinsonian state, strength of IP is much increased than that in the case of normal healthy state, leading to disharmony between DP and IP. Due to such break-up of harmony between DP and IP, impaired movement occurs. Finally, we also study treatment of the pathological Parkinsonian state via recovery of harmony between DP and IP.

Rethinking dopamine-guided action sequence learning

As opposed to those requiring a single action for reward acquisition, tasks necessitating action sequences demand that animals learn action elements and their sequential order and sustain the behaviour until the sequence is completed. With repeated learning, animals not only exhibit precise execution of these sequences but also demonstrate enhanced smoothness and efficiency. Previous research has demonstrated that midbrain dopamine and its major projection target, the striatum, play crucial roles in these processes. Recent studies have shown that dopamine from the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA) serve distinct functions in action sequence learning. The distinct contributions of dopamine also depend on the striatal subregions, namely the ventral, dorsomedial and dorsolateral striatum. Here, we have reviewed recent findings on the role of striatal dopamine in action sequence learning, with a focus on recent rodent studies.

Activity-Dependent Remodeling of Corticostriatal Axonal Boutons During Motor Learning

Motor skill learning induces long-lasting synaptic plasticity at not only the inputs, such as dendritic spines1-4, but also at the outputs to the striatum of motor cortical neurons5,6. However, very little is known about the activity and structural plasticity of corticostriatal axons during learning in the adult brain. Here, we used longitudinal in vivo two-photon imaging to monitor the activity and structure of thousands of corticostriatal axonal boutons in the dorsolateral striatum in awake mice. We found that learning a new motor skill induces dynamic regulation of axonal boutons. The activities of motor corticostriatal axonal boutons exhibited selectivity for rewarded movements (RM) and un-rewarded movements (UM). Strikingly, boutons on the same axonal branches showed diverse responses during behavior. Motor learning significantly increased the fraction of RM boutons and reduced the heterogeneity of bouton activities. Moreover, motor learning-induced profound structural dynamism in boutons. By combining structural and functional imaging, we identified that newly formed axonal boutons are more likely to exhibit selectivity for RM and are stabilized during motor learning, while UM boutons are selectively eliminated. Our results highlight a novel form of plasticity at corticostriatal axons induced by motor learning, indicating that motor corticostriatal axonal boutons undergo dynamic reorganization that facilitates the acquisition and execution of motor skills.

Phase Delays between Mouse Globus Pallidus Neurons Entrained by Common Oscillatory Drive Arise from Their Intrinsic Properties, Not Their Coupling

A hallmark of Parkinson's disease is the appearance of correlated oscillatory discharge throughout the cortico-basal ganglia (BG) circuits. In the primate globus pallidus (GP), where the discharge of GP neurons is normally uncorrelated, pairs of GP neurons exhibit oscillatory spike correlations with a broad distribution of pairwise phase delays in experimental parkinsonism. The transition to oscillatory correlations is thought to indicate the collapse of the normally segregated information channels traversing the BG. The large phase delays are thought to reflect pathological changes in synaptic connectivity in the BG. Here we study the structure and phase delays of spike correlations measured from neurons in the mouse external GP (GPe) subjected to identical 1-100 Hz sinusoidal drive but recorded in separate experiments. First, we found that spectral modes of a GPe neuron's empirical instantaneous phase response curve (iPRC) elucidate at what phases of the oscillatory drive the GPe neuron locks when it is entrained and the distribution of phases at which it spikes when it is not. Then, we show that in this case the pairwise spike cross-correlation equals the cross-correlation function of these spike phase distributions. Finally, we show that the distribution of GPe phase delays arises from the diversity of iPRCs and is broadened when the neurons become entrained. Modeling GPe networks with realistic intranuclear connectivity demonstrates that the connectivity decorrelates GPe neurons without affecting phase delays. Thus, common oscillatory input gives rise to GPe correlations whose structure and pairwise phase delays reflect their intrinsic properties captured by their iPRCs.

Effective Regulation of Auditory Processing by Parvalbumin Interneurons in the Tail of the Striatum

Parvalbumin (PV) interneurons in the auditory cortex (AC) play a crucial role in shaping auditory processing, including receptive field formation, temporal precision enhancement, and gain regulation. PV interneurons are also the primary inhibitory neurons in the tail of the striatum (TS), which is one of the major descending brain regions in the auditory nervous system. However, the specific roles of TS-PV interneurons in auditory processing remain elusive. In this study, morphological and slice recording experiments in both male and female mice revealed that TS-PV interneurons, compared with AC-PV interneurons, were present in fewer numbers but exhibited longer projection distances, which enabled them to provide sufficient inhibitory inputs to spiny projection neurons (SPNs). Furthermore, TS-PV interneurons received dense auditory input from both the AC and medial geniculate body (MGB), particularly from the MGB, which rendered their auditory responses comparable to those of AC-PV interneurons. Optogenetic manipulation experiments demonstrated that TS-PV interneurons were capable of bidirectionally regulating the auditory responses of SPNs. Our findings suggest that PV interneurons can effectively modulate auditory processing in the TS and may play a critical role in auditory-related behaviors.

Striatal Neurons Are Recruited Dynamically into Collective Representations of Self-Initiated and Learned Actions in Freely Moving Mice

Striatal spiny projection neurons are hyperpolarized-at-rest (HaR) and driven to action potential threshold by a small number of powerful inputs-an input-output configuration that is detrimental to response reliability. Because the striatum is important for habitual behaviors and goal-directed learning, we conducted a microendoscopic imaging in freely moving mice that express a genetically encoded Ca2+ indicator sparsely in striatal HaR neurons to evaluate their response reliability during self-initiated movements and operant conditioning. The sparse expression was critical for longitudinal studies of response reliability, and for studying correlations among HaR neurons while minimizing spurious correlations arising from contamination by the background signal. We found that HaR neurons are recruited dynamically into action representation, with distinct neuronal subsets being engaged in a moment-by-moment fashion. While individual neurons respond with little reliability, the population response remained stable across days. Moreover, we found evidence for the temporal coupling between neuronal subsets during conditioned (but not innate) behaviors.

Mapping Dysfunctional Circuits in the Frontal Cortex Using Deep Brain Stimulation

Frontal circuits play a critical role in motor, cognitive, and affective processing - and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)function remains largely elusive. Here, we study 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregate the frontal cortex into circuits that became dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to rostral, ranging from interconnections with sensorimotor cortices in dystonia, with the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairment in the human brain.

Enhancing reinforcement learning models by including direct and indirect pathways improves performance on striatal dependent tasks

A major advance in understanding learning behavior stems from experiments showing that reward learning requires dopamine inputs to striatal neurons and arises from synaptic plasticity of cortico-striatal synapses. Numerous reinforcement learning models mimic this dopamine-dependent synaptic plasticity by using the reward prediction error, which resembles dopamine neuron firing, to learn the best action in response to a set of cues. Though these models can explain many facets of behavior, reproducing some types of goal-directed behavior, such as renewal and reversal, require additional model components. Here we present a reinforcement learning model, TD2Q, which better corresponds to the basal ganglia with two Q matrices, one representing direct pathway neurons (G) and another representing indirect pathway neurons (N). Unlike previous two-Q architectures, a novel and critical aspect of TD2Q is to update the G and N matrices utilizing the temporal difference reward prediction error. A best action is selected for N and G using a softmax with a reward-dependent adaptive exploration parameter, and then differences are resolved using a second selection step applied to the two action probabilities. The model is tested on a range of multi-step tasks including extinction, renewal, discrimination; switching reward probability learning; and sequence learning. Simulations show that TD2Q produces behaviors similar to rodents in choice and sequence learning tasks, and that use of the temporal difference reward prediction error is required to learn multi-step tasks. Blocking the update rule on the N matrix blocks discrimination learning, as observed experimentally. Performance in the sequence learning task is dramatically improved with two matrices. These results suggest that including additional aspects of basal ganglia physiology can improve the performance of reinforcement learning models, better reproduce animal behaviors, and provide insight as to the role of direct- and indirect-pathway striatal neurons.

The Mesencephalic Locomotor Region: Beyond Locomotor Control

The mesencephalic locomotor region (MLR) was discovered several decades ago in the cat. It was functionally defined based on the ability of low threshold electrical stimuli within a region comprising the cuneiform and pedunculopontine nucleus to evoke locomotion. Since then, similar regions have been found in diverse vertebrate species, including the lamprey, skate, rodent, pig, monkey, and human. The MLR, while often viewed under the lens of locomotion, is involved in diverse processes involving the autonomic nervous system, respiratory system, and the state-dependent activation of motor systems. This review will discuss the pedunculopontine nucleus and cuneiform nucleus that comprises the MLR and examine their respective connectomes from both an anatomical and functional angle. From a functional perspective, the MLR primes the cardiovascular and respiratory systems before the locomotor activity occurs. Inputs from a variety of higher structures, and direct outputs to the monoaminergic nuclei, allow the MLR to be able to respond appropriately to state-dependent locomotion. These state-dependent effects are roughly divided into escape and exploratory behavior, and the MLR also can reinforce the selection of these locomotor behaviors through projections to adjacent structures such as the periaqueductal gray or to limbic and cortical regions. Findings from the rat, mouse, pig, and cat will be discussed to highlight similarities and differences among diverse species.

Corticocortical innervation subtypes of layer 5 intratelencephalic cells in the murine secondary motor cortex

Feedback projections from the secondary motor cortex (M2) to the primary motor and sensory cortices are essential for behavior selection and sensory perception. Intratelencephalic (IT) cells in layer 5 (L5) contribute feedback projections to diverse cortical areas. Here we show that L5 IT cells participating in feedback connections to layer 1 (L1) exhibit distinct projection patterns, genetic profiles, and electrophysiological properties relative to other L5 IT cells. An analysis of the MouseLight database found that L5 IT cells preferentially targeting L1 project broadly to more cortical regions, including the perirhinal and auditory cortices, and innervate a larger volume of striatum than the other L5 IT cells. We found experimentally that in upper L5 (L5a), ER81 (ETV1) was found more often in L1-preferring IT cells, and in IT cells projecting to perirhinal/auditory regions than those projecting to primary motor or somatosensory regions. The perirhinal region-projecting L5a IT cells were synaptically connected to each other and displayed lower input resistance than contra-M2 projecting IT cells including L1-preferring and nonpreferring cells. Our findings suggest that M2-L5a IT L1-preferring cells exhibit stronger ER81 expression and broader cortical/striatal projection fields than do cells that do not preferentially target L1.

Cell-Type-Specific Adaptions in Striatal Medium-Sized Spiny Neurons and Their Roles in Behavioral Responses to Drugs of Abuse

Drug addiction is defined as a compulsive pattern of drug-seeking- and taking- behavior, with recurrent episodes of abstinence and relapse, and a loss of control despite negative consequences. Addictive drugs promote reinforcement by increasing dopamine in the mesocorticolimbic system, which alters excitatory glutamate transmission within the reward circuitry, thereby hijacking reward processing. Within the reward circuitry, the striatum is a key target structure of drugs of abuse since it is at the crossroad of converging glutamate inputs from limbic, thalamic and cortical regions, encoding components of drug-associated stimuli and environment, and dopamine that mediates reward prediction error and incentive values. These signals are integrated by medium-sized spiny neurons (MSN), which receive glutamate and dopamine axons converging onto their dendritic spines. MSN primarily form two mostly distinct populations based on the expression of either DA-D1 (D1R) or DA-D2 (D2R) receptors. While a classical view is that the two MSN populations act in parallel, playing antagonistic functional roles, the picture seems much more complex. Herein, we review recent studies, based on the use of cell-type-specific manipulations, demonstrating that dopamine differentially modulates dendritic spine density and synapse formation, as well as glutamate transmission, at specific inputs projecting onto D1R-MSN and D2R-MSN to shape persistent pathological behavioral in response to drugs of abuse. We also discuss the identification of distinct molecular events underlying the detrimental interplay between dopamine and glutamate signaling in D1R-MSN and D2R-MSN and highlight the relevance of such cell-type-specific molecular studies for the development of innovative strategies with potential therapeutic value for addiction. Because drug addiction is highly prevalent in patients with other psychiatric disorders when compared to the general population, we last discuss the hypothesis that shared cellular and molecular adaptations within common circuits could explain the co-occurrence of addiction and depression. We will therefore conclude this review by examining how the nucleus accumbens (NAc) could constitute a key interface between addiction and depression.

Basal ganglia: From the bench to the bed

The basal ganglia (BG) encompass a set of archaic structures of the vertebrate brain that have evolved relatively little during the phylogenetic process. From an anatomic point of view, they are widely distributed throughout brain from the telencephalon to the mesencephalon. The fact that they have been preserved through evolution suggests that they may play a critical role in behavioral monitoring. Indeed, a line of evidence suggests that they are involved in the building of behavioral routines and habits that drive most of our activities in everyday life. In this article, we first examine the organization and physiology of the basal ganglia to explain their function in the control of behavior. Then, we show how disruption of the putamen, and to a lesser extent of the cerebellum, might lead to various dystonic syndromes that frequently arise during childhood.

Complete representation of action space and value in all dorsal striatal pathways

The dorsal striatum plays a central role in the selection, execution, and evaluation of actions. An emerging model attributes action selection to the matrix and evaluation to the striosome compartment. Here, we use large-scale cell-type-specific calcium imaging to determine the activity of striatal projection neurons (SPNs) during motor and decision behaviors in the three major outputs of the dorsomedial striatum: Oprm1⁺ striosome versus D1⁺ direct and A2A⁺ indirect pathway SPNs. We find that Oprm1⁺ SPNs show complex tunings to simple movements and value-guided actions, which are conserved across many sessions in a single task but remap between contexts. During decision making, the SPN tuning profiles form a complete representation in which sequential SPN activity jointly encodes task progress and value. We propose that the three major output pathways in the dorsomedial striatum share a similarly complete representation of the entire action space, including task- and phase-specific signals of action value and choice.

What is dopamine doing in model-based reinforcement learning?

Experiments have implicated dopamine in model-based reinforcement learning (RL). These findings are unexpected as dopamine is thought to encode a reward prediction error (RPE), which is the key teaching signal in model-free RL. Here we examine two possible accounts for dopamine's involvement in model-based RL: the first that dopamine neurons carry a prediction error used to update a type of predictive state representation called a successor representation, the second that two well established aspects of dopaminergic activity, RPEs and surprise signals, can together explain dopamine's involvement in model-based RL.

Nucleus accumbens fast-spiking interneurons in motivational and addictive behaviors

The development of drug addiction is associated with functional adaptations within the reward circuitry, within which the nucleus accumbens (NAc) is anatomically positioned as an interface between motivational salience and behavioral output. The functional output of NAc is profoundly altered after exposure to drugs of abuse, and some of the functional changes continue to evolve during drug abstinence, contributing to numerous emotional and motivational alterations related drug taking, seeking, and relapse. As in most brain regions, the functional output of NAc is critically dependent on the dynamic interaction between excitation and inhibition. One of the most prominent sources of inhibition within the NAc arises from fast-spiking interneurons (FSIs). Each NAc FSI innervates hundreds of principal neurons, and orchestrates population activity through its powerful and sustained feedforward inhibition. While the role of NAc FSIs in the context of drug addiction remains poorly understood, emerging evidence suggests that FSIs and FSI-mediated local circuits are key targets for drugs of abuse to tilt the functional output of NAc toward a motivational state favoring drug seeking and relapse. In this review, we discuss recent findings and our conceptualization about NAc FSI-mediated regulation of motivated and cocaine-induced behaviors. We hope that the conceptual framework proposed in this review may provide a useful guidance for ongoing and future studies to determine how FSIs influence the function of NAc and related reward circuits, ultimately leading to addictive behaviors.

Spatiotemporal transformations for gaze control

Sensorimotor transformations require spatiotemporal coordination of signals, that is, through both time and space. For example, the gaze control system employs signals that are time-locked to various sensorimotor events, but the spatial content of these signals is difficult to assess during ordinary gaze shifts. In this review, we describe the various models and methods that have been devised to test this question, and their limitations. We then describe a new method that can (a) simultaneously test between all of these models during natural, head-unrestrained conditions, and (b) track the evolving spatial continuum from target (T) to future gaze coding (G, including errors) through time. We then summarize some applications of this technique, comparing spatiotemporal coding in the primate frontal eye field (FEF) and superior colliculus (SC). The results confirm that these areas preferentially encode eye-centered, effector-independent parameters, and show-for the first time in ordinary gaze shifts-a spatial transformation between visual and motor responses from T to G coding. We introduce a new set of spatial models (T-G continuum) that revealed task-dependent timing of this transformation: progressive during a memory delay between vision and action, and almost immediate without such a delay. We synthesize the results from our studies and supplement it with previous knowledge of anatomy and physiology to propose a conceptual model where cumulative transformation noise is realized as inaccuracies in gaze behavior. We conclude that the spatiotemporal transformation for gaze is both local (observed within and across neurons in a given area) and distributed (with common signals shared across remote but interconnected structures).

Activation of the mGlu1 metabotropic glutamate receptor has antipsychotic-like effects and is required for efficacy of M4 muscarinic receptor allosteric modulators

Recent clinical and preclinical studies suggest that selective activators of the M₄ muscarinic acetylcholine receptor have potential as a novel treatment for schizophrenia. M₄ activation inhibits striatal dopamine release by mobilizing endocannabinoids, providing a mechanism for local effects on dopamine signaling in the striatum but not in extrastriatal areas. G protein-coupled receptors (GPCRs) typically induce endocannabinoid release through activation of Gα_q/11-type G proteins whereas M₄ transduction occurs through Gα_i/o-type G proteins. We now report that the ability of M₄ to inhibit dopamine release and induce antipsychotic-like effects in animal models is dependent on co-activation of the Gα_q/11-coupled mGlu₁ subtype of metabotropic glutamate (mGlu) receptor. This is especially interesting in light of recent findings that multiple loss of function single nucleotide polymorphisms (SNPs) in the human gene encoding mGlu₁ (GRM1) are associated with schizophrenia, and points to GRM1/mGlu₁ as a gene within the "druggable genome" that could be targeted for the treatment of schizophrenia. Herein, we report that potentiation of mGlu₁ signaling following thalamo-striatal stimulation is sufficient to inhibit striatal dopamine release, and that a novel mGlu₁ positive allosteric modulator (PAM) exerts robust antipsychotic-like effects through an endocannabinoid-dependent mechanism. However, unlike M₄, mGlu₁ does not directly inhibit dopamine D₁ receptor signaling and does not reduce motivational responding. Taken together, these findings highlight a novel mechanism of cross talk between mGlu₁ and M₄ and demonstrate that highly selective mGlu₁ PAMs may provide a novel strategy for the treatment of positive symptoms associated with schizophrenia.

Neural reinforcement: re-entering and refining neural dynamics leading to desirable outcomes

How do organisms learn to do again, on-demand, a behavior that led to a desirable outcome? Dopamine-dependent cortico-striatal plasticity provides a framework for learning behavior's value, but it is less clear how it enables the brain to re-enter desired behaviors and refine them over time. Reinforcing behavior is achieved by re-entering and refining the neural patterns that produce it. We review studies using brain-machine interfaces which reveal that reinforcing cortical population activity requires cortico-basal ganglia circuits. Then, we propose a formal framework for how reinforcement in cortico-basal ganglia circuits acts on the neural dynamics of cortical populations. We propose two parallel mechanisms: i) fast reinforcement which selects the inputs that permit the re-entrance of the particular cortical population dynamics which naturally produced the desired behavior, and ii) slower reinforcement which leads to refinement of cortical population dynamics and more reliable production of neural trajectories driving skillful behavior on-demand.

Differential Striatal Axonal Arborizations of the Intratelencephalic and Pyramidal-Tract Neurons: Analysis of the Data in the MouseLight Database

There exist two major types of striatum-targeting neocortical neurons, specifically, intratelencephalic (IT) neurons and pyramidal-tract (PT) neurons. Regarding their striatal projections, it was once suggested that IT axons are extended whereas PT axons are primarily focal. However, subsequent study with an increased number of well-stained extended axons concluded that such an apparent distinction was spurious due to limited sample size. Recent work using genetically labeled neurons reintroduced the differential spatial extent of the striatal projections of IT and PT neurons through population-level analyses, complemented by observations of single axons. However, quantitative IT vs. PT comparison of a large number of axons remained to be conducted. We analyzed the data of axonal end-points of 161 IT neurons and 33 PT neurons in the MouseLight database (http://ml-neuronbrowser.janelia.org/). The number of axonal end-points in the ipsilateral striatum exhibits roughly monotonically decreasing distributions in both neuron types. Excluding neurons with no ipsilateral end-point, the distributions of the logarithm of the number of ipsilateral end-points are considerably overlapped between IT and PT neurons, although the proportion of neurons having more than 50 ipsilateral end-points is somewhat larger in IT neurons than in PT neurons. Looking at more details, among IT subpopulations in the secondary motor area (MOs), layer 5 neurons and bilateral striatum-targeting layer 2/3 neurons, but not contralateral striatum-non-targeting layer 2/3 neurons, have a larger number of ipsilateral end-points than MOs PT neurons. We also found that IT ipsilateral striatal axonal end-points are on average more widely distributed than PT end-points, especially in the medial-lateral direction. These results indicate that IT and PT striatal axons differ in the frequencies and spatial extent of end-points while there are wide varieties within each neuron type.

Dystonia and dopamine: From phenomenology to pathophysiology

A line of evidence suggests that the pathophysiology of dystonia involves the striatum, whose activity is modulated among other neurotransmitters, by the dopaminergic system. However, the link between dystonia and dopamine appears complex and remains unclear. Here, we propose a physiological approach to investigate the clinical and experimental data supporting a role of the dopaminergic system in the pathophysiology of dystonic syndromes. Because dystonia is a disorder of motor routines, we first focus on the role of dopamine and striatum in procedural learning. Second, we consider the phenomenology of dystonia from every angle in order to search for features giving food for thought regarding the pathophysiology of the disorder. Then, for each dystonic phenotype, we review, when available, the experimental and imaging data supporting a connection with the dopaminergic system. Finally, we propose a putative model in which the different phenotypes could be explained by changes in the balance between the direct and indirect striato-pallidal pathways, a process critically controlled by the level of dopamine within the striatum. Search strategy and selection criteria References for this article were identified through searches in PubMed with the search terms « dystonia », « dopamine", « striatum », « basal ganglia », « imaging data », « animal model », « procedural learning », « pathophysiology », and « plasticity » from 1998 until 2018. Articles were also identified through searches of the authors' own files. Only selected papers published in English were reviewed. The final reference list was generated on the basis of originality and relevance to the broad scope of this review.

Translating striatal activity from brain slice to whole animal neurophysiology: A guide for neuroscience research integrating diverse levels of analysis

An important goal of this review is highlighting research in neuroscience as examples of multilevel functional and anatomical analyses addressing basic science issues and applying results to the understanding of diverse disorders. The research of Dr. Michael Levine, a leader in neuroscience, exemplifies this approach by uncovering fundamental properties of basal ganglia function and translating these findings to clinical applications. The review focuses on neurophysiological research connecting results from in vitro and in vivo recordings. A second goal is to utilize these research connections to produce novel, accurate descriptions for corticostriatal processing involved in varied, complex functions. Medium spiny neurons in striatum act as integrators combining input with baseline activity creating motivational "events." Basic research on corticostriatal synapses is described and links developed to issues with clinical relevance such as inhibitory gating, self-injurious behavior, and relative reward valuation. Work is highlighted on dopamine-glutamate interactions. Individual medium spiny neurons express both D₁ and D₂ receptors and encode information in a bivalent manner depending upon the mix of receptors involved. Current work on neurophysiology of reward processing has taken advantage of these basic approaches at the cellular and molecular levels. Future directions in studying physiology of reward processing and action sequencing could profit by incorporating the divergent ways dopamine modulates incoming neurochemical signals. Primary investigators leading research teams should mirror Mike Levine's efforts in "climbing the mountain" of scientific inquiry by performing analyses at different levels of inquiry, integrating the findings, and building comprehensive answers to problems unsolvable without this bold approach.

Synchronicity: The Role of Midbrain Dopamine in Whole-Brain Coordination

Midbrain dopamine seems to play an outsized role in motivated behavior and learning. Widely associated with mediating reward-related behavior, decision making, and learning, dopamine continues to generate controversies in the field. While many studies and theories focus on what dopamine cells encode, the question of how the midbrain derives the information it encodes is poorly understood and comparatively less addressed. Recent anatomical studies suggest greater diversity and complexity of afferent inputs than previously appreciated, requiring rethinking of prior models. Here, we elaborate a hypothesis that construes midbrain dopamine as implementing a Bayesian selector in which individual dopamine cells sample afferent activity across distributed brain substrates, comprising evidence to be evaluated on the extent to which stimuli in the on-going sensorimotor stream organizes distributed, parallel processing, reflecting implicit value. To effectively generate a temporally resolved phasic signal, a population of dopamine cells must exhibit synchronous activity. We argue that synchronous activity across a population of dopamine cells signals consensus across distributed afferent substrates, invigorating responding to recognized opportunities and facilitating further learning. In framing our hypothesis, we shift from the question of how value is computed to the broader question of how the brain achieves coordination across distributed, parallel processing. We posit the midbrain is part of an “axis of agency” in which the prefrontal cortex (PFC), basal ganglia (BGS), and midbrain form an axis mediating control, coordination, and consensus, respectively.

What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation

Deciding what to do and when to move is vital to our survival. Clinical and fundamental studies have identified basal ganglia circuits as critical for this process. The main input nucleus of the basal ganglia, the striatum, receives inputs from frontal, sensory, and motor cortices and interconnected thalamic areas that provide information about potential goals, context, and actions and directly or indirectly modulates basal ganglia outputs. The striatum also receives dopaminergic inputs that can signal reward prediction errors and also behavioral transitions and movement initiation. Here we review studies and models of how direct and indirect pathways can modulate basal ganglia outputs to facilitate movement initiation, and we discuss the role of cortical and dopaminergic inputs to the striatum in determining what to do and if and when to do it. Complex but exciting scenarios emerge that shed new light on how basal ganglia circuits modulate self-paced movement initiation.

Role of the striatum in incidental learning of sound categories

Humans are born as “universal listeners.” However, over the first year, infants’ perception is shaped by native speech categories. How do these categories naturally emerge without explicit training or overt feedback? Using fMRI, we examined the neural basis of incidental sound category learning as participants played a videogame in which sound category exemplars had functional utility in guiding videogame success. Even without explicit categorization of the sounds, participants learned functionally relevant sound categories that generalized to novel exemplars when exemplars had an organized distributional structure. Critically, the striatum was engaged and functionally connected to the auditory cortex during game play, and this activity and connectivity predicted the learning outcome. These findings elucidate the neural mechanism by which humans incidentally learn “real-world” categories.

Humans are born as “universal listeners” without a bias toward any particular language. However, over the first year of life, infants’ perception is shaped by learning native speech categories. Acoustically different sounds—such as the same word produced by different speakers—come to be treated as functionally equivalent. In natural environments, these categories often emerge incidentally without overt categorization or explicit feedback. However, the neural substrates of category learning have been investigated almost exclusively using overt categorization tasks with explicit feedback about categorization decisions. Here, we examined whether the striatum, previously implicated in category learning, contributes to incidental acquisition of sound categories. In the fMRI scanner, participants played a videogame in which sound category exemplars aligned with game actions and events, allowing sound categories to incidentally support successful game play. An experimental group heard nonspeech sound exemplars drawn from coherent category spaces, whereas a control group heard acoustically similar sounds drawn from a less structured space. Although the groups exhibited similar in-game performance, generalization of sound category learning and activation of the posterior striatum were significantly greater in the experimental than control group. Moreover, the experimental group showed brain–behavior relationships related to the generalization of all categories, while in the control group these relationships were restricted to the categories with structured sound distributions. Together, these results demonstrate that the striatum, through its interactions with the left superior temporal sulcus, contributes to incidental acquisition of sound category representations emerging from naturalistic learning environments.

Cholinergic modulation of striatal microcircuits

The purpose of this review is to bridge the gap between earlier literature on striatal cholinergic interneurons and mechanisms of microcircuit interaction demonstrated with the use of newly available tools. It is well known that the main source of the high level of acetylcholine in the striatum, compared to other brain regions, is the cholinergic interneurons. These interneurons provide an extensive local innervation that suggests they may be a key modulator of striatal microcircuits. Supporting this idea requires the consideration of functional properties of these interneurons, their influence on medium spiny neurons, other interneurons, and interactions with other synaptic regulators. Here, we underline the effects of intrastriatal and extrastriatal afferents onto cholinergic interneurons and discuss the activation of pre‐ and postsynaptic muscarinic and nicotinic receptors that participate in the modulation of intrastriatal neuronal interactions. We further address recent findings about corelease of other transmitters in cholinergic interneurons and actions of these interneurons in striosome and matrix compartments. In addition, we summarize recent evidence on acetylcholine‐mediated striatal synaptic plasticity and propose roles for cholinergic interneurons in normal striatal physiology. A short examination of their role in neurological disorders such as Parkinson's, Huntington's, and Tourette's pathologies and dystonia is also included.

Inhibition enhances spatially-specific calcium encoding of synaptic input patterns in a biologically constrained model

Synaptic plasticity, which underlies learning and memory, depends on calcium elevation in neurons, but the precise relationship between calcium and spatiotemporal patterns of synaptic inputs is unclear. Here, we develop a biologically realistic computational model of striatal spiny projection neurons with sophisticated calcium dynamics, based on data from rodents of both sexes, to investigate how spatiotemporally clustered and distributed excitatory and inhibitory inputs affect spine calcium. We demonstrate that coordinated excitatory synaptic inputs evoke enhanced calcium elevation specific to stimulated spines, with lower but physiologically relevant calcium elevation in nearby non-stimulated spines. Results further show a novel and important function of inhibition-to enhance the difference in calcium between stimulated and non-stimulated spines. These findings suggest that spine calcium dynamics encode synaptic input patterns and may serve as a signal for both stimulus-specific potentiation and heterosynaptic depression, maintaining balanced activity in a dendritic branch while inducing pattern-specific plasticity.

The Thalamostriatal Projections Contribute to the Initiation and Execution of a Sequence of Movements

One of the main inputs driving striatal activity is the thalamostriatal projection. While the hypothesis postulating that the different thalamostriatal projections contribute differentially to shape the functions of the striatum is largely accepted, existing technical limitations have hampered efforts to prove it. Here, through the use of electrophysiological recordings of antidromically photo-identified thalamostriatal neurons and the optogenetic inhibition of thalamostriatal terminals, we identify that the thalamostriatal projections from the parafascicular and the ventroposterior regions of the thalamus contribute to the smooth initiation and the appropriate execution of a sequence of movements. Our results support a model in which both thalamostriatal projections have specific contributions to the initiation and execution of sequences, highlighting the specific contribution of the ventroposterior thalamostriatal connection for the repetition of actions.

The Striatum Organizes 3D Behavior via Moment-to-Moment Action Selection

Many naturalistic behaviors are built from modular components that are expressed sequentially. Although striatal circuits have been implicated in action selection and implementation, the neural mechanisms that compose behavior in unrestrained animals are not well understood. Here, we record bulk and cellular neural activity in the direct and indirect pathways of dorsolateral striatum (DLS) as mice spontaneously express action sequences. These experiments reveal that DLS neurons systematically encode information about the identity and ordering of sub-second 3D behavioral motifs; this encoding is facilitated by fast-timescale decorrelations between the direct and indirect pathways. Furthermore, lesioning the DLS prevents appropriate sequence assembly during exploratory or odor-evoked behaviors. By characterizing naturalistic behavior at neural timescales, these experiments identify a code for elemental 3D pose dynamics built from complementary pathway dynamics, support a role for DLS in constructing meaningful behavioral sequences, and suggest models for how actions are sculpted over time.

A Proposed Circuit Computation in Basal Ganglia: History-Dependent Gain

In this Scientific Perspectives we first review the recent advances in our understanding of the functional architecture of basal ganglia circuits. Then we argue that these data can best be explained by a model in which basal ganglia act to control the gain of movement kinematics to shape performance based on prior experience, which we refer to as a history-dependent gain computation. Finally, we discuss how insights from the history-dependent gain model might translate from the bench to the bedside, primarily the implications for the design of adaptive deep brain stimulation. Thus, we explicate the key empirical and conceptual support for a normative, computational model with substantial explanatory power for the broad role of basal ganglia circuits in health and disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Dopamine, Inference, and Uncertainty

The hypothesis that the phasic dopamine response reports a reward prediction error has become deeply entrenched. However, dopamine neurons exhibit several notable deviations from this hypothesis. A coherent explanation for these deviations can be obtained by analyzing the dopamine response in terms of Bayesian reinforcement learning. The key idea is that prediction errors are modulated by probabilistic beliefs about the relationship between cues and outcomes, updated through Bayesian inference. This account can explain dopamine responses to inferred value in sensory preconditioning, the effects of cue preexposure (latent inhibition), and adaptive coding of prediction errors when rewards vary across orders of magnitude. We further postulate that orbitofrontal cortex transforms the stimulus representation through recurrent dynamics, such that a simple error-driven learning rule operating on the transformed representation can implement the Bayesian reinforcement learning update.

Predicting the response of striatal spiny neurons to sinusoidal input

Spike-timing effects of small-amplitude sinusoidal currents were measured in mouse striatal spiny neurons firing repetitively. Spike-timing reliability varied with the stimulus frequency. For frequencies near the cell's firing rate, the cells altered firing rate to match the stimulus and became phase locked to it. The stimulus phase of firing during lock depended on the stimulus frequency relative to the cell's unperturbed firing rate. Interspike intervals during sinusoidal stimulation were predicted using an iterative map constructed from the cells' phase-resetting curve. Variability of interspike intervals was reduced by stimulation at all frequencies higher than about half the cell's unperturbed rate, and interspike intervals were accurately predicted by the map. Long sequences of spike times were predicted by iterating on the map. The accuracy of that prediction varied with frequency. Spike time predictability was highest near and during phase lock. The map predicted the phase of firing on the input and its dependence on stimulus frequency. Prediction errors, when they occurred, were of two kinds: unpredicted variation in interspike interval from intrinsic cell noise and accumulation of prediction errors from previous interspike intervals. Each type of prediction error arose from a different mechanism, and their impact was also predicted from the phase model. When two oscillatory input currents were presented simultaneously, striatal neurons responded selectively to only one of them, the one closest in frequency to the cell's unperturbed firing rate. Their spike times encoded the frequency and phase of that single oscillatory input.NEW & NOTEWORTHY During repetitive firing, the timing of action potentials is determined by the interaction between the input and voltage-sensitive currents throughout the interspike interval. This interaction is encapsulated in the neuron's phase-resetting curve. The phase-resetting curve predicted spike timing to small sinusoidal currents over a wide range of stimulus frequencies. Firing patterns were most sensitive to oscillatory components near the cell's own firing rate, even in the presence of noise and other inputs.

Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations

Network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease. The striatum, the main input nucleus of the basal ganglia, receives massive glutamatergic inputs from the cortex and is highly susceptible to external oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. Using a network model of the striatum and corticostriatal projections, we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Here, we propose that fast-spiking interneurons can perform an important role in transferring cortical oscillations to the striatum especially to those medium spiny neurons that are not directly driven by the cortical oscillations. We show how the activity levels of different populations, the strengths of different inhibitory synapses, degree of outgoing projections of striatal cells, ongoing activity and synchronicity of inputs can influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is most efficient, if conveyed via the fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.

A Feedforward Inhibitory Circuit Mediated by CB1-Expressing Fast-Spiking Interneurons in the Nucleus Accumbens

The nucleus accumbens (NAc) gates motivated behaviors through the functional output of principle medium spiny neurons (MSNs), whereas dysfunctional output of NAc MSNs contributes to a variety of psychiatric disorders. Fast-spiking interneurons (FSIs) are sparsely distributed throughout the NAc, forming local feedforward inhibitory circuits. It remains elusive how FSI-based feedforward circuits regulate the output of NAc MSNs. Here, we investigated a distinct subpopulation of NAc FSIs that express the cannabinoid receptor type-1 (CB1). Using a combination of paired electrophysiological recordings and pharmacological approaches, we characterized and compared feedforward inhibition of NAc MSNs from CB1⁺ FSIs and lateral inhibition from recurrent MSN collaterals. We observed that CB1⁺ FSIs exerted robust inhibitory control over a large percentage of nearby MSNs in contrast to local MSN collaterals that provided only sparse and weak inhibitory input to their neighboring MSNs. Furthermore, CB1⁺ FSI-mediated feedforward inhibition was preferentially suppressed by endocannabinoid (eCB) signaling, whereas MSN-mediated lateral inhibition was unaffected. Finally, we demonstrated that CB1⁺ FSI synapses onto MSNs are capable of undergoing experience-dependent long-term depression in a voltage- and eCB-dependent manner. These findings demonstrated that CB1⁺ FSIs are a major source of local inhibitory control of MSNs and a critical component of the feedforward inhibitory circuits regulating the output of the NAc.

A Low-Correlation Resting State of the Striatum during Cortical Avalanches and Its Role in Movement Suppression

During quiet resting behavior, involuntary movements are suppressed. Such movement control is attributed to cortico-basal ganglia loops, yet population dynamics within these loops during resting and their relation to involuntary movements are not well characterized. Here, we show by recording cortical and striatal ongoing population activity in awake rats during quiet resting that intrastriatal inhibition maintains a low-correlation striatal resting state in the presence of cortical neuronal avalanches. Involuntary movements arise from disturbed striatal resting activity through two different population dynamics. Nonselectively reducing intrastriatal γ-aminobutyric acid (GABA) receptor-A inhibition synchronizes striatal dynamics, leading to involuntary movements at low rate. In contrast, reducing striatal interneuron (IN)-mediated inhibition maintains decorrelation and induces intermittent involuntary movements at high rate. This latter scenario was highly effective in modulating cortical dynamics at a subsecond timescale. To distinguish intrastriatal processing from loop dynamics, cortex-striatum-midbrain cultures, which lack feedback to cortex, were used. Cortical avalanches in vitro were accompanied by low-correlated resting activity in the striatum and nonselective reduction in striatal inhibition synchronized striatal neurons similar to in vivo. Importantly, reduction of inhibition from striatal INs maintained low correlations in the striatum while reorganizing functional connectivities among striatal neurons. Our results demonstrate the importance of two major striatal microcircuits in distinctly regulating striatal and cortical resting state dynamics. These findings suggest that specific functional connectivities of the striatum that are maintained by local inhibition are important in movement control.

Why don’t neuronal “avalanches” in resting-state cortex cause involuntary movements? This study shows that a low-correlation striatal resting state suppresses such movements and explores mechanisms that disrupt this inhibition.

Even in the absence of apparent motor output, the brain produces a rich repertoire of neuronal activity patterns known as “resting state” activity. In the outer layer of the cortex, resting state patterns emerge as neuronal avalanches, precisely scale-invariant spatiotemporal bursts that often engage large populations of neurons. Little is known about how the brain suppresses involuntary movements during such activity. Here, we show that the striatum, which is part of the cortex-basal ganglia loop, maintains a low-correlation state during resting activity. By using a combination of in vivo and in vitro approaches with pharmacological manipulations, we demonstrate that the precise configuration of this low-correlation state effectively contributes to involuntary movements. Nonselective blockade of intra-striatal inhibition abolished the low-correlation striatal resting state, barely affected cortical avalanches, and led to involuntary movements at low rate. In contrast, selectively reducing striatal interneuron inhibition strongly affected cortical avalanches and triggered involuntary movements at high rate while maintaining a relatively decorrelated striatal resting state. Our results demonstrate the importance of different inhibitory striatal circuits in the suppression of involuntary movements and suggest that the precise spatiotemporal configuration of striatal activity plays an active role in the regulation of cortical resting state activity and motor control.

The functional logic of corticostriatal connections

Unidirectional connections from the cortex to the matrix of the corpus striatum initiate the cortico-basal ganglia (BG)-thalamocortical loop, thought to be important in momentary action selection and in longer-term fine tuning of behavioural repertoire; a discrete set of striatal compartments, striosomes, has the complementary role of registering or anticipating reward that shapes corticostriatal plasticity. Re-entrant signals traversing the cortico-BG loop impact predominantly frontal cortices, conveyed through topographically ordered output channels; by contrast, striatal input signals originate from a far broader span of cortex, and are far more divergent in their termination. The term 'disclosed loop' is introduced to describe this organisation: a closed circuit that is open to outside influence at the initial stage of cortical input. The closed circuit component of corticostriatal afferents is newly dubbed 'operative', as it is proposed to establish the bid for action selection on the part of an incipient cortical action plan; the broader set of converging corticostriatal afferents is described as contextual. A corollary of this proposal is that every unit of the striatal volume, including the long, C-shaped tail of the caudate nucleus, should receive a mandatory component of operative input, and hence include at least one area of BG-recipient cortex amongst the sources of its corticostriatal afferents. Individual operative afferents contact twin classes of GABAergic striatal projection neuron (SPN), distinguished by their neurochemical character, and onward circuitry. This is the basis of the classic direct and indirect pathway model of the cortico-BG loop. Each pathway utilises a serial chain of inhibition, with two such links, or three, providing positive and negative feedback, respectively. Operative co-activation of direct and indirect SPNs is, therefore, pictured to simultaneously promote action, and to restrain it. The balance of this rival activity is determined by the contextual inputs, which summarise the external and internal sensory environment, and the state of ongoing behavioural priorities. Notably, the distributed sources of contextual convergence upon a striatal locus mirror the transcortical network harnessed by the origin of the operative input to that locus, thereby capturing a similar set of contingencies relevant to determining action. The disclosed loop formulation of corticostriatal and subsequent BG loop circuitry, as advanced here, refines the operating rationale of the classic model and allows the integration of more recent anatomical and physiological data, some of which can appear at variance with the classic model. Equally, it provides a lucid functional context for continuing cellular studies of SPN biophysics and mechanisms of synaptic plasticity.

In vivo two-photon imaging of striatal neuronal circuits in mice

Imaging studies of the subcortical striatum in vivo have been technically challenging despite its functional importance in movement control and procedural learning. Here, we report a method for imaging striatal neuronal circuits in mice in vivo using two-photon microscopy. Cell bodies and intermingled dendrites of GABAergic neurons labeled with fluorescent proteins were imaged in the dorsal striatum through an imaging window implanted in the overlying cortex. This technique could be highly useful for studying the structure and function of striatal networks at cellular and subcellular resolutions in normal mice, as well as in mouse models of neurological disorders.

Neuronal activity in dorsomedial and dorsolateral striatum under the requirement for temporal credit assignment

To investigate neural processes underlying temporal credit assignment in the striatum, we recorded neuronal activity in the dorsomedial and dorsolateral striatum (DMS and DLS, respectively) of rats performing a dynamic foraging task in which a choice has to be remembered until its outcome is revealed for correct credit assignment. Choice signals appeared sequentially, initially in the DMS and then in the DLS, and they were combined with action value and reward signals in the DLS when choice outcome was revealed. Unlike in conventional dynamic foraging tasks, neural signals for chosen value were elevated in neither brain structure. These results suggest that dynamics of striatal neural signals related to evaluating choice outcome might differ drastically depending on the requirement for temporal credit assignment. In a behavioral context requiring temporal credit assignment, the DLS, but not the DMS, might be in charge of updating the value of chosen action by integrating choice, action value, and reward signals together.

Mutual Control of Cholinergic and Low-Threshold Spike Interneurons in the Striatum

The striatum is the largest nucleus of the basal ganglia and is crucially involved in action selection and reward processing. Cortical and thalamic inputs to the striatum are processed by local networks in which several classes of interneurons play an important, but still poorly understood role. Here we investigated the interactions between cholinergic and low-threshold spike (LTS) interneurons. LTS interneurons were hyperpolarized by co-application of muscarinic and nicotinic receptor antagonists (atropine and mecamylamine, respectively). Mecamylamine alone also caused hyperpolarizations, while atropine alone caused depolarizations and increased firing. LTS interneurons were also under control of tonic GABA, as application of the GABA_A receptor antagonist picrotoxin caused depolarizations and increased firing. Frequency of spontaneous GABAergic events in LTS interneurons was increased by co-application of atropine and mecamylamine or by atropine alone, but reduced by mecamylamine alone. In the presence of picrotoxin and tetrodotoxin (TTX), atropine and mecamylamine depolarized the LTS interneurons. We concluded that part of the excitatory effects of tonic acetylcholine (ACh) on LTS interneurons were due to cholinergic modulation of tonic GABA. We then studied the influence of LTS interneurons on cholinergic interneurons. Application of antagonists of somatostatin or neuropeptide Y (NPY) receptors or of an inhibitor of nitric oxide synthase (L-NAME) did not cause detectable effects in cholinergic interneurons. However, prolonged synchronized depolarizations of LTS interneurons (elicited with optogenetics tools) caused slow-onset depolarizations in cholinergic interneurons, which were often accompanied by strong action potential firing and were fully abolished by L-NAME. Thus, a mutual excitatory influence exists between LTS and cholinergic interneurons in the striatum, providing an opportunity for sustained activation of the two cell types. This activation may endow the striatal microcircuits with the ability to enter a high ACh/high nitric oxide regime when adequately triggered by external excitatory stimuli to these interneurons.

Transition from Target to Gaze Coding in Primate Frontal Eye Field during Memory Delay and Memory-Motor Transformation

The frontal eye fields (FEFs) participate in both working memory and sensorimotor transformations for saccades, but their role in integrating these functions through time remains unclear. Here, we tracked FEF spatial codes through time using a novel analytic method applied to the classic memory-delay saccade task. Three-dimensional recordings of head-unrestrained gaze shifts were made in two monkeys trained to make gaze shifts toward briefly flashed targets after a variable delay (450-1500 ms). A preliminary analysis of visual and motor response fields in 74 FEF neurons eliminated most potential models for spatial coding at the neuron population level, as in our previous study (Sajad et al., 2015). We then focused on the spatiotemporal transition from an eye-centered target code (T; preferred in the visual response) to an eye-centered intended gaze position code (G; preferred in the movement response) during the memory delay interval. We treated neural population codes as a continuous spatiotemporal variable by dividing the space spanning T and G into intermediate T–G models and dividing the task into discrete steps through time. We found that FEF delay activity, especially in visuomovement cells, progressively transitions from T through intermediate T–G codes that approach, but do not reach, G. This was followed by a final discrete transition from these intermediate T–G delay codes to a “pure” G code in movement cells without delay activity. These results demonstrate that FEF activity undergoes a series of sensory–memory–motor transformations, including a dynamically evolving spatial memory signal and an imperfect memory-to-motor transformation.

Untangling Cortico-Striatal Connectivity and Cross-Frequency Coupling in L-DOPA-Induced Dyskinesia

We simultaneously recorded local field potentials (LFPs) in the primary motor cortex and sensorimotor striatum in awake, freely behaving, 6-OHDA lesioned hemi-parkinsonian rats in order to study the features directly related to pathological states such as parkinsonian state and levodopa-induced dyskinesia. We analyzed the spectral characteristics of the obtained signals and observed that during dyskinesia the most prominent feature was a relative power increase in the high gamma frequency range at around 80 Hz, while for the parkinsonian state it was in the beta frequency range. Here we show that during both pathological states effective connectivity in terms of Granger causality is bidirectional with an accent on the striatal influence on the cortex. In the case of dyskinesia, we also found a high increase in effective connectivity at 80 Hz. In order to further understand the 80-Hz phenomenon, we performed cross-frequency analysis and observed characteristic patterns in the case of dyskinesia but not in the case of the parkinsonian state or the control state. We noted a large decrease in the modulation of the amplitude at 80 Hz by the phase of low frequency oscillations (up to ~10 Hz) across both structures in the case of dyskinesia. This may suggest a lack of coupling between the low frequency activity of the recorded network and the group of neurons active at ~80 Hz.

Striatal Circuits as a Common Node for Autism Pathophysiology

Autism spectrum disorders (ASD) are characterized by two seemingly unrelated symptom domains-deficits in social interactions and restrictive, repetitive patterns of behavioral output. Whether the diverse nature of ASD symptomatology represents distributed dysfunction of brain networks or abnormalities within specific neural circuits is unclear. Striatal dysfunction is postulated to underlie the repetitive motor behaviors seen in ASD, and neurological and brain-imaging studies have supported this assumption. However, as our appreciation of striatal function expands to include regulation of behavioral flexibility, motivational state, goal-directed learning, and attention, we consider whether alterations in striatal physiology are a central node mediating a range of autism-associated behaviors, including social and cognitive deficits that are hallmarks of the disease. This review investigates multiple genetic mouse models of ASD to explore whether abnormalities in striatal circuits constitute a common pathophysiological mechanism in the development of autism-related behaviors. Despite the heterogeneity of genetic insult investigated, numerous genetic ASD models display alterations in the structure and function of striatal circuits, as well as abnormal behaviors including repetitive grooming, stereotypic motor routines, deficits in social interaction and decision-making. Comparative analysis in rodents provides a unique opportunity to leverage growing genetic association data to reveal canonical neural circuits whose dysfunction directly contributes to discrete aspects of ASD symptomatology. The description of such circuits could provide both organizing principles for understanding the complex genetic etiology of ASD as well as novel treatment routes. Furthermore, this focus on striatal mechanisms of behavioral regulation may also prove useful for exploring the pathogenesis of other neuropsychiatric diseases, which display overlapping behavioral deficits with ASD.

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.

Distinct dynamics of ramping activity in the frontal cortex and caudate nucleus in monkeys

The prefronto-striatal network is involved in many cognitive functions, including perceptual decision making and reward-modulated behaviors. For well-trained subjects, neural responses frequently show similar patterns in the prefrontal cortex and striatum, making it difficult to tease apart distinct regional contributions. Here I show that, despite similar mean firing rate patterns, prefrontal and striatal responses differ in other temporal dynamics for both perceptual and reward-based tasks. Compared with simulation results, the temporal dynamics of prefrontal activity are consistent with an accumulation of sensory evidence used to solve a perceptual task but not with an accumulation of reward context-related information used for the development of a reward bias. In contrast, the dynamics of striatal activity is consistent with an accumulation of reward context-related information and with an accumulation of sensory evidence during early stimulus viewing. These results suggest that prefrontal and striatal neurons may have specialized functions for different tasks even with similar average activity.

Neuronal response impedance mechanism implementing cooperative networks with low firing rates and μs precision

Realizations of low firing rates in neural networks usually require globally balanced distributions among excitatory and inhibitory links, while feasibility of temporal coding is limited by neuronal millisecond precision. We show that cooperation, governing global network features, emerges through nodal properties, as opposed to link distributions. Using in vitro and in vivo experiments we demonstrate microsecond precision of neuronal response timings under low stimulation frequencies, whereas moderate frequencies result in a chaotic neuronal phase characterized by degraded precision. Above a critical stimulation frequency, which varies among neurons, response failures were found to emerge stochastically such that the neuron functions as a low pass filter, saturating the average inter-spike-interval. This intrinsic neuronal response impedance mechanism leads to cooperation on a network level, such that firing rates are suppressed toward the lowest neuronal critical frequency simultaneously with neuronal microsecond precision. Our findings open up opportunities of controlling global features of network dynamics through few nodes with extreme properties.

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.