Up and down states in striatal medium spiny neurons simultaneously recorded with spontaneous activity in fast-spiking interneurons studied in cortex-striatum-substantia nigra organotypic cultures

Ex vivo cortical circuits learn to predict and spontaneously replay temporal patterns

It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, that neural mechanisms are in place to allow neocortical circuits to autonomously learn the temporal structure of external stimuli and generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two temporal patterns using dual-optical stimulation. After 24-h of training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay of the learned temporal structure during spontaneous activity. Furthermore, some neurons exhibited timed prediction errors as revealed by larger responses when the expected stimulus was omitted compared to when it was present. Mechanistically our results indicate that learning relied in part on asymmetric connectivity between distinct neuronal ensembles with temporally-ordered activation. These findings further suggest that local cortical microcircuits are intrinsically capable of learning temporal information and generating predictions, and that the learning rules underlying temporal learning and spontaneous replay can be intrinsic to local cortical microcircuits and not necessarily dependent on top-down interactions.

Temporal dynamics of neocortical development in organotypic mouse brain cultures: a comprehensive analysis

Murine organotypic brain slice cultures have been widely used in neuroscientific research and are offering the opportunity to study neuronal function under normal and disease conditions. Despite the broad application, the mechanisms governing the maturation of immature cortical circuits in vitro are not well understood. In this study, we present a detailed investigation into the development of the neocortex in vitro. Using a holistic approach, we studied organotypic whole hemisphere brain slice cultures from postnatal mice and tracked the development of the somatosensory area over a 5-wk period. Our analysis revealed the maturation of passive and active intrinsic properties of pyramidal cells together with their morphology, closely resembling in vivo development. Detailed multielectrode array (MEA) electrophysiological assessments and RNA expression profiling demonstrated stable network properties by 2 wk in culture, followed by the transition of spontaneous activity toward more complex patterns including high-frequency oscillations. However, culturing weeks 4 and 5 exhibited increased variability and initial signs of neuronal loss, highlighting the importance of considering developmental stages in experimental design. This comprehensive characterization is vital for understanding the temporal dynamics of the neocortical development in vitro, with implications for neuroscientific research methodologies, particularly in the investigation of diseases such as epilepsy and other neurodevelopmental disorders.NEW & NOTEWORTHY The development of the mouse neocortex in vitro mimics the in vivo development. Mouse brain cultures can serve as a model system for cortical development for the first 2 wk in vitro and as a model system for the adult cortex from 2 to 4 wk in vitro. Mouse organotypic brain slice cultures develop high-frequency network oscillations at γ frequency after 2 wk in vitro. Mouse brain cultures exhibit increased heterogeneity and variability after 4 wk in culture.

A Basal Ganglia model for understanding working memory functions in healthy and Parkinson's conditions

Working memory (WM) is considered as the scratchpad for reading, writing, and processing information necessary to perform cognitive tasks. The Basal Ganglia (BG) and Prefrontal Cortex are two important parts of the brain that are involved in WM functions, and both structures receive projections from dopaminergic nuclei. In this modelling study, we specifically focus on modelling the WM functions of the BG, the WM deficits in Parkinson's disease (PD) conditions, and the impact of dopamine deficiency on different kinds of WM functions. Though there are many experimental and modelling studies of WM properties, there is a paucity of models of the BG that provide insights into the contributions of the BG in WM functions. The proposed model of BG uses bistable flip-flop neurons to model striatal up-down neurons, a network of nonlinear oscillators to model the oscillations of the Indirect Pathway of BG and race-model for action selection. Five different WM tasks are used to demonstrate the generalisation ability of the proposed model. Experimental data from the four tasks are compared with model performance in both control and PD conditions. The model is extended to predict the response time of subjects and in the PD version of the model, the effect of dopaminergic medication on WM performance is also simulated. The proposed model of BG is a unified model that can explain the WM functions of the BG over a wide variety of tasks in both normal and PD conditions, and can be used to understand why specific WM functions are impaired whereas others remain intact in PD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-10056-y.

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

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

Highlights

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

eTOC

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

Ex Vivo Cortical Circuits Learn to Predict and Spontaneously Replay Temporal Patterns

It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, that neural mechanisms are in place to allow neocortical circuits to autonomously learn the temporal structure of external stimuli and generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two specific temporal patterns using dual-optical stimulation. After 24-hours of training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay of the learned temporal structure during spontaneous activity. Furthermore, some neurons exhibited timed prediction errors. Mechanistically our results indicate that learning relied in part on asymmetric connectivity between distinct neuronal ensembles with temporally-ordered activation. These findings further suggest that local cortical microcircuits are intrinsically capable of learning temporal information and generating predictions, and that the learning rules underlying temporal learning and spontaneous replay can be intrinsic to local cortical microcircuits and not necessarily dependent on top-down interactions.

Neuronal ensembles: Building blocks of neural circuits

Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.

Cell-Type Specific Connectivity of Whisker-Related Sensory and Motor Cortical Input to Dorsal Striatum

The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in their connection strength with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS and, as a result, exert distinct influences on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution of striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1 in male and female mice and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex vivo patch clamp electrophysiology. We found that M1 and S1 dually innervate SPNs and FSIs; however, there is a consistent bias towards the M1 input in SPNs that is not found in FSIs. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPN and FSI dendrites. Notably, closely localized M1 and S1 clusters of inputs were more prevalent in SPNs than FSIs, suggesting that cortical inputs are integrated through cell-type specific mechanisms. Our results suggest that the stronger functional connectivity from M1 to SPNs compared to S1, as previously observed, is due to a higher quantity of synaptic inputs. Our results have implications for how sensorimotor integration is performed in the striatum through cell-specific differences in corticostriatal connections.

Cell-Type Specific Connectivity of Whisker-Related Sensory and Motor Cortical Input to Dorsal Striatum

The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and is considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in the strength of their connections with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS, and as a result exert an opposing influence on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution onto striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1, and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex-vivo patch-clamp electrophysiology. We found that SPNs are less innervated by S1 compared to M1, but FSIs receive a similar number of inputs from both M1 and S1. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPNs and FSIs. Notably, clusters of inputs were prevalent in SPNs but not FSIs. Our results suggest that SPNs have stronger functional connectivity to M1 compared to S1 due to a higher density of synaptic inputs. The clustering of M1 and S1 inputs onto SPNs but not FSIs suggest that cortical inputs are integrated through cell-type specific mechanisms and more generally have implications for how sensorimotor integration is performed in the striatum.

Significance Statement

The dorsolateral striatum (DLS) is a key brain area involved in sensorimotor integration due to its dense innervation by the primary motor (M1) and sensory cortex (S1). However, the quantity and anatomical distribution of these inputs to the striatal cell population has not been well characterized. In this study we demonstrate that corticostriatal projections from M1 and S1 differentially innervate spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS. S1 inputs innervate SPNs less than M1 and are likely to form synaptic clusters in SPNs but not in FSIs. These findings suggest that sensorimotor integration is partly achieved by differences in the synaptic organization of corticostriatal inputs to local striatal microcircuits.

UBE3A expression during early postnatal brain development is required for proper dorsomedial striatal maturation

Angelman syndrome (AS) is a severe neurodevelopmental disorder (NDD) caused by loss of functional ubiquitin protein ligase E3A (UBE3A). Previous studies showed that UBE3A plays an important role in the first postnatal weeks of mouse brain development, but its precise role is unknown. Since impaired striatal maturation has been implicated in several mouse models for NDDs, we studied the importance of UBE3A in striatal maturation. We used inducible Ube3a mouse models to investigate the maturation of medium spiny neurons (MSNs) from dorsomedial striatum. MSNs of mutant mice matured properly till postnatal day 15 (P15) but remained hyperexcitable with fewer excitatory synaptic events at later ages, indicative of stalled striatal maturation in Ube3a mice. Reinstatement of UBE3A expression at P21 fully restored MSN excitability but only partially restored synaptic transmission and the operant conditioning behavioral phenotype. Gene reinstatement at P70 failed to rescue both electrophysiological and behavioral phenotypes. In contrast, deletion of Ube3a after normal brain development did not result in these electrophysiological and behavioral phenotypes. This study emphasizes the role of UBE3A in striatal maturation and the importance of early postnatal reinstatement of UBE3A expression to obtain a full rescue of behavioral phenotypes associated with striatal function in AS.

Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Preserved Motility after Neonatal Dopaminergic Lesion Relates to Hyperexcitability of Direct Pathway Medium Spiny Neurons

In Parkinson's disease patients and rodent models, dopaminergic neuron loss (DAN) results in severe motor disabilities. In contrast, general motility is preserved after early postnatal DAN loss in rodents. Here we used mice of both sexes to show that the preserved motility observed after early DAN loss depends on functional changes taking place in medium spiny neurons (MSN) of the dorsomedial striatum (DMS) that belong to the direct pathway (dMSN). Previous animal model studies showed that adult loss of dopaminergic input depresses dMSN response to cortical input, which likely contributes to Parkinson's disease motor impairments. However, the response of DMS-dMSN to their preferred medial PFC input is preserved after neonatal DAN loss as shown by in vivo studies. Moreover, their response to inputs from adjacent cortical areas is increased, resulting in reduced cortical inputs selectivity. Additional ex vivo studies show that membrane excitability increases in dMSN. Furthermore, chemogenetic inhibition of DMS-dMSN has a more marked inhibitory effect on general motility in lesioned mice than in their control littermates, indicating that expression of normal levels of locomotion and general motility depend on dMSN activity after early DAN loss. Contrastingly, DMS-dMSN inhibition did not ameliorate a characteristic phenotype of the DAN-lesioned animals in a marble burying task demanding higher behavioral control. Thus, increased dMSN excitability likely promoting changes in corticostriatal functional connectivity may contribute to the distinctive behavioral phenotype emerging after developmental DAN loss, with implications for our understanding of the age-dependent effects of forebrain dopamine depletion and neurodevelopment disorders.SIGNIFICANCE STATEMENT The loss of striatal dopamine in the adult brain leads to life-threatening motor impairments. However, general motility remains largely unaffected after its early postnatal loss. Here, we show that the high responsiveness to cortical input of striatal neurons belonging to the direct basal ganglia pathway, crucial for proper motor functioning, is preserved after early dopamine neuron loss, in parallel with an increase in these cells' membrane excitability. Chemogenetic inhibition studies show that the preserved motility depends on this direct pathway hyperexcitability/hyperconnectivity, while other phenotypes characteristic of this condition remained unaltered despite the dMSN inhibition. This insight has implications for our understanding of the mechanism underlying the behavioral impairments observed in neuropsychiatric conditions linked to early dopaminergic hypofunction.

Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules

Cortical networks have the remarkable ability to self-assemble into dynamic regimes in which excitatory positive feedback is balanced by recurrent inhibition. This inhibition-stabilized regime is increasingly viewed as the default dynamic regime of the cortex, but how it emerges in an unsupervised manner remains unknown. We prove that classic forms of homeostatic plasticity are unable to drive recurrent networks to an inhibition-stabilized regime due to the well-known paradoxical effect. We next derive a novel family of cross-homeostatic rules that lead to the unsupervised emergence of inhibition-stabilized networks. These rules shed new light on how the brain may reach its default dynamic state and provide a valuable tool to self-assemble artificial neural networks into ideal computational regimes.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (W_E←E, W_E←I, W_I←E, and W_I←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of “cross-homeostatic” rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how—beginning from a silent network—self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

Activation of histamine type 2 receptors enhances intrinsic excitability of medium spiny neurons in the nucleus accumbens

Abstract

Histaminergic neurons are exclusively located in the hypothalamic tuberomammillary nucleus, from where they project to many brain areas including the nucleus accumbens (NAc), a brain area that integrates diverse monoaminergic inputs to coordinate motivated behaviours. While the NAc expresses various histamine receptor subtypes, the mechanisms by which histamine modulates NAc activity are still poorly understood. Using whole‐cell patch‐clamp recordings, we found that pharmacological activation of histamine 2 (H2) receptors elevates the excitability of NAc medium spiny neurons (MSNs), while activation of H1 receptors failed to significantly affect MSN excitability. The evoked firing of MSNs increased after seconds of local H2 agonist administration and remained elevated for minutes. H2 receptor (H2R) activation accelerated subthreshold depolarization in response to current injection, reduced the latency to fire, diminished action potential afterhyperpolarization and increased the action potential half‐width. The increased excitability was protein kinase A‐dependent and associated with decreased A‐type K⁺ currents. In addition, selective pharmacological inhibition of the Kv4.2 channel, the main molecular determinant of A‐type K⁺ currents in MSNs, mimicked and occluded the increased excitability induced by H2R activation. Our results indicate that histaminergic transmission in the NAc increases MSN intrinsic excitability through H2R‐dependent modulation of Kv4.2 channels. Activation of H2R will significantly alter spike firing in MSNs in vivo, and this effect could be an important mechanism by which these receptors mediate certain aspects of goal‐induced behaviours.

Key points

Histamine is synthesized and released by hypothalamic neurons of the tuberomammillary nucleus and serves as a general modulator for whole‐brain activity including the nucleus accumbens.

Histamine receptors type 2 (HR2), which are expressed in the nucleus accumbens, couple to Gαs/off proteins which elevate cyclic adenosine monophosphate levels and activate protein kinase A.

Whole‐cell patch‐clamp recordings revealed that H2R activation increased the evoked firing in medium spiny neurons of the nucleus accumbens via protein kinase A‐dependent mechanisms.

HR2 activation accelerated subthreshold depolarization in response to current injection, reduced the latency to fire, diminished action potential medium after‐hyperpolarization and increased the action potential half‐width. HR2 activation also reduced A‐type potassium current.

Selective pharmacological inhibition of the Kv4.2 channel mimicked and occluded the increased excitability induced by H2R activation.

Striatal synaptic adaptations in Parkinson's disease

The striatum is densely innervated by mesencephalic dopaminergic neurons that modulate acquisition and vigor of goal-directed actions and habits. This innervation is progressively lost in Parkinson's disease (PD), contributing to the defining movement deficits of the disease. Although boosting dopaminergic signaling with levodopa early in the course of the disease alleviates these deficits, later this strategy leads to the emergence of debilitating dyskinesia. Here, recent advances in our understanding of how striatal cells and circuits adapt to this progressive de-innervation and to levodopa therapy are discussed. First, we discuss how dopamine (DA) depletion triggers cell type-specific, homeostatic changes in spiny projection neurons (SPNs) that tend to normalize striatal activity but also lead to disruption of the synaptic architecture sculpted by experience. Second, we discuss the roles played by cholinergic and nitric oxide-releasing interneurons in these adaptations. Third, we examine recent work in freely moving mice suggesting that alterations in the spatiotemporal dynamics of striatal ensembles contributes to PD movement deficits. Lastly, we discuss recently published evidence from a progressive model of PD suggesting that contrary to the classical model, striatal pathway imbalance is necessary but not sufficient to produce frank parkinsonism.

Striatal Chloride Dysregulation and Impaired GABAergic Signaling Due to Cation-Chloride Cotransporter Dysfunction in Huntington’s Disease

Intracellular chloride (Cl–) levels in mature neurons must be tightly regulated for the maintenance of fast synaptic inhibition. In the mature central nervous system (CNS), synaptic inhibition is primarily mediated by gamma-amino butyric acid (GABA), which binds to Cl– permeable GABAA receptors (GABAARs). The intracellular Cl– concentration is primarily maintained by the antagonistic actions of two cation-chloride cotransporters (CCCs): Cl–-importing Na+-K+-Cl– co-transporter-1 (NKCC1) and Cl– -exporting K+-Cl– co-transporter-2 (KCC2). In mature neurons in the healthy brain, KCC2 expression is higher than NKCC1, leading to lower levels of intracellular Cl–, and Cl– influx upon GABAAR activation. However, in neurons of the immature brain or in neurological disorders such as epilepsy and traumatic brain injury, impaired KCC2 function and/or enhanced NKCC1 expression lead to intracellular Cl– accumulation and GABA-mediated excitation. In Huntington’s disease (HD), KCC2- and NKCC1-mediated Cl–-regulation are also altered, which leads to GABA-mediated excitation and contributes to the development of cognitive and motor impairments. This review summarizes the role of Cl– (dys)regulation in the healthy and HD brain, with a focus on the basal ganglia (BG) circuitry and CCCs as potential therapeutic targets in the treatment of HD.

Environment-based object values learned by local network in the striatum tail

Choosing good objects is a fundamental behavior for all animals, to which the basal ganglia (BG) contribute extensively. However, the object choice needs to be changed in different environments. The mechanism of object choice is based on the neuronal circuits originating from output neurons (MSNs) in the striatum. We found that the environment information is provided by fast-spiking interneurons (FSIs) connecting to the MSN circuit. More critically, the experimental reduction of the FSI-input to MSNs disabled the monkey to learn the environment-based object choice. This proved that the object choice controlled by the downstream BG circuit is modulated by the environmental context controlled by the internal circuits in the top of BG circuit. This is important for our flexible decision.

Basal ganglia contribute to object-value learning, which is critical for survival. The underlying neuronal mechanism is the association of each object with its rewarding outcome. However, object values may change in different environments and we then need to choose different objects accordingly. The mechanism of this environment-based value learning is unknown. To address this question, we created an environment-based value task in which the value of each object was reversed depending on the two scene-environments (X and Y). After experiencing this task repeatedly, the monkeys became able to switch the choice of object when the scene-environment changed unexpectedly. When we blocked the inhibitory input from fast-spiking interneurons (FSIs) to medium spiny projection neurons (MSNs) in the striatum tail by locally injecting IEM-1460, the monkeys became unable to learn scene-selective object values. We then studied the mechanism of the FSI-MSN connection. Before and during this learning, FSIs responded to the scenes selectively, but were insensitive to object values. In contrast, MSNs became able to discriminate the objects (i.e., stronger response to good objects), but this occurred clearly in one of the two scenes (X or Y). This was caused by the scene-selective inhibition by FSI. As a whole, MSNs were divided into two groups that were sensitive to object values in scene X or in scene Y. These data indicate that the local network of striatum tail controls the learning of object values that are selective to the scene-environment. This mechanism may support our flexible switching behavior in various environments.

Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions

In this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.

Neurons, even “at rest”, require a constant supply of energy to function. They cannot sustain high-frequency activity over long periods because of regulatory mechanisms, such as adaptation or sodium channels inactivation, and metabolic limitations. These limitations are especially severe in many neuronal disorders, where energy can become insufficient and make the neuronal response change drastically, leading to increased burstiness, network oscillations, or seizures. Capturing such behaviors and impact of energy constraints on them is an essential prerequisite to study disorders such as Parkinson’s disease and epilepsy. However, energy and spiking constraints are not present in any of the standard neuronal models used in computational neuroscience. Here we introduce models that provide a simple and scalable way to account for these features, enabling large-scale theoretical and computational studies of neurological disorders and activity patterns that could not be captured by previously used models. These models provide a way to study energy-associated disorders over the whole time-course of disease progression, and they enable a better assessment of energy-centered approaches to improve therapies.

K369I Tau Mice Demonstrate a Shift Towards Striatal Neuron Burst Firing and Goal-directed Behaviour

Pathological forms of the microtubule-associated protein tau are involved in a large group of neurodegenerative diseases named tauopathies, including frontotemporal lobar degeneration (FTLD-tau). K369I mutant tau transgenic mice (K3 mice) recapitulate neural and behavioural symptoms of FTLD, including tau aggregates in the cortex, alterations to nigrostriatum, memory deficits and parkinsonism. The aim of this study was to further characterise the K3 mouse model by examining functional alterations to the striatum. Whole-cell patch-clamp electrophysiology was used to investigate the properties of striatal neurons in K3 mice and wildtype controls. Additionally, striatal-based instrumental learning tasks were conducted to assess goal-directed versus habitual behaviours (i.e., by examining sensitivity to outcome devaluation and progressive ratios). The K3 model demonstrated significant alterations in the discharge properties of striatal neurons relative to wildtype mice, which manifested as a shift in neuronal output towards a burst firing state. K3 mice acquired goal-directed responding faster than control mice and were goal-directed at test unlike wildtype mice, which is likely to indicate reduced capacity to develop habitual behaviour. The observed pattern of behaviour in K3 mice is suggestive of deficits in dorsal lateral striatal function and this was supported by our electrophysiological findings. Thus, both the electrophysiological and behavioural alterations indicate that K3 mice have early deficits in striatal function. This finding adds to the growing literature which indicate that the striatum is impacted in tau-related neuropathies such as FTLD, and further suggests that the K3 model is a unique mouse model for investigating FTLD especially with striatal involvement.

Time-dependent branching processes: a model of oscillating neuronal avalanches

Recently, neuronal avalanches have been observed to display oscillations, a phenomenon regarded as the co-existence of a scale-free behaviour (the avalanches close to criticality) and scale-dependent dynamics (the oscillations). Ordinary continuous-time branching processes with constant extinction and branching rates are commonly used as models of neuronal activity, yet they lack any such time-dependence. In the present work, we extend a basic branching process by allowing the extinction rate to oscillate in time as a new model to describe cortical dynamics. By means of a perturbative field theory, we derive relevant observables in closed form. We support our findings by quantitative comparison to numerics and qualitative comparison to available experimental results.

The effects of Alzheimer's disease related striatal pathologic changes on the fractional amplitude of low-frequency fluctuations

This paper aims to correlate Alzheimer's disease (AD) related striatal pathologic changes with the fractional amplitude of low-frequency fluctuations (fALLF) in the blood oxygenation level-dependent (BOLD) signal in the resting state functional Magnetic Resonance Imaging (rs-fMRI). A dopamine modulated Izikhevich neuron model based network of striatum region is constructed. Balloon-Windkessel hemodynamic model is used to obtain BOLD signals. fALFF differences between two frequency bands (slow-5:0.01-0.027 Hz; slow-4:0.027-0.073 Hz) are investigated in the case of dopamine depletion, decrease in the synaptic connectivity and the input from cortical and thalamic region, assumed that they are the degenerations occurring in AD.

One Is Not Enough: Understanding and Modeling Polysubstance Use

Substance use disorder (SUD) is a chronic, relapsing disease with a highly multifaceted pathology that includes (but is not limited to) sensitivity to drug-associated cues, negative affect, and motivation to maintain drug consumption. SUDs are highly prevalent, with 35 million people meeting criteria for SUD. While drug use and addiction are highly studied, most investigations of SUDs examine drug use in isolation, rather than in the more prevalent context of comorbid substance histories. Indeed, 11.3% of individuals diagnosed with a SUD have concurrent alcohol and illicit drug use disorders. Furthermore, having a SUD with one substance increases susceptibility to developing dependence on additional substances. For example, the increased risk of developing heroin dependence is twofold for alcohol misusers, threefold for cannabis users, 15-fold for cocaine users, and 40-fold for prescription misusers. Given the prevalence and risk associated with polysubstance use and current public health crises, examining these disorders through the lens of co-use is essential for translatability and improved treatment efficacy. The escalating economic and social costs and continued rise in drug use has spurred interest in developing preclinical models that effectively model this phenomenon. Here, we review the current state of the field in understanding the behavioral and neural circuitry in the context of co-use with common pairings of alcohol, nicotine, cannabis, and other addictive substances. Moreover, we outline key considerations when developing polysubstance models, including challenges to developing preclinical models to provide insights and improve treatment outcomes.

Morphine Differentially Alters the Synaptic and Intrinsic Properties of D1R- and D2R-Expressing Medium Spiny Neurons in the Nucleus Accumbens

Exposure to opioids reshapes future reward and motivated behaviors partially by altering the functional output of medium spiny neurons (MSNs) in the nucleus accumbens shell. Here, we investigated how morphine, a highly addictive opioid, alters synaptic transmission and intrinsic excitability on dopamine D1-receptor (D1R) expressing and dopamine D2-receptor (D2R) expressing MSNs, the two main output neurons in the nucleus accumbens shell. Using whole-cell electrophysiology recordings, we show, that 24 h abstinence following repeated non-contingent administration of morphine (10 mg/kg, i.p.) in mice reduces the miniature excitatory postsynaptic current (mEPSC) frequency and miniature inhibitory postsynaptic current (mIPSC) frequency on D2R-MSNs, with concomitant increases in D2R-MSN intrinsic membrane excitability. We did not observe any changes in synaptic or intrinsic changes on D1R-MSNs. Last, in an attempt to determine the integrated effect of the synaptic and intrinsic alterations on the overall functional output of D2R-MSNs, we measured the input-output efficacy by measuring synaptically-driven action potential firing. We found that both D1R-MSN and D2R-MSN output was unchanged following morphine treatment.

The estrous cycle modulates rat caudate-putamen medium spiny neuron physiology

The neuroendocrine environment in which the brain operates is both dynamic and differs by sex. How differences in neuroendocrine state affect neuron properties has been significantly neglected in neuroscience research. Behavioral data across humans and rodents indicate that natural cyclical changes in steroid sex hormone production affect sensorimotor and cognitive behaviors in both normal and pathological contexts. These behaviors are critically mediated by the caudate-putamen. In the caudate-putamen, medium spiny neurons (MSNs) are the predominant and primary output neurons. MSNs express membrane-associated estrogen receptors and demonstrate estrogen sensitivity. However, how the cyclical hormone changes across the estrous cycle may modulate caudate-putamen MSN electrophysiological properties remains unknown. Here, we performed whole-cell patch-clamp recordings on male, diestrus female, proestrus female, and estrus female caudate-putamen MSNs. Action potential, passive membrane, and miniature excitatory post-synaptic current properties were assessed. Numerous MSN electrical properties robustly differed by cycle state, including resting membrane potential, rheobase, action potential threshold, maximum evoked action potential firing rate, and inward rectification. Strikingly, when considered independent of estrous cycle phase, all but one of these properties do not significantly differ from male MSNs. These data indicate that female caudate-putamen MSNs are sensitive to the estrous cycle, and more broadly, the importance of considering neuroendocrine state in studies of neuron physiology.

Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions

Cortico-basal ganglia circuits are thought to play a crucial role in the selection and control of motor behaviors and have also been implicated in the processing of motivational content and in higher cognitive functions. During the last two decades, electrophysiological recordings in basal ganglia circuits have shown that several disease conditions are associated with specific changes in the temporal patterns of neuronal activity. In particular, synchronized oscillations have been a frequent finding suggesting that excessive synchronization of neuronal activity may be a pathophysiological mechanism involved in a wide range of neurologic and psychiatric conditions. We here review the experimental support for this hypothesis primarily in relation to Parkinson’s disease but also in relation to dystonia, essential tremor, epilepsy, and psychosis/schizophrenia.

Glioblastoma's Next Top Model: Novel Culture Systems for Brain Cancer Radiotherapy Research

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains one of the least treatable cancers. Current standard of care—combining surgical resection, radiation, and alkylating chemotherapy—results in a median survival of only 15 months. Despite decades of investment and research into the development of new therapies, most candidate anti-glioma compounds fail to translate into effective treatments in clinical trials. One key issue underlying this failure of therapies that work in pre-clinical models to generate meaningful improvement in human patients is the profound mismatch between drug discovery systems—cell cultures and mouse models—and the actual tumors they are supposed to imitate. Indeed, current strategies that evaluate the effects of novel treatments on GBM cells in vitro fail to account for a wide range of factors known to influence tumor growth. These include secreted factors, the brain’s unique extracellular matrix, circulatory structures, the presence of non-tumor brain cells, and nutrient sources available for tumor metabolism. While mouse models provide a more realistic testing ground for potential therapies, they still fail to account for the full complexity of tumor-microenvironment interactions, as well as the role of the immune system. Based on the limitations of current models, researchers have begun to develop and implement novel culture systems that better recapitulate the complex reality of brain tumors growing in situ. A rise in the use of patient derived cells, creative combinations of added growth factors and supplements, may provide a more effective proving ground for the development of novel therapies. This review will summarize and analyze these exciting developments in 3D culturing systems. Special attention will be paid to how they enhance the design and identification of compounds that increase the efficacy of radiotherapy, a bedrock of GBM treatment.

Human cellular models of medium spiny neuron development and Huntington disease

The loss of gamma-aminobutyric acid (GABA)-ergic medium spiny neurons (MSNs) in the striatum is the hallmark of Huntington disease (HD), an incurable neurodegenerative disorder characterized by progressive motor, psychiatric, and cognitive symptoms. Transplantation of MSNs or their precursors represents a promising treatment strategy for HD. In initial clinical trials in which HD patients received fetal neurografts directly into the striatum without a pretransplant cell-differentiation step, some patients exhibited temporary benefits. Meanwhile, major challenges related to graft overgrowth, insufficient survival of grafted cells, and limited availability of donated fetal tissue remain. Thus, the development of approaches that allow modeling of MSN differentiation and HD development in cell culture platforms may improve our understanding of HD and translate, ultimately, into HD treatment options. Here, recent advances in the in vitro differentiation of MSNs derived from fetal neural stem cells/progenitor cells (NSCs/NPCs), embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and induced NSCs (iNSCs) as well as advances in direct transdifferentiation are reviewed. Progress in non-allele specific and allele specific gene editing of HTT is presented as well. Cell characterization approaches involving phenotyping as well as in vitro and in vivo functional assays are also discussed.

Dysregulation of Corticostriatal Connectivity in Huntington's Disease: A Role for Dopamine Modulation

Aberrant communication between striatum, the main information processing unit of the basal ganglia, and cerebral cortex plays a critical role in the emergence of Huntington’s disease (HD), a fatal monogenetic condition that typically strikes in the prime of life. Although both striatum and cortex undergo substantial cell loss over the course of HD, corticostriatal circuits become dysfunctional long before neurons die. Understanding the dysfunction is key to developing effective strategies for treating a progressively worsening triad of motor, cognitive, and psychiatric symptoms. Cortical output neurons drive striatal activity through the release of glutamate, an excitatory amino acid. Striatal outputs, in turn, release γ-amino butyric acid (GABA) and exert inhibitory control over downstream basal ganglia targets. Ample evidence from transgenic rodent models points to dysregulation of corticostriatal glutamate transmission along with corresponding changes in striatal GABA release as underlying factors in the HD behavioral phenotype. Another contributor is dysregulation of dopamine (DA), a modulator of both glutamate and GABA transmission. In fact, pharmacological manipulation of DA is the only currently available treatment for HD symptoms. Here, we review data from animal models and human patients to evaluate the role of DA in HD, including DA interactions with glutamate and GABA within the context of dysfunctional corticostriatal circuitry.

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.

Global and local excitation and inhibition shape the dynamics of the cortico-striatal-thalamo-cortical pathway

The cortico-striatal-thalamo-cortical (CSTC) pathway is a brain circuit that controls movement execution, habit formation and reward. Hyperactivity in the CSTC pathway is involved in obsessive compulsive disorder (OCD), a neuropsychiatric disorder characterized by the execution of repetitive involuntary movements. The striatum shapes the activity of the CSTC pathway through the coordinated activation of two classes of medium spiny neurons (MSNs) expressing D1 or D2 dopamine receptors. The exact mechanisms by which balanced excitation/inhibition (E/I) of these cells controls the network dynamics of the CSTC pathway remain unclear. Here we use non-linear modeling of neuronal activity and bifurcation theory to investigate how global and local changes in E/I of MSNs regulate the activity of the CSTC pathway. Our findings indicate that a global and proportionate increase in E/I pushes the system to states of generalized hyper-activity throughout the entire CSTC pathway. Certain disproportionate changes in global E/I trigger network oscillations. Local changes in the E/I of MSNs generate specific oscillatory behaviors in MSNs and in the CSTC pathway. These findings indicate that subtle changes in the relative strength of E/I of MSNs can powerfully control the network dynamics of the CSTC pathway in ways that are not easily predicted by its synaptic connections.

Dysregulation of striatal projection neurons in Parkinson's disease

The loss of nigrostriatal dopamine (DA) is the primary cause of motor dysfunction in Parkinson's disease (PD), but the underlying striatal mechanisms remain unclear. In spite of abundant literature portraying structural, biochemical and plasticity changes of striatal projection neurons (SPNs), in the past there has been a data vacuum from the natural human disease and its close model in non-human primates. Recently, single-cell recordings in advanced parkinsonian primates have generated new insights into the altered function of SPNs. Currently, there are also human data that provide direct evidence of profoundly dysregulated SPN activity in PD. Here, we review primate recordings that are impacting our understanding of the striatal dysfunction after DA loss, particularly through the analysis of physiologic correlates of parkinsonian motor behaviors. In contrast to recordings in rodents, data obtained in primates and patients demonstrate similar major abnormalities of the spontaneous SPN firing in the alert parkinsonian state. Furthermore, these studies also show altered SPN responses to DA replacement in the advanced parkinsonian state. Clearly, there is yet much to learn about the striatal discharges in PD, but studies using primate models are contributing unique information to advance our understanding of pathophysiologic mechanisms.

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.

Representation of the body in the lateral striatum of the freely moving rat: Fast Spiking Interneurons respond to stimulation of individual body parts

Numerous studies have shown that certain types of striatal interneurons play a crucial role in selection and regulation of striatal output. Striatal Fast-Spiking Interneurons (FSIs) are parvalbumin positive, GABAergic interneurons that constitute less than 1% of the total striatal population. It is becoming increasingly evident that these sparsely distributed neurons exert a strong inhibitory effect on Medium Spiny projection Neurons (MSNs). MSNs in lateral striatum receive direct synaptic input from regions of cortex representing discrete body parts, and show phasic increases in activity during touch or movement of specific body parts. In the present study, we sought to determine whether lateral striatal FSIs identified by their electrophysiological properties, i.e., short-duration spike and fast firing rate (FR), display body part sensitivity similar to that exhibited by MSNs. During video recorded somatosensorimotor exams, each individual body part was stimulated and responses of single neurons were observed and quantified. Individual FSIs displayed patterns of activity related selectively to stimulation of a discrete body part. Most patterns of activity were similar to those exhibited by typical MSNs, but some phasic decreases were observed. These results serve as evidence that some striatal FSIs process information related to discrete body parts and participate in sensorimotor processing by striatal networks that contribute to motor output.

STATEMENT OF SIGNIFICANCE

Parvalbumin positive, striatal FSIs are hypothesized to play an important role in behavior by inhibiting MSNs. We asked a fundamental question regarding information processed during behavior by FSIs: whether FSIs, which preferentially occupy the sensorimotor portion of the striatum, process activity of discrete body parts. Our finding that they do, in a selective manner similar to MSNs, begins to reveal the types of phasic signals that FSI feed forward to projection neurons during striatal processing of cortical input regarding a specific sensorimotor event. These findings suggest new avenues for testing feed-forward inhibition theory as applied to striatum in naturalistic conditions, such as whether FSI decreases facilitate excitation of MSNs related to the current movement while FSI increases silence MSNs unrelated to the current movement.

Subthalamic oscillations and phase amplitude coupling are greater in the more affected hemisphere in Parkinson's disease

OBJECTIVE

Determine the incidence of resting state oscillations in alpha/beta, high frequency (HFO) bands, and their phase amplitude coupling (PAC) in a large cohort in Parkinson's disease (PD).

METHODS

Intra-operative local field potentials (LFPs) from subthalamic nucleus (STN) were recorded from 100 PD subjects, data from 74 subjects were included in the analysis.

RESULTS

Alpha/beta oscillations were evident in >99%, HFO in 87% and PAC in 98% of cases. Alpha/beta oscillations (P<0.01) and PAC were stronger in the more affected (MA) hemisphere (P=0.03). Alpha/beta oscillations were primarily found in 13-20Hz (low beta). Beta and HFO frequencies with the greatest coupling, were positively correlated (P=0.001). Tremor attenuated alpha (P=0.002) and beta band oscillations (P<0.001).

CONCLUSIONS

STN alpha/beta band oscillations and PAC were evident in ⩾98% cases and were greater in MA hemisphere. Resting tremor attenuated underlying alpha/beta band oscillations.

SIGNIFICANCE

Beta band LFP power may be used to drive adaptive deep brain stimulation (aDBS), augmented by a kinematic classifier in tremor dominant PD.

Neuronal activity and amyloid plaque pathology: an update

A breakthrough in Alzheimer's disease (AD) research came with the discovery of the link between activity-dependent release of amyloid-β (Aβ) from neurons and formation of amyloid plaques. Along with elucidating the cellular basis of behavioral-dependent fluctuations in Aβ levels in the brain, insights have been gained toward understanding the mechanisms that warrant selective vulnerability of various forebrain circuits to amyloid pathology. The notion of elevated activity as a source of excessive Aβ production and plaque formation is, however, in conflict with ample electrophysiological data, which demonstrate exceedingly intense activity (both intrinsic and synaptic) of neurons in several brain regions that are spared or marginally affected by amyloid plaques of AD. Thus, the link between the functional load of brain circuits and their vulnerability to amyloidosis, while evident, is also complex and remains poorly understood. Here, we discuss emerging data suggestive of a major role for super-intense synchronous activity of cortical and limbic networks in excessive Aβ production and plaque formation. It is proposed that dense recurrent wiring of associative areas prone to epileptic seizures might be of critical relevance to their higher susceptibility to plaque pathology and related functional impairments.

Subthalamic beta oscillations are attenuated after withdrawal of chronic high frequency neurostimulation in Parkinson's disease

Subthalamic nucleus (STN) local field potential (LFP) recordings demonstrate beta (13-30Hz) band oscillations in Parkinson's disease (PD) defined as elevations of spectral power. The amount of attenuation of beta band power on therapeutic levels of high frequency (HF) deep brain stimulation (DBS) and/or dopaminergic medication has been correlated with the degree of improvement in bradykinesia and rigidity from the therapy, which has led to the suggestion that elevated beta band power is a marker of PD motor disability. A fundamental question has not been answered: whether there is a prolonged attenuation of beta band power after withdrawal of chronic HF DBS and whether this is related to a lack of progression or even improvement in the underlying motor disability. Until now, in human PD subjects, STN LFP recordings were only attainable in the peri-operative period and after short periods of stimulation. For the first time, using an investigational, implanted sensing neurostimulator (Activa® PC+S, Medtronic, Inc.), STN LFPs and motor disability were recorded/assessed after withdrawal of chronic (6 and 12month) HF DBS in freely moving PD subjects. Beta band power was similar within 14s and 60min after stimulation was withdrawn, suggesting that "off therapy" experiments can be conducted almost immediately after stimulation is turned off. After withdrawal of 6 and 12months of STN DBS, beta band power was significantly lower (P<0.05 at 6 and 12months) and off therapy UPDRS scores were better (P<0.05 at 12months) compared to before DBS was started. The attenuation in beta band power was correlated with improvement in motor disability scores (P<0.05). These findings were supported by evidence of a gradual increase in beta band power in two unstimulated STNs after 24months and could not be explained by changes in lead impedance. This suggests that chronic HF DBS exerts long-term plasticity in the sensorimotor network, which may contribute to a lack of progression in underlying motor disability in PD.

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.

Assessing the sensitivity of diffusion MRI to detect neuronal activity directly

Functional MRI (fMRI) is widely used to study brain function in the neurosciences. Unfortunately, conventional fMRI only indirectly assesses neuronal activity via hemodynamic coupling. Diffusion fMRI was proposed as a more direct and accurate fMRI method to detect neuronal activity, yet confirmative findings have proven difficult to obtain. Given that the underlying relation between tissue water diffusion changes and neuronal activity remains unclear, the rationale for using diffusion MRI to monitor neuronal activity has yet to be clearly established. Here, we studied the correlation between water diffusion and neuronal activity in vitro by simultaneous calcium fluorescence imaging and diffusion MR acquisition. We used organotypic cortical cultures from rat brains as a biological model system, in which spontaneous neuronal activity robustly emerges free of hemodynamic and other artifacts. Simultaneous fluorescent calcium images of neuronal activity are then directly correlated with diffusion MR signals now free of confounds typically encountered in vivo. Although a simultaneous increase of diffusion-weighted MR signals was observed together with the prolonged depolarization of neurons induced by pharmacological manipulations (in which cell swelling was demonstrated to play an important role), no evidence was found that diffusion MR signals directly correlate with normal spontaneous neuronal activity. These results suggest that, whereas current diffusion MR methods could monitor pathological conditions such as hyperexcitability, e.g., those seen in epilepsy, they do not appear to be sensitive or specific enough to detect or follow normal neuronal activity.

Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.

Functionally heterogeneous synaptic vesicle pools support diverse synaptic signalling

Synaptic communication between neurons is a highly dynamic process involving specialized structures. At the level of the presynaptic terminal, neurotransmission is ensured by fusion of vesicles to the membrane, which releases neurotransmitter in the synaptic cleft. Depending on the level of activity experienced by the terminal, the spatiotemporal properties of calcium invasion will dictate the timing and the number of vesicles that need to be released. Diverse presynaptic firing patterns are translated to neurotransmitter release with a distinct temporal feature. Complex patterns of neurotransmitter release can be achieved when different vesicles respond to distinct calcium dynamics in the presynaptic terminal. Specific vesicles from different pools are recruited during various modes of release as the particular molecular composition of their membrane proteins define their functional properties. Such diversity endows the presynaptic terminal with the ability to respond to distinct physiological signals via the mobilization of specific subpopulation of vesicles. There are several mechanisms by which a diverse vesicle population could be generated in single presynaptic terminals, including distinct recycling pathways that utilize various adaptor proteins. Several additional factors could potentially contribute to the development of a heterogeneous vesicle pool such as specialized release sites, spatial segregation within the terminal and specialized delivery pathways. Among these factors molecular heterogeneity plays a central role in defining the functional properties of different subpopulations of vesicles.

Activity of Caudate Nucleus Neurons in a Visual Fixation Paradigm in Behaving Cats

Beside its motor functions, the caudate nucleus (CN), the main input structure of the basal ganglia, is also sensitive to various sensory modalities. The goal of the present study was to investigate the effects of visual stimulation on the CN by using a behaving, head-restrained, eye movement-controlled feline model developed recently for this purpose. Extracellular multielectrode recordings were made from the CN of two cats in a visual fixation paradigm applying static and dynamic stimuli. The recorded neurons were classified in three groups according to their electrophysiological properties: phasically active (PAN), tonically active (TAN) and high-firing (HFN) neurons. The response characteristics were investigated according to this classification. The PAN and TAN neurons were sensitive primarily to static stimuli, while the HFN neurons responded primarily to changes in the visual environment i.e. to optic flow and the offset of the stimuli. The HFNs were the most sensitive to visual stimulation; their responses were stronger than those of the PANs and TANs. The majority of the recorded units were insensitive to the direction of the optic flow, regardless of group, but a small number of direction-sensitive neurons were also found. Our results demonstrate that both the static and the dynamic components of the visual information are represented in the CN. Furthermore, these results provide the first piece of evidence on optic flow processing in the CN, which, in more general terms, indicates the possible role of this structure in dynamic visual information processing.

Functional Clusters, Hubs, and Communities in the Cortical Microconnectome

Although relationships between networks of different scales have been observed in macroscopic brain studies, relationships between structures of different scales in networks of neurons are unknown. To address this, we recorded from up to 500 neurons simultaneously from slice cultures of rodent somatosensory cortex. We then measured directed effective networks with transfer entropy, previously validated in simulated cortical networks. These effective networks enabled us to evaluate distinctive nonrandom structures of connectivity at 2 different scales. We have 4 main findings. First, at the scale of 3-6 neurons (clusters), we found that high numbers of connections occurred significantly more often than expected by chance. Second, the distribution of the number of connections per neuron (degree distribution) had a long tail, indicating that the network contained distinctively high-degree neurons, or hubs. Third, at the scale of tens to hundreds of neurons, we typically found 2-3 significantly large communities. Finally, we demonstrated that communities were relatively more robust than clusters against shuffling of connections. We conclude the microconnectome of the cortex has specific organization at different scales, as revealed by differences in robustness. We suggest that this information will help us to understand how the microconnectome is robust against damage.

Transgenic labeling of parvalbumin-expressing neurons with tdTomato

Parvalbumin (PVALB)-expressing fast-spiking interneurons subserve important roles in many brain regions by modulating circuit function and dysfunction of these neurons is strongly implicated in neuropsychiatric disorders including schizophrenia and autism. To facilitate the study of PVALB neuron function we need to be able to identify PVALB neurons in vivo. We have generated a bacterial artificial chromosome (BAC) transgenic mouse line expressing the red fluorophore tdTomato under the control of endogenous regulatory elements of the Pvalb gene locus (JAX # 027395). We show that the tdTomato transgene is faithfully expressed relative to endogenous PVALB expression throughout the brain. Furthermore, targeted patch clamp recordings confirm that the labeled populations in neocortex, striatum, and hippocampus are fast-spiking interneurons based on intrinsic properties. This new transgenic mouse line provides a useful tool to study PVALB neuron function in the normal brain as well as in mouse models of psychiatric disease.