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

Increased [18F]Fluorodeoxyglucose Uptake in the Left Pallidum in Military Veterans with Blast-Related Mild Traumatic Brain Injury: Potential as an Imaging Biomarker and Mediation with Executive Dysfunction and Cognitive Impairment

Blast-related mild traumatic brain injury (blast-mTBI) can result in a spectrum of persistent symptoms leading to substantial functional impairment and reduced quality of life. Clinical evaluation and discernment from other conditions common to military service can be challenging and subject to patient recall bias and the limitations of available assessment measures. The need for objective biomarkers to facilitate accurate diagnosis, not just for symptom management and rehabilitation but for prognostication and disability compensation purposes is clear. Toward this end, we compared regional brain [18F]fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET) intensity-scaled uptake measurements and motor, neuropsychological, and behavioral assessments in 79 combat Veterans with retrospectively recalled blast-mTBI with 41 control participants having no lifetime history of TBI. Using an agnostic and unbiased approach, we found significantly increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI versus control participants, p < 0.0001; q = 3.29 × 10-9 [Cohen's d, 1.38, 95% confidence interval (0.96, 1.79)]. The degree of left pallidum [18F]FDG-uptake correlated with the number of self-reported blast-mTBIs, r2 = 0.22; p < 0.0001. Greater [18F]FDG-uptake in the left pallidum provided excellent discrimination between Veterans with blast-mTBI and controls, with a receiver operator characteristic area under the curve of 0.859 (p < 0.0001) and likelihood ratio of 21.19 (threshold:SUVR ≥ 0.895). Deficits in executive function assessed using the Behavior Rating Inventory of Executive Function-Adult Global Executive Composite T-score were identified in Veterans with blast-mTBI compared with controls, p < 0.0001. Regression-based mediation analyses determined that in Veterans with blast-mTBI, increased [18F]FDG-uptake in the left pallidum-mediated executive function impairments, adjusted causal mediation estimate p = 0.021; total effect estimate, p = 0.039. Measures of working and prospective memory (Auditory Consonant Trigrams test and Memory for Intentions Test, respectively) were negatively correlated with left pallidum [18F]FDG-uptake, p < 0.0001, with mTBI as a covariate. Increased left pallidum [18F]FDG-uptake in Veterans with blast-mTBI compared with controls did not covary with dominant handedness or with motor activity assessed using the Unified Parkinson's Disease Rating Scale. Localized increased [18F]FDG-uptake in the left pallidum may reflect a compensatory response to functional deficits following blast-mTBI. Limited imaging resolution does not allow us to distinguish subregions of the pallidum; however, the significant correlation of our data with behavioral but not motor outcomes suggests involvement of the ventral pallidum, which is known to regulate motivation, behavior, and emotions through basal ganglia-thalamo-cortical circuits. Increased [18F]FDG-uptake in the left pallidum in blast-mTBI versus control participants was consistently identified using two different PET scanners, supporting the generalizability of this finding. Although confirmation of our results by single-subject-to-cohort analyses will be required before clinical deployment, this study provides proof of concept that [18F]FDG-PET bears promise as a readily available noninvasive biomarker for blast-mTBI. Further, our findings support a causative relationship between executive dysfunction and increased [18F]FDG-uptake in the left pallidum.

Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture

Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or 'oscillatoriness' per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantification of rhythmicity. We applied pACF to human intracerebral stereoelectroencephalography (SEEG) and magnetoencephalography (MEG) data and uncovered a spectrally and anatomically fine-grained cortical architecture in the rhythmicity of single- and multi-frequency neuronal oscillations. Evidencing the functional significance of rhythmicity, we found it to be a prerequisite for long-range synchronization in resting-state networks and to be dynamically modulated during event-related processing. We also extended the pACF approach to measure 'burstiness' of oscillatory processes and characterized regions with stable and bursty oscillations. These findings show that rhythmicity is double-dissociable from amplitude and constitutes a functionally relevant and dynamic characteristic of neuronal oscillations.

Functional interaction of abnormal beta and gamma oscillations on bradykinesia in parkinsonian rats

Bradykinesia, a debilitating symptom characterized by impaired movement initiation and reduced speed in Parkinson's disease (PD), is associated with abnormal oscillatory activity in the motor cortex-basal ganglia circuit. We investigated the interplay between abnormal beta and gamma oscillations in relation to bradykinesia in parkinsonian rats. Our findings showed reduced movement activities in parkinsonian rats, accompanied by enhanced high beta oscillations in the motor cortex, which are closely associated with movement transitional difficulties. Additionally, gamma oscillations correlated with movement velocity in control rats but not in parkinsonian rats. We observed selective coupling between high beta oscillation phase and gamma oscillation amplitude in PD, as well as cortical high beta-broadband gamma phase-amplitude coupling (PAC) negatively influencing locomotor activities in control and PD rats. These findings suggest a collaborative role of cortical beta and gamma oscillations in facilitating movement execution, with beta oscillations being linked to movement initiation and gamma oscillations associated with movement speed. Importantly, the aberrant alterations of these oscillations are closely related to the development of bradykinesia. Furthermore, PAC hold promise as a biomarker for comprehensive assessment of movement performance in PD.

Neurophysiological treatment effects of mesdopetam, pimavanserin and clozapine in a rodent model of Parkinson's disease psychosis

Psychosis in Parkinson's disease is a common phenomenon associated with poor outcomes. To clarify the pathophysiology of this condition and the mechanisms of antipsychotic treatments, we have here characterized the neurophysiological brain states induced by clozapine, pimavanserin, and the novel prospective antipsychotic mesdopetam in a rodent model of Parkinson's disease psychosis, based on chronic dopaminergic denervation by 6-OHDA lesions, levodopa priming, and the acute administration of an NMDA antagonist. Parallel recordings of local field potentials from eleven cortical and sub-cortical regions revealed shared neurophysiological treatment effects for the three compounds, despite their different pharmacological profiles, involving reversal of features associated with the psychotomimetic state, such as a reduction of aberrant high-frequency oscillations in prefrontal structures together with a decrease of abnormal synchronization between different brain regions. Other drug-induced neurophysiological features were more specific to each treatment, affecting network oscillation frequencies and entropy, pointing to discrete differences in mechanisms of action. These findings indicate that neurophysiological characterization of brain states is particularly informative when evaluating therapeutic mechanisms in conditions involving symptoms that are difficult to assess in rodents such as psychosis, and that mesdopetam should be further explored as a potential novel antipsychotic treatment option for Parkinson psychosis.

Application of diffusional kurtosis imaging for insights into structurally aberrant topology in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) has been regarded as a disconnection syndrome with functional and structural disturbances. However, as the anatomic determinants, the structural disconnections in PD have yet to be fully elucidated.

PURPOSE

To non-invasively construct structural networks based on microstructural complexity and to further investigate their potential topological abnormalities in PD given the technical superiority of diffusion kurtosis imaging (DKI) to the quantification of microstructure.

MATERIAL AND METHODS

The microstructural data of gray matter in both the PD group and the healthy control (HC) group were acquired using DKI. The structural networks were constructed at the group level by a covariation approach, followed by the calculation of topological properties based on graph theory and statistical comparisons between groups.

RESULTS

A total of 51 patients with PD and 50 HCs were enrolled. Individuals were matched between groups with respect to demographic characteristics (P >0.05). The constructed structural networks in both the PD and HC groups featured small-world properties. In comparison with the HC group, the PD group exhibited significantly altered global properties, with higher normalized characteristic path lengths, clustering coefficients, local efficiency values, and characteristic path lengths and lower global efficiency values (P <0.05). In terms of nodal centralities, extensive nodal disruptions were observed in patients with PD (P <0.05); these disruptions were mainly distributed in the sensorimotor network, default mode network, frontal-parietal network, visual network, and subcortical network.

CONCLUSION

These findings contribute to the technical application of DKI and the elucidation of disconnection syndrome in PD.

A neurorobotics approach to behaviour selection based on human activity recognition

Behaviour selection has been an active research topic for robotics, in particular in the field of human-robot interaction. For a robot to interact autonomously and effectively with humans, the coupling between techniques for human activity recognition and robot behaviour selection is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting an initial neurorobotics model that embeds, in a simulated robot, computational models of parts of the mammalian brain that resembles neurophysiological aspects of the basal ganglia-thalamus-cortex (BG-T-C) circuit, coupled with human activity recognition techniques. A robotics simulation environment was developed for assessing the model, where a mobile robot accomplished tasks by using behaviour selection in accordance with the activity being performed by the inhabitant of an intelligent home. Initial results revealed that the initial neurorobotics model is advantageous, especially considering the coupling between the most accurate activity recognition approaches and the computational models of more complex animals.

The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates

Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.

Neural oscillatory characteristics of feedback-associated activity in globus pallidus interna

Neural oscillatory activities in basal ganglia have prominent roles in cognitive processes. However, the characteristics of oscillatory activities during cognitive tasks have not been extensively explored in human Globus Pallidus internus (GPi). This study aimed to compare oscillatory characteristics of GPi between dystonia and Parkinson's Disease (PD). A dystonia and a PD patient performed the Intra-Extra-Dimension shift (IED) task during both on and off-medication states. During the IED task, patients had to correctly choose between two visual stimuli containing shapes or lines based on a hidden rule via trial and error. Immediate auditory and visual feedback was provided upon the choice to inform participants if they chose correctly. Bilateral GPi Local Field Potentials (LFP) activity was recorded via externalized DBS leads. Transient high gamma activity (~ 100-150 Hz) was observed immediately after feedback in the dystonia patient. Moreover, these bursts were phase synchronous between left and right GPi with an antiphase clustering of phase differences. In contrast, no synchronous high gamma activity was detected in the PD patient with or without dopamine administration. The off-med PD patient also displayed enhanced low frequency clusters, which were ameliorated by medication. The current study provides a rare report of antiphase homotopic synchrony in human GPi, potentially related to incorporating and processing feedback information. The absence of these activities in off and on-med PD patient indicates the potential presence of impaired medication independent feedback processing circuits. Together, these findings suggest a potential role for GPi's synchronized activity in shaping feedback processing mechanisms required in cognitive tasks.

Photophysical Mechanisms of Photobiomodulation Therapy as Precision Medicine

Despite a significant focus on the photochemical and photoelectrical mechanisms underlying photobiomodulation (PBM), its complex functions are yet to be fully elucidated. To date, there has been limited attention to the photophysical aspects of PBM. One effect of photobiomodulation relates to the non-visual phototransduction pathway, which involves mechanotransduction and modulation to cytoskeletal structures, biophotonic signaling, and micro-oscillatory cellular interactions. Herein, we propose a number of mechanisms of PBM that do not depend on cytochrome c oxidase. These include the photophysical aspects of PBM and the interactions with biophotons and mechanotransductive processes. These hypotheses are contingent on the effect of light on ion channels and the cytoskeleton, the production of biophotons, and the properties of light and biological molecules. Specifically, the processes we review are supported by the resonant recognition model (RRM). This previous research demonstrated that protein micro-oscillations act as a signature of their function that can be activated by resonant wavelengths of light. We extend this work by exploring the local oscillatory interactions of proteins and light because they may affect global body circuits and could explain the observed effect of PBM on neuro-cortical electroencephalogram (EEG) oscillations. In particular, since dysrhythmic gamma oscillations are associated with neurodegenerative diseases and pain syndromes, including migraine with aura and fibromyalgia, we suggest that transcranial PBM should target diseases where patients are affected by impaired neural oscillations and aberrant brain wave patterns. This review also highlights examples of disorders potentially treatable with precise wavelengths of light by mimicking protein activity in other tissues, such as the liver, with, for example, Crigler-Najjar syndrome and conditions involving the dysregulation of the cytoskeleton. PBM as a novel therapeutic modality may thus behave as "precision medicine" for the treatment of various neurological diseases and other morbidities. The perspectives presented herein offer a new understanding of the photophysical effects of PBM, which is important when considering the relevance of PBM therapy (PBMt) in clinical applications, including the treatment of diseases and the optimization of health outcomes and performance.

Distinctive Effects of D1 and D2 Receptor Agonists on Cortico-Basal Ganglia Oscillations in a Rodent Model of L-DOPA-Induced Dyskinesia

L-DOPA-induced dyskinesia (LID) in Parkinson's disease has been linked to oscillatory neuronal activities in the cortico-basal ganglia network. We set out to examine the pattern of cortico-basal ganglia oscillations induced by selective agonists of D1 and D2 receptors in a rat model of LID. Local field potentials were recorded in freely moving rats using large-scale electrodes targeting three motor cortical regions, dorsomedial and dorsolateral striatum, external globus pallidus, and substantial nigra pars reticulata. Abnormal involuntary movements were elicited by the D1 agonist SKF82958 or the D2 agonist sumanirole, while overall motor activity was quantified using video analysis (DeepLabCut). Both SKF82958 and sumanirole induced dyskinesia, although with significant differences in temporal course, overall severity, and body distribution. The D1 agonist induced prominent narrowband oscillations in the high gamma range (70-110 Hz) in all recorded structures except for the nigra reticulata. Additionally, the D1 agonist induced strong functional connectivity between the recorded structures and the phase analysis revealed that the primary motor cortex (forelimb area) was leading a supplementary motor area and striatum. Following treatment with the D2 agonist, narrowband gamma oscillations were detected only in forelimb motor cortex and dorsolateral striatum, while prominent oscillations in the theta band occurred in the globus pallidus and nigra reticulata. Our results reveal that the dyskinetic effects of D1 and D2 receptor agonists are associated with distinct patterns of cortico-basal ganglia oscillations, suggesting a recruitment of partially distinct networks.

Cortical mechanisms of sensory trick in cervical dystonia

Patients with cervical dystonia (CD) often show an improvement in dystonic posture after sensory trick (ST), though the mechanisms underlying ST remain unclear. In this study, we aimed to investigate the effects of ST on cortical activity in patients with CD and to explore the contribution of motor and sensory components to ST mechanisms. To this purpose, we studied 15 CD patients with clinically effective ST, 17 without ST, and 14 healthy controls (HCs) who mimicked the ST. We used electroencephalographic (EEG) recordings and electromyography (EMG) data from bilateral sternocleidomastoid (SCM) muscles. We compared ST-related EEG spectral changes from sensorimotor and posterior parietal areas and EMG power changes between groups. To better understand the contribution of motor and sensory components to ST, we tested EEG and EMG correlates of three different conditions mimicking ST, the first without skin touch ("no touch" condition), the second without voluntary movements ("passive" condition), and finally without arm movements ("examiner touch" condition). Results showed ST-related alpha desynchronization in the sensorimotor cortex and theta desynchronization in the sensorimotor and posterior parietal cortex. Both spectral changes were more significant during maneuver execution in CD patients with ST than in CD patients without ST and HCs who mimicked the ST. Differently, the "no touch", "passive", or "examiner touch" conditions did not show significant differences in EEG or EMG changes determined by ST execution/mimicking between CD patients with or without ST. A higher desynchronization within alpha and theta bands in the sensorimotor and posterior parietal areas correlated with a more significant activity decrease in the contralateral SCM muscle, Findings from this study suggest that ST-related changes in the activity of sensorimotor and posterior parietal areas may restore dystonic posture and that both motor and sensory components contribute to the ST effect.

Transmission of delta band (0.5-4 Hz) oscillations from the globus pallidus to the substantia nigra pars reticulata in dopamine depletion

Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.

Neuronal oscillations predict deep brain stimulation outcome in Parkinson's disease

BACKGROUND

Neuronal oscillations are linked to symptoms of Parkinson's disease. This relation can be exploited for optimizing deep brain stimulation (DBS), e.g. by informing a device or human about the optimal location, time and intensity of stimulation. Whether oscillations predict individual DBS outcome is not clear so far.

OBJECTIVE

To predict motor symptom improvement from subthalamic power and subthalamo-cortical coherence.

METHODS

We applied machine learning techniques to simultaneously recorded magnetoencephalography and local field potential data from 36 patients with Parkinson's disease. Gradient-boosted tree learning was applied in combination with feature importance analysis to generate and understand out-of-sample predictions.

RESULTS

A few features sufficed for making accurate predictions. A model operating on five coherence features, for example, achieved correlations of r > 0.8 between actual and predicted outcomes. Coherence comprised more information in less features than subthalamic power, although in general their information content was comparable. Both signals predicted akinesia/rigidity reduction best. The most important local feature was subthalamic high-beta power (20-35 Hz). The most important connectivity features were subthalamo-parietal coherence in the very high frequency band (>200 Hz) and subthalamo-parietal coherence in low-gamma band (36-60 Hz). Successful prediction was not due to the model inferring distance to target or symptom severity from neuronal oscillations.

CONCLUSION

This study demonstrates for the first time that neuronal oscillations are predictive of DBS outcome. Coherence between subthalamic and parietal oscillations are particularly informative. These results highlight the clinical relevance of inter-areal synchrony in basal ganglia-cortex loops and might facilitate further improvements of DBS in the future.

The Dopamine System and Automatization of Movement Sequences: A Review With Relevance for Speech and Stuttering

The last decades of research have gradually elucidated the complex functions of the dopamine system in the vertebrate brain. The multiple roles of dopamine in motor function, learning, attention, motivation, and the emotions have been difficult to reconcile. A broad and detailed understanding of the physiology of cerebral dopamine is of importance in understanding a range of human disorders. One of the core functions of dopamine involves the basal ganglia and the learning and execution of automatized sequences of movements. Speech is one of the most complex and highly automatized sequential motor behaviors, though the exact roles that the basal ganglia and dopamine play in speech have been difficult to determine. Stuttering is a speech disorder that has been hypothesized to be related to the functions of the basal ganglia and dopamine. The aim of this review was to provide an overview of the current understanding of the cerebral dopamine system, in particular the mechanisms related to motor learning and the execution of movement sequences. The primary aim was not to review research on speech and stuttering, but to provide a platform of neurophysiological mechanisms, which may be utilized for further research and theoretical development on speech, speech disorders, and other behavioral disorders. Stuttering and speech are discussed here only briefly. The review indicates that a primary mechanism for the automatization of movement sequences is the merging of isolated movements into chunks that can be executed as units. In turn, chunks can be utilized hierarchically, as building blocks of longer chunks. It is likely that these mechanisms apply also to speech, so that frequent syllables and words are produced as motor chunks. It is further indicated that the main learning principle for sequence learning is reinforcement learning, with the phasic release of dopamine as the primary teaching signal indicating successful sequences. It is proposed that the dynamics of the dopamine system constitute the main neural basis underlying the situational variability of stuttering.

Device profile of the percept PC deep brain stimulation system for the treatment of Parkinson's disease and related disorders

INTRODUCTION

Several software and hardware advances in the field of deep brain stimulation (DBS) have been realized in recent years and devices from three manufacturers are available. The Percept™ PC platform (Medtronic, Inc.) enables brain sensing, the latest innovation. Clinicians should be familiar with the differences in devices, and with the latest technologies to deliver optimized patient care.Areas covered: In this device profile, the sensing capabilities of the Percept™ PC platform are described, and the system capabilities are differentiated from other available platforms. The development of the preceding Activa™ PC+S research platform, an investigational device to simultaneously sense brain signals and provide therapeutic stimulation, is provided to place Percept™ PC in the appropriate context.Expert opinion: Percept™ PC offers unique sensing and diary functions as a means to refine therapeutic stimulation, track symptoms and correlate them to neurophysiologic characteristics. Additional features enhance the patient experience with DBS, including 3 T magnetic resonance imaging compatibility, wireless telemetry, a smaller and thinner battery profile, and increased battery longevity. Future work will be needed to illustrate the clinical utility and added value of using sensing to optimize DBS therapy. Patients implanted with Percept™ PC will have ready access to future technology developments.

Cerebellar oscillations driven by synaptic pruning deficits of cerebellar climbing fibers contribute to tremor pathophysiology

Essential tremor (ET) is one of the most common movement disorders and the prototypical disorder for abnormal rhythmic movements. However, the pathophysiology of tremor generation in ET remains unclear. Here, we used autoptic cerebral tissue from patients with ET, clinical data, and mouse models to report that synaptic pruning deficits of climbing fiber (CF)-to-Purkinje cell (PC) synapses, which are related to glutamate receptor delta 2 (GluRδ2) protein insufficiency, cause excessive cerebellar oscillations and might be responsible for tremor. The CF-PC synaptic pruning deficits were correlated with the reduction in GluRδ2 expression in the postmortem ET cerebellum. Mice with GluRδ2 insufficiency and CF-PC synaptic pruning deficits develop ET-like tremor that can be suppressed with viral rescue of GluRδ2 protein. Step-by-step optogenetic or pharmacological inhibition of neuronal firing, axonal activity, or synaptic vesicle release confirmed that the activity of the excessive CF-to-PC synapses is required for tremor generation. In vivo electrophysiology in mice showed that excessive cerebellar oscillatory activity is CF dependent and necessary for tremor and optogenetic-driven PC synchronization was sufficient to generate tremor in wild-type animals. Human validation by cerebellar electroencephalography confirmed that excessive cerebellar oscillations also exist in patients with ET. Our findings identify a pathophysiologic contribution to tremor at molecular (GluRδ2), structural (CF-to-PC synapses), physiological (cerebellar oscillations), and behavioral levels (kinetic tremor) that might have clinical applications for treating ET.

Modeling nucleus accumbens : A Computational Model from Single Cell to Circuit Level

Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors.

Dopamine and Striatal Neuron Firing Respond to Frequency-Dependent DBS Detected by Microelectrode Arrays in the Rat Model of Parkinson's Disease

(1) Background: Deep brain stimulation (DBS) is considered as an efficient treatment method for alleviating motor symptoms in Parkinson’s disease (PD), while different stimulation frequency effects on the specific neuron patterns at the cellular level remain unknown. (2) Methods: In this work, nanocomposites-modified implantable microelectrode arrays (MEAs) were fabricated to synchronously record changes of dopamine (DA) concentration and striatal neuron firing in the striatum during subthalamic nucleus DBS, and different responses of medium spiny projecting neurons (MSNs) and fast spiking interneurons (FSIs) to DBS were analyzed. (3) Results: DA concentration and striatal neuron spike firing rate showed a similar change as DBS frequency changed from 10 to 350 Hz. Note that the increases in DA concentration (3.11 ± 0.67 μM) and neural spike firing rate (15.24 ± 2.71 Hz) were maximal after the stimulation at 100 Hz. The MSNs firing response to DBS was significant, especially at 100 Hz, while the FSIs remained stable after various stimulations. (4) Conclusions: DBS shows the greatest regulatory effect on DA concentration and MSNs firing rate at 100 Hz stimulation. This implantable MEA in the recording of the neurotransmitter and neural spike pattern response to DBS provides a new insight to understand the mechanism of PD at the cellular level.

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.

Delta oscillations are a robust biomarker of dopamine depletion severity and motor dysfunction in awake mice

Delta oscillations (0.5-4 Hz) are a robust feature of basal ganglia pathophysiology in patients with Parkinson's disease (PD) in relationship to tremor, but their relationship to other parkinsonian symptoms has not been investigated. While delta oscillations have been observed in mouse models of PD, they have only been investigated in anesthetized animals, suggesting that the oscillations may be an anesthesia artifact and limiting the ability to relate them to motor symptoms. Here, we establish a novel approach to detect spike oscillations embedded in noise to provide the first study of delta oscillations in awake, dopamine-depleted mice. We find that approximately half of neurons in the substantia nigra pars reticulata (SNr) exhibit delta oscillations in dopamine depletion and that these oscillations are a strong indicator of dopamine loss and akinesia, outperforming measures such as changes in firing rate, irregularity, bursting, and synchrony. These oscillations are typically weakened, but not ablated, during movement. We further establish that these oscillations are caused by the loss of D2-receptor activation and do not originate from motor cortex, contrary to previous findings in anesthetized animals. Instead, SNr oscillations precede those in M1 at a 100- to 300-ms lag, and these neurons' relationship to M1 oscillations can be used as the basis for a novel classification of SNr into two subpopulations. These results give insight into how dopamine loss leads to motor dysfunction and suggest a reappraisal of delta oscillations as a marker of akinetic symptoms in PD.NEW & NOTEWORTHY This work introduces a novel method to detect spike oscillations amidst neural noise. Using this method, we demonstrate that delta oscillations in the basal ganglia are a defining feature of awake, dopamine-depleted mice and are strongly correlated with dopamine loss and parkinsonian motor symptoms. These oscillations arise from a loss of D2-receptor activation and do not require motor cortex. Similar oscillations in human patients may be an underappreciated marker and target for Parkinson's disease (PD) treatment.

Basal ganglia oscillations as biomarkers for targeting circuit dysfunction in Parkinson's disease

Oscillations are a naturally occurring phenomenon in highly interconnected dynamical systems. However, it is thought that excessive synchronized oscillations in brain circuits can be detrimental for many brain functions by disrupting neuronal information processing. Because synchronized basal ganglia oscillations are a hallmark of Parkinson's disease (PD), it has been suggested that aberrant rhythmic activity associated with symptoms of the disease could be used as a physiological biomarker to guide pharmacological and electrical neuromodulatory interventions. We here briefly review the various manifestations of basal ganglia oscillations observed in human subjects and in animal models of PD. In this context, we also review the evidence supporting a pathophysiological role of different oscillations for the suppression of voluntary movements as well as for the induction of excessive motor activity. In light of these findings, it is discussed how oscillations could be used to guide a more precise targeting of dysfunctional circuits to obtain improved symptomatic treatment of PD.