Alpha and beta EEG power reflects L-dopa acute administration in parkinsonian patients

Harnessing Brainwave Entrainment: A Non-invasive Strategy To Alleviate Neurological Disorder Symptoms

From 1990-2019, the burden of neurological disorders varied considerably across countries and regions. Psychiatric disorders, often emerging in early to mid-adulthood, are linked to late-life neurodegenerative diseases like Alzheimer's disease and Parkinson's disease. Individuals with conditions such as Major Depressive Disorder, Anxiety Disorder, Schizophrenia, and Bipolar Disorder face up to four times higher risk of developing neurodegenerative disorders. Contrarily, 65 % of those with neurodegenerative conditions experience severe psychiatric symptoms during their illness. Further, the limitation of medical resources continues to make this burden a significant global and local challenge. Therefore, brainwave entrainment provides therapeutic avenues for improving the symptoms of diseases. Brainwaves are rhythmic oscillations produced either spontaneously or in response to stimuli. Key brainwave patterns include gamma, beta, alpha, theta, and delta waves, yet the underlying physiological mechanisms and the brain's ability to shift between these dynamic states remain areas for further exploration. In neurological disorders, brainwaves are often disrupted, a phenomenon termed "oscillopathy". However, distinguishing these impaired oscillations from the natural variability in brainwave activity across different regions and functional states poses significant challenges. Brainwave-mediated therapeutics represents a promising research field aimed at correcting dysfunctional oscillations. Herein, we discuss a range of non-invasive techniques such as non-invasive brain stimulation (NIBS), neurologic music therapy (NMT), gamma stimulation, and somatosensory interventions using light, sound, and visual stimuli. These approaches, with their minimal side effects and cost-effectiveness, offer potential therapeutic benefits. When integrated, they may not only help in delaying disease progression but also contribute to the development of innovative medical devices for neurological care.

Cortical modulations before lower limb motor blocks are associated with freezing of gait in Parkinson's disease: an EEG source localization study

BACKGROUND

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) characterized by paroxysmal episodes in which patients are unable to step forward. A research priority is identifying cortical changes before freezing in PD-FOG.

METHODS

We tested 19 patients with PD who had been assessed for FOG (n=14 with FOG and 5 without FOG). While seated, patients stepped bilaterally on pedals to progress forward through a virtual hallway while 64-channel EEG was recorded. We assessed cortical activities before and during lower limb motor blocks (LLMB), defined as a break in rhythmic pedaling, and stops, defined as movement cessation following an auditory stop cue. This task was selected because LLMB correlates with FOG severity in PD and allows recording of high-quality EEG. Patients were tested after overnight withdrawal from dopaminergic medications ("off" state) and in the "on" medications state. EEG source activities were evaluated using individual MRI and standardized low resolution brain electromagnetic tomography (sLORETA). Functional connectivity was evaluated by phase lag index between seeds and pre-defined cortical regions of interest.

RESULTS

EEG source activities for LLMB vs. cued stops localized to right posterior parietal area (Brodmann area 39), lateral premotor area (Brodmann area 6), and inferior frontal gyrus (Brodmann area 47). In these areas, PD-FOG (n=14) increased alpha rhythms (8-12 Hz) before LLMB vs. typical stepping, whereas PD without FOG (n=5) decreased alpha power. Alpha rhythms were linearly correlated with LLMB severity, and the relationship became an inverted U-shape when assessing alpha rhythms as a function of percent time in LLMB in the "off" medication state. Right inferior frontal gyrus and supplementary motor area connectivity was observed before LLMB in the beta band (13-30 Hz). This same pattern of connectivity was seen before stops. Dopaminergic medication improved FOG and led to less alpha synchronization and increased functional connections between frontal and parietal areas.

CONCLUSIONS

Right inferior parietofrontal structures are implicated in PD-FOG. The predominant changes were in the alpha rhythm, which increased before LLMB and with LLMB severity. Similar connectivity was observed for LLMB and stops between the right inferior frontal gyrus and supplementary motor area, suggesting that FOG may be a form of "unintended stopping." These findings may inform approaches to neurorehabilitation of PD-FOG.

Clinical and neurophysiological effects of bilateral repetitive transcranial magnetic stimulation and EEG-guided neurofeedback in Parkinson's disease: a randomized, four-arm controlled trial

BACKGROUND

Repetitive Transcranial Magnetic Stimulation (rTMS) and EEG-guided neurofeedback techniques can reduce motor symptoms in Parkinson's disease (PD). However, the effects of their combination are unknown. Our objective was to determine the immediate and short-term effects on motor and non-motor symptoms, and neurophysiological measures, of rTMS and EEG-guided neurofeedback, alone or combined, compared to no intervention, in people with PD.

METHODS

A randomized, single-blinded controlled trial with 4 arms was conducted. Group A received eight bilateral, high-frequency (10 Hz) rTMS sessions over the Primary Motor Cortices; Group B received eight 30-minute EEG-guided neurofeedback sessions focused on reducing average bilateral alpha and beta bands; Group C received a combination of A and B; Group D did not receive any therapy. The primary outcome measure was the UPDRS-III at post-intervention and two weeks later. Secondary outcomes were functional mobility, limits of stability, depression, health-related quality-of-life and cortical silent periods. Treatment effects were obtained by longitudinal analysis of covariance mixed-effects models.

RESULTS

Forty people with PD participated (27 males, age = 63 ± 8.26 years, baseline UPDRS-III = 15.63 ± 6.99 points, H&Y = 1-3). Group C showed the largest effect on motor symptoms, health-related quality-of-life and cortical silent periods, followed by Group A and Group B. Negligible differences between Groups A-C and Group D for functional mobility or limits of stability were found.

CONCLUSIONS

The combination of rTMS and EEG-guided neurofeedback diminished overall motor symptoms and increased quality-of-life, but this was not reflected by changes in functional mobility, postural stability or depression levels.

TRIAL REGISTRATION

NCT04017481.

Exploring the complexity of EEG patterns in Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily associated with motor dysfunctions. By the time of definitive diagnosis, about 60% of dopaminergic neurons have already been lost; moreover, even if dopaminergic drugs are highly effective in symptoms control, they only help maintaining a near-healthy condition when started as soon as possible. Therefore, interest in identifying early biomarkers of PD has grown in recent years, especially using neurophysiological techniques such as electroencephalography (EEG). This study aims to investigate brain complexity differences in PD patients compared to healthy controls, focusing on the beta band using approximate entropy (ApEn) analysis of resting-state EEG recordings. Sixty participants were recruited, including 25 PD patients and 35 healthy elderly subjects, matched for age and gender. EEG were recorded for each participant and ApEn values were computed in the beta 1 (13-20 Hz) and beta 2 (20-30 Hz) frequency bands for each EEG-channel and for ROIs. PD patients showed statistically lower ApEn values compared to controls in both beta 1 and beta 2 bands. Regarding electrodes analysis, beta 1 band alterations were found in frontocentral areas, while beta 2 band alterations were observed in centroparietal and frontocentral areas. Considering ROIs, statistically lower ApEn values for PD patients has been reported in central and parietal ROIs in the beta 2 band. Complexity reduction in these areas may underlie beta oscillatory activity dysfunction, reflecting impaired cortical mechanisms associated with motor dysfunction in PD. The results suggest that ApEn analysis of resting EEG activity may serve as a potential tool for early PD detection. Further studies are necessary to validate this approach in PD diagnosis and rehabilitation planning.

Neuroanatomical markers of social cognition in neglected adolescents

Growing up in neglectful households can impact multiple aspects of social cognition. However, research on neglect's effects on social cognition processes and their neuroanatomical correlates during adolescence is scarce. Here, we aimed to comprehensively assess social cognition processes (recognition of basic and contextual emotions, theory of mind, the experience of envy and Schadenfreude and empathy for pain) and their structural brain correlates in adolescents with legal neglect records within family-based care. First, we compared neglected adolescents (n = 27) with control participants (n = 25) on context-sensitive social cognition tasks while controlling for physical and emotional abuse and executive and intellectual functioning. Additionally, we explored the grey matter correlates of these domains through voxel-based morphometry. Compared to controls, neglected adolescents exhibited lower performance in contextual emotional recognition and theory of mind, higher levels of envy and Schadenfreude and diminished empathy. Physical and emotional abuse and executive or intellectual functioning did not explain these effects. Moreover, social cognition scores correlated with brain volumes in regions subserving social cognition and emotional processing. Our results underscore the potential impact of neglect on different aspects of social cognition during adolescence, emphasizing the necessity for preventive and intervention strategies to address these deficits in this population.

Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease

Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.

Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson's disease

Biomarkers obtained from the neurophysiological signals of patients with Parkinson's disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prominent cortical biomarkers of PD have typically been derived from various β band wave features. This study approached the topic from an alternative perspective and attempted to estimate a recently suggested measure representing α band nonlinear autocorrelative memory from a publicly available EEG dataset that involves 15 patients with earlier-stage PD (dopaminergic medication OFF and ON states) and 16 age-matched healthy controls. The cortical nonlinearity was elevated for the PD ON state compared with the OFF state for bilateral sensorimotor channels C3 and C4 (n = 26; P = 0.003). A similar statistical difference was also identified between PD OFF state and healthy subjects (n = 26; P = 0.049). Analysis over all channels revealed that the α band nonlinearity induced upon medication was constrained to sensorimotor regions. The α nonlinearity measure was compared with a well-accepted cortical biomarker of β-γ phase-amplitude coupling (PAC). They were in moderate negative correlation (r = -0.412; P = 0.036) for only healthy subjects, but not for the patients. The nonlinearity measure was found to be insusceptible to the nonstationary variations within the particular data. Our study provides further evidence that the α band nonlinearity measure can serve as a promising cortical biomarker of PD. The suggested measure can be estimated from a noninvasive low-resolution single scalp EEG channel of patients with relatively early-stage PD, who did not yet need to undergo deep brain stimulation operation.NEW & NOTEWORTHY This study suggests a nonlinearity measure that differentiates Parkinson's disease (PD) dopamine OFF-state scalp EEG data from those of dopamine ON-state patients and healthy subjects. Unlike typical PD cortical biomarkers based on β band activity, this metric shows elevation upon dopaminergic medication in the α band. We provide evidence supporting its potential as an early-stage promising PD biomarker that can be estimated from noninvasive EEG recordings with low resolution and SNR.

Characterizing neurocognitive impairments in Parkinson's disease with mobile EEG when walking and stepping over obstacles

The neural correlates that help us understand the challenges that Parkinson's patients face when negotiating their environment remain under-researched. This deficit in knowledge reflects the methodological constraints of traditional neuroimaging techniques, which include the need to remain still. As a result, much of our understanding of motor disorders is still based on animal models. Daily life challenges such as tripping and falling over obstacles represent one of the main causes of hospitalization for individuals with Parkinson's disease. Here, we report the neural correlates of naturalistic ambulatory obstacle avoidance in Parkinson's disease patients using mobile EEG. We examined 14 medicated patients with Parkinson's disease and 17 neurotypical control participants. Brain activity was recorded while participants walked freely, and while they walked and adjusted their gait to step over expected obstacles (preset adjustment) or unexpected obstacles (online adjustment) displayed on the floor. EEG analysis revealed attenuated cortical activity in Parkinson's patients compared to neurotypical participants in theta (4-7 Hz) and beta (13-35 Hz) frequency bands. The theta power increase when planning an online adjustment to step over unexpected obstacles was reduced in Parkinson's patients compared to neurotypical participants, indicating impaired proactive cognitive control of walking that updates the online action plan when unexpected changes occur in the environment. Impaired action planning processes were further evident in Parkinson's disease patients' diminished beta power suppression when preparing motor adaptation to step over obstacles, regardless of the expectation manipulation, compared to when walking freely. In addition, deficits in reactive control mechanisms in Parkinson's disease compared to neurotypical participants were evident from an attenuated beta rebound signal after crossing an obstacle. Reduced modulation in the theta frequency band in the resetting phase across conditions also suggests a deficit in the evaluation of action outcomes in Parkinson's disease. Taken together, the neural markers of cognitive control of walking observed in Parkinson's disease reveal a pervasive deficit of motor-cognitive control, involving impairments in the proactive and reactive strategies used to avoid obstacles while walking. As such, this study identified neural markers of the motor deficits in Parkinson's disease and revealed patients' difficulties in adapting movements both before and after avoiding obstacles in their path.

Levodopa-Induced Dyskinesias in Parkinson's Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson's disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.

Elevated Gaussian-modeled beta power in the cortex characterizes aging, but not Parkinson's disease

Aging is a key risk factor for the development of Parkinson's disease (PD). PD is characterized by excessive synchrony of beta oscillations (13-30 Hz) in the basal ganglia thalamo-cortical network. However, cortical beta power is not reliably elevated in individuals with PD. Here, we sought to disentangle how resting cortical beta power compares in younger controls, older controls, and individuals with PD using scalp electroencephalogram (EEG) and a novel approach for quantifying beta power. Specifically, we used a Gaussian model to determine if sensorimotor beta power distinguishes these groups. In addition, we looked at the distribution of beta power across the entire cortex. Our findings showed that Gaussian-modeled beta power does not differentiate individuals with PD (on medication) from healthy younger or older controls in sensorimotor cortex. However, beta power (and not theta or alpha) was higher in healthy older versus younger controls. This effect was most pronounced in regions near sensorimotor cortex including the frontal and parietal areas [P < 0.05, false discovery rate (FDR) corrected]. In addition, the bandwidth of the periodic beta was also higher in healthy older than young individuals in parietal regions. Finally, the aperiodic component, specifically the exponent of the signal, was higher (steeper) in younger controls than in individuals with PD in the right parietal-occipital region (P < 0.05, FDR corrected), possibly reflecting differences in neuronal spiking. Our findings suggest that cortical Gaussian beta power is possibly modulated by age and could be further explored in longitudinal studies to determine whether sensorimotor beta increases with increasing age.NEW & NOTEWORTHY Altered sensorimotor beta activity has been shown to be a feature in aging and PD. Using a novel approach, we clarify that resting sensorimotor beta power does not distinguish subjects with PD from healthy younger and older controls. However, beta power was higher in older compared with younger controls in central sensorimotor, frontal, and parietal regions. These results provide a clearer picture of sensorimotor beta power, demonstrating that it is elevated in aging but not PD.

The effects of gallic acid and vagotomy on motor function, intestinal transit, brain electrophysiology and oxidative stress alterations in a rat model of Parkinson's disease induced by rotenone

INTRODUCTION

The neuropathology of Parkinson's disease (PD) is complex and affects multiple systems of the body beyond the central nervous system. This study examined the effects of gallic acid (GA) and gastrointestinal vagotomy (VG) on motor, cognitive, intestinal transit time, and thalamic nuclei electrical power in an animal model of PD induced by rotenone.

MATERIALS AND METHODS

Male Wistar rats were divided into 4 groups: Sham, ROT, ROT+GA, VG + ROT. Sham rats received vehicle, those in ROT received rotenone (5 mg/kg/2 ml, ig), PD rats in ROT+GA were treated with GA (100 mg/kg, gavage/once daily, for 28 days), and in VG + ROT, the vagal nerve was dissected. Stride length, motor coordination and locomotion, intestinal transit time, cognitive and pain threshold, and thalamic local EEG were evaluated. Oxidative stress indexes in striatal tissue were also measured.

RESULTS

Rotenone diminished significantly the stride length (p < 0.001), motor coordination (p < 0.001), power of thalamic EEG (p < 0.01) and pain (p < 0.001). MDA increased significantly (p < 0.001) while GPx activity decreased (p < 0.001). Intestinal transit time rose significantly (p < 0.01). PD rats treated with GA improved all above disorders (p < 0.001, p < 0.01). Vagotomy prevented significant alterations of motor and non-motor parameters by rotenone.

CONCLUSION

According to current findings, rotenone acts as a toxin in GI and plays a role in the pathogenesis of PD through gastric vagal nerve. Thus, vagotomy could prevent the severity of toxicity by rotenone. In addition, GA improved symptoms of PD induced by rotenone. Therefore, GA can be regarded as a promising therapeutic candidate for PD patients.

Quantitative High Density EEG Brain Connectivity Evaluation in Parkinson's Disease: The Phase Locking Value (PLV)

INTRODUCTION

The present study explores brain connectivity in Parkinson's disease (PD) and in age matched healthy controls (HC), using quantitative EEG analysis, at rest and during a motor tasks. We also evaluated the diagnostic performance of the phase locking value (PLV), a measure of functional connectivity, in differentiating PD patients from HCs.

METHODS

High-density, 64-channels, EEG data from 26 PD patients and 13 HC were analyzed. EEG signals were recorded at rest and during a motor task. Phase locking value (PLV), as a measure of functional connectivity, was evaluated for each group in a resting state and during a motor task for the following frequency bands: (i) delta: 2-4 Hz; (ii) theta: 5-7 Hz; (iii) alpha: 8-12 Hz; beta: 13-29 Hz; and gamma: 30-60 Hz. The diagnostic performance in PD vs. HC discrimination was evaluated.

RESULTS

Results showed no significant differences in PLV connectivity between the two groups during the resting state, but a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. Comparing the resting state versus the motor task for each group, only HCs showed a higher PLV connectivity in the delta band during motor task. A ROC curve analysis for HC vs. PD discrimination, showed an area under the ROC curve (AUC) of 0.75, a sensitivity of 100%, and a negative predictive value (NPV) of 100%.

CONCLUSIONS

The present study evaluated the brain connectivity through quantitative EEG analysis in Parkinson's disease versus healthy controls, showing a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. This neurophysiology biomarkers showed the potentiality to be explored in future studies as a potential screening biomarker for PD patients.

Parkinson's disease is characterized by sub-second resting-state spatio-oscillatory patterns: A contribution from deep convolutional neural network

Deep convolutional neural network (DCNN) provides a multivariate framework to detect relevant spatio-oscillatory patterns in the data beyond common mass-univariate statistics. Yet, its practical application is limited due to the low interpretability of the results beyond accuracy. We opted to use DCNN with a minimalistic architecture design and large penalized terms to yield a generalizable and clinically relevant network model. Our network was trained based on the scalp topology of the electroencephalography (EEG) from an open access dataset, constituting our primary sample of healthy controls (n = 25) and Parkinson's disease (PD) patients (n = 25), with and without medication. Next, we validated the model on another independent, yet comparable open access EEG dataset (healthy controls (n = 20) and PD patients (n = 20)), which was unseen to the network. We applied Gradient-weighted Class Activation Mapping (Grad-CAM) interpretability technique to create a localization map exhibiting the key network predictors, based on the gradients of the classification score flowing into the last convolutional layer. Accordingly, our results indicated that a sub-second of intrinsic oscillatory power pattern in the beta band over the occipitoparietal, gamma band over the left motor cortex as well as theta band over the frontoparietal cluster, had the largest impact on the network score for dissociating the PD patients from age- and gender-matched healthy controls, across the two datasets. We further found that the off-medication motor symptoms were related to the occipitoparietal off-medication beta power whereas the disease duration was associated with the off-medication beta power of the motor cortex. The on-medication theta power of the frontoparietal was related to the improvement of the motor symptoms. In conclusion, our method enabled us to characterize PD patho-electrophysiology according to the multivariate topographic analysis approach, where both spatial and frequency aspects of the oscillations were simultaneously considered. Moreover, our approach was free from common reference problem of the EEG data analyses.

The effects of betulinic acid chronic administration on the motor, non-motor behaviors, and globus pallidus local field potential power in a rat model of hemiparkinsonism

OBJECTIVES

Parkinson's disease (PD) is a neurodegenerative disorder involving the central nervous system associated with motor and non-motor impairments. Betulinic acid (BA) is a natural substance considered an antioxidative agent. This study aimed to investigate the therapeutic potential of BA on motor dysfunctions and globus pallidus (GP) local EEG power in a 6-hydroxydopamine (6-OHDA)-induced rat model of hemiparkinsonism.

MATERIALS AND METHODS

Adult Wistar rats were categorized into different groups, containing; Sham, PD, and treated groups including different doses of BA (0.5, 5, and 10 mg/kg, IP), and L-dopa (20 mg/kg, PO, as positive control). The lesion was induced in the right medial forebrain bundle by injection of 6-OHDA (20 µg/kg). The treatment was begun just after the approved rotational test induced by apomorphine, 14 days after 6-OHDA administration. Motor behaviors such as catalepsy and stride-length and non-motor responses, including GP local EEG, were then assessed. Also, the levels of GSH, catalase, and concentration of dopamine in the brain tissue were measured.

RESULTS

Treatment of hemiparkinsonian rats with BA significantly improved catalepsy and stride-length (P<0.001 and P<0.01, respectively) and GP frequency bands' powers (P<0.001). Moreover, the activities of GSH (P<0.001), catalase (P<0.001), and the concentration of dopamine (P<0.001) in the brain were increased.

CONCLUSION

Current results proved the potent ability of BA to scavenge free radicals and to remove oxidative agents in the brain tissue. This natural product could be considered a possible therapeutic compound for motor and non-motor disorders in PD.

Large-scale frontoparietal theta, alpha, and beta phase synchronization: A set of EEG differential characteristics for freezing of gait in Parkinson's disease?

Freezing of gait (FOG) is a complex gait disturbance in Parkinson's disease (PD), during which the patient is not able to effectively initiate gait or continue walking. The mystery of the FOG phenomenon is still unsolved. Recent studies have revealed abnormalities in cortical activities associated with FOG, which highlights the importance of cortical and cortical-subcortical network dysfunction in PD patients with FOG. In this paper, phase-locking value (PLV) of eight frequency sub-bands between 0.05 Hz and 35 Hz over frontal, motor, and parietal areas [during an ankle dorsiflexion (ADF) task] is used to investigate EEG phase synchronization. PLV was investigated over both superficial and deeper networks by analyzing EEG signals preprocessed with and without Surface Laplacian (SL) spatial filter. Four groups of participants were included: PD patients with severe FOG (N = 5, 5 males), PD patients with mild FOG (N = 7, 6 males), PD patients without FOG (N = 14, 13 males), and healthy age-matched controls (N = 13, 10 males). Fifteen trials were recorded from each participant. At superficial layers, frontoparietal theta phase synchrony was a unique feature present in PD with FOG groups. At deeper networks, significant dominance of interhemispheric frontoparietal alpha phase synchrony in PD with FOG, in contrast to beta phase synchrony in PD without FOG, was identified. Alpha phase synchrony was more distributed in PD with severe FOG, with higher levels of frontoparietal alpha phase synchrony. In addition to FOG-related abnormalities in PLV analysis, phase-amplitude coupling (PAC) analysis was also performed on frequency bands with PLV abnormalities. PAC analysis revealed abnormal coupling between theta and low beta frequency bands in PD with severe FOG at the superficial layers over frontal areas. At deeper networks, theta and alpha frequency bands show high PAC over parietal areas in PD with severe FOG. Alpha and low beta also presented PAC over frontal areas in PD groups with FOG. The results introduced significant phase synchrony differences between PD with and without FOG and provided important insight into a possible unified underlying mechanism for FOG. These results thus suggest that PLV and PAC can potentially be used as EEG-based biomarkers for FOG.

Cognitive dysfunctions and spontaneous EEG alterations induced by hippocampal amyloid pathology in rats

PURPOSE

We aimed to determine the effects of different doses of amyloid-beta (Aβ) peptide on learning and memory, and whether the changes in brain oscillations induced by dose-dependent accumulation of Aβ could be used as biomarkers to detect early stages of Alzheimer's disease (AD).

MATERIAL AND METHODS

Male albino Wistar rats aged 3 months were randomly divided into four groups (n ​= ​12/group) obtained by i. h. Injection (to the dorsal hippocampus) of saline or different doses of 0.01 ​μg/μl, 0.1 ​μg/μl, and 1 ​μg/μl of Aβ. After two weeks of recovery period, open field and novel object recognition tests were performed and spontaneous EEG recordings were obtained. Later, hippocampus tissues were collected for Western blot and ELISA analysis.

RESULTS

A significant decrement in recognition memory was observed in 0.1 ​μg/μl, and 1 ​μg/μl injected groups. In addition, Aβ accumulation induced significant decrement of the expression of NeuN, SNAP-25, SYP, and PSD-95 proteins, and led to the increment of GFAP expression in hippocampus. Moreover, we detected remarkable alterations in spontaneous brain activity. The hippocampal Aβ levels were negatively correlated with hippocampal gamma power and positively correlated with hippocampal theta power. Also, we observed significant changes in coherence values, indicating the functional connectivity between different brain regions, after the accumulation of Aβ. Especially, there was a significant correlation between changes in frontohippocampal theta coherence and in frontotemporal theta coherence.

CONCLUSIONS

Our findings indicate that Aβ peptide induces AD-like molecular changes at certain doses, and these changes could be detected by evaluating brain oscillations.

The Lateralization of Resting Motor Threshold to Predict Medication-Mediated Improvement in Parkinson’s Disease

Cortical stimulation patterns in patients with Parkinson’s disease (PD) are asymmetric and get altered over time. This study examined cortical neurophysiological markers for PD and identified neurophysiological markers for lateralization in PD. We used transcranial magnetic stimulation (TMS) to study corticospinal and intracortical excitability in 21 patients with idiopathic PD. We used the Movement Disorder Society Unified Parkinson’s Disease Rating Scale for examination during on and off periods and evaluated inhibitory and facilitatory process markers using TMS, including resting motor thresholds (RMT), active motor thresholds, and motor evoked potential amplitude. The RMT in the more affected cortex was significantly shorter than in the less affected cortex, and was strongly correlated with improved motor function following medication. Patients in the tremor group exhibited significantly lower RMT compared to those in the akinetic-rigid group. Cortical electrophysiological laterality observed in patients with PD may be a useful marker for guiding treatment and identifying underlying compensatory mechanisms.

Evaluating the Different Stages of Parkinson's Disease Using Electroencephalography With Holo-Hilbert Spectral Analysis

Electroencephalography (EEG) can reveal the abnormalities of dopaminergic subcortico-cortical circuits in patients with Parkinson's disease (PD). However, conventional time-frequency analysis of EEG signals cannot fully reveal the non-linear processes of neural activities and interactions. A novel Holo-Hilbert Spectral Analysis (HHSA) was applied to reveal non-linear features of resting state EEG in 99 PD patients and 59 healthy controls (HCs). PD patients demonstrated a reduction of β bands in frontal and central regions, and reduction of γ bands in central, parietal, and temporal regions. Compared with early-stage PD patients, late-stage PD patients demonstrated reduction of β bands in the posterior central region, and increased θ and δ2 bands in the left parietal region. θ and β bands in all brain regions were positively correlated with Hamilton depression rating scale scores. Machine learning algorithms using three prioritized HHSA features demonstrated "Bag" with the best accuracy of 0.90, followed by "LogitBoost" with an accuracy of 0.89. Our findings strengthen the application of HHSA to reveal high-dimensional frequency features in EEG signals of PD patients. The EEG characteristics extracted by HHSA are important markers for the identification of depression severity and diagnosis of PD.

Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study

Dopaminergic medication for Parkinson's disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.

Analysis of complexity in the EEG activity of Parkinson's disease patients by means of approximate entropy

The objective of the present study is to explore the brain resting state differences between Parkinson's disease (PD) patients and age- and gender-matched healthy controls (elderly) in terms of complexity of electroencephalographic (EEG) signals. One non-linear approach to determine the complexity of EEG is the entropy. In this pilot study, 28 resting state EEGs were analyzed from 13 PD patients and 15 elderly subjects, applying approximate entropy (ApEn) analysis to EEGs in ten regions of interest (ROIs), five for each brain hemisphere (frontal, central, parietal, occipital, temporal). Results showed that PD patients presented statistically higher ApEn values than elderly confirming the hypothesis that PD is characterized by a remarkable modification of brain complexity and globally modifies the underlying organization of the brain. The higher-than-normal entropy of PD patients may describe a condition of low order and consequently low information flow due to an alteration of cortical functioning and processing of information. Understanding the dynamics of brain applying ApEn could be a useful tool to help in diagnosis, follow the progression of Parkinson's disease, and set up personalized rehabilitation programs.

Neural synchronization analysis of electroencephalography coherence in patients with Parkinson's disease-related mild cognitive impairment

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We studied brain functional connectivity in 20 patients with PD-MCI and 10 MCI patients without Parkinsonism.

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Cognitive impairment was related to decreased coherence in the alpha range [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19].

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Regional coherence in left FP had a higher correlation with cognitive function.

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Differences in EEG coherence may reflect a compensatory response to PD-MCI.

Introduction

The underlying pathophysiology of slight cognitive dysfunction in Parkinson’s disease-related mild cognitive impairment (PD-MCI) is yet to be elucidated. Our study aimed to evaluate the association between cognitive function and brain functional connectivity (FC) in patients with PD-MCI.

Methods

Twenty patients with sporadic PD-MCI were evaluated for FC in the brain network. Further, electroencephalography (EEG) coherence analysis in the whole-brain and quantified regional coherence using phase coupling were performed for each frequency, and motor and cognitive function were assessed in the whole-brain.

Results

The degree of cognitive impairment was related to a decrease in the coherence in the alpha ranges. The regional coherence in the left frontal-left parietal region rather than the right frontal-right parietal region showed a higher correlation with the cognitive function scores.

Conclusion

The differences in EEG coherence across different types of cognitive dysfunction reflect a compensatory response to the heterogeneous and complex clinical presentation of PD-MCI. Our findings indicate decreased brain efficiency and impaired neural synchronization in PD-MCI; these results may be crucial in elucidating the pathological exacerbation of PD-MCI.

Altered neural oscillations during complex sequential movements in patients with Parkinson's disease

The sequelae of Parkinson's disease (PD) includes both motor- and cognitive-related symptoms. Although traditionally considered a subcortical disease, there is increasing evidence that PD has a major impact on cortical function as well. Prior studies have reported alterations in cortical neural function in patients with PD during movement, but to date such studies have not examined whether the complexity of multicomponent movements modulate these alterations. In this study, 23 patients with PD (medication "off" state) and 27 matched healthy controls performed simple and complex finger tapping sequences during magnetoencephalography (MEG), and the resulting MEG data were imaged to identify the cortical oscillatory dynamics serving motor performance. The patients with PD were significantly slower than controls at executing the sequences overall, and both groups took longer to complete the complex sequences than the simple. In terms of neural differences, patients also exhibited weaker beta complexity-related effects in the right medial frontal gyrus and weaker complexity-related alpha activity in the right posterior and inferior parietal lobules, suggesting impaired motor sequence execution. Characterizing the cortical pathophysiology of PD could inform current and future therapeutic interventions that address both motor and cognitive symptoms.

Adaptive, personalized closed-loop therapy for Parkinson's disease: biochemical, neurophysiological, and wearable sensing systems

INTRODUCTION

Motor complication management is one of the main unmet needs in Parkinson's disease patients.

AREAS COVERED

Among the most promising emerging approaches for handling motor complications in Parkinson's disease, adaptive deep brain stimulation strategies operating in closed-loop have emerged as pivotal to deliver sustained, near-to-physiological inputs to dysfunctional basal ganglia-cortical circuits over time. Existing sensing systems that can provide feedback signals to close the loop include biochemical-, neurophysiological- or wearable-sensors. Biochemical sensing allows to directly monitor the pharmacokinetic and pharmacodynamic of antiparkinsonian drugs and metabolites. Neurophysiological sensing relies on neurotechnologies to sense cortical or subcortical brain activity and extract real-time correlates of symptom intensity or symptom control during DBS. A more direct representation of the symptom state, particularly the phenomenological differentiation and quantification of motor symptoms, can be realized via wearable sensor technology.

EXPERT OPINION

Biochemical, neurophysiologic, and wearable-based biomarkers are promising technological tools that either individually or in combination could guide adaptive therapy for Parkinson's disease motor symptoms in the future.

Revisión de electroencefalografía portable y su aplicabilidad en neurociencias

La electroencefalografía (EEG) es una técnica que permite registrar la actividad eléctrica del cerebro y ha sido estudiada durante los últimos cien años en diferentes ámbitos de la neurociencia. En los últimos años se ha investigado y desarrollado equipos de medición que sean portables y que permitan una buena calidad de la señal, por lo cual se realizó una revisión bibliográfica de las compañías fabricantes de algunos dispositivos de electroencefalografía portable disponibles en el mercado, se exponen sus características principales, algunos trabajos encontrados que fueron realizados con los dispositivos, comparaciones entre los mismos y una discusión acerca de las ventajas y desventajas de sus características. Finalmente se concluye que a la hora de comprar un dispositivo para electroencefalografía portable es necesario tener en cuenta el uso que se le va a dar y el costo-beneficio que tiene el equipo de acuerdo con sus características. Encephalography is a technique that allows the recording of electrical activity of the brain and has been studied during the last hundred years in different areas of neuroscience. For several years, measuring equipment that are portable and that allow a good signal quality to have been researched and developed, so a literature review of the manufacturing companies of some of portable electroencephalography devices available on the market was carried out: Its main features are exposed, as well as some of the work found that were made with those, comparisons between them and a discussion about the advantages and disadvantages of their features. It is concluded that, when a portable encephalography device is bought, it’s necessary to take into consideration the use that it will be having and the cost-benefit that the device has according to its features.

Spectral Electroencephalographic and Heart Rate Variability features enhance identification of medicated/non-medicated Parkinson's disease patients

Parkinson's Disease is a neuropathy that produces changes in several biomarkers, these changes could be used to evaluate even sub-clinical conditions. This paper presents an evaluation of indices extracted from electroencephalography and Heart Rate Variability (HRV), when used to classify a sample of subjects from three groups: control (healthy), medicated and non medicated subjects diagnosed with Parkinson's disease. Classification performance was measured using accuracy over these classes and a cross validation scheme was used to assess repeatability for the classification process. Results tend to prove that inclusion of an autonomic index derived from HRV analysis enhances classification, suggesting that Parkinson's disease could be related with unperceptible to mild alterations of the Autonomic Nervous System.

Disruption of the Cortical-Vagal Communication Network in Parkinson's Disease

Parkinson's disease (PD) is a neuropathy characterized by motor disorders, but it has also been associated with the presence of autonomic alterations as a result of degradation of the dopaminergic system. Studying the relation between Band Power time series (BPts) and Heart Rate Variability (HRV), has been proposed as a tool to explore the bidirectional communication pathways between cortex and autonomic control. This work presents a primer analysis on study brain ↔ heart interaction on a databse of PD patients under two conditions: without and after levadopa (L-dopa) intake. Additionally a healthy control population was also analyzed, and used as comparison level between both conditions. Results show PD affects pathways by reducing the number of connections, specially association of beta and power and the second faster component of HRV seems to be more sensitive to L-dopa administration.

Graph Theory on Brain Cortical Sources in Parkinson's Disease: The Analysis of 'Small World' Organization from EEG

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly population. Similarly to other neurodegenerative diseases, the early diagnosis of PD is quite difficult. The current pilot study aimed to explore the differences in brain connectivity between PD and NOrmal eLDerly (Nold) subjects to evaluate whether connectivity analysis may speed up and support early diagnosis. A total of 26 resting state EEGs were analyzed from 13 PD patients and 13 age-matched Nold subjects, applying to cortical reconstructions the graph theory analyses, a mathematical representation of brain architecture. Results showed that PD patients presented a more ordered structure at slow-frequency EEG rhythms (lower value of SW) than Nold subjects, particularly in the theta band, whereas in the high-frequency alpha, PD patients presented more random organization (higher SW) than Nold subjects. The current results suggest that PD could globally modulate the cortical connectivity of the brain, modifying the functional network organization and resulting in motor and non-motor signs. Future studies could validate whether such an approach, based on a low-cost and non-invasive technique, could be useful for early diagnosis, for the follow-up of PD progression, as well as for evaluating pharmacological and neurorehabilitation treatments.

Effective Connectivity During Rest and Music Listening: An EEG Study on Parkinson's Disease

Music-based interventions seem to enhance motor, sensory and cognitive functions in Parkinson’s disease (PD), but the underlying action mechanisms are still largely unknown. This electroencephalography (EEG) study aimed to investigate the effective connectivity patterns characterizing PD in the resting state and during music listening. EEG recordings were obtained from fourteen non-demented PD patients and 12 healthy controls, at rest and while listening to three music tracks. Theta- and alpha-band power spectral density and multivariate partial directed coherence were computed. Power and connectivity measures were compared between patients and controls in the four conditions and in music vs. rest. Compared to controls, patients showed enhanced theta-band power and slightly enhanced alpha-band power, but markedly reduced theta- and alpha-band interactions among EEG channels, especially concerning the information received by the right central channel. EEG power differences were partially reduced by music listening, which induced power increases in controls but not in patients. Connectivity differences were slightly compensated by music, whose effects largely depended on the track. In PD, music enhanced the frontotemporal inter-hemispheric communication. Our findings suggest that PD is characterized by enhanced activity but reduced information flow within the EEG network, being only partially normalized by music. Nevertheless, music capability to facilitate inter-hemispheric communication might underlie its beneficial effects on PD pathophysiology and should be further investigated.

Identification of nonlinear features in cortical and subcortical signals of Parkinson's Disease patients via a novel efficient measure

This study offers a novel and efficient measure based on a higher order version of autocorrelative signal memory that can identify nonlinearities in a single time series. The suggested method was applied to simultaneously recorded subthalamic nucleus (STN) local field potentials (LFP) and magnetoencephalography (MEG) from fourteen Parkinson's Disease (PD) patients who underwent surgery for deep brain stimulation. Recordings were obtained during rest for both OFF and ON dopaminergic medication states. We analyzed the bilateral LFP channels that had the maximum beta power in the OFF state and the cortical sources that had the maximum coherence with the selected LFP channels in the alpha band. Our findings revealed the inherent nonlinearity in the PD data as subcortical high beta (20-30 Hz) band and cortical alpha (8-12 Hz) band activities. While the former was discernible without medication (p=0.015), the latter was induced upon the dopaminergic medication (p<6.10-4). The degree of subthalamic nonlinearity was correlated with contralateral tremor severity (r=0.45, p=0.02). Conversely, for the cortical signals nonlinearity was present for the ON medication state with a peak in the alpha band and correlated with contralateral akinesia and rigidity (r=0.46, p=0.02). This correlation appeared to be independent from that of alpha power and the two measures combined explained 34 % of the variance in contralateral akinesia scores. Our findings suggest that particular frequency bands and brain regions display nonlinear features closely associated with distinct motor symptoms and functions.

Using pharmacological manipulations to study the role of dopamine in human reward functioning: A review of studies in healthy adults

Dopamine (DA) plays a key role in reward processing and is implicated in psychological disorders such as depression, substance use, and schizophrenia. The role of DA in reward processing is an area of highly active research. One approach to this question is drug challenge studies with drugs known to alter DA function. These studies provide good experimental control and can be performed in parallel in laboratory animals and humans. This review aimed to summarize results of studies using pharmacological manipulations of DA in healthy adults. 'Reward' is a complex process, so we separated 'phases' of reward, including anticipation, evaluation of cost and benefits of upcoming reward, execution of actions to obtain reward, pleasure in response to receiving a reward, and reward learning. Results indicated that i) DAergic drugs have different effects on different phases of reward; ii) the relationship between DA and reward functioning appears unlikely to be linear; iii) our ability to detect the effects of DAergic drugs varies depending on whether subjective, behavioral, imaging measures are used.

Abnormalities of resting-state EEG in patients with prodromal and overt dementia with Lewy bodies: Relation to clinical symptoms

OBJECTIVE

Here we tested if cortical sources of resting state electroencephalographic (rsEEG) rhythms may differ in sub-groups of patients with prodromal and overt dementia with Lewy bodies (DLB) as a function of relevant clinical symptoms.

METHODS

We extracted clinical, demographic and rsEEG datasets in matched DLB patients (N = 60) and control Alzheimer's disease (AD, N = 60) and healthy elderly (Nold, N = 60) seniors from our international database. The eLORETA freeware was used to estimate cortical rsEEG sources.

RESULTS

As compared to the Nold group, the DLB and AD groups generally exhibited greater spatially distributed delta source activities (DLB > AD) and lower alpha source activities posteriorly (AD > DLB). As compared to the DLB "controls", the DLB patients with (1) rapid eye movement (REM) sleep behavior disorders showed lower central alpha source activities (p < 0.005); (2) greater cognitive deficits exhibited higher parietal and central theta source activities as well as higher central, parietal, and occipital alpha source activities (p < 0.01); (3) visual hallucinations pointed to greater parietal delta source activities (p < 0.005).

CONCLUSIONS

Relevant clinical features were associated with abnormalities in spatial and frequency features of rsEEG source activities in DLB patients.

SIGNIFICANCE

Those features may be used as neurophysiological surrogate endpoints of clinical symptoms in DLB patients in future cross-validation prospective studies.

Identifying controllable cortical neural markers with machine learning for adaptive deep brain stimulation in Parkinson's disease

The identification of oscillatory neural markers of Parkinson's disease (PD) can contribute not only to the understanding of functional mechanisms of the disorder, but may also serve in adaptive deep brain stimulation (DBS) systems. These systems seek online adaptation of stimulation parameters in closed-loop as a function of neural markers, aiming at improving treatment's efficacy and reducing side effects. Typically, the identification of PD neural markers is based on group-level studies. Due to the heterogeneity of symptoms across patients, however, such group-level neural markers, like the beta band power of the subthalamic nucleus, are not present in every patient or not informative about every patient's motor state. Instead, individual neural markers may be preferable for providing a personalized solution for the adaptation of stimulation parameters. Fortunately, data-driven bottom-up approaches based on machine learning may be utilized. These approaches have been developed and applied successfully in the field of brain-computer interfaces with the goal of providing individuals with means of communication and control. In our contribution, we present results obtained with a novel supervised data-driven identification of neural markers of hand motor performance based on a supervised machine learning model. Data of 16 experimental sessions obtained from seven PD patients undergoing DBS therapy show that the supervised patient-specific neural markers provide improved decoding accuracy of hand motor performance, compared to group-level neural markers reported in the literature. We observed that the individual markers are sensitive to DBS therapy and thus, may represent controllable variables in an adaptive DBS system.

Reduction of spontaneous cortical beta bursts in Parkinson's disease is linked to symptom severity

Parkinson's disease is characterized by a gradual loss of dopaminergic neurons, which is associated with altered neuronal activity in the beta-band (13-30 Hz). Assessing beta-band activity typically involves transforming the time-series to get the power of the signal in the frequency domain. Such transformation assumes that the time-series can be reduced to a combination of steady-state sine- and cosine waves. However, recent studies have suggested that this approach masks relevant biophysical features in the beta-band-for example, that the beta-band exhibits transient bursts of high-amplitude activity. In an exploratory study, we used magnetoencephalography to record beta-band activity from the sensorimotor cortex, to characterize how spontaneous cortical beta bursts manifest in Parkinson's patients on and off dopaminergic medication, and compare this to matched healthy controls. We extracted the time-course of beta-band activity from the sensorimotor cortex and characterized bursts in the signal. We then compared the burst rate, duration, inter-burst interval and peak amplitude between the Parkinson's patients and healthy controls. Our results show that Parkinson's patients off medication had a 5-17% lower beta bursts rate compared to healthy controls, while both the duration and the amplitude of the bursts were the same for healthy controls and medicated state of the Parkinson's patients. These data thus support the view that beta bursts are fundamental underlying features of beta-band activity, and show that changes in cortical beta-band power in Parkinson's disease can be explained-primarily by changes in the underlying burst rate. Importantly, our results also revealed a relationship between beta burst rate and motor symptom severity in Parkinson's disease: a lower burst rate scaled with increased severity of bradykinesia and postural/kinetic tremor. Beta burst rate might thus serve as a neuromarker for Parkinson's disease that can help in the assessment of symptom severity in Parkinson's disease or in the evaluation of treatment effectiveness.

EEG alpha reactivity and cholinergic system integrity in Lewy body dementia and Alzheimer's disease

BACKGROUND

Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), is characterised by marked deficits within the cholinergic system which are more severe than in Alzheimer's disease (AD) and are mainly caused by degeneration of the nucleus basalis of Meynert (NBM) whose widespread cholinergic projections provide the main source of cortical cholinergic innervation. EEG alpha reactivity, which refers to the reduction in alpha power over occipital electrodes upon opening the eyes, has been suggested as a potential marker of cholinergic system integrity.

METHODS

Eyes-open and eyes-closed resting state EEG data were recorded from 41 LBD patients (including 24 patients with DLB and 17 with PDD), 21 patients with AD, and 40 age-matched healthy controls. Alpha reactivity was calculated as the relative reduction in alpha power over occipital electrodes when opening the eyes. Structural MRI data were used to assess volumetric changes within the NBM using a probabilistic anatomical map.

RESULTS

Alpha reactivity was reduced in AD and LBD patients compared to controls with a significantly greater reduction in LBD compared to AD. Reduced alpha reactivity was associated with smaller volumes of the NBM across all groups (ρ = 0.42, pFDR = 0.0001) and in the PDD group specifically (ρ = 0.66, pFDR = 0.01).

CONCLUSIONS

We demonstrate that LBD patients show an impairment in alpha reactivity upon opening the eyes which distinguishes this form of dementia from AD. Furthermore, our results suggest that reduced alpha reactivity might be related to a loss of cholinergic drive from the NBM, specifically in PDD.

L-dopa treatment increases oscillatory power in the motor cortex of Parkinson's disease patients

Parkinson's disease (PD) is a movement disorder caused by dopaminergic neurodegeneration. Levodopa (L-dopa) is an effective medication for alleviating motor symptoms in PD that has been shown previously to reduce subcortical beta (13-30 Hz) oscillations. How L-dopa influences oscillations in the motor cortex is unclear. In this study, 21 PD patients were recorded with magnetoencephalography (MEG) in L-dopa ON and OFF states. Oscillatory components of resting-state power spectra were compared between the two states and the significant effect was localized using beamforming. Unified Parkinson's Disease Rating Scale (UPDRS) III akinesia and rigidity sub-scores for the most affected hemibody were correlated with source power values for the contralateral hemisphere. An L-dopa-induced power increase was found over the central sensors significant in the 18-30 Hz range (F(1,20)  > 14.8, PFWE corr < 0.05, cluster size inference with P = 0.001 cluster-forming threshold). Beamforming localization of this effect revealed distinct peaks at the bilateral sensorimotor cortex. A significant correlation between the magnitude of L-dopa induced 18-30 Hz oscillatory motor-cortical power increase and the degree of improvement in contralateral akinesia and rigidity was found (F(2, 19) = 4.9, pone-tailed = 0.02, R2 = 0.2). Power in the same range was also inversely correlated with combined akinesia and rigidity scores in the L-dopa OFF state (F(2, 19) = 9.2, ptwo-tailed = 0.007, R2 = 0.33) but not in the L-dopa ON state (F(2, 19) = 0.27, ptwo-tailed = 0.6, R2 = 0.01). These results suggest that the role of motor cortical beta oscillations in PD is distinct from that of subcortical beta.

Altered dynamics of visual contextual interactions in Parkinson's disease

Over the last decades, psychophysical and electrophysiological studies in patients and animal models of Parkinson's disease (PD), have consistently revealed a number of visual abnormalities. In particular, specific alterations of contrast sensitivity curves, electroretinogram (ERG), and visual-evoked potentials (VEP), have been attributed to dopaminergic retinal depletion. However, fundamental mechanisms of cortical visual processing, such as normalization or "gain control" computations, have not yet been examined in PD patients. Here, we measured electrophysiological indices of gain control in both space (surround suppression) and time (sensory adaptation) in PD patients based on steady-state VEP (ssVEP). Compared with controls, patients exhibited a significantly higher initial ssVEP amplitude that quickly decayed over time, and greater relative suppression of ssVEP amplitude as a function of surrounding stimulus contrast. Meanwhile, EEG frequency spectra were broadly elevated in patients relative to controls. Thus, contrary to what might be expected given the reduced contrast sensitivity often reported in PD, visual neural responses are not weaker; rather, they are initially larger but undergo an exaggerated degree of spatial and temporal gain control and are embedded within a greater background noise level. These differences may reflect cortical mechanisms that compensate for dysfunctional center-surround interactions at the retinal level.

Aberrant resting-state oscillatory brain activity in Parkinson's disease patients with visual hallucinations: An MEG source-space study

To gain insight into possible underlying mechanism(s) of visual hallucinations (VH) in Parkinson's disease (PD), we explored changes in local oscillatory activity in different frequency bands with source-space magnetoencephalography (MEG). Eyes-closed resting-state MEG recordings were obtained from 20 PD patients with hallucinations (Hall+) and 20 PD patients without hallucinations (Hall-), matched for age, gender and disease severity. The Hall+ group was subdivided into 10 patients with VH only (unimodal Hall+) and 10 patients with multimodal hallucinations (multimodal Hall+). Subsequently, neuronal activity at source-level was reconstructed using an atlas-based beamforming approach resulting in source-space time series for 78 cortical and 12 subcortical regions of interest in the automated anatomical labeling (AAL) atlas. Peak frequency (PF) and relative power in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) were compared between Hall+ and Hall-, unimodal Hall+ and Hall-, multimodal Hall+ and Hall-, and unimodal Hall+ and multimodal Hall+ patients. PF and relative power per frequency band did not differ between Hall+ and Hall-, and multimodal Hall+ and Hall- patients. Compared to the Hall- group, unimodal Hall+ patients showed significantly higher relative power in the theta band (p = 0.005), and significantly lower relative power in the beta (p = 0.029) and gamma (p = 0.007) band, and lower PF (p = 0.011). Compared to the unimodal Hall+, multimodal Hall+ showed significantly higher PF (p = 0.007). In conclusion, a subset of PD patients with only VH showed slowing of MEG-based resting-state brain activity with an increase in theta activity, and a concomitant decrease in beta and gamma activity, which could indicate central cholinergic dysfunction as underlying mechanism of VH in PD. This signature was absent in PD patients with multimodal hallucinations.

Quantitative EEG and Verbal Fluency in DBS Patients: Comparison of Stimulator-On and -Off Conditions

Introduction: Deep brain stimulation of the subthalamic nucleus (STN-DBS) ameliorates motor function in patients with Parkinson's disease and allows reducing dopaminergic therapy. Beside effects on motor function STN-DBS influences many non-motor symptoms, among which decline of verbal fluency test performance is most consistently reported. The surgical procedure itself is the likely cause of this decline, while the influence of the electrical stimulation is still controversial. STN-DBS also produces widespread changes of cortical activity as visualized by quantitative EEG. The present study aims to link an alteration in verbal fluency performance by electrical stimulation of the STN to alterations in quantitative EEG.

Methods: Sixteen patients with STN-DBS were included. All patients had a high density EEG recording (256 channels) while testing verbal fluency in the stimulator on/off situation. The phonemic, semantic, alternating phonemic and semantic fluency was tested (Regensburger Wortflüssigkeits-Test).

Results: On the group level, stimulation of STN did not alter verbal fluency performance. EEG frequency analysis showed an increase of relative alpha2 (10–13 Hz) and beta (13–30 Hz) power in the parieto-occipital region (p ≤ 0.01). On the individual level, changes of verbal fluency induced by stimulation of the STN were disparate and correlated inversely with delta power in the left temporal lobe (p < 0.05).

Conclusion: STN stimulation does not alter verbal fluency performance in a systematic way at group level. However, when in individual patients an alteration of verbal fluency performance is produced by electrical stimulation of the STN, it correlates inversely with left temporal delta power.

Seasonal variation of spontaneous blink rate and beta EEG activity

Seasonal variations of the photoperiod have been shown to regulate biological and behavioral functions, with also effects on clinical symptom and course of several psychiatric conditions. Although melatonin is considered the principal signal used to transmit informations about the light and dark cycle, a dopamine (DA) role in regulating seasonal changes has been suggested. Few studies have addressed a seasonal pattern of dopamine, and human studies have been conducted on inter-subject differences, comparing measures obtained during fall-winter with those of spring-summer. We studied within-subject seasonal changes of blink rate (BR), a indirect marker of central DA activity, in 26 normal subjects (15 females and 11 males, mean age: 24.7 ± 4.0) during winter, spring, summer and fall. Occipital EEG activity and subjective measures of vigilance and mood were also assessed to account for variations on arousal and fatigue. A significant seasonal effect was found for BR, with higher rate in summer, and for EEG beta activity, with higher activity in spring and summer. Subjective fatigue was found higher in winter. According to our data, it is possible that higher BR and increased EEG beta activity result by an arousal activation sustained by dopamine systems during the months with a long photoperiod.

Clinical correlates of quantitative EEG in Parkinson disease: A systematic review

OBJECTIVE

To assess the relevance of quantitative EEG (qEEG) measures as outcomes of disease severity and progression in Parkinson disease (PD).

METHODS

Main databases were systematically searched (January 2018) for studies of sufficient methodologic quality that examined correlations between clinical symptoms of idiopathic PD and cortical (surface) qEEG metrics.

RESULTS

Thirty-six out of 605 identified studied were included. Results were classified into 4 domains: cognition (23 studies), motor function (13 studies), responsiveness to interventions (7 studies), and other (10 studies). In cross-sectional studies, EEG slowing correlated with global cognitive impairment and with diffuse deterioration in other domains. In longitudinal studies, decreased dominant frequency and increased θ power, reflecting EEG slowing, were biomarkers of cognitive deterioration at an individual level. Results on motor dysfunction and treatment yielded contrasting findings. Studies on functional connectivity at an individual level and longitudinal studies on other domains or on connectivity measures were lacking.

CONCLUSION

qEEG measures reflecting EEG slowing, particularly decreased dominant frequency and increased θ power, correlate with cognitive impairment and predict future cognitive deterioration. qEEG could provide reliable and widely available biomarkers for nonmotor disease severity and progression in PD, potentially promoting early diagnosis of nonmotor symptoms and an objective monitoring of progression. More studies are needed to clarify the role of functional connectivity and network analyses.

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.

Short-Term Effects of Binaural Beats on EEG Power, Functional Connectivity, Cognition, Gait and Anxiety in Parkinson’s Disease

We applied rhythmic binaural sound to Parkinson’s Disease (PD) patients to investigate its influence on several symptoms of this disease and on Electrophysiology (Electrocardiography and Electroencephalography (EEG)). We conducted a double-blind, randomized controlled study in which rhythmic binaural beats and control were administered over two randomized and counterbalanced sessions (within-subjects repeated-measures design). Patients ([Formula: see text], age [Formula: see text], stage I–III Hoehn & Yahr scale) participated in two sessions of sound stimulation for 10[Formula: see text]min separated by a minimum of 7 days. Data were collected immediately before and after both stimulations with the following results: (1) a decrease in theta activity, (2) a general decrease in Functional Connectivity (FC), and (3) an improvement in working memory performance. However, no significant changes were identified in the gait performance, heart rate or anxiety level of the patients. With regard to the control stimulation, we did not identify significant changes in the variables analyzed. The use of binaural-rhythm stimulation for PD, as designed in this study, seems to be an effective, portable, inexpensive and noninvasive method to modulate brain activity. This influence on brain activity did not induce changes in anxiety or gait parameters; however, it resulted in a normalization of EEG power (altered in PD), normalization of brain FC (also altered in PD) and working memory improvement (a normalizing effect). In summary, we consider that sound, particularly binaural-rhythmic sound, may be a co-assistant tool in the treatment of PD, however more research is needed to consider the use of this type of stimulation as an effective therapy.

Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.

Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation

Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson's disease (PD), Alzheimer's disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets.

Abnormalities of cortical neural synchronization mechanisms in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

The aim of this retrospective exploratory study was that resting state eyes-closed electroencephalographic (rsEEG) rhythms might reflect brain arousal in patients with dementia due to Alzheimer's disease dementia (ADD), Parkinson's disease dementia (PDD), and dementia with Lewy body (DLB). Clinical and rsEEG data of 42 ADD, 42 PDD, 34 DLB, and 40 healthy elderly (Nold) subjects were available in an international archive. Demography, education, and Mini-Mental State Evaluation score were not different between the patient groups. Individual alpha frequency peak (IAF) determined the delta, theta, alpha 1, alpha 2, and alpha 3 frequency bands. Fixed beta 1, beta 2, and gamma bands were also considered. rsEEG cortical sources were estimated by means of the exact low-resolution brain electromagnetic source tomography and were then classified across individuals, on the basis of the receiver operating characteristic curves. Compared to Nold, IAF showed marked slowing in PDD and DLB and moderate slowing in ADD. Furthermore, all patient groups showed lower posterior alpha 2 source activities. This effect was dramatic in ADD, marked in DLB, and moderate in PDD. These groups also showed higher occipital delta source activities, but this effect was dramatic in PDD, marked in DLB, and moderate in ADD. The posterior delta and alpha sources allowed good classification accuracy (approximately 0.85-0.90) between the Nold subjects and patients, and between ADD and PDD patients. In quiet wakefulness, delta and alpha sources unveiled different spatial and frequency features of the cortical neural synchronization underpinning brain arousal in ADD, PDD, and DLB patients. Future prospective cross-validation studies should test these rsEEG markers for clinical applications and drug discovery.