Neurons in the globus pallidus do not show correlated activity in the normal monkey, but phase-locked oscillations appear in the MPTP model of parkinsonism

Clinico-physiological correlates of Parkinson's disease from multi-resolution basal ganglia recordings

Parkinson's disease (PD) has been associated with pathological neural activity within the basal ganglia. Herein, we analyzed resting-state single-neuron and local field potential (LFP) activities from people with PD who underwent awake deep brain stimulation surgery of the subthalamic nucleus (STN; n = 125) or globus pallidus internus (GPi; n = 44), and correlated rate-based and oscillatory features with UPDRSIII off-medication subscores. Rate-based single-neuron features did not correlate with PD symptoms. STN single-neuron and LFP low-beta (12-21 Hz) power and burst dynamics showed modest correlations with bradykinesia and rigidity severity, while STN spiketrain theta (4-8 Hz) power correlated modestly with tremor severity. GPi low- and high-beta (21-30 Hz) power and burst dynamics correlated moderately with bradykinesia and axial symptom severity. These findings suggest that elevated single-neuron and LFP oscillations may be linked to symptoms, though modest correlations imply that the pathophysiology of PD may extend beyond resting-state beta oscillations.

Why so slow? Models of parkinsonian bradykinesia

Bradykinesia, or slowness of movement, is a defining feature of Parkinson disease (PD) and a major contributor to the negative effects on quality of life associated with this disorder and related conditions. A dominant pathophysiological model of bradykinesia in PD has existed for approximately 30 years and has been the basis for the development of several therapeutic interventions, but accumulating evidence has made this model increasingly untenable. Although more recent models have been proposed, they also appear to be flawed. In this Perspective, I consider the leading prior models of bradykinesia in PD and argue that a more functionally related model is required, one that considers changes that disrupt the fundamental process of accurate information transmission. In doing so, I review emerging evidence of network level functional connectivity changes, information transfer dysfunction and potential motor code transmission error and present a novel model of bradykinesia in PD that incorporates this evidence. I hope that this model may reconcile inconsistencies in its predecessors and encourage further development of therapeutic interventions.

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

Synchronization is a phenomenon observed in neuronal networks involved in diverse brain activities. Neural mass models such as Wilson-Cowan (WC) and Jansen-Rit (JR) manifest synchronized states. Despite extensive research on these models over the past several decades, their potential of manifesting second-order phase transitions (SOPT) and criticality has not been sufficiently acknowledged. In this study, two networks of coupled WC and JR nodes with small-world topologies were constructed and Kuramoto order parameter (KOP) was used to quantify the amount of synchronization. In addition, we investigated the presence of SOPT using the synchronization coefficient of variation. Both networks reached high synchrony by changing the coupling weight between their nodes. Moreover, they exhibited abrupt changes in the synchronization at certain values of the control parameter not necessarily related to a phase transition. While SOPT was observed only in JR model, neither WC nor JR model showed power-law behavior. Our study further investigated the global synchronization phenomenon that is known to exist in pathological brain states, such as seizure. JR model showed global synchronization, while WC model seemed to be more suitable in producing partially synchronized patterns.

Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity

Abnormally strong neural synchronization may impair brain function, as observed in several brain disorders. We computationally study how neuronal dynamics, synaptic weights, and network structure co-emerge, in particular, during (de)synchronization processes and how they are affected by external perturbation. To investigate the impact of different types of plasticity mechanisms, we combine a network of excitatory integrate-and-fire neurons with different synaptic weight and/or structural plasticity mechanisms: (i) only spike-timing-dependent plasticity (STDP), (ii) only homeostatic structural plasticity (hSP), i.e., without weight-dependent pruning and without STDP, (iii) a combination of STDP and hSP, i.e., without weight-dependent pruning, and (iv) a combination of STDP and structural plasticity (SP) that includes hSP and weight-dependent pruning. To accommodate the diverse time scales of neuronal firing, STDP, and SP, we introduce a simple stochastic SP model, enabling detailed numerical analyses. With tools from network theory, we reveal that structural reorganization may remarkably enhance the network's level of synchrony. When weaker contacts are preferentially eliminated by weight-dependent pruning, synchrony is achieved with significantly sparser connections than in randomly structured networks in the STDP-only model. In particular, the strengthening of contacts from neurons with higher natural firing rates to those with lower rates and the weakening of contacts in the opposite direction, followed by selective removal of weak contacts, allows for strong synchrony with fewer connections. This activity-led network reorganization results in the emergence of degree-frequency, degree-degree correlations, and a mixture of degree assortativity. We compare the stimulation-induced desynchronization of synchronized states in the STDP-only model (i) with the desynchronization of models (iii) and (iv). The latter require stimuli of significantly higher intensity to achieve long-term desynchronization. These findings may inform future pre-clinical and clinical studies with invasive or non-invasive stimulus modalities aiming at inducing long-lasting relief of symptoms, e.g., in Parkinson's disease.

A Computational Model of Deep Brain Stimulation for Parkinson's Disease Tremor and Bradykinesia

Parkinson's disease (PD) is a progressive neurological disorder that is typically characterized by a range of motor dysfunctions, and its impact extends beyond physical abnormalities into emotional well-being and cognitive symptoms. The loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) leads to an array of dysfunctions in the functioning of the basal ganglia (BG) circuitry that manifests into PD. While active research is being carried out to find the root cause of SNc cell death, various therapeutic techniques are used to manage the symptoms of PD. The most common approach in managing the symptoms is replenishing the lost dopamine in the form of taking dopaminergic medications such as levodopa, despite its long-term complications. Another commonly used intervention for PD is deep brain stimulation (DBS). DBS is most commonly used when levodopa medication efficacy is reduced, and, in combination with levodopa medication, it helps reduce the required dosage of medication, prolonging the therapeutic effect. DBS is also a first choice option when motor complications such as dyskinesia emerge as a side effect of medication. Several studies have also reported that though DBS is found to be effective in suppressing severe motor symptoms such as tremors and rigidity, it has an adverse effect on cognitive capabilities. Henceforth, it is important to understand the exact mechanism of DBS in alleviating motor symptoms. A computational model of DBS stimulation for motor symptoms will offer great insights into understanding the mechanisms underlying DBS, and, along this line, in our current study, we modeled a cortico-basal ganglia circuitry of arm reaching, where we simulated healthy control (HC) and PD symptoms as well as the DBS effect on PD tremor and bradykinesia. Our modeling results reveal that PD tremors are more correlated with the theta band, while bradykinesia is more correlated with the beta band of the frequency spectrum of the local field potential (LFP) of the subthalamic nucleus (STN) neurons. With a DBS current of 220 pA, 130 Hz, and a 100 microsecond pulse-width, we could found the maximum therapeutic effect for the pathological dynamics simulated using our model using a set of parameter values. However, the exact DBS characteristics vary from patient to patient, and this can be further studied by exploring the model parameter space. This model can be extended to study different DBS targets and accommodate cognitive dynamics in the future to study the impact of DBS on cognitive symptoms and thereby optimize the parameters to produce optimal performance effects across modalities. Combining DBS with rehabilitation is another frontier where DBS can reduce symptoms such as tremors and rigidity, enabling patients to participate in their therapy. With DBS providing instant relief to patients, a combination of DBS and rehabilitation can enhance neural plasticity. One of the key motivations behind combining DBS with rehabilitation is to expect comparable results in motor performance even with milder DBS currents.

Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Information flow in brain networks is reflected in local field potentials that have both periodic and aperiodic components. The 1/fχ aperiodic component of the power spectra tracks arousal and correlates with other physiological and pathophysiological states. Here we explored the aperiodic activity in the human thalamus and basal ganglia in relation to simultaneously recorded cortical activity. We elaborated on the parameterization of the aperiodic component implemented by specparam (formerly known as FOOOF) to avoid parameter unidentifiability and to obtain independent and more easily interpretable parameters. This allowed us to seamlessly fit spectra with and without an aperiodic knee, a parameter that captures a change in the slope of the aperiodic component. We found that the cortical aperiodic exponent χ, which reflects the decay of the aperiodic component with frequency, is correlated with Parkinson's disease symptom severity. Interestingly, no aperiodic knee was detected from the thalamus, the pallidum, or the subthalamic nucleus, which exhibited an aperiodic exponent significantly lower than in cortex. These differences were replicated in epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences.

SIGNIFICANCE STATEMENT

The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

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.

Spatiomolecular Characterization of Dopamine D2 Receptors Cells in the Mouse External Globus Pallidus

The external globus pallidus (GPe) is part of the basal ganglia circuit and plays a key role in controlling the actions. Although, many evidence indicate that dopamine through its activation of dopamine D2 receptors (D2Rs) modulates the GPe neuronal activity, the precise spatiomolecular characterization of cell populations expressing D2Rs in the mouse GPe is still lacking. By combining single molecule in situ hybridization, cell type-specific imaging analyses, and electrophysiology slice recordings, we found that GPe D2R cells are neurons preferentially localized in the caudal portion of GPe. These neurons comprising pallido-striatal, pallido-nigral, and pallido-cortical neurons segregate into two distinct populations displaying molecular and electrophysiological features of GPe GABAergic PV/NKX2.1 and cholinergic neurons respectively. By clarifying the spatial molecular identity of GPe D2R neurons in the mouse, this work provides the basis for future studies aiming at disentangling the action of dopamine within the GPe.

External segment of the globus pallidus in health and disease: Its interactions with the striatum and subthalamic nucleus

The external segment of the globus pallidus (GPe) has long been considered a homogeneous structure that receives inputs from the striatum and sends processed information to the subthalamic nucleus, composing a relay nucleus of the indirect pathway that contributes to movement suppression. Recent methodological revolution in rodents led to the identification of two distinct cell types in the GPe with different fiber connections. The GPe may be regarded as a dynamic, complex and influential center within the basal ganglia circuitry, rather than a simple relay nucleus. On the other hand, many studies have so far been performed in monkeys to clarify the functions of the basal ganglia in the healthy and diseased states, but have not paid much attention to such classification and functional differences of GPe neurons. In this minireview, we consider the knowledge on the rodent GPe and discuss its impact on the understanding of the basal ganglia circuitry in monkeys.

Increased expression of Nav1.6 of reactive astrocytes in the globus pallidus is closely associated with motor deficits in a model of Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative disease in elderly people, which is characterized by motor disabilities in PD patients. Nav1.6 is the most abundant subtype of voltage-gated sodium channels (VGSCs) in the brain of adult mammals and rodents. Here we investigated the role of Nav1.6 in the external globus pallidus (GP) involved in the pathogenesis of motor deficits in unilateral 6-OHDA(6-hydroxydopamine)lesioned rats. The results show that Nav1.6 is dramatically increased in reactive astrocytes of the ipsilateral GP in the middle stage, but not different from the control rats in the later stage of the pathological process in 6-OHDA lesioned rats. Furthermore, the down-regulation of Nav1.6 expression in the ipsilateral GP can significantly improve motor deficits in 6-OHDA lesioned rats in the middle stage of the pathological process. The electrophysiological experiments show that the down-regulation of Nav1.6 expression in the ipsilateral GP significantly decreases the abnormal high synchronization between the ipsilateral M1 (the primary motor cortex) and GP in 6-OHDA lesioned rats. Ca2+ imaging reveals that the down-regulation of Nav1.6 expression reduces the intracellular concentration of Ca2+ ([Ca2+ ]i) in primary cultured astrocytes. These findings suggest that the increased Nav1.6 expression of reactive astrocytes in the GP play an important role in the pathogenesis of motor dysfunction in the middle stage in 6-OHDA lesioned rats, which may participate in astrocyte-neuron communication by regulating [Ca2+ ]i of astrocytes, thereby contributing to the formation of abnormal electrical signals of the basal ganglia (BG) in 6-OHDA lesioned rats.

Tuned to Tremor: Increased Sensitivity of Cortico-Basal Ganglia Neurons to Tremor Frequency in the MPTP Nonhuman Primate Model of Parkinson's Disease

Rest tremor is one of the most prominent clinical features of Parkinson's disease (PD). Here, we hypothesized that cortico-basal ganglia neurons tend to fire in a pattern that matches PD tremor frequency, suggesting a resonance phenomenon. We recorded spiking activity in the primary motor cortex (M1) and globus pallidus external segment of 2 female nonhuman primates, before and after parkinsonian state induction with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The arm of nonhuman primates was passively rotated at seven different frequencies surrounding and overlapping PD tremor frequency. We found entrainment of the spiking activity to arm rotation and a significant sharpening of the tuning curves in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine state, with a peak response at frequencies that matched the frequency of PD tremor. These results reveal increased sensitivity of the cortico-basal ganglia network to tremor frequency and could indicate that this network acts not only as a tremor switch but is involved in setting its frequency.SIGNIFICANCE STATEMENT Tremor is a prominent clinical feature of Parkinson's disease; however, its underlying pathophysiology is still poorly understood. Using electrophysiological recordings of single cortico-basal ganglia neurons before and after the induction of a parkinsonian state, and in response to passive arm rotation, this study reports increased sensitivity to tremor frequency in Parkinson's disease. We found sharpening of the population tuning to the midrange of the tested frequencies (1-13.3 Hz) in the healthy state that further increased in the parkinsonian state. These results hint at the increased frequency-tuned sensitivity of cortico-basal ganglia neurons and suggest that they tend to resonate with the tremor.

The transcription regulator Lmo3 is required for the development of medial ganglionic eminence derived neurons in the external globus pallidus

The external globus pallidus (GPe) is an essential component of the basal ganglia, a group of subcortical nuclei that are involved in control of action. Changes in the firing of GPe neurons are associated with both passive and active body movements. Aberrant activity of GPe neurons has been linked to motor symptoms of a variety of movement disorders, such as Parkinson's Disease, Huntington's disease and dystonia. Recent studies have helped delineate functionally distinct subtypes of GABAergic GPe projection neurons. However, not much is known about specific molecular mechanisms underlying the development of GPe neuronal subtypes. We show that the transcriptional regulator Lmo3 is required for the development of medial ganglionic eminence derived Nkx2.1+ and PV+ GPe neurons, but not lateral ganglionic eminence derived FoxP2+ neurons. As a consequence of the reduction in PV+ neurons, Lmo3-null mice have a reduced GPe input to the subthalamic nucleus.

Adaptive Stimulations in a Biophysical Network Model of Parkinson’s Disease

Deep brain stimulation (DBS)—through a surgically implanted electrode to the subthalamic nucleus (STN)—has become a widely used therapeutic option for the treatment of Parkinson’s disease and other neurological disorders. The standard conventional high-frequency stimulation (HF) that is currently used has several drawbacks. To overcome the limitations of HF, researchers have been developing closed-loop and demand-controlled, adaptive stimulation protocols wherein the amount of current that is delivered is turned on and off in real-time in accordance with a biophysical signal. Computational modeling of DBS in neural network models is an increasingly important tool in the development of new protocols that aid researchers in animal and clinical studies. In this computational study, we seek to implement a novel technique of DBS where we stimulate the STN in an adaptive fashion using the interspike time of the neurons to control stimulation. Our results show that our protocol eliminates bursts in the synchronized bursting neuronal activity of the STN, which is hypothesized to cause the failure of thalamocortical neurons (TC) to respond properly to excitatory cortical inputs. Further, we are able to significantly decrease the TC relay errors, representing potential therapeutics for Parkinson’s disease.

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/fχ broadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinson's disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent (χSTN=1.3±0.2, χVIM=1.4±0.1, χGPi =1.4±0.1) that differed markedly from cortical values (χCortex=3.2±0.4, fkCortex=17±5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex.

Sensory processing in external globus pallidus neurons

Sensory processing is crucial for execution of appropriate behavior. The external globus pallidus (GPe), a nucleus within the basal ganglia, is highly involved in the control of movement and could potentially integrate sensory-motor information. The GPe comprises prototypic and arkypallidal cells, which receive partially overlapping inputs. It is unclear, however, which inputs convey sensory information to them. Here, we used in vivo whole-cell recordings in the mouse GPe and optogenetic silencing to characterize the pathways that shape the response to whisker stimulation in prototypic and arkypallidal cells. Our results show that sensory integration in prototypic cells is controlled by the subthalamic nucleus and indirect pathway medium spiny neurons (MSNs), whereas in arkypallidal cells, it is primarily shaped by direct pathway MSNs. These results suggest that GPe subpopulations receive sensory information from largely different neural populations, reinforcing that the GPe consists of two parallel pathways, which differ anatomically and functionally.

Dichotomous activity and function of neurons with low- and high-frequency discharge in the external globus pallidus of non-human primates

To date, there is a consensus that there are at least two neuronal populations in the non-human primate (NHP) external globus pallidus (GPe): low-frequency discharge (LFD) and high-frequency discharge (HFD) neurons. Nevertheless, almost all NHP physiological studies have neglected the functional importance of LFD neurons. This study examined the discharge features of these two GPe neuronal subpopulations recorded in four NHPs engaged in a classical conditioning task with cues predicting reward, neutral and aversive outcomes. The results show that LFD neurons tended to burst, encoded the salience of behavioral cues, and exhibited correlated spiking activity. By contrast, the HFD neurons tended to pause, encoded cue valence, and exhibited uncorrelated spiking activity. Overall, these findings point to the dichotomic organization of the NHP GPe, which is likely to be critical to the implementation of normal basal ganglia functions and computations.

Basal ganglia functional connectivity network analysis does not support the 'noisy signal' hypothesis of Parkinson's disease

The 'noisy signal' hypothesis of basal ganglia dysfunction in Parkinson's disease (PD) suggests that major motor symptoms of the disorder are caused by the development of abnormal basal ganglia activity patterns resulting in the propagation of 'noisy' signals to target systems. While such abnormal activity patterns might be useful biomarkers for the development of therapeutic interventions, correlation between specific changes in activity and PD symptoms has been inconsistently demonstrated, and raises questions concerning the accuracy of the hypothesis. Here, we tested this hypothesis by considering three nodes of the basal ganglia network, the subthalamus, globus pallidus interna, and cortex during self-paced and cued movements in patients with PD. Interactions between these regions were analyzed using measures that assess both linear and non-linear relationships. Marked changes in the network are observed with dopamine state. Specifically, we detected functional disconnection of the basal ganglia from the cortex and higher network variability in untreated PD, but various patterns of directed functional connectivity with lower network variability in treated PD. When we examine the system output, significant correlation is observed between variability in the cortico-basal ganglia network and muscle activity variability but only in the treated state. Rather than supporting a role of the basal ganglia in the transmission of noisy signals in patients with PD, these findings suggest that cortico-basal ganglia network interactions by fault or design, in the treated Parkinsonian state, are actually associated with improved cortical network output variability.

U(1) dynamics in neuronal activities

Neurons convert external stimuli into action potentials, or spikes, and encode the contained information into the biological nervous system. Despite the complexity of neurons and the synaptic interactions in between, rate models are often adapted to describe neural encoding with modest success. However, it is not clear whether the firing rate, the reciprocal of the time interval between spikes, is sufficient to capture the essential features for the neuronal dynamics. Going beyond the usual relaxation dynamics in Ginzburg-Landau theory for statistical systems, we propose that neural activities can be captured by the U(1) dynamics, integrating the action potential and the "phase" of the neuron together. The gain function of the Hodgkin-Huxley neuron and the corresponding dynamical phase transitions can be described within the U(1) neuron framework. In addition, the phase dependence of the synaptic interactions is illustrated and the mapping to the Kinouchi-Copelli neuron is established. It suggests that the U(1) neuron is the minimal model for single-neuron activities and serves as the building block of the neuronal network for information processing.

Dynamics of phase oscillator networks with synaptic weight and structural plasticity

We study the dynamics of Kuramoto oscillator networks with two distinct adaptation processes, one varying the coupling strengths and the other altering the network structure. Such systems model certain networks of oscillatory neurons where the neuronal dynamics, synaptic weights, and network structure interact with and shape each other. We model synaptic weight adaptation with spike-timing-dependent plasticity (STDP) that runs on a longer time scale than neuronal spiking. Structural changes that include addition and elimination of contacts occur at yet a longer time scale than the weight adaptations. First, we study the steady-state dynamics of Kuramoto networks that are bistable and can settle in synchronized or desynchronized states. To compare the impact of adding structural plasticity, we contrast the network with only STDP to one with a combination of STDP and structural plasticity. We show that the inclusion of structural plasticity optimizes the synchronized state of a network by allowing for synchronization with fewer links than a network with STDP alone. With non-identical units in the network, the addition of structural plasticity leads to the emergence of correlations between the oscillators' natural frequencies and node degrees. In the desynchronized regime, the structural plasticity decreases the number of contacts, leading to a sparse network. In this way, adding structural plasticity strengthens both synchronized and desynchronized states of a network. Second, we use desynchronizing coordinated reset stimulation and synchronizing periodic stimulation to induce desynchronized and synchronized states, respectively. Our findings indicate that a network with a combination of STDP and structural plasticity may require stronger and longer stimulation to switch between the states than a network with STDP only.

A translational perspective on pathophysiological changes of oscillatory activity in dystonia and parkinsonism

Intracerebral recordings from movement disorders patients undergoing deep brain stimulation have allowed the identification of pathophysiological patterns in oscillatory activity that correlate with symptom severity. Changes in oscillatory synchrony occur within and across brain areas, matching the classification of movement disorders as network disorders. However, the underlying mechanisms of oscillatory changes are difficult to assess in patients, as experimental interventions are technically limited and ethically problematic. This is why animal models play an important role in neurophysiological research of movement disorders. In this review, we highlight the contributions of translational research to the mechanistic understanding of pathological changes in oscillatory activity, with a focus on parkinsonism and dystonia, while addressing the limitations of current findings and proposing possible future directions.

Long-Lasting Desynchronization of Plastic Neuronal Networks by Double-Random Coordinated Reset Stimulation

Hypersynchrony of neuronal activity is associated with several neurological disorders, including essential tremor and Parkinson's disease (PD). Chronic high-frequency deep brain stimulation (HF DBS) is the standard of care for medically refractory PD. Symptoms may effectively be suppressed by HF DBS, but return shortly after cessation of stimulation. Coordinated reset (CR) stimulation is a theory-based stimulation technique that was designed to specifically counteract neuronal synchrony by desynchronization. During CR, phase-shifted stimuli are delivered to multiple neuronal subpopulations. Computational studies on CR stimulation of plastic neuronal networks revealed long-lasting desynchronization effects obtained by down-regulating abnormal synaptic connectivity. This way, networks are moved into attractors of stable desynchronized states such that stimulation-induced desynchronization persists after cessation of stimulation. Preclinical and clinical studies confirmed corresponding long-lasting therapeutic and desynchronizing effects in PD. As PD symptoms are associated with different pathological synchronous rhythms, stimulation-induced long-lasting desynchronization effects should favorably be robust to variations of the stimulation frequency. Recent computational studies suggested that this robustness can be improved by randomizing the timings of stimulus deliveries. We study the long-lasting effects of CR stimulation with randomized stimulus amplitudes and/or randomized stimulus timing in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity. Performing computer simulations and analytical calculations, we study long-lasting desynchronization effects of CR with and without randomization of stimulus amplitudes alone, randomization of stimulus times alone as well as the combination of both. Varying the CR stimulation frequency (with respect to the frequency of abnormal target rhythm) and the number of separately stimulated neuronal subpopulations, we reveal parameter regions and related mechanisms where the two qualitatively different randomization mechanisms improve the robustness of long-lasting desynchronization effects of CR. In particular, for clinically relevant parameter ranges double-random CR stimulation, i.e., CR stimulation with the specific combination of stimulus amplitude randomization and stimulus time randomization, may outperform regular CR stimulation with respect to long-lasting desynchronization. In addition, our results provide the first evidence that an effective reduction of the overall stimulation current by stimulus amplitude randomization may improve the frequency robustness of long-lasting therapeutic effects of brain stimulation.

Local inhibition in a model of the indirect pathway globus pallidus network slows and deregularizes background firing, but sharpens and synchronizes responses to striatal input

The external segment of globus pallidus (GPe) is a network of oscillatory neurons connected by inhibitory synapses. We studied the intrinsic dynamic and the response to a shared brief inhibitory stimulus in a model GPe network. Individual neurons were simulated using a phase resetting model based on measurements from mouse GPe neurons studied in slices. The neurons showed a broad heterogeneity in their firing rates and in the shapes and sizes of their phase resetting curves. Connectivity in the network was set to match experimental measurements. We generated statistically equivalent neuron heterogeneity in a small-world model, in which 99% of connections were made with near neighbors and 1% at random, and in a model with entirely random connectivity. In both networks, the resting activity was slowed and made more irregular by the local inhibition, but it did not show any periodic pattern. Cross-correlations among neuron pairs were limited to directly connected neurons. When stimulated by a shared inhibitory input, the individual neuron responses separated into two groups: one with a short and stereotyped period of inhibition followed by a transient increase in firing probability, and the other responding with a sustained inhibition. Despite differences in firing rate, the responses of the first group of neurons were of fixed duration and were synchronized across cells.

The Origin of Abnormal Beta Oscillations in the Parkinsonian Corticobasal Ganglia Circuits

Parkinson's disease (PD) is a neurodegenerative brain disorder associated with motor and nonmotor symptoms. Exaggerated beta band (15–30 Hz) neuronal oscillations are widely observed in corticobasal ganglia (BG) circuits during parkinsonism. Abnormal beta oscillations have been linked to motor symptoms of PD, but their exact relationship is poorly understood. Nevertheless, reduction of beta oscillations can induce therapeutic effects in PD patients. While it is widely believed that the external globus pallidus (GPe) and subthalamic nucleus (STN) are jointly responsible for abnormal rhythmogenesis in the parkinsonian BG, the role of other cortico-BG circuits cannot be ignored. To shed light on the origin of abnormal beta oscillations in PD, here we review changes of neuronal activity observed in experimental PD models and discuss how the cortex and different BG nuclei cooperate to generate and stabilize abnormal beta oscillations during parkinsonism. This may provide further insights into the complex relationship between abnormal beta oscillations and motor dysfunction in PD, which is crucial for potential target-specific therapeutic interventions in PD patients.

Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology

Parkinson's disease (PD) is a multi-systemic neurodegenerative brain disorder. Motor symptoms of PD are linked to the significant dopamine (DA) loss in substantia nigra pars compacta (SNc) followed by basal ganglia (BG) circuit dysfunction. Increasing experimental and computational evidence indicates that (synaptic) plasticity plays a key role in the emergence of PD-related pathological changes following DA loss. Spike-timing-dependent plasticity (STDP) mediated by DA provides a mechanistic model for synaptic plasticity to modify synaptic connections within the BG according to the neuronal activity. To shed light on how DA-mediated STDP can shape neuronal activity and synaptic connectivity in the PD condition, we reviewed experimental and computational findings addressing the modulatory effect of DA on STDP as well as other plasticity mechanisms and discussed their potential role in PD pathophysiology and related network dynamics and connectivity. In particular, reshaping of STDP profiles together with other plasticity-mediated processes following DA loss may abnormally modify synaptic connections in competing pathways of the BG. The cascade of plasticity-induced maladaptive or compensatory changes can impair the excitation-inhibition balance towards the BG output nuclei, leading to the emergence of pathological activity-connectivity patterns in PD. Pre-clinical, clinical as well as computational studies reviewed here provide an understanding of the impact of synaptic plasticity and other plasticity mechanisms on PD pathophysiology, especially PD-related network activity and connectivity, after DA loss. This review may provide further insights into the abnormal structure-function relationship within the BG contributing to the emergence of pathological states in PD. Specifically, this review is intended to provide detailed information for the development of computational network models for PD, serving as testbeds for the development and optimization of invasive and non-invasive brain stimulation techniques. Computationally derived hypotheses may accelerate the development of therapeutic stimulation techniques and potentially reduce the number of related animal experiments.

Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations

Βeta oscillatory activity (human: 13-35 Hz; primate: 8-24 Hz) is pervasive within the cortex and basal ganglia. Studies in Parkinson's disease patients and animal models suggest that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine tone remains unclear. We recorded neural activity in the cortex and basal ganglia of healthy non-human primates while acutely and chronically up- and down-modulating dopamine levels. We assessed changes in beta oscillations in patients with Parkinson's following acute and chronic changes in dopamine tone. Here we show beta oscillation frequency is strongly coupled with dopamine tone in both monkeys and humans. Power, coherence between single-units and local field potentials (LFP), spike-LFP phase-locking, and phase-amplitude coupling are not systematically regulated by dopamine levels. These results demonstrate that beta frequency is a key property of pathological oscillations in cortical and basal ganglia networks.

The mouse cortico-basal ganglia-thalamic network

The cortico–basal ganglia–thalamo–cortical loop is one of the fundamental network motifs in the brain. Revealing its structural and functional organization is critical to understanding cognition, sensorimotor behaviour, and the natural history of many neurological and neuropsychiatric disorders. Classically, this network is conceptualized to contain three information channels: motor, limbic and associative^1–4. Yet this three-channel view cannot explain the myriad functions of the basal ganglia. We previously subdivided the dorsal striatum into 29 functional domains on the basis of the topography of inputs from the entire cortex⁵. Here we map the multi-synaptic output pathways of these striatal domains through the globus pallidus external part (GPe), substantia nigra reticular part (SNr), thalamic nuclei and cortex. Accordingly, we identify 14 SNr and 36 GPe domains and a direct cortico-SNr projection. The striatonigral direct pathway displays a greater convergence of striatal inputs than the more parallel striatopallidal indirect pathway, although direct and indirect pathways originating from the same striatal domain ultimately converge onto the same postsynaptic SNr neurons. Following the SNr outputs, we delineate six domains in the parafascicular and ventromedial thalamic nuclei. Subsequently, we identify six parallel cortico–basal ganglia–thalamic subnetworks that sequentially transduce specific subsets of cortical information through every elemental node of the cortico–basal ganglia–thalamic loop. Thalamic domains relay this output back to the originating corticostriatal neurons of each subnetwork in a bona fide closed loop.

Mesoscale connectomic mapping of the cortico–basal ganglia–thalamic network reveals key architectural and information processing features.

Treatment Tone Spacing and Acute Effects of Acoustic Coordinated Reset Stimulation in Tinnitus Patients

Acoustic coordinated reset (aCR) therapy for tinnitus aims to desynchronize neuronal populations in the auditory cortex that exhibit pathologically increased coincident firing. The original therapeutic paradigm involves fixed spacing of four low-intensity tones centered around the frequency of a tone matching the tinnitus pitch, f T , but it is unknown whether these tones are optimally spaced for induction of desynchronization. Computational and animal studies suggest that stimulus amplitude, and relatedly, spatial stimulation profiles, of coordinated reset pulses can have a major impact on the degree of desynchronization achievable. In this study, we transform the tone spacing of aCR into a scale that takes into account the frequency selectivity of the auditory system at each therapeutic tone's center frequency via a measure called the gap index. Higher gap indices are indicative of more loosely spaced aCR tones. The gap index was found to be a significant predictor of symptomatic improvement, with larger gap indices, i.e., more loosely spaced aCR tones, resulting in reduction of tinnitus loudness and annoyance scores in the acute stimulation setting. A notable limitation of this study is the intimate relationship of hearing impairment with the gap index. Particularly, the shape of the audiogram in the vicinity of the tinnitus frequency can have a major impact on tone spacing. However, based on our findings we suggest hypotheses-based experimental protocols that may help to disentangle the impact of hearing loss and tone spacing on clinical outcome, to assess the electrophysiologic correlates of clinical improvement, and to elucidate the effects following chronic rather than acute stimulation.

Long-Term Desynchronization by Coordinated Reset Stimulation in a Neural Network Model With Synaptic and Structural Plasticity

Several brain disorders are characterized by abnormal neuronal synchronization. To specifically counteract abnormal neuronal synchrony and, hence, related symptoms, coordinated reset (CR) stimulation was computationally developed. In principle, successive epochs of synchronizing and desynchronizing stimulation may reversibly move neural networks with plastic synapses back and forth between stable regimes with synchronized and desynchronized firing. Computationally derived predictions have been verified in pre-clinical and clinical studies, paving the way for novel therapies. However, as yet, computational models were not able to reproduce the clinically observed increase of desynchronizing effects of regularly administered CR stimulation intermingled by long stimulation-free epochs. We show that this clinically important phenomenon can be computationally reproduced by taking into account structural plasticity (SP), a mechanism that deletes or generates synapses in order to homeostatically adapt the firing rates of neurons to a set point-like target firing rate in the course of days to months. If we assume that CR stimulation favorably reduces the target firing rate of SP, the desynchronizing effects of CR stimulation increase after long stimulation-free epochs, in accordance with clinically observed phenomena. Our study highlights the pivotal role of stimulation- and dosing-induced modulation of homeostatic set points in therapeutic processes.

Long-Lasting Desynchronization Effects of Coordinated Reset Stimulation Improved by Random Jitters

Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands.

Revisiting the "Paradox of Stereotaxic Surgery": Insights Into Basal Ganglia-Thalamic Interactions

Basal ganglia dysfunction is implicated in movement disorders including Parkinson Disease, dystonia, and choreiform disorders. Contradicting standard "rate models" of basal ganglia-thalamic interactions, internal pallidotomy improves both hypo- and hyper-kinetic movement disorders. This "paradox of stereotaxic surgery" was recognized shortly after rate models were developed, and is underscored by the outcomes of deep brain stimulation (DBS) for movement disorders. Despite strong evidence that DBS activates local axons, the clinical effects of lesions and DBS are nearly identical. These observations argue against standard models in which GABAergic basal ganglia output gates thalamic activity, and raise the question of how lesions and stimulation can have similar effects. These paradoxes may be resolved by considering thalamocortical loops as primary drivers of motor output. Rather than suppressing or releasing cortex via motor thalamus, the basal ganglia may modulate the timing of thalamic perturbations to cortical activity. Motor cortex exhibits rotational dynamics during movement, allowing the same thalamocortical perturbation to affect motor output differently depending on its timing with respect to the rotational cycle. We review classic and recent studies of basal ganglia, thalamic, and cortical physiology to propose a revised model of basal ganglia-thalamocortical function with implications for basic physiology and neuromodulation.

Bilateral Intracranial Beta Activity During Forced and Spontaneous Movements in a 6-OHDA Hemi-PD Rat Model

Cortico-basal ganglia beta oscillations (13–30 Hz) are assumed to be involved in motor impairments in Parkinson’s Disease (PD), especially in bradykinesia and rigidity. Various studies have utilized the unilateral 6-hydroxydopamine (6-OHDA) rat PD model to further investigate PD and test novel treatments. However, a detailed behavioral and electrophysiological characterization of the model, including analyses of popular PD treatments such as DBS, has not been documented in the literature. We hence challenged the 6-OHDA rat hemi-PD model with a series of experiments (i.e., cylinder test, open field test, and rotarod test) aimed at assessing the motor impairments, analyzing the effects of Deep Brain Stimulation (DBS), and identifying under which conditions excessive beta oscillations occur. We found that 6-OHDA hemi-PD rats presented an impaired performance in all experiments compared to the sham group, and DBS could improve their overall performance. Across all the experiments and behaviors, the power in the high beta band was observed to be an important biomarker for PD as it showed differences between healthy and lesioned hemispheres and between 6-OHDA-lesioned and sham rats. This all shows that the 6-OHDA hemi-PD model accurately represents many of the motor and electrophysiological symptoms of PD and makes it a useful tool for the pre-clinical testing of new treatments when low β (13–21 Hz) and high β (21–30 Hz) frequency bands are considered separately.

Connectivity of EEG synchronization networks increases for Parkinson's disease patients with freezing of gait

Freezing of gait (FoG), a paroxysmal gait disturbance commonly experienced by patients with Parkinson's disease (PD), is characterized by sudden episodes of inability to generate effective forward stepping. Recent studies have shown an increase in beta frequency of local-field potentials in the basal-ganglia during FoG, however, comprehensive research on the synchronization between different brain locations and frequency bands in PD patients is scarce. Here, by developing tools based on network science and non-linear dynamics, we analyze synchronization networks of electroencephalography (EEG) brain waves of three PD patient groups with different FoG severity. We find higher EEG amplitude synchronization (stronger network links) between different brain locations as PD and FoG severity increase. These results are consistent across frequency bands (theta, alpha, beta, gamma) and independent of the specific motor task (walking, still standing, hand tapping) suggesting that an increase in severity of PD and FoG is associated with stronger EEG networks over a broad range of brain frequencies. This observation of a direct relationship of PD/FoG severity with overall EEG synchronization together with our proposed EEG synchronization network approach may be used for evaluating FoG propensity and help to gain further insight into PD and the pathophysiology leading to FoG.

Increasing Serotonin to Reduce Parkinsonian Tremor

While current dopamine-based drugs seem to be effective for most Parkinson's disease (PD) motor dysfunctions, they produce variable responsiveness for resting tremor. This lack of consistency could be explained by considering recent evidence suggesting that PD resting tremor can be divided into different partially overlapping phenotypes based on the dopamine response. These phenotypes may be associated with different pathophysiological mechanisms produced by a cortical-subcortical network involving even non-dopaminergic areas traditionally not directly related to PD. In this study, we propose a bio-constrained computational model to study the neural mechanisms underlying a possible type of PD tremor: the one mainly involving the serotoninergic system. The simulations run with the model demonstrate that a physiological serotonin increase can partially recover dopamine levels at the early stages of the disease before the manifestation of overt tremor. This result suggests that monitoring serotonin concentration changes could be critical for early diagnosis. The simulations also show the effectiveness of a new pharmacological treatment for tremor that acts on serotonin to recover dopamine levels. This latter result has been validated by reproducing existing data collected with human patients.

Altered Dynamic Information Flow through the Cortico-Basal Ganglia Pathways Mediates Parkinson's Disease Symptoms

Parkinson’s disease (PD) is a progressive neurodegenerative disorder caused by dopamine deficiency. To elucidate network-level changes through the cortico-basal ganglia pathways in PD, we recorded neuronal activity in PD monkeys treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. We applied electrical stimulation to the motor cortices and examined responses in the internal (GPi) and external (GPe) segments of the globus pallidus, the output and relay nuclei of the basal ganglia, respectively. In the normal state, cortical stimulation induced a triphasic response composed of early excitation, inhibition, and late excitation in the GPi and GPe. In the PD state, cortically evoked inhibition in the GPi mediated by the cortico-striato-GPi “direct” pathway was largely diminished, whereas late excitation in the GPe mediated by the cortico-striato-GPe-subthalamo (STN)-GPe pathway was elongated. l-DOPA treatment ameliorated PD signs, particularly akinesia/bradykinesia, and normalized cortically evoked responses in both the GPi and GPe. STN blockade by muscimol injection ameliorated the motor deficit and unmasked cortically evoked inhibition in the GPi. These results suggest that information flow through the direct pathway responsible for the initiation of movements is largely reduced in PD and fails to release movements, resulting in akinesia/bradykinesia. Restoration of the information flow through the direct pathway recovers execution of voluntary movements.

Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns

We have previously established that PV+ neurons and Npas1+ neurons are distinct neuron classes in the external globus pallidus (GPe): they have different topographical, electrophysiological, circuit, and functional properties. Aside from Foxp2+ neurons, which are a unique subclass within the Npas1+ class, we lack driver lines that effectively capture other GPe neuron subclasses. In this study, we examined the utility of Kcng4-Cre, Npr3-Cre, and Npy2r-Cre mouse lines (both males and females) for the delineation of GPe neuron subtypes. By using these novel driver lines, we have provided the most exhaustive investigation of electrophysiological studies of GPe neuron subtypes to date. Corroborating our prior studies, GPe neurons can be divided into two statistically distinct clusters that map onto PV+ and Npas1+ classes. By combining optogenetics and machine learning-based tracking, we showed that optogenetic perturbation of GPe neuron subtypes generated unique behavioral structures. Our findings further highlighted the dissociable roles of GPe neurons in regulating movement and anxiety-like behavior. We concluded that Npr3+ neurons and Kcng4+ neurons are distinct subclasses of Npas1+ neurons and PV+ neurons, respectively. Finally, by examining local collateral connectivity, we inferred the circuit mechanisms involved in the motor patterns observed with optogenetic perturbations. In summary, by identifying mouse lines that allow for manipulations of GPe neuron subtypes, we created new opportunities for interrogations of cellular and circuit substrates that can be important for motor function and dysfunction.SIGNIFICANCE STATEMENT Within the basal ganglia, the external globus pallidus (GPe) has long been recognized for its involvement in motor control. However, we lacked an understanding of precisely how movement is controlled at the GPe level as a result of its cellular complexity. In this study, by using transgenic and cell-specific approaches, we showed that genetically-defined GPe neuron subtypes have distinct roles in regulating motor patterns. In addition, the in vivo contributions of these neuron subtypes are in part shaped by the local, inhibitory connections within the GPe. In sum, we have established the foundation for future investigations of motor function and disease pathophysiology.

Mechanisms of Network Interactions for Flexible Cortico-Basal Ganglia-Mediated Action Control

In humans, finely tuned γ synchronization (60-90 Hz) rapidly appears at movement onset in a motor control network involving primary motor cortex, the basal ganglia and motor thalamus. Yet the functional consequences of brief movement-related synchronization are still unclear. Distinct synchronization phenomena have also been linked to different forms of motor inhibition, including relaxing antagonist muscles, rapid movement interruption and stabilizing network dynamics for sustained contractions. Here, I will introduce detailed hypotheses about how intrasite and intersite synchronization could interact with firing rate changes in different parts of the network to enable flexible action control. The here proposed cause-and-effect relationships shine a spotlight on potential key mechanisms of cortico-basal ganglia-thalamo-cortical (CBGTC) communication. Confirming or revising these hypotheses will be critical in understanding the neuronal basis of flexible movement initiation, invigoration and inhibition. Ultimately, the study of more complex cognitive phenomena will also become more tractable once we understand the neuronal mechanisms underlying behavioral readouts.

Periodic unitary synaptic currents in the mouse globus pallidus during spontaneous firing in slices

Neurons in the external globus pallidus (GPe) are autonomous pacemakers, but their spontaneous firing is continually perturbed by synaptic input. Because GPe neurons fire rhythmically in slices, spontaneous inhibitory synaptic currents (IPSCs) should be evident there. We identified periodic series of IPSCs in slices, each corresponding to unitary synaptic currents from one presynaptic cell. Optogenetic stimulation of the striatal indirect pathway axons caused a pause and temporal resetting of the periodic input, confirming that it arose from local neurons subject to striatal inhibition. We determined the firing statistics of the presynaptic neurons from the unitary IPSC statistics and estimated their frequencies, peak amplitudes, and reliabilities. To determine what types of GPe neurons received the spontaneous inhibition, we recorded from genetically labeled parvalbumin (PV) and Npas1-expressing neurons. Both cell types received periodic spontaneous IPSCs with similar frequencies. Optogenetic inhibition of PV neurons reduced the spontaneous IPSC rate in almost all neurons with active unitary inputs, whereas inhibition of Npas1 neurons rarely affected the spontaneous IPSC rate in any neurons. These results suggest that PV neurons provided most of the active unitary inputs to both cell types. Optogenetic pulse stimulation of PV neurons at light levels that can activate cut axons yielded an estimate of connectivity in the fully connected network. The local network is a powerful source of inhibition to both PV and Npas1 neurons, which contributes to irregular firing and may influence the responses to external synaptic inputs.NEW & NOTEWORTHY Brain circuits are often quiet in slices. In the globus pallidus, network activity continues because of the neurons' rhythmic autonomous firing. In this study, synaptic currents generated by the network barrage were measured in single neurons. Unitary synaptic currents arising from single presynaptic neurons were identified by their unique periodicity. Periodic synaptic currents were large and reliable, even at the cell's natural firing rates, but arose from a small number of other globus pallidus neurons.

Long-Lasting Desynchronization of Plastic Neural Networks by Random Reset Stimulation

Excessive neuronal synchrony is a hallmark of neurological disorders such as epilepsy and Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency (HF) deep brain stimulation (DBS). However, symptoms return shortly after cessation of HF-DBS. Recently developed decoupling stimulation approaches, such as Random Reset (RR) stimulation, specifically target pathological connections to achieve long-lasting desynchronization. During RR stimulation, a temporally and spatially randomized stimulus pattern is administered. However, spatial randomization, as presented so far, may be difficult to realize in a DBS-like setup due to insufficient spatial resolution. Motivated by recently developed segmented DBS electrodes with multiple stimulation sites, we present a RR stimulation protocol that copes with the limited spatial resolution of currently available depth electrodes for DBS. Specifically, spatial randomization is realized by delivering stimuli simultaneously to L randomly selected stimulation sites out of a total of M stimulation sites, which will be called L/M-RR stimulation. We study decoupling by L/M-RR stimulation in networks of excitatory integrate-and-fire neurons with spike-timing dependent plasticity by means of theoretical and computational analysis. We find that L/M-RR stimulation yields parameter-robust decoupling and long-lasting desynchronization. Furthermore, our theory reveals that strong high-frequency stimulation is not suitable for inducing long-lasting desynchronization effects. As a consequence, low and high frequency L/M-RR stimulation affect synaptic weights in qualitatively different ways. Our simulations confirm these predictions and show that qualitative differences between low and high frequency L/M-RR stimulation are present across a wide range of stimulation parameters, rendering stimulation with intermediate frequencies most efficient. Remarkably, we find that L/M-RR stimulation does not rely on a high spatial resolution, characterized by the density of stimulation sites in a target area, corresponding to a large M. In fact, L/M-RR stimulation with low resolution performs even better at low stimulation amplitudes. Our results provide computational evidence that L/M-RR stimulation may present a way to exploit modern segmented lead electrodes for long-lasting therapeutic effects.

Parkinsonism Alters Beta Burst Dynamics across the Basal Ganglia-Motor Cortical Network

Elevated synchronized oscillatory activity in the beta band has been hypothesized to be a pathophysiological marker of Parkinson's disease (PD). Recent studies have suggested that parkinsonism is closely associated with increased amplitude and duration of beta burst activity in the subthalamic nucleus (STN). How beta burst dynamics are altered from the normal to parkinsonian state across the basal ganglia-thalamocortical (BGTC) motor network, however, remains unclear. In this study, we simultaneously recorded local field potential activity from the STN, internal segment of the globus pallidus (GPi), and primary motor cortex (M1) in three female rhesus macaques, and characterized how beta burst activity changed as the animals transitioned from normal to progressively more severe parkinsonian states. Parkinsonism was associated with an increased incidence of beta bursts with longer duration and higher amplitude in the low beta band (8-20 Hz) in both the STN and GPi, but not in M1. We observed greater concurrence of beta burst activity, however, across all recording sites (M1, STN, and GPi) in PD. The simultaneous presence of low beta burst activity across multiple nodes of the BGTC network that increased with severity of PD motor signs provides compelling evidence in support of the hypothesis that low beta synchronized oscillations play a significant role in the underlying pathophysiology of PD. Given its immersion throughout the motor circuit, we hypothesize that this elevated beta-band activity interferes with spatial-temporal processing of information flow in the BGTC network that contributes to the impairment of motor function in PD.SIGNIFICANCE STATEMENT This study fills a knowledge gap regarding the change in temporal dynamics and coupling of beta burst activity across the basal ganglia-thalamocortical (BGTC) network during the evolution from normal to progressively more severe parkinsonian states. We observed that changes in beta oscillatory activity occur throughout BGTC and that increasing severity of parkinsonism was associated with a higher incidence of longer duration, higher amplitude low beta bursts in the basal ganglia, and increased concurrence of beta bursts across the subthalamic nucleus, globus pallidus, and motor cortex. These data provide new insights into the potential role of changes in the temporal dynamics of low beta activity within the BGTC network in the pathogenesis of Parkinson's disease.

Closed-Loop neuromodulation for clustering neuronal populations

Pathological synchronization of neurons is associated with symptoms of movement disorders, such as Parkinson's disease and essential tremor. High-frequency deep brain stimulation (DBS) suppresses symptoms, presumably through the desynchronization of neurons. Coordinated reset (CR) delivers trains of high-frequency stimuli to different regions in the brain through multiple electrodes and may have more persistent therapeutic effects than conventional DBS. As an alternative to CR, we present a closed-loop control setup that desynchronizes neurons in brain slices by inducing clusters using a single electrode. Our setup uses calcium fluorescence imaging to extract carbachol-induced neuronal oscillations in real time. To determine the appropriate stimulation waveform for inducing clusters in a population of neurons, we calculate the phase of the neuronal populations and then estimate the phase response curve (PRC) of those populations to electrical stimulation. The phase and PRC are then fed into a control algorithm called the input of maximal instantaneous efficiency (IMIE). By using IMIE, the synchrony across the slice is decreased by dividing the population of neurons into subpopulations without suppressing the oscillations locally. The desynchronization effect is persistent 10 s after stimulation is stopped. The IMIE control algorithm may be used as a novel closed-loop DBS approach to suppress the symptoms of Parkinson's disease and essential tremor by inducing clusters with a single electrode.NEW & NOTEWORTHY Here, we present a closed-loop controller to desynchronize neurons in brain slices by inducing clusters using a single electrode using calcium imaging feedback. Phase of neurons are estimated in real time, and from the phase response curve stimulation is applied to achieve target phase differences. This method is an alternative to coordinated reset and is a novel therapy that could be used to disrupt synchronous neuronal oscillations thought to be the mechanism underlying Parkinson's disease.

Differential Synaptic Input to External Globus Pallidus Neuronal Subpopulations In Vivo

The rodent external globus pallidus (GPe) contains two main neuronal subpopulations, prototypic and arkypallidal cells, which differ in their cellular properties. Their functional synaptic connectivity is largely unknown. Here we studied the membrane properties, synaptic inputs, and sensory responses of these subpopulations in the mouse GPe. We performed in vivo whole-cell recordings in GPe neurons and used optogenetic stimulation to dissect their afferent inputs from the striatum and subthalamic nucleus (STN). Both GPe subpopulations received barrages of excitatory and inhibitory inputs during slow wave activity and responded to sensory stimulation with distinct multiphasic patterns. Prototypic cells synaptically inhibited arkypallidal and prototypic cells. Both GPe subpopulations received synaptic input from STN and striatal medium spiny neurons (MSNs). Although STN and indirect pathway MSNs strongly targeted prototypic cells, direct pathway MSNs selectively inhibited arkypallidal cells. We show that GPe subtypes have distinct connectivity patterns that underlie their respective functional roles.

A case study of foliglurax, the first clinical mGluR4 PAM for symptomatic treatment of Parkinson's disease: translational gaps or a failing industry innovation model?

INTRODUCTION

Approximately 40% of Parkinson's disease (PD) patients that take mostly dopamine receptor agonists for motor fluctuations, experience the return of symptoms between regular doses. This is a phenomenon known as 'OFF periods.' Positive allosteric modulators (PAMs) of metabotropic glutamate receptor 4 (mGluR4) are a promising non-dopaminergic mechanism with potential to address the unmet need of patients suffering from OFF periods. Foliglurax is the first mGluR4 PAM that has advanced into clinical testing in PD patients.

AREAS COVERED

We summarize the chemistry, pharmacokinetics, and preclinical pharmacology of foliglurax. Translational PET imaging studies, clinical efficacy data, and a competitive landscape analysis of available therapies are presented to the readers. In this Perspective article, foliglurax is used as a case study to illustrate the inherent R&D challenges that companies face when developing drugs. These challenges include the delivery of drugs acting through novel mechanisms, long-term scientific investment, and commercial success and shorter-term positive financial returns.

EXPERT OPINION

Failure to meet the primary and secondary endpoints in a Phase 2 study led Lundbeck to discontinue the development of foliglurax. Understanding the evidence supporting compound progression into Phase 2 will enable the proper assessment of the therapeutic potential of mGluR4 PAMs.

Miniaturized Intracerebral Potential Recorder for Long-Term Local Field Potential of Deep Brain Signals

A miniaturized intracerebral potential recorder for long-term local field potential (LFP) of deep brain signals is proposed. LFP can be recorded by deep brain electrodes. The abnormal beta-band oscillation of LFP in subthalamic nucleus and internal globus pallidus in patients with Parkinson's disease (PD) are associated with the severity of the symptoms. The LFP signal from patients who have been implanted with deep brain electrode can be monitored by our system for at least 24 hours in real time. Graphical user interface has also been developed for use by medical personnel. Imitation experiments and in vivo experiments were performed to successfully verify that our system can measure LFP signals. With 24-hour intracerebral signals, researchers can analyze what is happened in the brain in daily life. In the future, more effective PD treatment can be developed, such as intelligent closed-loop deep brain stimulation.

Neural activity during a simple reaching task in macaques is counter to gating and rebound in basal ganglia-thalamic communication

Task-related activity in the ventral thalamus, a major target of basal ganglia output, is often assumed to be permitted or triggered by changes in basal ganglia activity through gating- or rebound-like mechanisms. To test those hypotheses, we sampled single-unit activity from connected basal ganglia output and thalamic nuclei (globus pallidus-internus [GPi] and ventrolateral anterior nucleus [VLa]) in monkeys performing a reaching task. Rate increases were the most common peri-movement change in both nuclei. Moreover, peri-movement changes generally began earlier in VLa than in GPi. Simultaneously recorded GPi-VLa pairs rarely showed short-time-scale spike-to-spike correlations or slow across-trials covariations, and both were equally positive and negative. Finally, spontaneous GPi bursts and pauses were both followed by small, slow reductions in VLa rate. These results appear incompatible with standard gating and rebound models. Still, gating or rebound may be possible in other physiological situations: simulations show how GPi-VLa communication can scale with GPi synchrony and GPi-to-VLa convergence, illuminating how synchrony of basal ganglia output during motor learning or in pathological conditions may render this pathway effective. Thus, in the healthy state, basal ganglia-thalamic communication during learned movement is more subtle than expected, with changes in firing rates possibly being dominated by a common external source.

Cortico-Striatal Oscillations Are Correlated to Motor Activity Levels in Both Physiological and Parkinsonian Conditions

Oscillatory neural activity in the cortico-basal ganglia-thalamocortical (CBGTC) loop is associated with the motor state of a subject, but also with the availability of modulatory neurotransmitters. For example, increased low-frequency oscillations in Parkinson’s disease (PD) are related to decreased levels of dopamine and have been proposed as biomarkers to adapt and optimize therapeutic interventions, such as deep brain stimulation. Using neural oscillations as biomarkers require differentiating between changes in oscillatory patterns associated with parkinsonism vs. those related to a subject’s motor state. To address this point, we studied the correlation between neural oscillatory activity in the motor cortex and striatum and varying degrees of motor activity under normal and parkinsonian conditions. Using rats with bilateral or unilateral 6-hydroxydopamine lesions as PD models, we correlated the motion index (MI)—a measure based on the physical acceleration of the head of rats—to the local field potential (LFP) oscillatory power in the 1–80 Hz range. In motor cortices and striata, we observed a robust correlation between the motion index and the oscillatory power in two main broad frequency ranges: a low-frequency range [5.0–26.5 Hz] was negatively correlated to motor activity, whereas a high-frequency range [35.0–79.9 Hz] was positively correlated. We observed these correlations in both normal and parkinsonian conditions. In addition to these general changes in broad-band power, we observed a more restricted narrow-band oscillation [25–40 Hz] in dopamine-denervated hemispheres. This oscillation, which seems to be selective to the parkinsonian state, showed a linear frequency dependence on the concurrent motor activity level. We conclude that, independently of the parkinsonian condition, changes in broad-band oscillatory activities of cortico-basal ganglia networks (including changes in the relative power of low- and high-frequency bands) are closely correlated to ongoing motions, most likely reflecting he operations of these neural circuits to control motor activity. Hence, biomarkers based on neural oscillations should focus on specific features, such as narrow frequency bands, to allow differentiation between parkinsonian states and physiological movement-dependent circuit modulation.

Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces

A deep brain stimulation system capable of closed-loop neuromodulation is a type of bidirectional deep brain-computer interface (dBCI), in which neural signals are recorded, decoded, and then used as the input commands for neuromodulation at the same site in the brain. The challenge in assuring successful implementation of bidirectional dBCIs in Parkinson's disease (PD) is to discover and decode stable, robust and reliable neural inputs that can be tracked during stimulation, and to optimize neurostimulation patterns and parameters (control policies) for motor behaviors at the brain interface, which are customized to the individual. In this perspective, we will outline the work done in our lab regarding the evolution of the discovery of neural and behavioral control variables relevant to PD, the development of a novel personalized dual-threshold control policy relevant to the individual's therapeutic window and the application of these to investigations of closed-loop STN DBS driven by neural or kinematic inputs, using the first generation of bidirectional dBCIs.

Weakly correlated activity of pallidal neurons in behaving monkeys

The basal ganglia play a crucial role in the control of voluntary movements. Neurons in both the external and internal segments of the globus pallidus, the connecting and output nuclei of the basal ganglia, respectively, change their firing rates in relation to movements. Firing rate changes of movement-related neurons seem to convey signals for motor control. On the other hand, coincident spikes among neurons, that is, correlated activity, may also contribute to motor control. To address this issue, we first identified multiple pallidal neurons receiving inputs from the forelimb regions of the primary motor cortex and supplementary motor area, recorded neuronal activity of these neurons simultaneously, and analyzed their spike correlations while monkeys performed a hand-reaching task. Most (79%) pallidal neurons exhibited task-related firing rate changes, whereas only a small fraction (20%) showed significant but small and short correlated activity during the task performance. These results suggest that motor control signals are conveyed primarily by firing rate changes in the external and internal segments of the globus pallidus and that the contribution of correlated activity may play only a minor role in the healthy state.