Beta Synchronization Research Articles

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

Losses resulting from deliberate exploration trigger beta oscillations in frontal cortex.

We examined the neural signature of directed exploration by contrasting MEG beta (16-30 Hz) power changes between disadvantageous and advantageous choices in the two-choice probabilistic reward task. We analyzed the choices made after the participants have learned the probabilistic contingency between choices and their outcomes, i.e., acquired the inner model of choice values. Therefore, rare disadvantageous choices might serve explorative, environment-probing purposes. The study brought two main findings. Firstly, decision making leading to disadvantageous choices took more time and evidenced greater large-scale suppression of beta oscillations than its advantageous alternative. Additional neural resources recruited during disadvantageous decisions strongly suggest their deliberately explorative nature. Secondly, an outcome of disadvantageous and advantageous choices had qualitatively different impact on feedback-related beta oscillations. After the disadvantageous choices, only losses-but not gains-were followed by late beta synchronization in frontal cortex. Our results are consistent with the role of frontal beta oscillations in the stabilization of neural representations for selected behavioral rule when explorative strategy conflicts with value-based behavior. Punishment for explorative choice being congruent with its low value in the reward history is more likely to strengthen, through punishment-related beta oscillations, the representation of exploitative choices consistent with the inner utility model.

Increased sensitivity of spatial filters by combining the magnetic and electrical components of the sensorimotor cortical beta rhythm

Modulation of human magnetic or electrical sensorimotor rhythms during motor imagery is widely used in fundamental and applied neurophysiological research. To date, there is evidence of a better sensitivity of magnetic field sensors to beta-rhythm modulation, however, the potential synergistic effect of combining the two modalities has not yet been investigated. In this study, simultaneous registration of electroencephalogram (EEG) and magnetoencephalogram (MEG) was carried out in eight healthy volunteers during voluntary and imaginary movements, as well as during electrical stimulation of the median nerve. In all subjects, it was possible to identify desynchronization (suppression) of mu and beta rhythms during the performance of sensorimotor tasks, as well as beta synchronization after the end of movement or stimulation. Using the common projections of the covariance matrices of signals of the electric, magnetic, and combined (“MEEG”) modalities, the most sensitive individual spatial filters were calculated separately for each type of reaction. Relative to the pre-stimulus control, the changes in the amplitude of the sensorimotor rhythm components turned out to be the largest in the combined MEEG modality. At the same time, for mu-desynchronization, MEEG turned out to be significantly better than MEG, and for beta-desynchronization, MEEG turned out to be significantly better than both MEG and EEG. For beta synchronization, a shift in the position of sources in the fronto-medial direction was shown, and there were no significant differences in amplitude between modalities. It was also shown that for beta desynchronization, most subjects identified MEG sources with identical EEG projections or without pronounced EEG projections, which indicates the presence of several small tangentially located cortical dipoles involved in beta rhythm desynchronization. The results obtained indicate that in studies of modulation of sensorimotor rhythm components, in particular beta desynchronization, the combination of MEG and EEG leads to greater sensitivity. The multifocal nature of the magnetic beta rhythm and its varying severity in EEG sources indicate the presence of independent regulatory circuits of cortical-thalamic or intracortical origin.

Aperiodic subthalamic activity predicts motor severity and stimulation response in Parkinson disease

IntroductionRhythmic beta activity in the subthalamic nucleus (STN) local field potential (LFP) is associated with Parkinson disease (PD) severity, though not all studies have found this relationship. We investigated whether aperiodic ‘noise’ elements of LFP, specifically slope of the 1/f broadband, predict PD motor symptoms and outcomes of STN-DBS. MethodsWe studied micro-LFP from 19 PD patients undergoing STN-DBS, relating the aperiodic 1/f slope and the periodic beta oscillation components to motor severity using the UPDRS-III and improvement with DBS at 1 year. ResultsBeta power, not 1/f slope, independently predicted baseline UPDRS-III (r = 0.425, p = 0.020; r = −0.434, p = 0.032, respectively), but multiple regression using both predicted better (F (2, 16) = 6.621, p = 0.008, R2 = 0.453). Only multiple regression using both slope and beta power predicted improvement in UPDRS-III at 1 year post-operatively (F (2, 15) = 6.049, R2 = 0.446, p = 0.012). ConclusionsBoth beta synchronization and slope of the 1/f broadband are informative of motor symptoms in PD and predict response to STN-DBS.

Hyperscanning EEG Paradigm Applied to Remote vs. Face-To-Face Learning in Managerial Contexts: Which Is Better?

We propose a hyperscanning research design, where electroencephalographic (EEG) data were collected on an instructor and teams of learners. We compared neurophysiological measures within the frequency domain (delta, theta, alpha, and beta EEG bands) in the two conditions: face-to-face and remote settings. Data collection was carried out using wearable EEG systems. Conversational analysis was previously applied to detect comparable EEG time blocks and semantic topics. The digitalization of training can be considered a challenge but also a chance for organizations. However, if not carefully addressed, it might constitute a criticality. Limited research explored how remote, as opposed to face-to-face, training affects cognitive, (such as memory and attention), affective, and social processes in workgroups. Data showed an alpha desynchronization and, conversely, a theta and beta synchronization for the face-to-face condition. Moreover, trainees showed different patterns for beta power depending on the setting condition, with significantly increased power spectral density (PSD) in the face-to-face condition. These results highlight the relevance of neurophysiological measures in testing the e-learning process, in relation to the emotional engagement, memory encoding, and attentional processing.

Bradykinesia and Its Progression Are Related to Interhemispheric Beta Coherence.

Bradykinesia is the major cardinal motor sign of Parkinson disease (PD), but its neural underpinnings are unclear. The goal of this study was to examine whether changes in bradykinesia following long-term subthalamic nucleus (STN) deep brain stimulation (DBS) are linked to local STN beta (13-30 Hz) dynamics or a wider bilateral network dysfunction. Twenty-one individuals with PD implanted with sensing neurostimulators (Activa® PC + S, Medtronic, PLC) in the STN participated in a longitudinal 'washout' therapy study every three to 6 months for an average of 3 years. At each visit, participants were withdrawn from medication (12/24/48hours) and had DBS turned off (>60minutes) before completing a repetitive wrist-flexion extension task, a validated quantitative assessment of bradykinesia, while local field potentials were recorded. Local STN beta dynamics were investigated via beta power and burst duration, while interhemispheric beta synchrony was assessed with STN-STN beta coherence. Higher interhemispheric STN beta coherence, but not contralateral beta power or burst duration, was significantly associated with worse bradykinesia. Bradykinesia worsened off therapy over time. Interhemispheric STN-STN beta coherence also increased over time, whereas beta power and burst duration remained stable. The observed change in bradykinesia was related to the change in interhemispheric beta coherence, with greater increases in synchrony associated with further worsening of bradykinesia. Together, these findings implicate interhemispheric beta synchrony as a neural correlate of the progression of bradykinesia following chronic STN DBS. This could imply the existence of a pathological bilateral network contributing to bradykinesia in PD. ANN NEUROL 2023;93:1029-1039.

Stereo-EEG recordings extend known distributions of canonical movement-related oscillations

Objective. Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement mostly from recordings of primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a broader array of brain areas such as those sampled by stereoelectroencephalography (sEEG), especially in humans. We aimed to identify and characterize different movement-related oscillations across a relatively broad sampling of brain areas in humans and if they extended beyond brain areas previously associated with movement. Approach. We used a linear support vector machine to decode time-frequency spectrograms time-locked to movement, and we validated our results with cluster permutation testing and common spatial pattern decoding. Main results. We were able to accurately classify sEEG spectrograms during a keypress movement task versus the inter-trial interval. Specifically, we found these previously-described patterns: beta (13–30 Hz) desynchronization, beta synchronization (rebound), pre-movement alpha (8–15 Hz) modulation, a post-movement broadband gamma (60–90 Hz) increase and an event-related potential. These oscillatory patterns were newly observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiology recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside primary and secondary motor cortices. Significance. Our classification revealed prominent time-frequency patterns which were also observed in previous studies that used non-invasive electroencephalography and electrocorticography, but here we identified these patterns in brain regions that had not yet been associated with movement. This provides new evidence for the anatomical extent of the system of putative motor networks that exhibit each of these oscillatory patterns.

Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson’s patients

Pathologically increased beta power has been described as a biomarker for Parkinson’s disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson’s patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.

Effect of Task Complexity on the Post-Movement Beta Synchronization in the Sensorimotor Cortex

Effect of Task Complexity on the Post-Movement Beta Synchronization in the Sensorimotor Cortex

P 15 Long-term subthalamic deep brain stimulation modulates pathological beta oscillations in the AAV-A53T-Synuclein Parkinson's disease rat model

Introduction: Aberrant beta (13-35 Hz) synchrony within the cortico-basal ganglia circuit has been reported as disease-specific hallmark of human Parkinson's disease (PD). The suppression of pathologically enhanced beta oscillations following subthalamic deep brain stimulation (STN-DBS ) is considered to be a crucial mechanism mediating improved motor function in PD patients and animal models. However, it remains unclear how long-term STN-DBS modulates beta oscillations over time in PD models with ongoing dopaminergic neurodegeneration. To clarify, we performed 3 weeks of continuous STN-DBS in a pathologically-relevant preclinical AAV-A53T-αSynuclein PD rat model (A53T). This model is characterized by a gradual nigrostriatal degeneration and reflects clinical hallmarks of human PD, thus allowing us to study neuromodulatory effects of long -term STN-DBS. Materials & methods: In this study, adult male Sprague Dawley rats were randomly assigned to EV (Empty Vector) and A53T groups and additionally divided into 2 subgroups: stim-ON and stim-OFF. During stereotaxic injection of viral vectors (EV or human AAV-A53T-αSynuclein virus), electrophysiological recordings and DBS electrodes were implanted. To obtain the LFP and ECoG data, we conducted monopolar LFP recordings in globus pallidus - external segment (GPe) and electrocorticography (ECoG) in motor cortex during 4 recording sessions - 1, 3, 6, 8 weeks after surgery. Continuous high frequency DBS / sham-DBS was induced from the 3rd week on, lasting for additional 3 weeks. Neuromodulatory effects of long-term STN-DBS on LFP / ECoG were evaluated immediately at stimulation termination in awake, resting state animals, and repeated after wash-out period for 2 weeks. Results: Both A53T groups developed augmented beta activity in MCx and GPe vs. EV at week 3 after surgery (X 2 ≥7.33, p≤0.03; z≥-2.45, p≤0.05). In the A53T stim-ON group, 3 weeks of continuous STN-DBS suppressed the elevated MCx and GPe beta power compared to EV at week 6 (z≥-1.12, p≥0.25). Specifically, in the A53T stim-ON group, the suppressive effect of beta power after the long-term STN-DBS was still present after 2 weeks wash-out period in the GPe (z = -1.41, p = 0.16), but not in the MCx (z = -2.12, p = 0.03) compared to EV. In contrast, the A53T stim-OFF group augmented MCx and GPe beta power sustainably for 8 weeks (z≥-2.45, p≤0.05). Conclusion: Our preliminary results suggest that long-term STN-DBS has a suppressive effect on pathological beta oscillations in the progressive A53T-aSyn PD rat model.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit.

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.

337 Neural Network Changes with Loss of Consciousness in Parkinson's Disease

INTRODUCTION: Consciousness is likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. The pallidocortical circuit is of particular interest given the putative role of pallidum in consciousness, according to the mesocircuit model, though this has not been well studied. METHODS: We characterized changes in pallidocortical circuits in awake versus propofol-induced unconscious states in humans by directly and simultaneously recording from perirolandic cortices and the pallidum in twelve Parkinson Disease (PD) patients undergoing implantation of therapeutic deep brain stimulation (DBS) leads. RESULTS: Propofol-induced LOC resulted in power increases up to 20 Hz in globus pallidus internus (GPi), 35 Hz in globus pallidus externus (GPe), and 100 Hz in sensorimotor cortices (S1/M1). At a network level, LOC resulted in increased pallidocortical alpha coherence with increases in Granger causality (GC) in the alpha/low beta range from GPe to all other nodes. In contrast, LOC was associated with decreased network-wide beta coherence with decreased GC in the beta range from M1 to the rest of the network. CONCLUSION: These results not only confirm the LOC-related changes in pallidocortical circuitry, but GC results suggest that widely reported LOC-related increases in alpha band power emanate from GPe. These findings support a significant role of the GPe in modulating consciousness. Simultaneous LOC-related suppression of beta synchrony from M1 to other nodes suggests that distinct oscillatory frequencies can act independently, conveying unique network level activity. Given the pathophysiologic role of beta synchrony in PD, LOC-related suppresion of beta synchrony may be amplified in this patient population, but may also highlight a parallel network mediating LOC-related loss of motor control.

Novel approaches for quantifying beta synchrony in Parkinson's disease.

Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.

Repeated Subconcussive Exposure Alters Low-Frequency Neural Oscillation in Memory Retrieval Processing.

Repeated subconcussive head impacts are frequently experienced by athletes involved in competitive sports, such as boxing. The objective of the present study was to investigate the changes in working memory performance and memory retrieval-related neural oscillations in boxing athletes who experienced repeated subconcussive head impacts. Twenty-one boxing athletes (boxing group) and 25 matched controls (control group) completed a modified visual working memory task, and their continuous scalp electroencephalography (EEG) data were collected simultaneously. The behavioral measures and retrieval-related low-frequency neural oscillations were analyzed at each working memory set size in both groups. Subjects in the boxing group showed a reduced mean accuracy, diminished capacity estimates, and slower reaction time at demanding set sizes, and a marginally increased intra-individual coefficient of variation (ICV) for overall set sizes. Additionally, decreased event-related frontal theta synchronization, parieto-occipital alpha desynchronization, and frontal low beta synchronization were observed in the boxing group, suggesting underlying working memory dysfunction for efficient neurocognitive resource employment, inhibition of distracting stimuli, and post-retrieval control in the boxing group. Moreover, a negative correlation was found between frontal beta synchronization and reaction time for most set sizes in both groups. The present study was the first to reveal the underlying working memory deficits caused by the cumulative effects of boxing-related subconcussive head impacts from the perspective of behavior and EEG time-frequency oscillations. Joint analysis of EEG low-frequency oscillations and the innovative task with multiple challenging load conditions may serve as a promising way to detect concealed deficiencies within working memory processing.

The Neurophysiological Impact of Subacute Stroke: Changes in Cortical Oscillations Evoked by Bimanual Finger Movement.

Introduction To design more effective interventions, such as neurostimulation, for stroke rehabilitation, there is a need to understand early physiological changes that take place that may be relevant for clinical monitoring. We aimed to study changes in neurophysiology following recent ischemic stroke, both at rest and with motor planning and execution. Materials and Methods We included 10 poststroke patients, between 7 and 10 days after stroke, and 20 age-matched controls to assess changes in cortical motor output via transcranial magnetic stimulation and in dynamics of oscillations, as recorded using electroencephalography (EEG). Results We found significant differences in cortical oscillatory patterns comparing stroke patients with healthy participants, particularly in the beta rhythm during motor planning (p = 0.011) and execution (p = 0.004) of a complex movement with fingers from both hands simultaneously. Discussion. The stroke lesion induced a decrease in event-related desynchronization in patients, in comparison to controls, providing evidence for decreased disinhibition. Conclusions After a stroke lesion, the dynamics of cortical oscillations is changed, with an increasing neural beta synchronization in the course of motor preparation and performance of complex bimanual finger tasks. The observed patterns may provide a potential functional measure that could be used to monitor and design interventional approaches in subacute stages.

Oscillation suppression effects of intermittent noisy deep brain stimulation induced by coordinated reset pattern based on a computational model

Noisy stimulation (NS) has been proposed to alleviate the pathological state in a computational model of Parkinson’s disease. Based on a resonance effect, NS modulates the neural firing pattern so as to suppress the excessive beta (12–35 Hz) synchronization and improve the relay reliability of the thalamus. However, in common with clinically-used pulsed high-frequency stimulation, the use of a continuous stimulation waveform for NS still may require an energy expenditure that is greater than necessary. A coordinated reset (CR) method to optimize NS is explored in this work that considers that the neural nature of the Parkinsonian condition is the enhancement of synchronization. CR methods has an advantage in disturbing the abnormal synchronous rhythm. Thesimulation resultsshow that coordinated reset noisy stimulation (CRNS) can further inhibit the enhanced pathological synchronization in a basal ganglia-thalamus network model with lower energy expenditure, as compared to basic NS. Moreover, two kinds of intermittent CRNS strategies are further derived by adding and adjusting the stimulation-off phases in the CRNS strategy. It is found that m:n ON-OFF CRNS strategies and delayed CRNS may further reduce the stimulation energy cost by 21.2% and 15.3% without compromising control performance, respectively. This work provides a new insight into the optimization of deep brain stimulation and may guide a new approach to treating Parkinson’s disease by optimizing the noise-induced improvement of the basal ganglia dysfunction.

Learning of Pseudoword-Movement Association is Accompanied by Enhanced Beta Synchronization

This article presents the case for, and against, using the term crash versus accident to describe unintended events that involve motor vehicles in transport on a trafficway and which result in damage to property or injury to involved persons. The history of the preference for crash versus accident among safety practitioners goes back to the 1960s. The change is not yet universal for a variety of reasons; however, it is gaining acceptance both within and outside the traffic safety field. The case for crash relies mainly on the observation that these events, while unintended, are not unavoidable and the causes and contributing factors are known. Moreover, we can apply effective countermeasures and measure the impact of those countermeasures in reducing the frequency and severity of these events. The counterargument, that the term accident is best, relies mostly on historic precedent and parallel terminology in industrial safety. The preference for crash is strongest among safety practitioners who focus on implementing countermeasures (behavior change, vehicle systems, and the roadway environment) and among those harmed in crashes and their families. We must also recognize the special case of intentionally harmful events that clearly are not accidental under any accepted definition. Those who argue in favor of using the word accident have some difficulty classifying which of the crash contributing factors point to intentional behaviors about which they must agree the term accident is a poor choice. Evidence suggests that media outlets are starting to adopt the changed word choice as well. In the United States, some states are resistant because their laws include the term accident, but classification guidance and standards from the National Highway Traffic Safety Administration (NHTSA) and the American National Standards Institute (ANSI) have made the change a permanent part of the safety lexicon, and some states are following this guidance as well. Note that the majority of this article presents discussions that are taking place in and about the situation in the United States. I have included some information about the situation in the rest of the world regarding terminology and mind-sets and for that input I thank my international colleagues.

Articulatory Gain Predicts Motor Cortex and Subthalamic Nucleus Activity During Speech.

Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson's disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.

Reduced readiness potential and post-movement beta synchronization reflect self-disorders in early course schizophrenia

Disturbances of conscious awareness, or self-disorders, are a defining feature of schizophrenia. These include symptoms such as delusions of control, i.e. the belief that one’s actions are controlled by an external agent. Models of self-disorders point at altered neural mechanisms of source monitoring, i.e. the ability of the brain to discriminate self-generated stimuli from those driven by the environment. However, evidence supporting this putative relationship is currently lacking. We performed electroencephalography (EEG) during self-paced, brisk right fist closures in ten (M = 9; F = 1) patients with Early-Course Schizophrenia (ECSCZ) and age and gender-matched healthy volunteers. We measured the Readiness Potential (RP), i.e. an EEG feature preceding self-generated movements, and movement-related EEG spectral changes. Self-disorders in ECSCZ were assessed with the Examination of Anomalous Self-Experience (EASE). Patients showed a markedly reduced RP and altered post-movement Event-Related Synchronization (ERS) in the beta frequency band (14–24 Hz) compared to healthy controls. Importantly, smaller RP and weaker ERS were associated with higher EASE scores in ECSCZ. Our data suggest that disturbances of neural correlates preceding and following self-initiated movements may reflect the severity of self-disorders in patients suffering from ECSCZ. These findings point towards deficits in basic mechanisms of sensorimotor integration as a substrate for self-disorders.

Watching the Brain as It (Un)Binds: Beta Synchronization Relates to Distractor-Response Binding.

Human action control relies on event files, that is, short-term stimulus-response bindings that result from the integration of perception and action. The present EEG study examined oscillatory brain activities related to the integration and disintegration of event files in the distractor-response binding (DRB) task, which relies on a sequential prime-probe structure with orthogonal variation of distractor and response relations between prime and probe. Behavioral results indicated a DRB effect in RTs, which was moderated by the duration of the response-stimulus interval (RSI) between prime response and probe stimulus onset. Indeed, a DRB effect was observed for a short RSI of 500 msec but not for a longer RSI of 2000 msec, indicating disintegration of event files over time. EEG results revealed a positive correlation between individual DRB in the RSI-2000 condition and postmovement beta synchronization after both prime and probe responses. Beamformer analysis localized this correlation effect to the middle occipital gyrus, which also showed highest coherency with precentral and inferior parietal brain regions. Together, these findings suggest that postmovement beta synchronization is a marker of event file disintegration, with the left middle occipital gyrus being a hub region for stimulus-response bindings in the visual DRB task.