Abnormal oscillatory synchronisation in the motor system leads to impaired movement

Anodal tDCS modulates cortical activity and synchronization in Parkinson's disease depending on motor processing

Background

Transcranial direct current stimulation (tDCS) may alleviate motor symptoms in Parkinson's disease (PD). However, the neurophysiological effects of tDCS on cortical activation, synchronization, and the relation to clinical motor symptoms and motor integration need characterization.

Objective

We aimed to explore the effect of tDCS over the left sensorimotor area on clinical motor outcome, right hand fine motor performance as well as cortical activity and synchronization in the high beta range.

Methods

In this double-blind randomized sham-controlled clinico-neurophysiological study we investigated ten idiopathic PD patients and eleven matched healthy controls (HC) on two days during an isometric precision grip task and at rest before and after ‘verum’ and ‘sham’ anodal tDCS (20 min; 1 mA; anode [C3], cathode [Fp2]). We measured clinical outcome, fine motor performance, and analysed both cortical frequency domain activity and corticocortical imaginary coherence.

Results

tDCS improved PD motor symptoms. Neurophysiological features indicated a motor-task-specific modulation of activity and coherence from 22 to 27 Hz after ‘verum’ stimulation in PD. Activity was significantly reduced over the left sensorimotor and right frontotemporal area. Before stimulation, PD patients showed reduced coherence over the left sensorimotor area during motor task compared to HC, and this increased after ‘verum’ stimulation in the motor task. The activity and synchronization modulation were neither observed at rest, after sham stimulation nor in healthy controls.

Conclusion

Verum tDCS modulated the PD cortical network specifically during fine motor integration. Cortical oscillatory features were not in general deregulated in PD, but depended on motor processing.

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tDCS improved motor function in Parkinson's disease.

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tDCS modulated cortical beta activity and synchronization in Parkinson's disease.

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the Parkinson's disease motor network may be susceptible to cortical stimulation.

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tDCS may reverse pathologic cortical network states.

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.

Admixing MPTP-resistant and MPTP-vulnerable mice enhances striatal field potentials and calbindin-D28K expression to avert motor behaviour deficits

Asian-Indians are less vulnerable to Parkinson's disease (PD) than the Caucasians. Their admixed populace has even lesser risk. Studying this phenomenon using 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-susceptible C57BL/6J, MPTP-resistant CD-1 and their resistant crossbred mice revealed differences in the nigrostriatal cyto-molecular features. Here, we investigated the electrophysiological and behavioural correlates for differential MPTP-susceptibility and their outcome upon admixing. We recorded local field potentials (LFPs) from dorsal striatum and assessed motor co-ordination using rotarod and grip strength measures. Nigral calbindin-D28K expression, a regulator of striatal activity through nigrostriatal projections was evaluated using immunohistochemistry. The crossbreds had significantly higher baseline striatal LFPs. MPTP significantly increased the neuronal activity in delta (0.5-4 Hz) and low beta (12-16 Hz) ranges in C57BL/6J; significant increase across frequency bands till high beta (0.5-30 Hz) in CD-1, and caused no alterations in crossbreds. MPTP further depleted the already low nigral calbindin-D28K expression in C57BL/6J. While in crossbreds, it was further up-regulated. MPTP affected the rotarod and grip strength performance of the C57BL/6J, while the injected CD-1 and crossbreds performed well. The increased striatal β-oscillations are comparable to that in PD patients. Higher power in CD-1 may be compensatory in nature, which were also reported in pre-symptomatic monkeys. Concurrent up-regulation of nigral calbindin-D28K may assist maintenance of striatal activity by buffering calcium overload in nigra. Thus, preserved motor behaviour in PD reminiscent conditions in CD-1 and crossbreds complement compensated/unaffected striatal LFPs. Similar electrophysiological correlates and cytomorphological features are envisaged in human phenomenon of differential PD prevalence, which are modulated upon admixing.

Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson's disease

In this paper, we present a novel Bayesian adaptive dual controller (ADC) for autonomously programming deep brain stimulation devices. We evaluated the Bayesian ADC's performance in the context of reducing beta power in a computational model of Parkinson's disease, in which it was tasked with finding the set of stimulation parameters which optimally reduced beta power as fast as possible. Here, the Bayesian ADC has dual goals: (a) to minimize beta power by exploiting the best parameters found so far, and (b) to explore the space to find better parameters, thus allowing for better control in the future. The Bayesian ADC is composed of two parts: an inner parameterized feedback stimulator and an outer parameter adjustment loop. The inner loop operates on a short time scale, delivering stimulus based upon the phase and power of the beta oscillation. The outer loop operates on a long time scale, observing the effects of the stimulation parameters and using Bayesian optimization to intelligently select new parameters to minimize the beta power. We show that the Bayesian ADC can efficiently optimize stimulation parameters, and is superior to other optimization algorithms. The Bayesian ADC provides a robust and general framework for tuning stimulation parameters, can be adapted to use any feedback signal, and is applicable across diseases and stimulator designs.

Synchronization of heterogeneous oscillator populations in response to weak and strong coupling

Synchronous behavior of a population of chemical oscillators is analyzed in the presence of both weak and strong coupling. In each case, we derive upper bounds on the critical coupling strength which are valid for arbitrary populations of nonlinear, heterogeneous oscillators. For weak perturbations, infinitesimal phase response curves are used to characterize the response to coupling, and graph theoretical techniques are used to predict synchronization. In the strongly perturbed case, we observe a phase dependent perturbation threshold required to elicit an immediate spike and use this behavior for our analytical predictions. Resulting upper bounds on the critical coupling strength agree well with our experimental observations and numerical simulations. Furthermore, important system parameters which determine synchronization are different in the weak and strong coupling regimes. Our results point to new strategies by which limit cycle oscillators can be studied when the applied perturbations become strong enough to immediately reset the phase.

Robust desynchronization of Parkinson's disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation

The hyperkinetic symptoms of Parkinson's Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.

Characteristics of Globus Pallidus Internus Local Field Potentials in Hyperkinetic Disease

Background: Dystonia and Huntington's disease (HD) are both hyperkinetic movement disorders but exhibit distinct clinical characteristics. Aberrant output from the globus pallidus internus (GPi) is involved in the pathophysiology of both HD and dystonia, and deep brain stimulation (DBS) of the GPi shows good clinical efficacy in both disorders. The electrode externalized period provides an opportunity to record local field potentials (LFPs) from the GPi to examine if activity patterns differ between hyperkinetic disorders and are associated with specific clinical characteristics.

Methods: LFPs were recorded from 7 chorea-dominant HD and nine cervical dystonia patients. Differences in oscillatory activities were compared by power spectrum and Lempel-Ziv complexity (LZC). The discrepancy band power ratio was used to control for the influence of absolute power differences between groups. We further identified discrepant frequency bands and frequency band ratios for each subject and examined the correlations with clinical scores.

Results: Dystonia patients exhibited greater low frequency power (6–14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26–43 Hz) (p < 0.0298, corrected). United Huntington Disease Rating Scale chorea sub-score was positively correlated with 26–43 Hz frequency band power and negatively correlated with the 6–14 Hz/26–43 Hz band power ratio.

Conclusion: Dystonia and HD are characterized by distinct oscillatory activity patterns, which may relate to distinct clinical characteristics. Specifically, chorea may be related to elevated high-beta and low-gamma band power, while dystonia may be related to elevated low frequency band power. These LFPs may be useful biomarkers for adaptive DBS to treat hyperkinetic diseases.

Pallidal stimulation in Parkinson disease differentially modulates local and network β activity

β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets.

OBJECTIVES

We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex.

APPROACH

We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open.

MAIN RESULTS

DBS significantly suppressed low β power within the GPi (-26.98%  ±  15.14%), p  <  0.05) without modulation of sensorimotor cortical β power (low or high). In contrast, stimulation suppressed pallidocortical high β coherence (-38.89%  ±  6.19%, p  =  0.02) and dWPLI (-61.40%  ±  8.75%, p  =  0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex.

SIGNIFICANCE

We highlight the role of DBS in desynchronizing network activity, particularly in the high β band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low β oscillations locally within the basal ganglia and high β oscillations across the BGTC motor circuit.

The influence of moving with music on motor cortical activity

Although there is a growing interest in using music to improve movement performance in various populations, there remains a need to better understand how music influences motor cortical activity. Listening to music is tightly linked to neural processes within the motor cortex and can modulate motor cortical activity in healthy young adult (HYAs). There is limited evidence regarding how moving to music modulates motor cortical activity. Thus, the purpose of this study was to explore the influence of moving to music on motor cortical activity in HYAs. Electroencephalography was collected while 32 HYAs tapped their index finger in time with a tone and with two contrasting music styles. Two movement rates were presented for each condition. Power spectra were obtained from data collected over the primary sensorimotor region and supplemental motor area and were compared between conditions. Results revealed a significant difference between both music conditions and the tone only condition for both the regions. For both music styles, power was increased in the beta band for low movement rates and increased in the alpha band for high movement rates. A secondary analysis determining the effect of music experience on motor cortical activity revealed a significant difference between musicians and non-musicians. Power in the beta band was increased across all conditions. The results of this study provide the initial step towards a more complete understanding of the neurophysiological underpinnings of music on movement performance which may inform future studies and therapeutic strategies.

Burst synchronization in a scale-free neuronal network with inhibitory spike-timing-dependent plasticity

We are concerned about burst synchronization (BS), related to neural information processes in health and disease, in the Barabási-Albert scale-free network (SFN) composed of inhibitory bursting Hindmarsh-Rose neurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without considering iSTDP, BS was found to appear in a range of noise intensities for fixed synaptic inhibition strengths. In contrast, in our present work, we take into consideration iSTDP and investigate its effect on BS by varying the noise intensity. Our new main result is to find occurrence of a Matthew effect in inhibitory synaptic plasticity: good BS gets better via LTD, while bad BS get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). We note that, due to inhibition, the roles of LTD and LTP in inhibitory synaptic plasticity are reversed in comparison with those in excitatory synaptic plasticity. Moreover, emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic burst onset times. Finally, in the presence of iSTDP we investigate the effects of network architecture on BS by varying the symmetric attachment degree l ∗ and the asymmetry parameter Δ l in the SFN.

Systems approaches to optimizing deep brain stimulation therapies in Parkinson's disease

Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive-compulsive disorders, essential tremor, Parkinson's disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients' responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson's disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.

Deep Brain Stimulation and L-DOPA Therapy: Concepts of Action and Clinical Applications in Parkinson's Disease

L-DOPA is still the most effective pharmacological therapy for the treatment of motor symptoms in Parkinson's disease (PD) almost four decades after it was first used. Deep brain stimulation (DBS) is a safe and highly effective treatment option in patients with PD. Even though a clear understanding of the mechanisms of both treatment methods is yet to be obtained, the combination of both treatments is the most effective standard evidenced-based therapy to date. Recent studies have demonstrated that DBS is a therapy option even in the early course of the disease, when first complications arise despite a rigorous adjustment of the pharmacological treatment. The unique feature of this therapeutic approach is the ability to preferentially modulate specific brain networks through the choice of stimulation site. The clinical effects have been unequivocally confirmed in recent studies; however, the impact of DBS and the supplementary effect of L-DOPA on the neuronal network are not yet fully understood. In this review, we present emerging data on the presumable mechanisms of DBS in patients with PD and discuss the pathophysiological similarities and differences in the effects of DBS in comparison to dopaminergic medication. Targeted, selective modulation of brain networks by DBS and pharmacodynamic effects of L-DOPA therapy on the central nervous system are presented. Moreover, we outline the perioperative algorithms for PD patients before and directly after the implantation of DBS electrodes and strategies for the reduction of side effects and optimization of motor and non-motor symptoms.

Generic dynamic causal modelling: An illustrative application to Parkinson's disease

We present a technical development in the dynamic causal modelling of electrophysiological responses that combines qualitatively different neural mass models within a single network. This affords the option to couple various cortical and subcortical nodes that differ in their form and dynamics. Moreover, it enables users to implement new neural mass models in a straightforward and standardized way. This generic framework hence supports flexibility and facilitates the exploration of increasingly plausible models. We illustrate this by coupling a basal ganglia-thalamus model to a (previously validated) cortical model developed specifically for motor cortex. The ensuing DCM is used to infer pathways that contribute to the suppression of beta oscillations induced by dopaminergic medication in patients with Parkinson's disease. Experimental recordings were obtained from deep brain stimulation electrodes (implanted in the subthalamic nucleus) and simultaneous magnetoencephalography. In line with previous studies, our results indicate a reduction of synaptic efficacy within the circuit between the subthalamic nucleus and external pallidum, as well as reduced efficacy in connections of the hyperdirect and indirect pathway leading to this circuit. This work forms the foundation for a range of modelling studies of the synaptic mechanisms (and pathophysiology) underlying event-related potentials and cross-spectral densities.

Patterned low-frequency deep brain stimulation induces motor deficits and modulates cortex-basal ganglia neural activity in healthy rats

Deep brain stimulation (DBS) is an effective therapy for movement disorders, including Parkinson's disease (PD), although the mechanisms of action remain unclear. Abnormal oscillatory neural activity is correlated with motor symptoms, and pharmacological or DBS treatment that alleviates motor symptoms appears to suppress abnormal oscillations. However, whether such oscillatory activity is causal of motor deficits such as tremor remains unclear. Our goal was to generate abnormal oscillatory activity in the cortex-basal ganglia loop using patterned subthalamic nucleus DBS and to quantify motor behavior in awake healthy rats. Stimulation patterns were designed via model-based optimization to increase power in the low-frequency (7-11 Hz) band because these oscillations are associated with the emergence of motor symptoms in the 6-hydroxydopamine lesioned rat model of parkinsonism. We measured motor activity using a head-mounted accelerometer, as well as quantified neural activity in cortex and globus pallidus (GP), in response to 5 stimulation patterns that generated a range of 7- to 11-Hz spectral power. Stimulation patterns induced oscillatory activity in the low-frequency band in the cortex and GP and caused tremor, whereas control patterns and regular 50-Hz DBS did not generate any such effects. Neural and motor-evoked responses observed during stimulation were synchronous and time-locked to stimulation bursts within the patterns. These results identified elements of irregular patterns of stimulation that were correlated with tremor and tremor-related neural activity in the cortex and basal ganglia and may lead to the identification of the oscillatory activity and structures associated with the generation of tremor activity. NEW & NOTEWORTHY Subthalamic nucleus deep brain stimulation is a promising therapy for movement disorders such as Parkinson's disease. Several groups reported correlation between suppression of abnormal oscillatory activity in the cortex-basal ganglia and motor symptoms, but it remains unclear whether such oscillations play a causal role in the emergence of motor symptoms. We demonstrate generation of tremor and pathological oscillatory activity in otherwise healthy rats by stimulation with patterns that produced increases in low-frequency oscillatory activity.

Alternating Modulation of Subthalamic Nucleus Beta Oscillations during Stepping

Gait disturbances in Parkinson's disease are commonly refractory to current treatment options and majorly impair patient's quality of life. Auditory cues facilitate gait and prevent motor blocks. We investigated how neural dynamics in the human subthalamic nucleus of Parkinsons's disease patients (14 male, 2 female) vary during stepping and whether rhythmic auditory cues enhance the observed modulation. Oscillations in the beta band were suppressed after ipsilateral heel strikes, when the contralateral foot had to be raised, and reappeared after contralateral heel strikes, when the contralateral foot rested on the floor. The timing of this 20–30 Hz beta modulation was clearly distinct between the left and right subthalamic nucleus, and was alternating within each stepping cycle. This modulation was similar, whether stepping movements were made while sitting, standing, or during gait, confirming the utility of the stepping in place paradigm. During stepping in place, beta modulation increased with auditory cues that assisted patients in timing their steps more regularly. Our results suggest a link between the degree of power modulation within high beta frequency bands and stepping performance. These findings raise the possibility that alternating deep brain stimulation patterns may be superior to constant stimulation for improving parkinsonian gait.

SIGNIFICANCE STATEMENT Gait disturbances in Parkinson's disease majorly reduce patients' quality of life and are often refractory to current treatment options. We investigated how neural activity in the subthalamic nucleus of patients who received deep brain stimulation surgery covaries with the stepping cycle. 20–30 Hz beta activity was modulated relative to each step, alternating between the left and right STN. The stepping performance of patients improved when auditory cues were provided, which went along with enhanced beta modulation. This raises the possibility that alternating stimulation patterns may also enhance beta modulation and may be more beneficial for gait control than continuous stimulation, which needs to be tested in future studies.

On the neuronal circuitry mediating L-DOPA-induced dyskinesia

With the advent of rodent models of l-DOPA-induced dyskinesia (LID), a growing literature has linked molecular changes in the striatum to the development and expression of abnormal involuntary movements. Changes in information processing at the striatal level are assumed to impact on the activity of downstream basal ganglia nuclei, which in turn influence brain-wide networks, but very little is actually known about systems-level mechanisms of dyskinesia. As an aid to approach this topic, we here review the anatomical and physiological organisation of cortico-basal ganglia-thalamocortical circuits, and the changes affecting these circuits in animal models of parkinsonism and LID. We then review recent findings indicating that an abnormal cerebellar compensation plays a causal role in LID, and that structures outside of the classical motor circuits are implicated too. In summarizing the available data, we also propose hypotheses and identify important knowledge gaps worthy of further investigation. In addition to informing novel therapeutic approaches, the study of LID can provide new clues about the interplay between different brain circuits in the control of movement.

Incongruent visual feedback during a postural task enhances cortical alpha and beta modulation in patients with Parkinson's disease

OBJECTIVE

In patients with Parkinson's disease (PD), augmented visual feedback (VF) can improve functional motor performance. Conversely, they appear to rely more on visual information than healthy subjects, which is unfavorable when this information is unreliable. Cortical beta activity is thought to be associated with the need for motor adaptation. We here compared event-related EEG parameters during a whole-body postural weight-shifting task between congruent and incongruent feedback conditions.

METHODS

Twenty-four patients with PD and fifteen healthy, age- and gender-matched controls performed rhythmic swaying movements. VF was presented in real-time (congruent), delayed (incongruent), or was entirely absent. We estimated source activity in four regions-of-interest and determined motor-related spectral power and power modulation in alpha and beta frequency bands.

RESULTS

For congruent VF no significant differences in cortical activity between the two groups were present. For incongruent VF, the PD group showed significantly higher beta modulation in primary motor cortex, and higher alpha modulation in primary visual cortex.

CONCLUSIONS

Event-related beta modulation in the motor network and alpha modulation in visual areas discriminated between groups, suggesting altered visuomotor processing in PD patients.

SIGNIFICANCE

This study finds evidence for increased modulation of alpha/beta activity during perceptual-motor tasks in PD, possibly indicating an unwarranted higher confidence in VF.

High-resolution local field potentials measured with deep brain stimulation arrays

OBJECTIVE

Local field potential (LFP) recordings along a deep brain stimulation (DBS) lead can provide useful feedback for titrating DBS therapy. However, conventional DBS leads with four cylindrical macroelectrodes likely undersample the spatial distribution of sinks and sources in a given brain region. In this study, we investigated the spectral power and spatial feature sizes of LFP activity in non-human primate subthalamic nucleus and globus pallidus using chronically implanted 32-channel directional DBS arrays.

APPROACH

Subthalamic nucleus and globus pallidus LFP signals were recorded from directional DBS arrays in the resting state and during a reach-and-retrieval task in two non-human primates in naïve and parkinsonian conditions. LFP recordings were compared amongst bipolar pairs of electrodes using individual and grouped electrode configurations, with the latter mimicking the cylindrical macroelectrode configurations used in current clinical LFP recordings.

MAIN RESULTS

Recordings from these DBS arrays showed that (1) beta oscillations have spatial 'fingerprints' in the subthalamic nucleus and globus pallidus, and (2) that these oscillations were muted when grouping electrode contacts together to create cylindrical macroelectrodes similar in relative dimension to those used clinically. Further, these maps depended on parkinsonian condition and whether the subject was resting or performing a motor task.

SIGNIFICANCE

Development of future closed-loop DBS therapies that rely on LFP feedback will benefit from implanting DBS arrays with electrode sizes and spacings that are more consistent with the dimensions of oscillatory sinks and sources within the brain.

Value encoding in the globus pallidus: fMRI reveals an interaction effect between reward and dopamine drive

The external part of the globus pallidus (GPe) is a core nucleus of the basal ganglia (BG) whose activity is disrupted under conditions of low dopamine release, as in Parkinson's disease. Current models assume decreased dopamine release in the dorsal striatum results in deactivation of dorsal GPe, which in turn affects motor expression via a regulatory effect on other nuclei of the BG. However, recent studies in healthy and pathological animal models have reported neural dynamics that do not match with this view of the GPe as a relay in the BG circuit. Thus, the computational role of the GPe in the BG is still to be determined. We previously proposed a neural model that revisits the functions of the nuclei of the BG, and this model predicts that GPe encodes values which are amplified under a condition of low striatal dopaminergic drive. To test this prediction, we used an fMRI paradigm involving a within-subject placebo-controlled design, using the dopamine antagonist risperidone, wherein healthy volunteers performed a motor selection and maintenance task under low and high reward conditions. ROI-based fMRI analysis revealed an interaction between reward and dopamine drive manipulations, with increased BOLD activity in GPe in a high compared to low reward condition, and under risperidone compared to placebo. These results confirm the core prediction of our computational model, and provide a new perspective on neural dynamics in the BG and their effects on motor selection and cognitive disorders.

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We investigate the representation of action-state values in the basal ganglia.

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Value representation is enhanced in the GPe under reduced dopaminergic drive.

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Value representation is enhanced in the SNr under basal dopaminergic drive.

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The results validate a proposed neural model of the basal ganglia.

Frequency-Dependent Corticostriatal Disinhibition Resulting from Chronic Dopamine Depletion: Role of Local Striatal cGMP and GABA-AR Signaling

The onset of motor deficits in parkinsonism is thought to result from dopamine (DA) loss-induced corticostriatal disruption and the development of excessive cortico-basal ganglia synchronization. To gain insights into the mechanisms underlying such corticostriatal dysfunction, we conducted local field potential (LFP) recordings in rats and measured how striatal manipulations of DA, cyclic guanosine monophosphate (cGMP), and gamma-aminobutyric acid- A receptor (GABA-AR) signaling impact corticostriatal transmission at specific oscillatory frequencies. Results indicate that the degree of 6-hydroxydopamine-induced DA lesion and subsequent changes in striatal DA, cGMP, and GABA-AR signaling contribute to impair LFP suppression such that the DA-depleted striatum becomes more permissive to cortically driven oscillations at 10-20 Hz, and to a lesser extent, at 40 Hz. Notably, the corticostriatal dysfunction at 40 Hz emerged only when the degree of chronic DA lesion surpassed 90%, which coincides with the appearance of severe forelimb stepping deficits. Collectively, these results indicate that several mechanisms contribute to suppress LFP within the 10-20 Hz range, yet a critical level of striatal GABAergic activity is required for sustaining corticostriatal inhibition at 40 Hz. Both the degree and chronicity of DA lesion are major contributing factors to the severity of motor and striatal GABAergic deficits that could only be reversed by strengthening local GABA-AR function.

Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease

The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD.

Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat

Much of the motor impairment associated with Parkinson’s disease is thought to arise from pathological activity in the networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in parkinsonism, we investigated changes to the directed connectivity in BG networks following dopamine depletion. We recorded local field potentials (LFPs) in the cortex and basal ganglia of rats rendered parkinsonian by injection of 6-hydroxydopamine (6-OHDA) and in dopamine-intact controls. We performed systematic analyses of the networks using a novel tool for estimation of directed interactions (nonparametric directionality, NPD). We used a “conditioned” version of the NPD analysis that reveals the dependence of the correlation between two signals on a third reference signal. We find evidence of the dopamine dependency of both low-beta (14–20 Hz) and high-beta/low-gamma (20–40 Hz) directed network interactions. Notably, 6-OHDA lesions were associated with enhancement of the cortical “hyperdirect” connection to the subthalamic nucleus (STN) and its feedback to the cortex and striatum. We find that pathological beta synchronization resulting from 6-OHDA lesioning is widely distributed across the network and cannot be located to any individual structure. Furthermore, we provide evidence that high-beta/gamma oscillations propagate through the striatum in a pathway that is independent of STN. Rhythms at high beta/gamma show susceptibility to conditioning that indicates a hierarchical organization compared with those at low beta. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in parkinsonism.

NEW & NOTEWORTHY We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson’s disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a “short-circuiting” of the network that gives rise to the conditions from which pathological synchronization may arise.

Spatio-temporal dynamics of cortical drive to human subthalamic nucleus neurons in Parkinson's disease

Pathological synchronisation of beta frequency (12–35 Hz) oscillations between the subthalamic nucleus (STN) and cerebral cortex is thought to contribute to motor impairment in Parkinson's disease (PD). For this cortico-subthalamic oscillatory drive to be mechanistically important, it must influence the firing of STN neurons and, consequently, their downstream targets. Here, we examined the dynamics of synchronisation between STN LFPs and units with multiple cortical areas, measured using frontal ECoG, midline EEG and lateral EEG, during rest and movement. STN neurons lagged cortical signals recorded over midline (over premotor cortices) and frontal (over prefrontal cortices) with stable time delays, consistent with strong corticosubthalamic drive, and many neurons maintained these dynamics during movement. In contrast, most STN neurons desynchronised from lateral EEG signals (over primary motor cortices) during movement and those that did not had altered phase relations to the cortical signals. The strength of synchronisation between STN units and midline EEG in the high beta range (25–35 Hz) correlated positively with the severity of akinetic-rigid motor symptoms across patients. Together, these results suggest that sustained synchronisation of STN neurons to premotor-cortical beta oscillations play an important role in disrupting the normal coding of movement in PD.

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Multi-channel EEG with coincident STN single unit and local field potential recordings

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Variable time delays between beta oscillations in different cortical areas and STN neurons.

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Frontal/premotor cortical areas have most stable oscillatory synchronisation with STN neurons.

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Correlation between cortico-subthalamic beta-frequency synchronisation and clinical scores in PD.

High-fat diet-induced obesity and insulin resistance are characterized by differential beta oscillatory signaling of the limbic cortico-basal ganglia loop

The concept of brain circuit disorders has been proposed for a variety of neuropsychiatric diseases, characterized by pathological disturbances of neuronal networks including changes in oscillatory signaling of re-entrant cortico-subcortical loops in the basal ganglia system. Parts of this circuitry play a pivotal role in energy homeostasis. We therefore investigated whether high-fat diet (HFD) induced obesity is associated with changes in oscillatory signaling in the limbic cortico-basal ganglia loop. We performed multi-site in-vivo electrophysiological recordings of local field potentials within this network under urethane anesthesia in adult rats after 4 weeks of HFD feeding compared to age-matched controls. Recordings were performed at baseline and during systemic glucose challenge. Our analysis demonstrates increased oscillatory beta power in the nucleus accumbens (NAC) associated with decreased beta coherence between cortex and NAC in animals fed a HFD. Spontaneous beta oscillatory power strongly correlated with endocrine markers of obesity. The glucose challenge increased beta oscillations in control animals but not in animals receiving the HFD. Furthermore direct intracerebroventricular insulin injection increased beta oscillations in the NAC. The present study provides evidence for aberrant oscillatory signaling in the limbic cortico-basal ganglia loop that might contribute to the dysfunctional information processing in obesity.

Homogeneous processing in the striatal direct and indirect pathways: single body part sensitive type IIb neurons may express either dopamine receptor D1 or D2

Striatal medium spiny projection neurons (MSNs) output through two diverging circuits, the 'direct and indirect pathways' which originate from minimally overlapping populations of MSNs expressing either the dopamine receptor D1 or the dopamine receptor D2. One modern theory of direct and indirect pathway function proposes that activation of direct pathway MSNs facilitates output of desired motor programs, while activation of indirect pathway MSNs inhibits competing motor programs. A separate theory suggests that coordinated timing or synchrony of the direct and indirect pathways is critical for the execution of refined movements. These hypotheses are made testable by a common type of striatal neuron known as type IIb MSNs. Clusters of these MSNs exhibit phasic increases in firing rate related to sensorimotor activity of single body parts. If these MSNs were to reside in only the direct pathway, evidence would be provided that D1 MSNs are 'motor program' specific, which would lend credence to the 'competing motor programs' hypothesis. However, if type IIb MSNs reside in both pathways, evidence would be provided for the 'coordinated timing or synchrony' hypothesis. Our results show that type IIb neurons may express either D1 or D2. This evidence supports the theory that the coordinated timing or synchrony of the direct and indirect pathways is critical for refined movements. We also propose a model in which the direct and indirect pathways act as a differentiator circuit, providing a possible mechanism by which coordinated activity of D1 and D2 neurons may output meaningful somatosensorimotor information to downstream structures.

Distinct Roles of Ventromedial versus Ventrolateral Striatal Medium Spiny Neurons in Reward-Oriented Behavior

The ventral striatum (VS) is a key brain center regulating reward-oriented behavior [1-4]. The VS can be anatomically divided into medial (VMS) and lateral (VLS) portions based on cortical input patterns. The VMS receives inputs from medial pallium-originated limbic structures (e.g., the medial prefrontal cortex [mPFC]), and the VLS receives inputs from the lateral pallium-originated areas (e.g., the insula) [5, 6]. This anatomical feature led us to hypothesize a functional segregation within the VS in terms of the regulation of reward-oriented behavior. Here, we engineered a fiber photometry system [4] and monitored population-level Ca²⁺ activities of dopamine D2-receptor-expressing medium spiny neurons (D2-MSNs), one of the major cell types in the striatum, during a food-seeking discrimination task. We found that VLS D2-MSNs were activated at the time of cue presentation. In stark contrast, VMS D2-MSNs were inhibited at this time point. Optogenetic counteraction of those changes in the VLS and VMS impaired action initiation and increased responding toward non-rewarded cues, respectively. During lever-press reversal training, VMS inhibition at the time of cue presentation temporarily ceased and optogenetic activation of VMS D2-MSNs facilitated acquisition of the new contingency. These data indicate that the opposing inhibition and excitation in VMS and VLS are important for selecting and initiating a proper action in a reward-oriented behavior. We propose distinct subregional roles within the VS in the execution of successful reward-oriented behavior.

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.

Decreased global field synchronization of multichannel frontal EEG measurements in obsessive-compulsive disorders

Global field synchronization (GFS) quantifies the synchronization level of brain oscillations. The GFS method has been introduced to measure functional synchronization of EEG data in the frequency domain. GFS also detects phase interactions between EEG signals acquired from all of the electrodes. If a considerable amount of local brain neurons has the same phase, these neurons appear to interact with each other. EEG data were received from 17 obsessive-compulsive disorder (OCD) patients and 17 healthy controls (HC). OCD effects on local and large-scale brain circuits were studied. Analysis of the GFS results showed significantly decreased values in the delta and full frequency bands. This research suggests that OCD causes synchronization disconnection in both the frontal and large-scale regions. This may be related to motivational, emotional and cognitive dysfunctions.

Myoclonus epilepsy and ataxia due to KCNC1 mutation: Analysis of 20 cases and K+ channel properties

OBJECTIVE

To comprehensively describe the new syndrome of myoclonus epilepsy and ataxia due to potassium channel mutation (MEAK), including cellular electrophysiological characterization of observed clinical improvement with fever.

METHODS

We analyzed clinical, electroclinical, and neuroimaging data for 20 patients with MEAK due to recurrent KCNC1 p.R320H mutation. In vitro electrophysiological studies were conducted using whole cell patch-clamp to explore biophysical properties of wild-type and mutant K_V 3.1 channels.

RESULTS

Symptoms began at between 3 and 15 years of age (median = 9.5), with progressively severe myoclonus and rare tonic-clonic seizures. Ataxia was present early, but quickly became overshadowed by myoclonus; 10 patients were wheelchair-bound by their late teenage years. Mild cognitive decline occurred in half. Early death was not observed. Electroencephalogram (EEG) showed generalized spike and polyspike wave discharges, with documented photosensitivity in most. Polygraphic EEG-electromyographic studies demonstrated a cortical origin for myoclonus and striking coactivation of agonist and antagonist muscles. Magnetic resonance imaging revealed symmetrical cerebellar atrophy, which appeared progressive, and a prominent corpus callosum. Unexpectedly, transient clinical improvement with fever was noted in 6 patients. To explore this, we performed high-temperature in vitro recordings. At elevated temperatures, there was a robust leftward shift in activation of wild-type K_V 3.1, increasing channel availability.

INTERPRETATION

MEAK has a relatively homogeneous presentation, resembling Unverricht-Lundborg disease, despite the genetic and biological basis being quite different. A remarkable improvement with fever may be explained by the temperature-dependent leftward shift in activation of wild-type K_V 3.1 subunit-containing channels, which would counter the loss of function observed for mutant channels, highlighting KCNC1 as a potential target for precision therapeutics. Ann Neurol 2017;81:677-689.

Independent Causal Contributions of Alpha- and Beta-Band Oscillations during Movement Selection

To select a movement, specific neuronal populations controlling particular features of that movement need to be activated, whereas other populations are downregulated. The selective (dis)inhibition of cortical sensorimotor populations is governed by rhythmic neural activity in the alpha (8-12 Hz) and beta (15-25 Hz) frequency range. However, it is unclear whether and how these rhythms contribute independently to motor behavior. Building on a recent dissociation of the sensorimotor alpha- and beta-band rhythms, we test the hypothesis that the beta-band rhythm governs the disinhibition of task-relevant neuronal populations, whereas the alpha-band rhythm suppresses neurons that may interfere with task performance. Cortical alpha- and beta-band rhythms were manipulated with transcranial alternating current stimulation (tACS) while human participants selected how to grasp an object. Stimulation was applied at either 10 or 20 Hz and was imposed on the sensorimotor cortex contralaterally or ipsilaterally to the grasping hand. In line with task-induced changes in endogenous spectral power, the effect of the tACS intervention depended on the frequency and site of stimulation. Whereas tACS stimulation generally increased movement selection times, 10 Hz stimulation led to relatively faster selection times when applied to the hemisphere ipsilateral to the grasping hand, compared with other stimulation conditions. These effects occurred selectively when multiple movements were considered. These observations functionally differentiate the causal contribution of alpha- and beta-band oscillations to movement selection. The findings suggest that sensorimotor beta-band rhythms disinhibit task-relevant populations, whereas alpha-band rhythms inhibit neuronal populations that could interfere with movement selection.

SIGNIFICANCE STATEMENT

This study shows dissociable effects of 10 Hz and 20 Hz tACS on the duration of movement selection. These observations have two elements of general relevance. First, the finding that alpha- and beta-band oscillations contribute independently to movement selection provides insight in how oscillations orchestrate motor behavior, which is key to understand movement selection deficits in neurodegenerative disorders. Second, the findings highlight the potential of 10 Hz stimulation as a neurophysiologically grounded intervention to enhance human performance. In particular, this intervention can potentially be exploited to boost rehabilitation after neural damage by targeting the unaffected hemisphere.

Acute In Vivo Electrophysiological Recordings of Local Field Potentials and Multi-unit Activity from the Hyperdirect Pathway in Anesthetized Rats

Converging evidence shows that many neuropsychiatric diseases should be understood as disorders of large-scale neuronal networks. To better understand the pathophysiological basis of these diseases, it is necessary to precisely characterize in which way the processing of information is disturbed between the different neuronal parts of the circuit. Using extracellular in vivo electrophysiological recordings, it is possible to accurately delineate neuronal activity within a neuronal network. The application of this method has several advantages over alternative techniques, e.g., functional magnetic resonance imaging and calcium imaging, as it allows a unique temporal and spatial resolution and does not rely on genetically engineered organisms. However, the use of extracellular in vivo recordings is limited since it is an invasive technique that cannot be universally applied. In this article, a simple and easy to use method is presented with which it is possible to simultaneously record extracellular potentials such as local field potentials and multiunit activity at multiple sites of a network. It is detailed how a precise targeting of subcortical nuclei can be achieved using a combination of stereotactic surgery and online analysis of multi-unit recordings. Thus, it is demonstrated, how a complete network such as the hyperdirect cortico-basal ganglia loop can be studied in anesthetized animals in vivo.

Effect of Eye Opening on Single-Unit Activity and Local Field Potentials in the Subthalamic Nucleus

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN DBS) is an established treatment in Parkinson's disease (PD). We investigate the effect of eye opening on neuronal activity and local field potentials (LFPs) in the STN.

METHODS

We prospectively enrolled 25 PD patients undergoing STN DBS in our institution. During DBS, single-unit activity (SUA) and LFPs were measured when eyes were open and closed. As movement is known to result in changes in LFPs, we tested response to eye opening in the presence and absence of movement.

RESULTS

Neither eye state nor arm movement has a significant influence on SUA recordings. There is a statistically significant interaction between eye state and arm movement (p < 0.05). In the presence of movement, STN SUA increase when eyes open (p < 0.05). When eyes are closed, STN SUA decrease with movement (p < 0.05). STN theta LFP oscillations decrease when eyes are open compared to closed, irrespective of movement status (p < 0.05).

DISCUSSION

STN activity is influenced by eye state and arm movement. It is unclear whether this is attributed to a change in the STN's role in oculomotor control or from a change in attentional state. Understanding how physiologic normal activity alters neural activity is critical for the optimization of DBS therapy, particularly in closed-loop neuromodulation.

Inducible ablation of dopamine D2 receptors in adult mice impairs locomotion, motor skill learning and leads to severe parkinsonism

Motor execution and planning are tightly regulated by dopamine D1 and D2 receptors present in basal ganglia circuits. Although stimulation of D1 receptors is known to enhance motor function, the global effect of D2 receptor (D2R) stimulation or blockade remains highly controversial, with studies showing increasing, decreasing or no changes in motor activity. Moreover, pharmacological and genetic attempts to block or eliminate D2R have led to controversial results that questioned the importance of D2R in motor function. In this study, we generated an inducible Drd2 null-allele mouse strain that circumvented developmental compensations found in constitutive Drd2^-/- mice and allowed us to directly evaluate the participation of D2R in spontaneous locomotor activity and motor learning. We have found that loss of D2R during adulthood causes severe motor impairments, including hypolocomotion, deficits in motor coordination, impaired learning of new motor routines and spontaneous catatonia. Moreover, severe motor impairment, resting tremor and abnormal gait and posture, phenotypes reminiscent of Parkinson's disease, were evident when the mutation was induced in aged mice. Altogether, the conditional Drd2 knockout model studied here revealed the overall fundamental contribution of D2R in motor functions and explains some of the side effects elicited by D2R blockers when used in neurological and psychiatric conditions, including schizophrenia, bipolar disorder, Tourette's syndrome, dementia, alcohol-induced delusions and obsessive-compulsive disorder.

Movement-related beta oscillations show high intra-individual reliability

Oscillatory activity in the beta frequency range (15-30Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic. Here, we used scalp electroencephalography (EEG) to evaluate intra-individual reliability of beta-band oscillations over six sessions, focusing on changes in beta activity during movement (Movement-Related Beta Desynchronization, MRBD) and after movement termination (Post-Movement Beta Rebound, PMBR). Subjects performed visually-cued unimanual wrist flexion and extension. We assessed Intraclass Correlation Coefficients (ICC) and between-session correlations for spectral power and peak frequency measures of movement-related and resting beta activity. Movement-related and resting beta power from both sensorimotor cortices was highly reliable across sessions. Resting beta power yielded highest reliability (average ICC=0.903), followed by MRBD (average ICC=0.886) and PMBR (average ICC=0.663). Notably, peak frequency measures yielded lower ICC values compared to the assessment of spectral power, particularly for movement-related beta activity (ICC=0.386-0.402). Our data highlight that power measures of movement-related beta oscillations are highly reliable, while corresponding peak frequency measures show greater intra-individual variability across sessions. Importantly, our finding that beta power estimates show high intra-individual reliability over time serves to validate the notion that these measures reflect meaningful individual differences that can be utilised in basic research and clinical studies.

The cortical signature of symptom laterality in Parkinson's disease

Patients with Parkinson's disease (PD) often present with unilateral motor symptoms that eventually spread to the other side. This symptom lateralization is diagnostically important, as it serves to distinguish PD from other motor disorders with overlapping symptom profiles. Further, recent studies have shown that the side of symptom onset is important for prognosis, as there are differences in the rate of disease progression and the incidence of secondary symptoms between right- and left-dominant (RD, LD) patients. Physiologically, previous studies have shown asymmetrical decline in structure and metabolism throughout the basal ganglia, although connecting this directly to motor function has been difficult. To identify the neurophysiological basis of symptom laterality in PD, we recorded magnetoencephalography (MEG) during left- and right-hand movement paradigms in patients with PD who exhibited either RD or LD symptomatology. The beta oscillations serving these movements were then imaged using beamforming methods, and we extracted the time series of the peak voxel in the left and right primary motor cortices for each movement. In addition, each patient's symptom asymmetry was quantitated using the Unified Parkinson's Disease Rating Scale (UPDRS), which allowed the relationship between symptom asymmetry and neural asymmetry to be assessed. We found that LD patients had stronger beta suppression during movement, as well as greater post-movement beta rebound compared to patients with RD symptoms, independent of the hand that was moved. Interestingly, the asymmetry of beta activity during right-hand movement uniquely correlated with symptom asymmetry, such that the more LD the symptom profile, the more left-lateralized (i.e., contralateral to movement) the beta response; conversely, the more RD the symptom profile, the more right-lateralized (i.e., ipsilateral to movement) the beta response. This study is the first to directly probe the relationship between symptom asymmetry and the laterality of neural activity during movement in patients with PD, and suggests that LD patients have a fundamentally different and more “healthy” oscillatory pattern relative to RD patients.

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Right-dominant expression of Parkinson's has been connected to faster progression.

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Linkage between symptom asymmetry and cortical physiology remains unknown.

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Cortical motor activity was measured in patients with left/right-dominant symptoms.

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Patients with left-dominant symptoms had “healthier” pattern of motor responses.

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Laterality of cortical activity during movement was related to symptom laterality.

Optimized temporal pattern of brain stimulation designed by computational evolution

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in a parkinsonian rat model and in patients. Both optimized and standard high-frequency stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution of temporal patterns to increase the efficiency of brain stimulation in treating Parkinson's disease and thereby reduce the energy required for successful treatment below that of current brain stimulation paradigms.

The Cellular Diversity of the Pedunculopontine Nucleus: Relevance to Behavior in Health and Aspects of Parkinson's Disease

The pedunculopontine nucleus (PPN) is a rostral brainstem structure that has extensive connections with basal ganglia nuclei and the thalamus. Through these the PPN contributes to neural circuits that effect cortical and hippocampal activity. The PPN also has descending connections to nuclei of the pontine and medullary reticular formations, deep cerebellar nuclei, and the spinal cord. Interest in the PPN has increased dramatically since it was first suggested to be a novel target for treating patients with Parkinson's disease who are refractory to medication. However, application of frequency-specific electrical stimulation of the PPN has produced inconsistent results. A central reason for this is that the PPN is not a heterogeneous structure. In this article, we review current knowledge of the neurochemical identity and topographical distribution of neurons within the PPN of both humans and experimental animals, focusing on studies that used neuronally selective targeting strategies to ascertain how the neurochemical heterogeneity of the PPN relates to its diverse functions in relation to movement and cognitive processes. If the therapeutic potential of the PPN is to be realized, it is critical to understand the complex structure-function relationships that exist here.

Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion

Coupling between cortical oscillations and muscle activity facilitates neuronal communication during motor control. The linear part of this coupling, known as corticomuscular coherence, has received substantial attention, even though neuronal communication underlying motor control has been demonstrated to be highly nonlinear. A full assessment of corticomuscular coupling, including the nonlinear part, is essential to understand the neuronal communication within the sensorimotor system. In this study, we applied the recently developed n:m coherence method to assess nonlinear corticomuscular coupling during isotonic wrist flexion. The n:m coherence is a generalized metric for quantifying nonlinear cross-frequency coupling as well as linear iso-frequency coupling. By using independent component analysis (ICA) and equivalent current dipole source localization, we identify four sensorimotor related brain areas based on the locations of the dipoles, i.e., the contralateral primary sensorimotor areas, supplementary motor area (SMA), prefrontal area (PFA) and posterior parietal cortex (PPC). For all these areas, linear coupling between electroencephalogram (EEG) and electromyogram (EMG) is present with peaks in the beta band (15–35 Hz), while nonlinear coupling is detected with both integer (1:2, 1:3, 1:4) and non-integer (2:3) harmonics. Significant differences between brain areas is shown in linear coupling with stronger coherence for the primary sensorimotor areas and motor association cortices (SMA, PFA) compared to the sensory association area (PPC); but not for the nonlinear coupling. Moreover, the detected nonlinear coupling is similar to previously reported nonlinear coupling of cortical activity to somatosensory stimuli. We suggest that the descending motor pathways mainly contribute to linear corticomuscular coupling, while nonlinear coupling likely originates from sensory feedback.

The network sustaining action myoclonus: a MEG-EMG study in patients with EPM1

Background

To explore the cortical network sustaining action myoclonus and to found markers of the resulting functional impairment, we evaluated the distribution of the cortico-muscular coherence (CMC) and the frequency of coherent cortical oscillations with magnetoencephalography (MEG). All patients had EPM1 (Unverricht-Lundborg) disease known to present with prominent and disabling movement-activated myoclonus.

Methods

Using autoregressive models, we evaluated CMC on MEG sensors grouped in regions of interests (ROIs) above the main cortical areas. The movement was a repeated sustained isometric extension of the right hand and right foot. We compared the data obtained in 10 EPM1 patients with those obtained in 10 age-matched controls.

Results

As expected, CMC in beta band was significantly higher in EPM1 patients compared to controls in the ROIs exploring the sensorimotor cortex, but, it was also significantly higher in adjacent ROIs ipsilateral and contralateral to the activated limb. Moreover, the beta-CMC peak occurred at frequencies significantly slower and more stable frequencies in EPM1 patients with respect to controls. The frequency of the beta-CMC peak inversely correlated with the severity of myoclonus.

Conclusions

the high and spatially extended beta-CMC peaking in a restricted range of low-beta frequencies in EPM1 patients, suggest that action myoclonus may result not only from an enhanced local synchronization but also from a specific oscillatory activity involving an expanded neuronal pool. The significant relationship between beta-CMC peak frequency and the severity of the motor impairment can represent a useful neurophysiological marker for the patients’ evaluation and follow-up.

Cortical Neural Computation by Discrete Results Hypothesis

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.