Bad oscillations in Parkinson's disease

The neuromechanical of Beta-band corticomuscular coupling within the human motor system

Beta-band activity in the sensorimotor cortex is considered a potential biomarker for evaluating motor functions. The intricate connection between the brain and muscle (corticomuscular coherence), especially in beta band, was found to be modulated by multiple motor demands. This coherence also showed abnormality in motion-related disorders. However, although there has been a substantial accumulation of experimental evidence, the neural mechanisms underlie corticomuscular coupling in beta band are not yet fully clear, and some are still a matter of controversy. In this review, we summarized the findings on the impact of Beta-band corticomuscular coherence to multiple conditions (sports, exercise training, injury recovery, human functional restoration, neurodegenerative diseases, age-related changes, cognitive functions, pain and fatigue, and clinical applications), and pointed out several future directions for the scientific questions currently unsolved. In conclusion, an in-depth study of Beta-band corticomuscular coupling not only elucidates the neural mechanisms of motor control but also offers new insights and methodologies for the diagnosis and treatment of motor rehabilitation and related disorders. Understanding these mechanisms can lead to personalized neuromodulation strategies and real-time neurofeedback systems, optimizing interventions based on individual neurophysiological profiles. This personalized approach has the potential to significantly improve therapeutic outcomes and athletic performance by addressing the unique needs of each individual.

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.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.

Timing to be precise? An overview of spike timing-dependent plasticity, brain rhythmicity, and glial cells interplay within neuronal circuits

In the mammalian brain information processing and storage rely on the complex coding and decoding events performed by neuronal networks. These actions are based on the computational ability of neurons and their functional engagement in neuronal assemblies where precise timing of action potential firing is crucial. Neuronal circuits manage a myriad of spatially and temporally overlapping inputs to compute specific outputs that are proposed to underly memory traces formation, sensory perception, and cognitive behaviors. Spike-timing-dependent plasticity (STDP) and electrical brain rhythms are suggested to underlie such functions while the physiological evidence of assembly structures and mechanisms driving both processes continues to be scarce. Here, we review foundational and current evidence on timing precision and cooperative neuronal electrical activity driving STDP and brain rhythms, their interactions, and the emerging role of glial cells in such processes. We also provide an overview of their cognitive correlates and discuss current limitations and controversies, future perspectives on experimental approaches, and their application in humans.

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.

The Genetic Etiology of Parkinson's Disease Does Not Robustly Affect Subthalamic Physiology

BACKGROUND

It is unknown whether Parkinson's disease (PD) genetic heterogeneity, leading to phenotypic and pathological variability, is also associated with variability in the unique PD electrophysiological signature. Such variability might have practical implications for adaptive deep brain stimulation (DBS).

OBJECTIVE

The aim of our work was to study the electrophysiological activity in the subthalamic nucleus (STN) of patients with PD with pathogenic variants in different disease-causing genes.

METHODS

Electrophysiological data from participants with negative genetic tests were compared with those from GBA, LRRK2, and PRKN-PD.

RESULTS

We analyzed data from 93 STN trajectories (GBA-PD: 28, LRRK2-PD: 22, PARK-PD: 10, idiopathic PD: 33) of 52 individuals who underwent DBS surgery. Characteristics of β oscillatory activity in the dorsolateral motor part of the STN were similar for patients with negative genetic tests and for patients with different forms of monogenic PD.

CONCLUSIONS

The genetic heterogeneity in PD is not associated with electrophysiological differences. Therefore, similar adaptive DBS algorithms would be applicable to genetically heterogeneous patient populations. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Global dynamics of neural mass models

Neural mass models are used to simulate cortical dynamics and to explain the electrical and magnetic fields measured using electro- and magnetoencephalography. Simulations evince a complex phase-space structure for these kinds of models; including stationary points and limit cycles and the possibility for bifurcations and transitions among different modes of activity. This complexity allows neural mass models to describe the itinerant features of brain dynamics. However, expressive, nonlinear neural mass models are often difficult to fit to empirical data without additional simplifying assumptions: e.g., that the system can be modelled as linear perturbations around a fixed point. In this study we offer a mathematical analysis of neural mass models, specifically the canonical microcircuit model, providing analytical solutions describing slow changes in the type of cortical activity, i.e. dynamical itinerancy. We derive a perturbation analysis up to second order of the phase flow, together with adiabatic approximations. This allows us to describe amplitude modulations in a relatively simple mathematical format providing analytic proof-of-principle for the existence of semi-stable states of cortical dynamics at the scale of a cortical column. This work allows for model inversion of neural mass models, not only around fixed points, but over regions of phase space that encompass transitions among semi or multi-stable states of oscillatory activity. Crucially, these theoretical results speak to model inversion in the context of multiple semi-stable brain states, such as the transition between interictal, pre-ictal and ictal activity in epilepsy.

Movement-related beta ERD and ERS abnormalities in neuropsychiatric disorders

Movement-related oscillations in the beta range (from 13 to 30 Hz) have been observed over sensorimotor areas with power decrease (i.e., event-related desynchronization, ERD) during motor planning and execution followed by an increase (i.e., event-related synchronization, ERS) after the movement's end. These phenomena occur during active, passive, imaged, and observed movements. Several electrophysiology studies have used beta ERD and ERS as functional indices of sensorimotor integrity, primarily in diseases affecting the motor system. Recent literature also highlights other characteristics of beta ERD and ERS, implying their role in processes not strictly related to motor function. Here we review studies about movement-related ERD and ERS in diseases characterized by motor dysfunction, including Parkinson's disease, dystonia, stroke, amyotrophic lateral sclerosis, cerebral palsy, and multiple sclerosis. We also review changes of beta ERD and ERS reported in physiological aging, Alzheimer's disease, and schizophrenia, three conditions without overt motor symptoms. The review of these works shows that ERD and ERS abnormalities are present across the spectrum of the examined pathologies as well as development and aging. They further suggest that cognition and movement are tightly related processes that may share common mechanisms regulated by beta modulation. Future studies with a multimodal approach are warranted to understand not only the specific topographical dynamics of movement-related beta modulation but also the general meaning of beta frequency changes occurring in relation to movement and cognitive processes at large. Such an approach will provide the foundation to devise and implement novel therapeutic approaches to neuropsychiatric disorders.

Clinical neurophysiology of Parkinson's disease and parkinsonism

•

This review is part of the series on the clinical neurophysiology of movement disorders and focuses on Parkinson’s disease and parkinsonism.

•

The pathophysiology of cardinal parkinsonian motor symptoms and myoclonus are reviewed.

•

The recordings from microelectrode and deep brain stimulation electrodes are reported in detail.

This review is part of the series on the clinical neurophysiology of movement disorders. It focuses on Parkinson’s disease and parkinsonism. The topics covered include the pathophysiology of tremor, rigidity and bradykinesia, balance and gait disturbance and myoclonus in Parkinson’s disease. The use of electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies of cortical excitability with single and paired transcranial magnetic stimulation, studies of plasticity, intraoperative microelectrode recordings and recording of local field potentials from deep brain stimulation, and electrocorticography are also reviewed. In addition to advancing knowledge of pathophysiology, neurophysiological studies can be useful in refining the diagnosis, localization of surgical targets, and help to develop novel therapies for Parkinson’s disease.

Long Term Performance of a Bi-Directional Neural Interface for Deep Brain Stimulation and Recording

Background: In prior reports, we described the design and initial performance of a fully implantable, bi-directional neural interface system for use in deep brain and other neurostimulation applications. Here we provide an update on the chronic, long-term neural sensing performance of the system using traditional 4-contact leads and extend those results to include directional 8-contact leads.

Methods: Seven ovine subjects were implanted with deep brain stimulation (DBS) leads at different nodes within the Circuit of Papez: four with unilateral leads in the anterior nucleus of the thalamus and hippocampus; two with bilateral fornix leads, and one with bilateral hippocampal leads. The leads were connected to either an Activa PC+S^® (Medtronic) or Percept PC^°ledR (Medtronic) deep brain stimulation and recording device. Spontaneous local field potentials (LFPs), evoked potentials (EPs), LFP response to stimulation, and electrode impedances were monitored chronically for periods of up to five years in these subjects.

Results: The morphology, amplitude, and latencies of chronic hippocampal EPs evoked by thalamic stimulation remained stable over the duration of the study. Similarly, LFPs showed consistent spectral peaks with expected variation in absolute magnitude dependent upon behavioral state and other factors, but no systematic degradation of signal quality over time. Electrode impedances remained within expected ranges with little variation following an initial stabilization period. Coupled neural activity between the two nodes within the Papez circuit could be observed in synchronized recordings up to 5 years post-implant. The magnitude of passive LFP power recorded from directional electrode segments was indicative of the contacts that produced the greatest stimulation-induced changes in LFP power within the Papez network.

Conclusion: The implanted device performed as designed, providing the ability to chronically stimulate and record neural activity within this network for up to 5 years of follow-up.

Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson’s disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.

Event-related oscillations differentiate between cognitive, motor and visual impairments

BACKGROUND

Parkinson's disease (PD) and dementia with Lewy bodies (DLB) share pathological and clinical similarities while differing in the timing and severity of motor cognitive and visual impairment. Previous EEG studies found abnormal neural oscillations in PD, mild cognitive impairment (MCI) and Alzheimer's disease, however, the electrophysiological signature of clinical symptoms is still unclear. We assessed the specificity of event-related oscillations in distinguishing between cognitive, motor and visual involvement in patients with neurodegenerative conditions.

METHODS

EEG was recorded during a visual oddball task in 30 PD, 28 DLB, 30 MCI patients and 32 age-matched healthy controls. Target and non-target event-related power were examined in the time-frequency domain using complex Morlet wavelet convolution and compared within and between the study groups.

RESULTS

MCI (z = - 1.8, p = 0.04, Cohen's d = - 0.5) and DLB (z = - 3.1, p < 0.001, d = - 1.0) patients showed decreased delta-band target event-related synchronization compared to participants with normal cognition. PD (z = 1.6, p = 0.05, d = 0.5) and DLB (z = 2.7, p < 0.01, d = 0.9) patients showed decreased beta suppression compared to MCI patients and controls. DLB patients with visual hallucinations (VH) showed decreased early-alpha suppression (z = 2.08, p = 0.019, d = 3.19, AUC = 1.0 ± 0.0) compared to DLB-VH^-.

CONCLUSIONS

Decreased event-related delta-band synchronization, reflecting a decline in information processing ability, was characteristic of cognitive impairment due to any cause. Decreased event-related beta suppression, reflecting impaired execution of motor action, was specific to PD and DLB. Decreased event-related early-alpha suppression was characteristic of the presence of VH in DLB. These findings show that specific oscillations may reflect specific clinical symptoms, being a marker of network dysfunction.

They Affect the Person, but for Better or Worse? Perceptions of Electroceutical Interventions for Depression Among Psychiatrists, Patients, and the Public

Responding to reports of cases of personality change following deep brain stimulation, neuroethicists have debated the nature and ethical implications of these changes. Recently, this literature has been challenged as being overblown and therefore potentially an impediment to patients accessing needed treatment. We interviewed 16 psychiatrists, 16 patients with depression, and 16 members of the public without depression, all from the Midwestern United States, about their views on how three electroceutical interventions (deep brain stimulation, electroconvulsive therapy, and transcranial magnetic stimulation) used to treat depression might affect the self. Participants were also asked to compare the electroceuticals' effects on the self with the effects of commonly used depression treatments (psychotherapy and pharmaceuticals). Using qualitative content analysis, we found that participants' views on electroceuticals' potential effects on the self mainly focused on treatment effectiveness and side effects. Our results have implications for both theoretical discussions in neuroethics and clinical practice in psychiatry.

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Essential tremor, a common, debilitating motor disorder, is thought to be caused by cerebellar malfunction. It has been shown that rhythmic Purkinje cell firing is both necessary and sufficient to induce body tremor. During tremor, cerebellar nuclei (CN) cells also display oscillatory activity. This study examined whether rhythmic activity in the CN characterizes the occurrence of body tremor, or alternatively, whether aberrant bursting activity underlies body tremor. Cerebellar nuclei activity was chronically recorded and analyzed in freely moving and in harmaline treated rats. CN neurons displayed rhythmic activity in both conditions, but the number of oscillatory neurons and the relative oscillation time were significantly higher under harmaline. The dominant frequencies of the oscillations were broadly distributed under harmaline and the likelihood that two simultaneously recorded neurons would co-oscillate and their oscillation coherence were significantly lower. It is argued that these alterations rather than neuronal rhythmicity per se underlie harmaline-induced body tremor.

Reduced cortico-muscular beta coupling in Parkinson's disease predicts motor impairment

Long-range communication through the motor system is thought to be facilitated by phase coupling between neural activity in the 15–30 Hz beta range. During periods of sustained muscle contraction (grip), such coupling is manifest between motor cortex and the contralateral forearm muscles—measured as the cortico-muscular coherence. We examined alterations in cortico-muscular coherence in individuals with Parkinson’s disease, while equating grip strength between individuals with Parkinson’s disease (off their medication) and healthy control participants. We show a marked reduction in beta cortico-muscular coherence in the Parkinson’s disease group, even though the grip strength was comparable between the two groups. Moreover, the reduced cortico-muscular coherence was related to motor symptoms, so that individuals with lower cortico-muscular coherence also displayed worse motor symptoms. These findings highlight the cortico-muscular coherence as a simple, effective and clinically relevant neural marker of Parkinson’s disease pathology, with the potential to aid monitoring of disease progression and the efficacy of novel treatments for Parkinson’s disease.

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.

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity

BACKGROUND AND PURPOSE

The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.

METHODS

We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations.

RESULTS

We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters.

CONCLUSION

The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.

Understanding the Role of Sensorimotor Beta Oscillations

Beta oscillations have been predominantly observed in sensorimotor cortices and basal ganglia structures and they are thought to be involved in somatosensory processing and motor control. Although beta activity is a distinct feature of healthy and pathological sensorimotor processing, the role of this rhythm is still under debate. Here we review recent findings about the role of beta oscillations during experimental manipulations (i.e., drugs and brain stimulation) and their alteration in aging and pathology. We show how beta changes when learning new motor skills and its potential to integrate sensory input with prior contextual knowledge. We conclude by discussing a novel methodological approach analyzing beta oscillations as a series of transient bursting events.

Sensory Attenuation in Sport and Rehabilitation: Perspective from Research in Parkinson's Disease

People with Parkinson's disease (PD) experience motor symptoms that are affected by sensory information in the environment. Sensory attenuation describes the modulation of sensory input caused by motor intent. This appears to be altered in PD and may index important sensorimotor processes underpinning PD symptoms. We review recent findings investigating sensory attenuation and reconcile seemingly disparate results with an emphasis on task-relevance in the modulation of sensory input. Sensory attenuation paradigms, across different sensory modalities, capture how two identical stimuli can elicit markedly different perceptual experiences depending on our predictions of the event, but also the context in which the event occurs. In particular, it appears as though contextual information may be used to suppress or facilitate a response to a stimulus on the basis of task-relevance. We support this viewpoint by considering the role of the basal ganglia in task-relevant sensory filtering and the use of contextual signals in complex environments to shape action and perception. This perspective highlights the dual effect of basal ganglia dysfunction in PD, whereby a reduced capacity to filter task-relevant signals harms the ability to integrate contextual cues, just when such cues are required to effectively navigate and interact with our environment. Finally, we suggest how this framework might be used to establish principles for effective rehabilitation in the treatment of PD.

Mechanomyography and acceleration show interlimb asymmetries in Parkinson patients without tremor compared to controls during a unilateral motor task

The mechanical muscular oscillations are rarely the objective of investigations regarding the identification of a biomarker for Parkinson's disease (PD). Therefore, the aim of this study was to investigate whether or not this specific motor output differs between PD patients and controls. The novelty is that patients without tremor are investigated performing a unilateral isometric motor task. The force of armflexors and the forearm acceleration (ACC) were recorded as well as the mechanomyography of the biceps brachii (MMGbi), brachioradialis (MMGbra) and pectoralis major (MMGpect) muscles using a piezoelectric-sensor-based system during a unilateral motor task at 70% of the MVIC. The frequency, a power-frequency-ratio, the amplitude variation, the slope of amplitudes and their interlimb asymmetries were analysed. The results indicate that the oscillatory behavior of muscular output in PD without tremor deviates from controls in some parameters: Significant differences appeared for the power-frequency-ratio (p = 0.001, r = 0.43) and for the amplitude variation (p = 0.003, r = 0.34) of MMGpect. The interlimb asymmetries differed significantly concerning the power-frequency-ratio of MMGbi (p = 0.013, r = 0.42) and MMGbra (p = 0.048, r = 0.39) as well as regarding the mean frequency (p = 0.004, r = 0.48) and amplitude variation of MMGpect (p = 0.033, r = 0.37). The mean (M) and variation coefficient (CV) of slope of ACC differed significantly (M: p = 0.022, r = 0.33; CV: p = 0.004, r = 0.43). All other parameters showed no significant differences between PD and controls. It remains open, if this altered mechanical muscular output is reproducible and specific for PD.

Parvalbumin+ and Npas1+ Pallidal Neurons Have Distinct Circuit Topology and Function

The external globus pallidus (GPe) is a critical node within the basal ganglia circuit. Phasic changes in the activity of GPe neurons during movement and their alterations in Parkinson's disease (PD) argue that the GPe is important in motor control. Parvalbumin-positive (PV+) neurons and Npas1+ neurons are the two principal neuron classes in the GPe. The distinct electrophysiological properties and axonal projection patterns argue that these two neuron classes serve different roles in regulating motor output. However, the causal relationship between GPe neuron classes and movement remains to be established. Here, by using optogenetic approaches in mice (both males and females), we showed that PV+ neurons and Npas1+ neurons promoted and suppressed locomotion, respectively. Moreover, PV+ neurons and Npas1+ neurons are under different synaptic influences from the subthalamic nucleus (STN). Additionally, we found a selective weakening of STN inputs to PV+ neurons in the chronic 6-hydroxydopamine lesion model of PD. This finding reinforces the idea that the reciprocally connected GPe-STN network plays a key role in disease symptomatology and thus provides the basis for future circuit-based therapies.SIGNIFICANCE STATEMENT The external pallidum is a key, yet an understudied component of the basal ganglia. Neural activity in the pallidum goes awry in neurologic diseases, such as Parkinson's disease. While this strongly argues that the pallidum plays a critical role in motor control, it has been difficult to establish the causal relationship between pallidal activity and motor function/dysfunction. This was in part because of the cellular complexity of the pallidum. Here, we showed that the two principal neuron types in the pallidum have opposing roles in motor control. In addition, we described the differences in their synaptic influence. Importantly, our research provides new insights into the cellular and circuit mechanisms that explain the hypokinetic features of Parkinson's disease.

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.

Sedative drugs modulate the neuronal activity in the subthalamic nucleus of parkinsonian patients

Microelectrode recording (MER) is often used to identify electrode location which is critical for the success of deep brain stimulation (DBS) treatment of Parkinson’s disease. The usage of anesthesia and its’ impact on MER quality and electrode placement is controversial. We recorded neuronal activity at a single depth inside the Subthalamic Nucleus (STN) before, during, and after remifentanil infusion. The root mean square (RMS) of the 250–6000 Hz band-passed signal was used to evaluate the regional spiking activity, the power spectrum to evaluate the oscillatory activity and the coherence to evaluate synchrony between two microelectrodes. We compare those to new frequency domain (spectral) analysis of previously obtained data during propofol sedation. Results showed Remifentanil decreased the normalized RMS by 9% (P < 0.001), a smaller decrease compared to propofol. Regarding the beta range oscillatory activity, remifentanil depressed oscillations (drop from 25 to 5% of oscillatory electrodes), while propofol did not (increase from 33.3 to 41.7% of oscillatory electrodes). In the cases of simultaneously recorded oscillatory electrodes, propofol did not change the synchronization while remifentanil depressed it. In conclusion, remifentanil interferes with the identification of the dorsolateral oscillatory region, whereas propofol interferes with RMS identification of the STN borders. Thus, both have undesired effect during the MER procedure.

Trial registration: NCT00355927 and NCT00588926.

6-Hydroxydopamine lesion and levodopa treatment modify the effect of buspirone in the substantia nigra pars reticulata

BACKGROUND AND PURPOSE

l-DOPA-induced dyskinesia (LID) is considered a major complication in the treatment of Parkinson's disease (PD). Buspirone (5-HT1A partial agonist) have shown promising results in the treatment of PD and LID, however no 5-HT-based treatment has been approved in PD. The present study was aimed to investigate how the substantia nigra pars reticulata (SNr) is affected by buspirone and whether it is a good target to study 5-HT antidyskinetic treatments.

EXPERIMENTAL APPROACH

Buspirone was studied using in vivo single-unit, electrocorticogram, local field potential recordings along with microdialysis and immunohistochemistry in naïve/sham, 6-hydroxydopamine (6-OHDA)-lesioned or 6-OHDA-lesioned and l-DOPA-treated (6-OHDA/l-DOPA) rats.

KEY RESULTS

Local buspirone inhibited SNr neuron activity in all groups. However, systemic buspirone reduced burst activity in 6-OHDA-lesioned rats (with or without l-DOPA treatment), whereas 8-OH-DPAT, a full 5-HT1A agonist induced larger inhibitory effects in sham animals. Neither buspirone nor 8-OH-DPAT markedly modified the low-frequency oscillatory activity in the SNr or synchronization within the SNr with the cortex. In addition, local perfusion of buspirone increased GABA and glutamate release in the SNr of naïve and 6-OHDA-lesioned rats but no effect in 6-OHDA/l-DOPA rats. In the 6-OHDA/l-DOPA group, increased 5-HT transporter and decreased 5-HT1A receptor expression was found.

CONCLUSIONS AND IMPLICATIONS

The effects of buspirone in SNr are influenced by dopamine loss and l-DOPA treatment. The present results suggest that the regulation of burst activity of the SNr induced by DA loss may be a good target to test new drugs for the treatment of PD and LID.

Interactions Between Motor Thalamic Field Potentials and Single-Unit Spiking Are Correlated With Behavior in Rats

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1–4 Hz), beta (13–30 Hz), low gamma (30–70 Hz), and high gamma (70–200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Pre-Movement Cortico-Muscular Dynamics Underlying Improved Parkinson Gait Initiation after Instructed Arm Swing

BACKGROUND

The supplementary motor area (SMA) is implicated in both motor initiation and stereotypic multi-limb movements such as walking with arm swing. Gait in Parkinson's disease exhibits starting difficulties and reduced arm swing, consistent with reduced SMA activity.

OBJECTIVE

We tested whether enhanced arm swing could improve Parkinson gait initiation and assessed whether increased SMA activity during preparation might facilitate such improvement.

METHODS

Effects of instructed arm swing on cortical activity, muscle activity and kinematics were assessed by ambulant EEG, EMG, accelerometers and video in 17 Parkinson patients and 19 controls. At baseline, all participants repeatedly started walking after a simple auditory cue. Next, patients started walking at this cue, which now meant starting with enhanced arm swing. EEG changes over the putative SMA and leg motor cortex were assessed by event related spectral perturbation (ERSP) analysis of recordings at Fz and Cz.

RESULTS

Over the putative SMA location (Fz), natural PD gait initiation showed enhanced alpha/theta synchronization around the auditory cue, and reduced alpha/beta desynchronization during gait preparation and movement onset, compared to controls. Leg muscle activity in patients was reduced during preparation and movement onset, while the latter was delayed compared to controls. When starting with enhanced arm swing, these group differences virtually disappeared.

CONCLUSION

Instructed arm swing improves Parkinson gait initiation. ERSP normalization around the cue indicates that the attributed information may serve as a semi-internal cue, recruiting an internalized motor program to overcome initiation difficulties.

Electrophysiological and Neurochemical Considerations of Distinct Neuronal Populations in the Rat Pedunculopontine Nucleus and Their Responsiveness Following 6-Hydroxydopamine Lesions

The pedunculopontine nucleus (PPN) is composed of a morphologically and neurochemically heterogeneous population of neurons, which is severely affected by Parkinson’s disease (PD). However, the role of each subtype of neurons within the PPN in the pathophysiology of PD has not been completely elucidated. In this study, we present the discharge profiles of three classified subtypes of PPN neurons and their alterations after 6-hydroxydopamine (6-OHDA) lesion. Following 6-OHDA lesion, the spike timing of the Type II (GABAergic) and Type III (glutamatergic) neurons had phase-lock with the oscillations in the delta and beta band frequency range in the PPN, respectively. Morphological evidence has shown distinct alteration in three kinds of neurons after 6-OHDA lesion. These findings revealed that the changes in the firing characteristics of neurons in PPN in hemi-parkinsonism rats are closely associated with damaged neuronal morphology, which would make contributions to the divergence of dysfunctions in Parkinsonism.

Quantitative Susceptibility Mapping and Resting State Network Analyses in Parkinsonian Phenotypes-A Systematic Review of the Literature

An imbalance of iron metabolism with consecutive aggregation of α-synuclein and axonal degeneration of neurons has been postulated as the main pathological feature in the development of Parkinson’s disease (PD). Quantitative susceptibility mapping (QSM) is a new imaging technique, which enables to measure structural changes caused by defective iron deposition in parkinsonian brains. Due to its novelty, its potential as a new imaging technique remains elusive for disease-specific characterization of motor and non-motor symptoms (characterizing the individual parkinsonian phenotype). Functional network changes associated with these symptoms are however frequently described for both magnetoencephalography (MEG) and resting state functional magnetic imaging (rs-fMRI). Here, we performed a systematic review of the current literature about QSM imaging, MEG and rs-fMRI in order to collect existing data about structural and functional changes caused by motor and non-motor symptoms in PD. Whereas all three techniques provide an effect in the motor domain, the understanding of network changes caused by non-motor symptoms is much more lacking for MEG and rs-fMRI, and does not yet really exist for QSM imaging. In order to better understand the influence of pathological iron distribution onto the functional outcome, whole-brain QSM analyses should be integrated in functional analyses (especially for the non-motor domain), to enable a proper pathophysiological interpretation of MEG and rs-fMRI network changes in PD. Herewith, a better understanding of the relationship between neuropathological changes, functional network changes and clinical phenotype might become possible.

Dichotomy between motor and cognitive functions of midbrain cholinergic neurons

Cholinergic neurons of the pedunculopontine nucleus (PPN) are interconnected with all the basal ganglia structures, as well as with motor centers in the brainstem and medulla. Recent theories put into question whether PPN cholinergic neurons form part of a locomotor region that directly regulates the motor output, and rather suggest a modulatory role in adaptive behavior involving both motor and cognitive functions. In support of this, experimental studies in animals suggest that cholinergic neurons reinforce actions by signaling reward prediction and shape adaptations in behavior during changes of environmental contingencies. This is further supported by clinical studies proposing that decreased cholinergic transmission originated in the PPN is associated with impaired sensorimotor integration and perseverant behavior, giving rise to some of the symptoms observed in Parkinson's disease and progressive supranuclear palsy. Altogether, the evidence suggests that cholinergic neurons of the PPN, mainly through their interactions with the basal ganglia, have a leading role in action control.

Frequency Shifts and Depth Dependence of Premotor Beta Band Activity during Perceptual Decision-Making

Neural activity in the premotor and motor cortices shows prominent structure in the beta frequency range (13-30 Hz). Currently, the behavioral relevance of this beta band activity (BBA) is debated. The underlying source of motor BBA and how it changes as a function of cortical depth are also not completely understood. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex of 2 male rhesus macaques performing a visual reaction time (RT) reach discrimination task. We observed robust BBA before and after the onset of the visual stimulus but not during the arm movement. While poststimulus BBA was positively correlated with RT throughout the beta frequency range, prestimulus correlation varied by frequency. Low beta frequencies (∼12-20 Hz) were positively correlated with RT, and high beta frequencies (∼22-30 Hz) were negatively correlated with RT. Analysis and simulations suggested that these frequency-dependent correlations could emerge due to a shift in the component frequencies of the prestimulus BBA as a function of RT, such that faster RTs are accompanied by greater power in high beta frequencies. We also observed a laminar dependence of BBA, with deeper electrodes demonstrating stronger power in low beta frequencies both prestimulus and poststimulus. The heterogeneous nature of BBA and the changing relationship between BBA and RT in different task epochs may be a sign of the differential network dynamics involved in cue expectation, decision-making, motor preparation, and movement execution.SIGNIFICANCE STATEMENT Beta band activity (BBA) has been implicated in motor tasks, in disease states, and as a potential signal for brain-machine interfaces. However, the behavioral relevance of BBA and its laminar organization in premotor cortex have not been completely elucidated. Here we addressed these unresolved issues using simultaneous recordings from multiple cortical layers of the premotor cortex of monkeys performing a decision-making task. Our key finding is that BBA is not a monolithic signal. Instead, BBA consists of at least two frequency bands. The relationship between BBA and eventual behavior, such as reaction time, also dynamically changes depending on task epoch. We also provide further evidence that BBA is laminarly organized, with greater power in deeper electrodes for low beta frequencies.

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Oscillatory Activity in the Cortex, Motor Thalamus and Nucleus Reticularis Thalami in Acute TTX and Chronic 6-OHDA Dopamine-Depleted Animals

The motor thalamus (MTh) and the nucleus reticularis thalami (NRT) have been largely neglected in Parkinson's disease (PD) research, despite their key role as interface between basal ganglia (BG) and cortex (Cx). In the present study, we investigated the oscillatory activity within the Cx, MTh, and NRT, in normal and different dopamine (DA)-deficient states. We performed our experiments in both acute and chronic DA-denervated rats by injecting into the medial forebrain bundle (MFB) tetrodotoxin (TTX) or 6-hydroxydopamine (6-OHDA), respectively. Interestingly, almost all the electroencephalogram (EEG) frequency bands changed in acute and/or chronic DA depletion, suggesting alteration of all oscillatory activities and not of a specific band. Overall, δ (2-4 Hz) and θ (4-8 Hz) band decreased in NRT and Cx in acute and chronic state, whilst, α (8-13 Hz) band decreased in acute and chronic states in the MTh and NRT but not in the Cx. The β (13-40 Hz) and γ (60-90 Hz) bands were enhanced in the Cx. In the NRT the β bands decreased, except for high-β (Hβ, 25-30 Hz) that increased in acute state. In the MTh, Lβ and Hβ decreased in acute DA depletion state and γ decreased in both TTX and 6-OHDA-treated animals. These results confirm that abnormal cortical β band are present in the established DA deficiency and it might be considered a hallmark of PD. The abnormal oscillatory activity in frequency interval of other bands, in particular the dampening of low frequencies in thalamic stations, in both states of DA depletion might also underlie PD motor and non-motor symptoms. Our data highlighted the effects of acute depletion of DA and the strict interplay in the oscillatory activity between the MTh and NRT in both acute and chronic stage of DA depletion. Moreover, our findings emphasize early alterations in the NRT, a crucial station for thalamic information processing.

Longer β oscillatory episodes reliably identify pathological subthalamic activity in Parkinsonism

BACKGROUND

The efficacy of deep brain stimulation (DBS) - primarily of the subthalamic nucleus (STN) - for advanced Parkinson's disease (PD) is commonly attributed to the suppression of pathological synchronous β oscillations along the cortico-thalamo-basal ganglia network. Conventional continuous high-frequency DBS indiscriminately influences pathological and normal neural activity. The DBS protocol would therefore be more effective if stimulation was only applied when necessary (closed-loop adaptive DBS).

OBJECTIVES AND METHODS

Our study aimed to identify a reliable biomarker of the pathological neuronal activity in parkinsonism that could be used as a trigger for adaptive DBS. To this end, we examined the oscillatory features of paired spiking activities recorded in three distinct nodes of the basal ganglia network of 2 African green monkeys before and after induction of parkinsonism (by MPTP intoxication).

RESULTS

Parkinsonism-related basal ganglia β oscillations consisted of synchronized time-limited episodes, rather than a continuous stretch, of β oscillatory activity. Episodic basal ganglia β oscillatory activity, although prolonged in parkinsonism, was not necessarily pathological given that short β episodes could also be detected in the healthy state. Importantly, prolongation of the basal ganglia β episodes was more pronounced than their intensification in the parkinsonian state-especially in the STN. Hence, deletion of longer β episodes was more effective than deletion of stronger β episodes in reducing parkinsonian STN synchronized oscillatory activity.

CONCLUSIONS

Prolonged STN β episodes are pathological in parkinsonism and can be used as optimal trigger for future adaptive DBS applications. © 2018 International Parkinson and Movement Disorder Society.

Modeling and Analysis of Beta Oscillations in the Basal Ganglia

Enhanced beta (12-30 Hz) oscillatory activity in the basal ganglia (BG) is a prominent feature of the Parkinsonian state in animal models and in patients with Parkinson's disease. Increased beta oscillations are associated with severe dopaminergic striatal depletion. However, the mechanisms underlying these pathological beta oscillations remain elusive. Inspired by the experimental observation that only subsets of neurons within each nucleus in the BG exhibit oscillatory activities, a computational model of the BG-thalamus neuronal network is proposed, which is characterized by subdivided nuclei within the BG. Using different currents externally applied to the neurons within a given nucleus, neurons behave according to one of the two subgroups, named "-N" and "-P," where "-N" and "-P" denote the normal and the Parkinsonian states, respectively. The ratio of "-P" to "-N" neurons indicates the degree of the Parkinsonian state. Simulation results show that if "-P" neurons have a high degree of connectivity in the subthalamic nucleus (STN), they will have a significant downstream effect on the generation of beta oscillations in the globus pallidus. Interestingly, however, the generation of beta oscillations in the STN is independent of the selection of the "-P" neurons in the external segment of the globus pallidus (GPe), despite the reciprocal structure between STN and GPe. This computational model may pave the way to revealing the mechanism of such pathological behaviors in a realistic way that can replicate experimental observations. The simulation results suggest that the STN is more suitable than GPe as a deep brain stimulation target.

Brain oscillations reveal impaired novelty detection from early stages of Parkinson's disease

The identification of reliable biomarkers for early diagnosis and progression tracking of neurodegenerative diseases has become an important objective in clinical neuroscience in the last years. The P3a event-related potential, considered as the neurophysiological hallmark of novelty detection, has been shown to be reduced in Parkinson's disease (PD) and proposed as a sensitive measure for illness duration and severity. Our aim for this study was to explore for the first time whether impaired novelty detection could be observed through phase- and time-locked brain oscillatory activity at early PD. Twenty-seven patients with idiopathic PD at early stages (disease duration <5 years and Hoehn and Yahr stage <3) were included. A healthy control group (n = 24) was included as well. All participants performed an auditory involuntary attention task including frequent and deviant tones while a digital EEG was obtained. A neuropsychological battery was administered as well. Time-frequency representations of power and phase-locked oscillations and P3a amplitudes were compared between groups. We found a significant reduction of power and phase locking of slow oscillations (3-7 Hz) for deviant tones in the PD group compared to controls in the P3a time range (300-550 ms). Also, reduced modulation of late induced (not phase locked) alpha-beta oscillations (400-650 ms, 8-25 Hz) was observed in the PD group after deviant tones onset. The P3a amplitude was predicted by years of evolution in the PD group. Finally, while phase-locked slow oscillations were associated with task behavioral distraction effects, induced alpha-beta activity was related to cognitive flexibility performance. Our results show that novelty detection impairment can be identified in neurophysiological terms from very early stages of PD, and such impairment increases linearly as the disease progresses. Also, induced alpha-beta oscillations underlying novelty detection are related to executive functioning.

Dysregulation of striatal projection neurons in Parkinson's disease

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

Subthalamic nucleus deep brain stimulation on motor-symptoms of Parkinson's disease: Focus on neurochemistry

Deep brain stimulation (DBS) has become a standard therapy for Parkinson's disease (PD) and it is also currently under investigation for other neurological and psychiatric disorders. Although many scientific, clinical and ethical issues are still unresolved, DBS delivered into the subthalamic nucleus (STN) has improved the quality of life of several thousands of patients. The mechanisms underlying STN-DBS have been debated extensively in several reviews; less investigated are the biochemical consequences, which are still under scrutiny. Crucial and only partially understood, for instance, are the complex interplays occurring between STN-DBS and levodopa (LD)-centred therapy in the post-surgery follow-up. The main goal of this review is to address the question of whether an improved motor control, based on STN-DBS therapy, is also achieved through the additional modulation of other neurotransmitters, such as noradrenaline (NA) and serotonin (5-HT). A critical issue is to understand not only acute DBS-mediated effects, but also chronic changes, such as those involving cyclic nucleotides, capable of modulating circuit plasticity. The present article will discuss the neurochemical changes promoted by STN-DBS and will document the main results obtained in microdialysis studies. Furthermore, we will also examine the preliminary achievements of voltammetry applied to humans, and discuss new hypothetical investigational routes, taking into account novel players such as glia, or subcortical regions such as the pedunculopontine (PPN) area. Our further understanding of specific changes in brain chemistry promoted by STN-DBS would further disseminate its utilisation, at any stage of disease, avoiding an irreversible lesioning approach.

Deep brain stimulation of the subthalamic nucleus in obsessive-compulsive disorder: Neuroanatomical and pathophysiological considerations

Obsessive-compulsive disorder (OCD) is among the most disabling chronic psychiatric disorders and has a significant negative impact on multiple domains of quality of life. For patients suffering from severe refractory OCD, deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been applied. Reviewing the literature of the last years we believe that through its central position within the cortico-basal ganglia-thalamocortical circuits, the STN has a coordinating role in decision-making and action-selection mechanisms. Dysfunctional information-processing at the level of the STN is responsible for some of the core symptoms of OCD. Research confirms an electrophysiological dysfunction in the associative and limbic (non-motor) parts of the STN. Compared to Parkinson׳s disease patients, STN neurons in OCD exhibit a lower firing rate, less frequent but longer bursts, increased burst activity in the anterior ventromedial area, an asymmetrical left-sided burst distribution, and a predominant oscillatory activity in the δ-band. Moreover, there is direct evidence for the involvement of the STN in both checking behavior and OCD symptoms, which are both related to changes in electrophysiological activity in the non-motor STN. Through a combination of mechanisms, DBS of the STN seems to interrupt the disturbed information-processing, leading to a normalization of connectivity within the cortico-basal ganglia-thalamocortical circuits and consequently to a reduction in symptoms. In conclusion, based on the STN׳s strategic position within cortico-basal ganglia-thalamocortical circuits and its involvement in action-selection mechanisms that are responsible for some of the core symptoms of OCD, the STN is a mechanism-based target for DBS in OCD.

A neural mass model of basal ganglia nuclei simulates pathological beta rhythm in Parkinson's disease

An increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with movement disorder, such as Parkinson's disease. The motor cortex and an excitatory-inhibitory neuronal network composed of the subthalamic nucleus (STN) and the external globus pallidus (GPe) are thought to play an important role in the generation of these oscillations. In this paper, we propose a neuron mass model of the basal ganglia on the population level that reproduces the Parkinsonian oscillations in a reciprocal excitatory-inhibitory network. Moreover, it is shown that the generation and frequency of these pathological beta oscillations are varied by the coupling strength and the intrinsic characteristics of the basal ganglia. Simulation results reveal that increase of the coupling strength induces the generation of the beta oscillation, as well as enhances the oscillation frequency. However, for the intrinsic properties of each nucleus in the excitatory-inhibitory network, the STN primarily influences the generation of the beta oscillation while the GPe mainly determines its frequency. Interestingly, describing function analysis applied on this model theoretically explains the mechanism of pathological beta oscillations.

Quiet connections: Reduced fronto-temporal connectivity in nondemented Parkinson's Disease during working memory encoding

Parkinson's disease (PD) is a common neurodegenerative disorder characterized primarily by motor symptoms such as bradykinesia, muscle rigidity, and resting tremor. It is now broadly accepted that these motor symptoms frequently co-occur with cognitive impairments, with deficits in working memory and attention being among the most common cognitive sequelae associated with PD. While these cognitive impairments are now recognized, the underlying neural dynamics and precise regions involved remain largely unknown. To this end, we examined the oscillatory dynamics and interregional functional connectivity that serve working memory processing in a group of unmedicated adults with PD and a matched group without PD. Each participant completed a high-load, Sternberg-type working memory task during magnetoencephalography (MEG), and we focused on the encoding and maintenance phases. All data were transformed into the time-frequency domain and significant oscillatory activity was imaged using a beamforming approach. Phase-coherence (connectivity) was also computed among the brain subregions exhibiting the strongest responses. Our most important findings were that unmedicated patients with PD had significantly diminished working memory performance (i.e., accuracy), and reduced functional connectivity between left inferior frontal cortices and left supramarginal-superior temporal cortices compared to participants without PD during the encoding phase of working memory processing. We conclude that patients with PD have reduced neural interactions between left prefrontal executive circuits and temporary verbal storage centers in the left supramarginal/superior temporal cortices during the stimulus encoding phase, which may underlie their diminished working memory function. Hum Brain Mapp 37:3224-3235, 2016. © 2016 Wiley Periodicals, Inc.

Unitary synaptic connections among substantia nigra pars reticulata neurons

Neurons in substantia nigra pars reticulata (SNr) are synaptically coupled by local axon collaterals, providing a potential mechanism for local signal processing. Because SNr neurons fire spontaneously, these synapses are constantly active. To investigate their properties, we recorded spontaneous inhibitory postsynaptic currents (sIPSCs) from SNr neurons in brain slices, in which afferents from upstream nuclei are severed, and the cells fire rhythmically. The sIPSC trains contained a mixture of periodic and aperiodic events. Autocorrelation analysis of sIPSC trains showed that a majority of cells had one to four active unitary inputs. The properties of the unitary IPSCs (uIPSCs) were analyzed for cells with one unitary input, using a model of periodic presynaptic firing and stochastic synaptic transmission. The inferred presynaptic firing rates and coefficient of variation of interspike intervals (ISIs) corresponded well with direct measurements of spiking in SNr neurons. Methods were developed to estimate the success probability, amplitude distributions, and kinetics of the uIPSCs, while removing the contribution from aperiodic sIPSCs. The sIPSC amplitudes were not increased upon release from halorhodopsin silencing, suggesting that most synapses were not depressed at the spontaneous firing rate. Gramicidin perforated-patch recordings indicated that the average reversal potential of spontaneous inhibitory postsynaptic potentials was -64 mV. Because of the change in driving force across the ISI, the unitary inputs are predicted to have a larger postsynaptic impact when they arrive late in the ISI. Simulations of network activity suggest that this very sparse inhibitory coupling may act to desynchronize the activity of SNr neurons while having only a small effect on firing rate.

Computational modelling of movement-related beta-oscillatory dynamics in human motor cortex

Oscillatory activity in the beta range, in human primary motor cortex (M1), shows interesting dynamics that are tied to behaviour and change systematically in disease. To investigate the pathophysiology underlying these changes, we must first understand how changes in beta activity are caused in healthy subjects. We therefore adapted a canonical (repeatable) microcircuit model used in dynamic causal modelling (DCM) previously used to model induced responses in visual cortex. We adapted this model to accommodate cytoarchitectural differences between visual and motor cortex. Using biologically plausible connections, we used Bayesian model selection to identify the best model of measured MEG data from 11 young healthy participants, performing a simple handgrip task. We found that the canonical M1 model had substantially more model evidence than the generic canonical microcircuit model when explaining measured MEG data. The canonical M1 model reproduced measured dynamics in humans at rest, in a manner consistent with equivalent studies performed in mice. Furthermore, the changes in excitability (self-inhibition) necessary to explain beta suppression during handgrip were consistent with the attenuation of sensory precision implied by predictive coding. These results establish the face validity of a model that can be used to explore the laminar interactions that underlie beta-oscillatory dynamics in humans in vivo. Our canonical M1 model may be useful for characterising the synaptic mechanisms that mediate pathophysiological beta dynamics associated with movement disorders, such as stroke or Parkinson's disease.

•

This work aims to bridge the gap in understanding between neuronal oscillations measured with MEG and laminar interactions within motor cortex.

•

We adapted a cortical microcircuit model used in sensory DCM studies to build a plausible model of laminar interactions in primary motor cortex.

•

The proposed M1 model showed significantly more model evidence in explaining MEG data from M1 in humans than the inherited model.

•

We replicated the in vitro finding of a dominant pathway from superficial to deep cortical layers at rest, providing face validity for our method.

•

We show novel characterisation of laminar interactions underpinning beta-oscillatory dynamics within M1 during volitional movement in humans.

Powerline noise elimination in biomedical signals via blind source separation and wavelet analysis

The distortion of biomedical signals by powerline noise from recording biomedical devices has the potential to reduce the quality and convolute the interpretations of the data. Usually, powerline noise in biomedical recordings are extinguished via band-stop filters. However, due to the instability of biomedical signals, the distribution of signals filtered out may not be centered at 50/60 Hz. As a result, self-correction methods are needed to optimize the performance of these filters. Since powerline noise is additive in nature, it is intuitive to model powerline noise in a raw recording and subtract it from the raw data in order to obtain a relatively clean signal. This paper proposes a method that utilizes this approach by decomposing the recorded signal and extracting powerline noise via blind source separation and wavelet analysis. The performance of this algorithm was compared with that of a 4th order band-stop Butterworth filter, empirical mode decomposition, independent component analysis and, a combination of empirical mode decomposition with independent component analysis. The proposed method was able to expel sinusoidal signals within powerline noise frequency range with higher fidelity in comparison with the mentioned techniques, especially at low signal-to-noise ratio.