High Beta Band Research Articles

EEG Oscillations Response To Dual-Target rTMS Therapy of Parkinson Disease and Co-Occuring Depression

The approach intended evaluating neurophysiological concomitants of treatment response to dual-target navigated TMS in patients with Parkinson’s disease and co-occuring depression. Patients with PD (n=46) were initially enrolled for a placebo-controlled study and randomly assigned to either an actively treated (rTMS, n = 23) or a sham-stimulation (sTMS, n=23) groups. Every TMS session was performed sequentially over the primary motor cortex (20 min) followed by the DLPFC (20 min). The patients received a total of 20 sessions on 20 consecutive days. For every participant the main outcome measure included the MDS-UPDRS Motor Examination Part (Part 3) scale score, BDI-II and DASS depression scores as well as spectral parameters of the resting EEG (the last ones were available for fewer patients - rTMS, n=15; sTMS, n=16). After the stimulation course the Part 3 scale scores demonstrated clinically meaningful improvement which was larger in the rTMS group (GROUP by TIME: F1,88= 44,06 p<.001). The BDI-2 and DASS scores showed significantly attenuated negative affect for both groups (TIME: BDI-2 - F1,44=4.48, p <.040; DASS - F1,44=15.34, p <.000). According to sLORETA, beneficial treatment response to the TMS course was accounted by selective EEG power increase over the theta, high beta and gamma frequency bands and significantly locked only to the rTMS group. Using source analysis, the generators of this power difference were localized to somatosensory and visual functional networks, as well as to separate nodes of the salience and default mode networks. There was an increased frontal lobe activation (the 9thand 10thBrodman areas). The main EEG power differences were locked to the ranges of 18-30 Hz and 30-45 Hz (sLORETA statistics at p < .05).The findings demonstrate the beneficial effects of the dual-target TMS in PD and hints to some EEG oscillatory signatures as putative predictors of the treatment response.

Electrophysiological correlates of cognitive symptoms in multiple sclerosis through neuromagnetic resting-state functional connectivity

Electrophysiological correlates of cognitive symptoms in multiple sclerosis through neuromagnetic resting-state functional connectivity

Electrophysiological Signatures of Intrinsic Functional Connectivity Related to rTMS Treatment for Mal de Debarquement Syndrome

To determine intrinsic functional connectivity (IFC) related to symptom changes induced by rTMS in mal de debarquement syndrome (MdDS), a motion perceptual disorder induced by entrainment to oscillating motion. Twenty right-handed women (mean age: 52.9 ± 12.6 years; mean duration illness: 35.2 ± 24.2 months) with MdDS received five sessions of rTMS (1 Hz right DLPFC, 10 Hz left DLPFC) over consecutive days. High-density (128-channel) resting-state EEG were recorded prior to and following treatment sessions and analyzed using a group-level independent component (IC) analysis. IFC between 19 ICs was quantified by inter-IC phase coherence (ICPC) in six frequency bands (delta, theta, low alpha, high alpha, beta, gamma). Correlational analyses between IFCs and symptoms were performed. Symptom improvement after rTMS was significantly correlated with (1) an increase in low alpha band (8–10 Hz) IFC but a decrease of IFC in all other bands, and (2) high baseline IFC in the high alpha (11–13 Hz) and beta bands (14–30 Hz). Most treatment related IFC changes occurred between frontal and parietal regions with a linear association between the degree of symptom improvement and the number of coherent IFC changes. Frequency band and region specific IFC changes correlate with and can predict symptom changes induced by rTMS over DLPFC in MdDS. MdDS symptom response correlates with high baseline IFC in most frequency bands. Treatment induced increase in long-range low alpha IFC and decreases in IFC in other bands as well as the proportion of coherent IFC changes correlate with symptom reduction.

Frontal EEG Temporal and Spectral Dynamics Similarity Analysis between Propofol and Desflurane Induced Anesthesia Using Hilbert-Huang Transform.

Electroencephalogram (EEG) signal analysis is commonly employed to extract information on the brain dynamics. It mainly targets brain status and communication, thus providing potential to trace differences in the brain's activity under different anesthetics. In this article, two kinds of gamma-amino butyric acid (type A -GABAA) dependent anesthetic agents, propofol and desflurane (28 and 23 patients), were studied and compared with respect to EEG spectrogram dynamics. Hilbert-Huang Transform (HHT) was employed to compute the time varying spectrum for different anesthetic levels in comparison with Fourier based method. Results show that the HHT method generates consistent band power (slow and alpha) dominance pattern as Fourier method does, but exhibits higher concentrated power distribution within each frequency band than the Fourier method during both drugs induced unconsciousness. HHT also finds slow and theta bands peak frequency with better convergence by standard deviation (propofol-slow: 0.46 to 0.24; theta: 1.42 to 0.79; desflurane-slow: 0.30 to 0.25; theta: 1.42 to 0.98) and a shift to relatively lower values for alpha band (propofol: 9.94 Hz to 10.33 Hz, desflurane 8.44 Hz to 8.84 Hz) than Fourier one. For different stage comparisons, although HHT shows significant alpha power increases during unconsciousness stage as the Fourier did previously, it finds no significant high frequency (low gamma) band power difference in propofol whereas it does in desflurane. In addition, when comparing the HHT results within two groups during unconsciousness, high beta band power in propofol is significantly larger than that of desflurane while delta band power behaves oppositely. In conclusion, this study convincingly shows that EEG analyzed here considerably differs between the HHT and Fourier method.

P106. Anodal tDCS over the left sensorimotor area improves motor symptoms and modulates corticocortical coherence in Parkinson’s disease

Network activity in the beta range is correlated with motor symptoms in Parkinson’s disease (PD). Anodal transcranial direct current stimulation (atDCS) over the sensorimotor area modulates cortical excitability and may alleviate motor symptoms in PD. In this study, we aimed to explore the effect of atDCS over the left sensorimotor area on clinical motor outcome, right hand fine motor performance and cortical motor network connectivity. In this double-blind randomized sham-controlled combined EEG and tDCS study, we investigated ten pharmacologically treated idiopathic PD patients after overnight withdrawal of dopaminergic medication and eleven healthy controls during an isometric precision grip task of the right hand before and after stimulation. Participants were studied and crossed-over in two sessions on different days with either ‘verum’ or ‘sham’ stimulation of atDCS (20 min; 1 mA; electrodes placed over left ‘C3’ (anode) and right ‘Fp2’ (cathode)). Cortical connectivity was expressed as corticocortical imaginary coherence in the high beta band (22–27 Hz) between ‘C3’ and all other EEG-channels; the topographic distribution was obtained from 25 cortical EEG channels placed according to the 10–20 system. Fine motor performance was expressed as accuracy error during the precision grip task with lower accuracy error indicating higher motor precision. Clinical motor outcome was measured using the UPDRS III motor score. PD patients with ‘verum’ stimulation showed an increase of corticocortical imaginary coherence in the high beta band from ‘C3’ to the right motor area 30 min after stimulation. This was paralleled by a significant decrease in the UPDRS III motor score. There was no similar modulation in PD ‘sham’ stimulation and in healthy controls in both ‘verum’ and ‘sham’ conditions. However, interestingly, HC showed beta band coupling prior to stimulation directed from ‘C3’ to the right hemisphere. Both groups showed no significant change regarding the accuracy error after stimulation. AtDCS of ‘C3’ entrains beta band coupling between ‘C3’ and the right sensorimotor area with ‘C3’ leading right hemispheric beta band oscillations in the temporal domain. We speculate that this could represent a mechanism to tone down inhibitory influences of the right hemisphere ipsilateral to the right hand, given that increased beta synchrony is associated with increasing motor inhibition in previous studies.

Interactions between frontal and posterior oscillatory dynamics support adjustment of stimulus processing during reinforcement learning

Reinforcement learning (RL) in humans is subserved by a network of striatal and frontal brain areas. The electrophysiological signatures of feedback evaluation are increasingly well understood, but how those signatures relate to the use of feedback to guide subsequent behavioral adjustment remains unclear. One mechanism for post-feedback behavioral optimization is the modulation of sensory processing. We used source-reconstructed MEG to test whether feedback affects the interactions between sources of oscillatory activity in the learning network and task-relevant stimulus-processing areas. Participants performed a probabilistic RL task in which they learned associations between colored faces and response buttons using trial-and-error feedback. Delta-band (2–4 Hz) and theta-band (4–8 Hz) power in multiple frontal regions were sensitive to feedback valence. Low and high beta-band power (12–20 and 20–30 Hz) in occipital, parietal, and temporal regions differentiated between color and face information. Consistent with our hypothesis, single-trial power-power correlations between frontal and posterior-sensory areas were modulated by the interaction between feedback valence and the relevant stimulus characteristic (color versus identity). These results suggest that long-range oscillatory coupling supports post-feedback updating of stimulus processing.

Individual Classification of Single Trial EEG Traces to Discriminate Brain responses to Speech with Different Signal-to-Noise Ratios.

To gain knowledge of listening effort in adverse situations, it is important to know how the brain processes speech with different signal-to-noise ratios (SNR). To investigate this, we conducted a study with 33 hearing impaired individuals, whose electroencephalographic (EEG) signals were recorded while listening to sentences presented in high and low levels of background noise. To discriminate between these two conditions, features from the 64-channel EEG recordings were extracted using the power spectrum obtained by a Fast Fourier Transform. Features vectors were selected on an individual basis by using the statistical R2 approach. The selected features were then classified by a Support Vector Machine with a nonlinear kernel, and the classification results were validated using a leave-one-out strategy, and presented an average classification accuracy over all 33 subjects of 83% (SD=6.4%). The most discriminative features were selected in the high-beta (19-30 Hz) and gamma (30-45 Hz) bands. These results suggest that specific brain oscillations are involved in addressing background noise during speech stimuli, which may reflect differences in cognitive load between the conditions of low and high background noise.

Predictive encoding of motor behavior in the supplementary motor area is disrupted in parkinsonism.

Many studies suggest that Parkinson's disease (PD) is associated with changes in neuronal activity patterns throughout the basal ganglia-thalamocortical motor circuit. There are limited electrophysiological data, however, describing how parkinsonism impacts the presupplementary motor area (pre-SMA) and SMA proper (SMAp), cortical areas known to be involved in movement planning and motor control. In this study, local field potentials (LFPs) were recorded in the pre-SMA/SMAp of a nonhuman primate during a visually cued reaching task. Recordings were made in the same subject in both the naive and parkinsonian state using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine model of parkinsonism. We found that in the naive animal, well before a go-cue providing instruction of reach onset and direction was given, LFP activity was dynamically modulated in both high (20-30 Hz) and low beta (10-20 Hz) bands, and the magnitude of this modulation (e.g., decrease/increase in beta amplitude for each band, respectively) correlated linearly with reaction time (RT) on a trial-to-trial basis, suggesting it may predictively encode for RT. Consistent with this hypothesis, we observed that this activity was more prominent within the pre-SMA compared with SMAp. In the parkinsonian state, however, pre-SMA/SMAp beta band modulation was disrupted, particularly in the high beta band, such that the predictive encoding of RT was significantly diminished. In addition, the predictive encoding of RT preferentially within pre-SMA over SMAp was lost. These findings add to our understanding of the role of pre-SMA/SMAp in motor behavior and suggest a fundamental role of these cortical areas in early preparatory and premovement processes that are altered in parkinsonism. NEW & NOTEWORTHY Goal-directed movements, such as reaching for an object, necessitate temporal preparation and organization of information processing within the basal ganglia-thalamocortical motor network. Impaired movement in parkinsonism is thought to be the result of pathophysiological activity disrupting information flow within this network. This work provides neurophysiological evidence linking altered motor preplanning processes encoded in pre-SMA/SMAp beta band modulation to the pathogenesis of motor disturbances in parkinsonism.

S64. Analysis of beta frequency oscillations in recorded local field potentials of Parkinson’s disease patients undergoing deep brain stimulation

Introduction Local field potential (LFP) recordings from implanted deep brain stimulator (DBS) leads can provide insight into the pathogenesis of the Parkinson’s disease (PD) specifically by looking at some of the local network properties at the location of the electrode. We recorded LFP activity from DBE leads implanted in the subthalamic nucleus (STN) and performed subsequent data analysis on PD patients undergoing DBS surgery in the off state both at rest and during continuous movement of the contralateral hand in order to identify any reproducible pathophysiological signatures of the disease. Methods LFPs were recorded in 8 patients with PD who underwent bilateral DBS lead implantation within the STN. Following DBS lead placement, bipolar (0–1, 1–2, 2–3) recordings were performed for 2 min at rest and another 2 min with contralateral repetitive hand grasp movements. All recordings were performed in the off state with at least 12 h of since their last medication and prior to macrostimulation testing in the nucleus. The raw LFP recordings were transformed to the frequency domain via the fast fourier transform and then a power spectral was generated from that data with a frequency resolution of 1.3 Hz. Beta-band spectral peaks were located and compared between the two testing states. Results In all patients, predominance of both low and high beta band frequencies (13–20 and 20–35 Hz respectively) were observed both at rest and during movement at the DBS contact where stimulation was deemed to be most therapeutic. Paradoxically, stronger beta peak energy was noted during movement as opposed to the rest state in all patients. Conclusion In patients with PD, excess beta band coupling that paradoxically synchronizes with movement may be a signature of the off state. This excess beta band activity appears to also correlate with the most active DBS lead contact. This increase in energy, or synchronization, during the movement phase is in contrast to what happens in the cortex during similar EEG analysis. This increase in the abnormal beta energy, in PD patients, may help explain the abnormal movements, such as rigidity and bradykinesia, seen in these patients. Further investigations may to help to identify and provide stimulation in situations where excess beta band activity is prevalent at the active contact.

Non-linear Relationship between BOLD Activation and Amplitude of Beta Oscillations in the Supplementary Motor Area during Rhythmic Finger Tapping and Internal Timing.

Functional imaging studies using BOLD contrasts have consistently reported activation of the supplementary motor area (SMA) both during motor and internal timing tasks. Opposing findings, however, have been shown for the modulation of beta oscillations in the SMA. While movement suppresses beta oscillations in the SMA, motor and non-motor tasks that rely on internal timing increase the amplitude of beta oscillations in the SMA. These independent observations suggest that the relationship between beta oscillations and BOLD activation is more complex than previously thought. Here we set out to investigate this rapport by examining beta oscillations in the SMA during movement with varying degrees of internal timing demands. In a simultaneous EEG-fMRI experiment, 20 healthy right-handed subjects performed an auditory-paced finger-tapping task. Internal timing was operationalized by including conditions with taps on every fourth auditory beat, which necessitates generation of a slow internal rhythm, while tapping to every auditory beat reflected simple auditory-motor synchronization. In the SMA, BOLD activity increased and power in both the low and the high beta band decreased expectedly during each condition compared to baseline. Internal timing was associated with a reduced desynchronization of low beta oscillations compared to conditions without internal timing demands. In parallel with this relative beta power increase, internal timing activated the SMA more strongly in terms of BOLD. This documents a task-dependent non-linear relationship between BOLD and beta-oscillations in the SMA. We discuss different roles of beta synchronization and desynchronization in active processing within the same cortical region.

Phase-coherence classification: A new wavelet-based method to separate local field potentials into local (in)coherent and volume-conducted components

BackgroundLocal field potentials (LFP) reflect the integrated electrophysiological activity of large neuron populations and may thus reflect the dynamics of spatially and functionally different networks. New methodWe introduce the wavelet-based phase-coherence classification (PCC), which separates LFP into volume-conducted, local incoherent and local coherent components. It allows to compute power spectral densities for each component associated with local or remote electrophysiological activity. ResultsWe use synthetic time series to estimate optimal parameters for the application to LFP from within the subthalamic nucleus of eight Parkinson patients. With PCC we identify multiple local tremor clusters and quantify the relative power of local and volume-conducted components. We analyze the electrophysiological response to an apomorphine injection during rest and hold. Here we show medication-induced significant decrease of incoherent activity in the low beta band and increase of coherent activity in the high beta band. On medication significant movement-induced changes occur in the high beta band of the local coherent signal. It increases during isometric hold tasks and decreases during phasic wrist movement. Comparison with existing methodsThe power spectra of local PCC components is compared to bipolar recordings. In contrast to bipolar recordings PCC can distinguish local incoherent and coherent signals. We further compare our results with classification based on the imaginary part of coherency and the weighted phase lag index. ConclusionsThe low and high beta band are more susceptible to medication- and movement-related changes reflected by incoherent and local coherent activity, respectively. PCC components may thus reflect functionally different networks.

Levetiracetam Alters Oscillatory Connectivity in Alzheimer’s Disease

Seizures occur at a higher frequency in people with Alzheimer's disease (AD) but overt, clinically obvious events are infrequent. Evidence from animal models and studies in mild cognitive impairment suggest that subclinical epileptic discharges may play a role in the clinical and pathophysiological manifestations of AD. In this feasibility study, the neurophysiological and cognitive effects of acute administration of levetiracetam (LEV) are measured in patients with mild AD to test whether it could have a therapeutic benefit. AD participants were administered low dose LEV (2.5 mg/kg), higher dose LEV (7.5 mg/kg), or placebo in a double-blind, within-subject repeated measures study with EEG recorded at rest before and after administration. After administration of higher dose of LEV, we found significant decreases in coherence in the delta band (1-3.99 Hz) and increases in the low beta (13-17.99 Hz) and the high beta band (24-29.99 Hz). Furthermore, we found trends toward increased power in the frontal and central regions in the high beta band (24-29.99 Hz). However, there were no significant changes in cognitive performance after this single dose administration. The pattern of decreased coherence in the lower frequency bands and increased coherence in the higher frequency bands suggests a beneficial effect of LEV for patients with AD. Larger longitudinal studies and studies with healthy age-matched controls are needed to determine whether this represents a relative normalization of EEG patterns, whether it is unique to AD as compared to normal aging, and whether longer term administration is associated with a beneficial clinical effect.

Toward an electrophysiological "sweet spot" for deep brain stimulation in the subthalamic nucleus.

Enhanced beta-band activity recorded in patients suffering from Parkinson's Disease (PD) has been described as a potential physiomarker for disease severity. Beta power is suppressed by Levodopa intake and STN deep brain stimulation (DBS) and correlates with disease severity across patients. The aim of the present study was to explore the promising signature of the physiomarker in the spatial domain. Based on local field potential data acquired from 54 patients undergoing STN-DBS, power values within alpha, beta, low beta, and high beta bands were calculated. Values were projected into common stereotactic space after DBS lead localization. Recorded beta power values were significantly higher at posterior and dorsal lead positions, as well as in active compared with inactive pairs. The peak of activity in the beta band was situated within the sensorimotor functional zone of the nucleus. In contrast, higher alpha activity was found in a more ventromedial region, potentially corresponding to associative or premotor functional zones of the STN. Beta- and alpha-power peaks were then used as seeds in a fiber tracking experiment. Here, the beta-site received more input from primary motor cortex whereas the alpha-site was more strongly connected to premotor and prefrontal areas. The results summarize predominant spatial locations of frequency signatures recorded in STN-DBS patients in a probabilistic fashion. The site of predominant beta-activity may serve as an electrophysiologically determined target for optimal outcome in STN-DBS for PD in the future. Hum Brain Mapp 38:3377-3390, 2017. © 2017 Wiley Periodicals, Inc.

Heightened Background Cortical Synchrony in Patients With Epilepsy: EEG Phase Synchrony Analysis During Awake and Sleep Stages Using Novel Ensemble Measure.

Excessive cortical synchrony within neural ensembles has been implicated as an important mechanism driving epileptiform activity. The current study measures and compares background electroencephalographic (EEG) phase synchronization in patients having various types of epilepsies and healthy controls during awake and sleep stages. A total of 120 patients with epilepsy (PWE) subdivided into 3 groups (juvenile myoclonic epilepsy [JME], temporal lobe epilepsy [TLE], and extra-temporal lobe epilepsy [Ex-TLE]; n = 40 in each group) and 40 healthy controls were subjected to overnight polysomnography. EEG phase synchronization (SI) between the 8 EEG channels was assessed for delta, theta, alpha, sigma, and high beta frequency bands using ensemble measure on 10-second representative time windows and compared between patients and controls and also between awake and sleep stages. Mean ± SD of SI was compared using 2-way analysis of variance followed by pairwise comparison ( P ≤ .05). In both delta and theta bands, the SI was significantly higher in patients with JME, TLE, and Ex-TLE compared with controls, whereas in alpha, sigma, and high beta bands, SI was comparable between the groups. On comparison of SI between sleep stages, delta band: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3, whereas REM (rapid eye movement) was comparable to wake; theta band: decreased SI during N2 and increase during N3; alpha band: SI was highest in wake and lower in N1, N2, N3, and REM; and sigma and high beta bands: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3; however, sigma band showed lower SI during REM. This study found an increased background cortical synchronization in PWE compared with healthy controls in delta and theta bands during wake and sleep. This background hypersynchrony may be an important property of epileptogenic brain circuitry in PWE, which enables them to effortlessly generate a paroxysmal EEG depolarization shift.

P214 Noninvasive manipulation of fronto-parietal synchrony improves conscious visual perception in humans

Question Correlational evidence in monkeys has reported increased synchrony of high-beta (22–34 Hz) cortical oscillations between frontal and parietal attentional regions during visual tasks engaging an endogenous capture of attention (Buschmann and Miller, Science, 2007). However, these results lack causality. We aim to demonstrate that this frequency specific intrahemispheric synchronization is causally linked to the modulation of visual performance. Methods We recorded EEG signals in human participants ( n = 14) who performed a conscious visual detection task while we manipulated cortical high-beta rhythms with brief rhythmic (30 Hz, 4 pulses) or random bursts of rhythmic Transcranial Magnetic Stimulation (rTMS) delivered to the right Frontal Eye Field (FEF). Participants had to report (yes/no) if he had seen the target (an individually titrated low contrast gabor at 50% detection levels) and if ‘yes’, where it had appeared (left/right of the fixation cross). Individual perceptual sensitivity (d ′ ) was determined using signal detection theory. From the EEG signal, a classical measure of phase-synchrony (evaluating the stability of the phase-relationship between 2 signals) was calculated between the electrode closest to the TMS coil position (FC2) and all other scalp electrodes. To rule-out artificial enhancement of synchrony between pairs of neighbouring scalp electrodes, zero-phase synchronization was not considered. Results We report, in the rhythmic TMS condition (compared to the random TMS control), an increase of inter-regional synchronization in the high-beta band (25–35 Hz) between the area stimulated (right FEF) and a group of parietal electrodes, as well as an increase of local inter-trial coherence in the same frequency band over parietal electrodes. Behaviorally, conscious visual detection was improved for left visual targets (contralateral to the stimulation) in the rhythmic but not random TMS condition. Conclusion Our results show that human high-beta inter-regional synchrony can be manipulated non-invasively and that high-beta oscillatory activity across the right dorsal fronto-parietal attention network causally contributes to the facilitation of conscious visual detection, suggesting potential applications of rhythmic non-invasive brain stimulation for the restoration of impaired visual behaviors. Download high-res image (1MB) Download full-size image

Detection of gait initiation failure in Parkinson's disease patients using EEG signals.

Gait Initiation Failure (GIF) is one of the most disabling gait disturbances seen in advanced Parkinson's disease (PD). Gait Initiation is a complex motor task that requires motor and cognitive processing to enable the correct selection, timing and scaling of movement. Failure to initiate the first step often precipitates falls and leads to significant morbidity. However, the brain mechanisms underlying GIF remain unknown. This study utilized an ambulatory electroencephalography (EEG) technique to investigate the brain dynamic changes underlying GIF and aims to detect the occurrence of GIF in four PD patients. We sought to determine whether episodes of GIF might be associated with a characteristic brain signal that could be detected by surface EEG. This preliminary investigation analyzed the EEG signals through power spectra density (PSD) and centroid frequency (CF) to show that the GIF episodes were associated with significant increases in the high beta band (21-38Hz) across the central, frontal, occipital and parietal EEG sites. By implementing PSD and CF as input features with two-layer Back Propagation neural networks as a classifier, the proposed system was able to detect GIF events with a classification performance of 84.27% sensitivity and 84.80% accuracy. This is the first study to show cortical dynamic changes associated with GIF in Parkinson's disease, providing valuable information to enhance the performance of future GIF detection that could be translated into clinical practice.

Characteristics of local field potentials correlate with pain relief by deep brain stimulation.

To investigate the link between neuronal activity recorded from the sensory thalamus and periventricular gray/periaqueductal gray (PVAG) and pain relief by deep brain stimulation (DBS). Local field potentials (LFPs) were recorded from the sensory thalamus and PVAG post-operatively from ten patients with neuropathic pain. The LFPs were quantified using spectral and time-frequency analysis, the relationship between the LFPs and pain relief was quantified with nonlinear correlation analysis. The theta oscillations of both sensory thalamus and PVAG correlated inversely with pain relief. The high beta oscillations in the sensory thalamus and the alpha oscillations in the PVAG correlated positively with pain relief. Moreover, the ratio of high-power duration to low-power duration of theta band activity in the sensory thalamus and PVAG correlated inversely with pain relief. The duration ratio at the high beta band in the sensory thalamus correlated positively with pain relief. Our results reveal distinct neuronal oscillations at the theta, alpha, and beta frequencies correlating with pain relief by DBS. The study provides quantitative measures for predicting the outcomes of neuropathic pain relief by DBS as well as potential biomarkers for developing adaptive stimulation strategies.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment.

Measuring complex behaviors of local oscillatory networks in deep brain local field potentials

BackgroundMultiple oscillations emerging from the same neuronal substrate serve to construct a local oscillatory network. The network usually exhibits complex behaviors of rhythmic, balancing and coupling between the oscillations, and the quantification of these behaviors would provide valuable insight into organization of the local network related to brain states. New methodAn integrated approach to quantify rhythmic, balancing and coupling neural behaviors based upon power spectral analysis, power ratio analysis and cross-frequency power coupling analysis was presented. Deep brain local field potentials (LFPs) were recorded from the thalamus of patients with neuropathic pain and dystonic tremor. t-Test was applied to assess the difference between the two patient groups. ResultsThe rhythmic behavior measured by power spectral analysis showed significant power spectrum difference in the high beta band between the two patient groups. The balancing behavior measured by power ratio analysis showed significant power ratio differences at high beta band to 8–20Hz, and 30–40Hz to high beta band between the patient groups. The coupling behavior measured by cross-frequency power coupling analysis showed power coupling differences at (theta band, high beta band) and (45–55Hz, 70–80Hz) between the patient groups. Comparison with existing methodThe study provides a strategy for studying the brain states in a multi-dimensional behavior space and a framework to screen quantitative characteristics for biomarkers related to diseases or nuclei. ConclusionsThe work provides a comprehensive approach for understanding the complex behaviors of deep brain LFPs and identifying quantitative biomarkers for brain states related to diseases or nuclei.

Bicycling and Walking are Associated with Different Cortical Oscillatory Dynamics.

Although bicycling and walking involve similar complex coordinated movements, surprisingly Parkinson’s patients with freezing of gait typically remain able to bicycle despite severe difficulties in walking. This observation suggests functional differences in the motor networks subserving bicycling and walking. However, a direct comparison of brain activity related to bicycling and walking has never been performed, neither in healthy participants nor in patients. Such a comparison could potentially help elucidating the cortical involvement in motor control and the mechanisms through which bicycling ability may be preserved in patients with freezing of gait. The aim of this study was to contrast the cortical oscillatory dynamics involved in bicycling and walking in healthy participants. To this end, EEG and EMG data of 14 healthy participants were analyzed, who cycled on a stationary bicycle at a slow cadence of 40 revolutions per minute (rpm) and walked at 40 strides per minute (spm), respectively. Relative to walking, bicycling was associated with a stronger power decrease in the high beta band (23–35 Hz) during movement initiation and execution, followed by a stronger beta power increase after movement termination. Walking, on the other hand, was characterized by a stronger and persisting alpha power (8–12 Hz) decrease. Both bicycling and walking exhibited movement cycle-dependent power modulation in the 24–40 Hz range that was correlated with EMG activity. This modulation was significantly stronger in walking. The present findings reveal differential cortical oscillatory dynamics in motor control for two types of complex coordinated motor behavior, i.e., bicycling and walking. Bicycling was associated with a stronger sustained cortical activation as indicated by the stronger high beta power decrease during movement execution and less cortical motor control within the movement cycle. We speculate this to be due to the more continuous nature of bicycling demanding less phase-dependent sensory processing and motor planning, as opposed to walking.