Reproducibility of Rolandic beta rhythm modulation in MEG and EEG.

The Rolandic beta rhythm, at ∼20 Hz, is generated in the somatosensory and motor cortices and is modulated by motor activity and sensory stimuli, causing a short lasting suppression that is followed by a rebound of the beta rhythm. The rebound reflects inhibitory changes in the primary sensorimotor (SMI) cortex, and thus it has been used as a biomarker to follow the recovery of patients with acute stroke. The longitudinal stability of beta rhythm modulation is a prerequisite for its use in long-term follow-ups. We quantified the reproducibility of beta rhythm modulation in healthy subjects in a 1-year-longitudinal study both for MEG and EEG at T0, 1 month (T1-month, n = 8) and 1 year (T1-year, n = 19). The beta rhythm (13-25 Hz) was modulated by fixed tactile and proprioceptive stimulations of the index fingers. The relative peak strengths of beta suppression and rebound did not differ significantly between the sessions, and intersession reproducibility was good or excellent according to intraclass correlation-coefficient values (0.70-0.96) both in MEG and EEG. Our results indicate that the beta rhythm modulation to tactile and proprioceptive stimulation is well reproducible within 1 year. These results support the use of beta modulation as a biomarker in long-term follow-up studies, e.g., to quantify the functional state of the SMI cortex during rehabilitation and drug interventions in various neurological impairments.NEW & NOTEWORTHY The present study demonstrates that beta rhythm modulation is highly reproducible in a group of healthy subjects within a year. Hence, it can be reliably used as a biomarker in longitudinal follow-up studies in different neurological patient groups to reflect changes in the functional state of the sensorimotor cortex.

Gamma-band synchronisation in a frontotemporal auditory information processing network.

Neural oscillations are fundamental mechanisms of the human brain that enable coordinated activity of different brain regions during perceptual and cognitive processes. A frontotemporal network generated by means of gamma oscillations and comprising the auditory cortex (AC) and the anterior cingulate cortex (ACC) has been shown to be involved in the cognitively demanding auditory information processing. This study aims to reveal patterns of functional and effective connectivity within this network in healthy subjects by means of simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We simultaneously recorded EEG and fMRI in 28 healthy subjects during the performance of a cognitively demanding auditory choice reaction task. Connectivity between the ACC and AC was analysed employing EEG and fMRI connectivity measures. We found a significant BOLD signal correlation between the ACC and AC, a significant task-dependant increase of fMRI connectivity (gPPI) and a significant increase in functional coupling in the gamma frequency range between these regions (LPS), which was increased in top-down direction (granger analysis). EEG and fMRI connectivity measures were positively correlated. The results of these study point to a role of a top-down influence of the ACC on the AC executed by means of gamma synchronisation. The replication of fMRI connectivity patterns in simultaneously recorded EEG data and the correlation between connectivity measures from both domains found in our study show, that brain connectivity based on the synchronisation of gamma oscillations is mirrored in fMRI connectivity patterns.

Differential classification of states of consciousness using envelope- and phase-based functional connectivity.

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.

EEG cross-frequency phase synchronization as an index of memory matching in visual search.

Visual perception is influenced by our expectancies about incoming sensory information. It is assumed that mental templates of expected sensory input are created and compared to actual input, which can be matching or not. When such mental templates are held in working memory, cross-frequency phase synchronization (CFS) between theta and gamma band activity has been proposed to serve matching processes between prediction and sensation. We investigated how this is affected by the number of activated templates that could be matched by comparing conditions where participants had to keep either one or multiple templates in mind for successful visual search. We found a transient CFS between EEG theta and gamma activity in an early time window around 150 ms after search display presentation, in right hemispheric parietal cortex. Our results suggest that for single template conditions, stronger transient theta-gamma CFS at posterior sites contralateral to target presentation can be observed than for multiple templates. This can be interpreted as evidence to the idea of sequential attentional templates. But mainly, it is understood in line with previous theoretical accounts strongly arguing for transient synchronization between posterior theta and gamma phase as a neural correlate of matching incoming sensory information with contents from working memory and as evidence for limitations in memory matching during multiple template search.

Disruptions of cortico-kinematic interactions in Parkinson's disease.

The cortical role of the motor symptoms reflected by kinematic characteristics in Parkinson's disease (PD) is poorly understood. In this study, we aim to explore how PD affects cortico-kinematic interactions. Electroencephalographic (EEG) and kinematic data were recorded from seven healthy participants and eight participants diagnosed with PD during a set of self-paced finger tapping tasks. Event-related desynchronization (ERD) was compared between groups in the α (8-14 Hz), low-ß (14-20 Hz), and high-ß (20-35 Hz) frequency bands to investigate between-group differences in the cortical activities associated with movement. Average kinematic peak amplitudes and latencies were extracted alongside Sample Entropy (SaEn), a measure of signal complexity, as variables for comparison between groups. These variables were further correlated with average EEG power in each frequency band to establish within-group interactions between cortical motor functions and kinematic motor output. High ß-band power correlated with mean kinematic peak latency and signal complexity in the healthy group, while no correlation was found in the PD group. Also, the healthy group demonstrated stronger ERD in the broad ß-band than the PD participants. Our results suggest that cortical ß-band power in healthy populations is graded to finger tapping latency and complexity of movement, but this relationship is impaired in PD. These insights could help further enhance our understanding of the role of cortical ß-band oscillations in healthy movement and the possible disruption of that relationship in PD. These outcomes can provide further directions for treatment and therapeutic applications and potentially establish cortical biomarkers of Parkinson's disease.

Beta synchrony for expressive language lateralizes to right hemisphere in development.

A left perisylvian network is known to support language in healthy adults. Low-beta (13-23 Hz) event-related desynchrony (ERD) has been observed during verb generation, at approximately 700-1200 ms post-stimulus presentation in past studies; the signal is known to reflect increased neuronal firing and metabolic demand during language production. In contrast, concurrent beta event-related synchrony (ERS) is thought to reflect neuronal inhibition but has not been well studied in the context of language. Further, while low-beta ERD for expressive language has been found to gradually shift from bilateral in childhood to left hemispheric by early adulthood, developmental lateralization of ERS has not been established. We used magnetoencephalography to study low beta ERS lateralization in a group of children and adolescents (n = 78), aged 4 to less than 19 years, who performed covert verb generation. We found that the youngest children had bilateral ERD and ERS. By adolescence, low-beta ERD was predominantly left lateralized in perisylvian cortex (i.e., Broca's and Wernicke's regions), while beta ERS was predominantly right lateralized. Increasing lateralization was significantly correlated to age for both ERD (Spearman's r = 0.45, p < 0.01) and ERS (Spearman's r = - 0.44, p < 0.01). Interestingly, while ERD lateralized in a linear manner, ERS lateralization followed a nonlinear trajectory, suggesting distinct developmental trajectories. Implications to early-age neuroplasticity and neuronal inhibition are discussed.

Synchronous spiking associated with prefrontal high γ oscillations evokes a 5-Hz rhythmic modulation of spiking in locus coeruleus.

The brainstem noradrenergic locus coeruleus (LC) is reciprocally connected with the prefrontal cortex (PFC). Coupling between LC spiking and the depolarizing phase of slow (1-2 Hz) waves in PFC field potentials during sleep and anesthesia suggests that LC drives cortical state transition. Reciprocal LC-PFC connectivity should also allow interactions in the opposing (top-down) direction, but prior work has only studied prefrontal control over LC activity using electrical or optogenetic stimulation. Here, we describe the physiological characteristics of spontaneously occurring top-down LC-PFC interactions. We recorded LC multiunit activity (MUA) simultaneously with PFC single-unit and local field potential (LFP) activity in urethane-anesthetized rats. We observed cross-regional coupling between the phase of 5-Hz oscillations in LC-MUA and the power of PFC LFP 60-200 Hz high γ (hγ). Transient increases in PFC hγ power preceded peaks in the 5-Hz LC-MUA oscillation. Analysis of cross-regional transfer entropy demonstrated that the PFC hγ transients were predictive of a transient increase in LC-MUA. An ∼29 ms delay between these signals was consistent with the conduction velocity from the PFC to the LC. Finally, we showed that PFC hγ transients are associated with synchronized spiking of a subset (27%) of PFC single units. Our data suggest that PFC hγ transients may indicate the timing of the top-down excitatory input to LC, at least under conditions when LC neuronal population activity fluctuates rhythmically at 5 Hz. Synchronized PFC neuronal spiking that occurs during hγ transients may provide a previously unknown mode of top-down control over the LC.NEW & NOTEWORTHY The prefrontal cortex (PFC) is thought to control activity in the noradrenergic locus coeruleus (LC). Prior anatomical and prefrontal stimulation studies demonstrated the potential for PFC-LC interactions; however, it is unknown what types of PFC activity affect the LC. Here, we show that transient increases in PFC high γ power and associated changes in PFC unit-pair synchrony are a potential sign of top-down control over the LC.

Measuring the effects of first antiepileptic medication in Temporal Lobe Epilepsy: Predictive value of quantitative-EEG analysis.

OBJECTIVE: To determine the quantitative EEG responses in a population of drug-naïve patients with Temporal Lobe Epilepsy (TLE) after Levetiracetam (LEV) initiation as first antiepileptic drug (AED). We hypothesized that the outcome of AED treatment can be predicted from EEG data in patients with TLE. METHODS: Twenty-three patients with TLE and twenty-five healthy controls were examined. Clinical outcome was dichotomized into seizure-free (SF) and non-seizure-free (NSF) after two years of LEV. EEG parameters were compared between healthy controls and patients with TLE at baseline (EEGpre) and after three months of AED therapy (EEGpre-post) and between SF and NSF patients. Receiver Operating Characteristic curves models were built to test whether EEG parameters predicted outcome. RESULTS: AED therapy induces an increase in EEG power for Alpha (p = 0.06) and a decrease in Theta (p < 0.05). Connectivity values were lower in SF compared to NSF patients (p < 0.001). Quantitative EEG predicted outcome after LEV treatment with an estimated accuracy varying from 65.2% to 91.3% (area under the curve [AUC] = 0.56-0.93) for EEGpre and from 69.9% to 86.9% (AUC = 0.69-0.94) for EEGpre-post. CONCLUSIONS: AED therapy induces EEG modifications in TLE patients, and such modifications are predictive of clinical outcome. SIGNIFICANCE: Quantitative EEG may help understanding the effect of AEDs in the central nervous system and offer new prognostic biomarkers for patients with epilepsy.

Effects of load and emotional state on EEG alpha-band power and inter-site synchrony during a visual working memory task.

Motivationally/emotionally engaging stimuli are strong competitors for the limited capacity of sensory and cognitive systems. Thus, they often act as distractors, interfering with performance in concurrent primary tasks. Keeping task-relevant information in focus while suppressing the impact of distracting stimuli is one of the functions of working memory (WM). Macroscopic brain oscillations in the alpha band (8-13 Hz) have recently been identified as a neural correlate of WM processing. Using electroencephalography, we examined the extent to which changes in alpha power and inter-site connectivity during a typical WM task are sensitive to load and emotional distraction. Participants performed a lateralized change-detection task with two levels of load (four vs. two items), which was preceded by naturalistic scenes rated either as unpleasant or neutral, acting as distractors. The results showed the expected parieto-occipital alpha reduction in the hemisphere contralateral to the WM task array, compared to the ipsilateral hemisphere, during the retention interval. Selectively heightened oscillatory coupling between frontal and occipital sensors was observed (1) during the retention interval as a function of load, and (2) upon the onset of the memory array, after viewing neutral compared to unpleasant distractors. At the end of the retention interval, we observed greater coupling during the unpleasant compared to the neutral condition. These findings are consistent with the notions that (1) representing more items in WM requires greater interconnectivity across cortical areas, and (2) unpleasant emotional distractors interfere with subsequent WM processing by disrupting processing during the encoding stage.

Brain functional connectivity in chronic tic disorders and Gilles de la Tourette syndrome.

The pathophysiology of chronic tic disorder (cTD) and Gilles de la Tourette syndrome (GTS) is characterized by the dysfunction of both motor and non - motor cortico - striatal - thalamo - cortical (CSTC) circuitries, which leads to tic release and comorbids. A role of fronto - parietal network (FPN) connectivity breakdown has been postulated for tic pathogenesis, given that the FPN entertain connections with limbic, paralimbic, and CSTC networks. Our study was aimed at characterizing the FPN functional connectivity in cTD and GTS in order to assess the role of its deterioration in tic severity and the degree of comorbids. We recorded scalp EEG during resting state in patients with cTD and GTS. The eLORETA current source densities were analyzed, and the lagged phase synchronization (LPS) was calculated to estimate nonlinear functional connectivity between cortical areas. We found that the FPN functional connectivity in delta band was more detrimental in more severe GTS patients. Also, the sensorimotor functional connectivity in beta2 band was stronger in more severe cTD and GTS patients. FPN functional connectivity deterioration correlated with comorbids presence and severity in patients with GTS. Our data suggest that a FPN disconnection may contribute to the motoric symptomatology and comorbid severity in GTS, whereas sensorimotor disconnection may contribute to tic severity in cTD and GTS. Although preliminary, our study points out a differently disturbed brain connectivity between patients with cTD and GTS. This may serve as diagnostic marker and potentially interesting base to develop pharmacological and noninvasive neuromodulation trials aimed at reducing tic symptomatology.

Electroencephalographic Phase Synchrony Index as a Biomarker of Poststroke Motor Impairment and Recovery.

Background. Motor recovery after stroke is of great clinical interest. Besides magnetic resonance imaging functional connectivity, electroencephalographic synchrony is also an available biomarker. However, the clinical relevance of electroencephalographic synchrony in hemiparesis has not been fully understood. Objective. We aimed to demonstrate the usefulness of the phase synchrony index (PSI) by showing associations between the PSI and poststroke outcome in patients with hemiparesis. Methods. This observational study included 40 participants with cortical ischemic stroke (aged 69.8 ± 13.8 years) and 22 healthy controls (aged 66.9 ± 6.5 years). Nineteen-channel electroencephalography was recorded at 36.9 ± 11.8 days poststroke. Upper extremity Fugl-Meyer scores were assessed at the time of admission/before discharge (FM-UE1/FM-UE2; 32.6 ± 12.3/121.0 ± 44.7 days poststroke). Then, correlations between the PSIs and FM-UE1 as well as impairment reduction after rehabilitation (FM-UEgain) were analyzed. Results. The interhemispheric PSI (alpha band) between the primary motor areas (M1s) was lower in patients than in controls and was selectively correlated with FM-UE1 (P = .001). In contrast, the PSI (theta band) centered on the contralesional M1 was higher in patients than in controls and was selectively correlated with FM-UEgain (P = .003). These correlations remained significant after adjusting for confounding factors (age, time poststroke, National Institute of Health Stroke Scale, and lesion volume). Furthermore, the latter correlation was significant in severely impaired patients (FM-UE1 ≤ 10). Conclusions. This study showed that the PSIs were selectively correlated with motor impairment and recovery. Therefore, the PSIs may be potential biomarkers in persons with a hemispheric infarction.

Activity-dependent myelination: A glial mechanism of oscillatory self-organization in large-scale brain networks.

Communication and oscillatory synchrony between distributed neural populations are believed to play a key role in multiple cognitive and neural functions. These interactions are mediated by long-range myelinated axonal fiber bundles, collectively termed as white matter. While traditionally considered to be static after development, white matter properties have been shown to change in an activity-dependent way through learning and behavior-a phenomenon known as white matter plasticity. In the central nervous system, this plasticity stems from oligodendroglia, which form myelin sheaths to regulate the conduction of nerve impulses across the brain, hence critically impacting neural communication. We here shift the focus from neural to glial contribution to brain synchronization and examine the impact of adaptive, activity-dependent changes in conduction velocity on the large-scale phase synchronization of neural oscillators. Using a network model based on primate large-scale white matter neuroanatomy, our computational and mathematical results show that such plasticity endows white matter with self-organizing properties, where conduction delay statistics are autonomously adjusted to ensure efficient neural communication. Our analysis shows that this mechanism stabilizes oscillatory neural activity across a wide range of connectivity gain and frequency bands, making phase-locked states more resilient to damage as reflected by diffuse decreases in connectivity. Critically, our work suggests that adaptive myelination may be a mechanism that enables brain networks with a means of temporal self-organization, resilience, and homeostasis.

EEG source-space synchrostate transitions and Markov modeling in the math-gifted brain during a long-chain reasoning task.

To reveal transition dynamics of global neuronal networks of math-gifted adolescents in handling long-chain reasoning, this study explores momentary phase-synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows during a reasoning task and non-task idle process. Through agglomerative hierarchical clustering for functional connectivity graphs and nested iterative cosine similarity tests, this study identifies seven general and one reasoning-specific prototypical functional connectivity patterns from all synchrostates. Markov modeling is performed for the time-sequential synchrostates of each trial to characterize the interstate transitions. The analysis reveals that default mode network, central executive network (CEN), dorsal attention network, cingulo-opercular network, left/right ventral frontoparietal network, and ventral visual network aperiodically recur over non-task or reasoning process, exhibiting high predictability in interactively reachable transitions. Compared to non-gifted subjects, math-gifted adolescents show higher fractional occupancy and mean duration in CEN and reasoning-triggered transient right frontotemporal network (rFTN) in the time course of the reasoning process. Statistical modeling of Markov chains reveals that there are more self-loops in CEN and rFTN of the math-gifted brain, suggesting robust state durability in temporally maintaining the topological structures. Besides, math-gifted subjects show higher probabilities in switching from the other types of synchrostates to CEN and rFTN, which represents more adaptive reconfiguration of connectivity pattern in the large-scale cortical network for focused task-related information processing, which underlies superior executive functions in controlling goal-directed persistence and high predictability of implementing imagination and creative thinking during long-chain reasoning.

Short-range and long-range neuronal oscillatory coupling in multiple frequency bands during face perception.

Neuronal oscillatory activity has been considered to play a key role in face processing through its functional effect on information flow and exchange in human brain. Specifically, most neuronal oscillatory activity is measured in different rhythm based on the electrophysiological signal at single channel level. Although, the neuronal oscillatory coupling between neuronal assembles is associated with the information flow and exchange between brain regions, few studies focus on this type of neuronal oscillatory activity in face processing. In this study, the neuronal oscillatory coupling was investigated based on electroencephalographic (EEG) data of 20 participants, which were recorded when the participants were in a face/non-face perceptual task. The phase lag index (PLI) was used to assess the neuronal oscillatory coupling between brain regions in typical frequency bands. Enhanced short-range coupling was observed in theta (4-8 Hz) and alpha (8-12 Hz) band over the frontal region, in gamma1 (30-49 Hz) band over the left posterior and occipito-temporal regions, and in gamma2 (51-75 Hz) over the right temporal region during face perception compared with non-face perception. Long-range coupling was increased in theta and gamma band over the right hemisphere during face perception. Moreover, increased long-range coupling was observed in alpha band over the left and right hemisphere respectively during face perception. The results suggested that frequency-specific neuronal oscillatory coupling within and between regions of frontal cortex and the ventral visual pathway played an important role in face perception, which might reflect underlying neural mechanism of face perception.

Music as a scaffold for listening to speech: Better neural phase-locking to song than speech.

Neural activity synchronizes with the rhythmic input of many environmental signals, but the capacity of neural activity to entrain to the slow rhythms of speech is particularly important for successful communication. Compared to speech, song has greater rhythmic regularity, a more stable fundamental frequency, discrete pitch movements, and a metrical structure, this may provide a temporal framework that helps listeners neurally track information better than the rhythmically irregular rhythms of speech. The current study used EEG to examine whether entrainment to the syllable rate of linguistic utterances, as indexed by cerebro-acoustic phase coherence, was greater when listeners heard sung than spoken sentences. We assessed listeners phase-locking in both easy (no time compression) and hard (50% time-compression) utterance conditions. Adults phase-locked equally well to speech and song in the easy listening condition. However, in the time-compressed condition, phase-locking was greater for sung than spoken utterances in the theta band (3.67-5 â€‹Hz). Thus, the musical temporal and spectral characteristics of song related to better phase-locking to the slow phrasal and syllable information (4-7 â€‹Hz) in the speech stream. These results highlight the possibility of using song as a tool for improving speech processing in individuals with language processing deficits, such as dyslexia.

Neurophysiological Biomarkers of Parkinson's Disease.

BACKGROUND: There is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics. OBJECTIVE: To demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease. METHODS: A multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls. RESULTS: Qualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET. CONCLUSION: Our results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy.

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis.

The purpose of this paper is to record and analyze induced gamma-band activity (GBA) (30-60 Hz) in cerebral motor areas during imaginary movement and to compare it quantitatively with activity recorded in the same areas during actual movement using a simplified electroencephalogram (EEG). Brain activity (basal activity, imaginary motor task and actual motor task) is obtained from 12 healthy volunteer subjects using an EEG (Cz channel). GBA is analyzed using the mean power spectral density (PSD) value. Event-related synchronization (ERS) is calculated from the PSD values of the basal GBA (GBAb), the GBA of the imaginary movement (GBAim) and the GBA of the actual movement (GBAac). The mean GBAim and GBAac values for the right and left hands are significantly higher than the GBAb value (p = 0.007). No significant difference is detected between mean GBA values during the imaginary and actual movement (p = 0.242). The mean ERS values for the imaginary movement (ERSimM (%) = 23.52) and for the actual movement (ERSacM = 27.47) do not present any significant difference (p = 0.117). We demonstrated that ERS could provide a useful way of indirectly checking the function of neuronal motor circuits activated by voluntary movement, both imaginary and actual. These results, as a proof of concept, could be applied to physiology studies, brain-computer interfaces, and diagnosis of cognitive or motor pathologies.

The Cumulative Effect of Transient Synchrony States on Motor Performance in Parkinson's Disease.

Bursts of beta frequency band activity in the basal ganglia of patients with Parkinson's disease (PD) are associated with impaired motor performance. Here we test in human adults whether small variations in the timing of movement relative to beta bursts have a critical effect on movement velocity and whether the cumulative effects of multiple beta bursts, both locally and across networks, matter. We recorded local field potentials from the subthalamic nucleus (STN) in 15 PD patients of both genders OFF-medication, during temporary lead externalization after deep brain stimulation surgery. Beta bursts were defined as periods exceeding the 75th percentile amplitude threshold. Subjects performed a visual cued joystick reaching task, with the visual cue being triggered in real time with different temporal relationships to bursts of STN beta activity. The velocity of actions made in response to cues prospectively triggered by STN beta bursts was slower than when responses were not time-locked to recent beta bursts. Importantly, slow movements were those that followed multiple bursts close to each other within a trial. In contrast, small differences in the delay between the last burst and movement onset had no significant impact on velocity. Moreover, when the overlap of bursts between the two STN was high, slowing was more pronounced. Our findings suggest that the cumulative, but recent, history of beta bursting, both locally and across basal ganglia networks, may impact on motor performance.SIGNIFICANCE STATEMENT Bursts of beta frequency band activity in the basal ganglia are associated with slowing of voluntary movement in patients with Parkinson's disease. We show that slow movements are those that follow multiple bursts close to each other and bursts that are coupled across regions. These results suggest that the cumulative, but recent, history of beta bursting, both locally and across basal ganglia networks, impacts on motor performance in this condition. The manipulation of burst dynamics may be a means of selectively improving motor impairment.

Linking alpha oscillations, attention and inhibitory control in adult ADHD with EEG neurofeedback.

Abnormal patterns of electrical oscillatory activity have been repeatedly described in adult ADHD. In particular, the alpha rhythm (8-12 Hz), known to be modulated during attention, has previously been considered as candidate biomarker for ADHD. In the present study, we asked adult ADHD patients to self-regulate their own alpha rhythm using neurofeedback (NFB), in order to examine the modulation of alpha oscillations on attentional performance and brain plasticity. Twenty-five adult ADHD patients and 22 healthy controls underwent a 64-channel EEG-recording at resting-state and during a Go/NoGo task, before and after a 30 min-NFB session designed to reduce (desynchronize) the power of the alpha rhythm. Alpha power was compared across conditions and groups, and the effects of NFB were statistically assessed by comparing behavioral and EEG measures pre-to-post NFB. Firstly, we found that relative alpha power was attenuated in our ADHD cohort compared to control subjects at baseline and across experimental conditions, suggesting a signature of cortical hyper-activation. Both groups demonstrated a significant and targeted reduction of alpha power during NFB. Interestingly, we observed a post-NFB increase in resting-state alpha (i.e. rebound) in the ADHD group, which restored alpha power towards levels of the normal population. Importantly, the degree of post-NFB alpha normalization during the Go/NoGo task correlated with individual improvements in motor inhibition (i.e. reduced commission errors) only in the ADHD group. Overall, our findings offer novel supporting evidence implicating alpha oscillations in inhibitory control, as well as their potential role in the homeostatic regulation of cortical excitatory/inhibitory balance.

International Federation of Clinical Neurophysiology (IFCN) - EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies.

In 1999, the International Federation of Clinical Neurophysiology (IFCN) published "IFCN Guidelines for topographic and frequency analysis of EEGs and EPs" (Nuwer et al., 1999). Here a Workgroup of IFCN experts presents unanimous recommendations on the following procedures relevant for the topographic and frequency analysis of resting state EEGs (rsEEGs) in clinical research defined as neurophysiological experimental studies carried out in neurological and psychiatric patients: (1) recording of rsEEGs (environmental conditions and instructions to participants; montage of the EEG electrodes; recording settings); (2) digital storage of rsEEG and control data; (3) computerized visualization of rsEEGs and control data (identification of artifacts and neuropathological rsEEG waveforms); (4) extraction of "synchronization" features based on frequency analysis (band-pass filtering and computation of rsEEG amplitude/power density spectrum); (5) extraction of "connectivity" features based on frequency analysis (linear and nonlinear measures); (6) extraction of "topographic" features (topographic mapping; cortical source mapping; estimation of scalp current density and dura surface potential; cortical connectivity mapping), and (7) statistical analysis and neurophysiological interpretation of those rsEEG features. As core outcomes, the IFCN Workgroup endorsed the use of the most promising "synchronization" and "connectivity" features for clinical research, carefully considering the limitations discussed in this paper. The Workgroup also encourages more experimental (i.e. simulation studies) and clinical research within international initiatives (i.e., shared software platforms and databases) facing the open controversies about electrode montages and linear vs. nonlinear and electrode vs. source levels of those analyses.