Baseline EEG Research Articles

Indications for continuous electroencephalographic (cEEG) monitoring: What do they tell us?

ObjectiveWhile studies have explored clinical and EEG predictors of seizures on continuous EEG (cEEG), the role of cEEG indications as predictors of seizures has not been studied. Our study aims to fill this knowledge gap. MethodsWe used the prospective cEEG database at Cleveland Clinic for the 2016 calendar year. Patients ≥ 18 years who underwent cEEG for the indication of altered mental status (AMS) and seizure-like events (SLE: motor or patient-reported events) were included. Baseline characteristics and EEG findings were compared between the two groups. Multivariable regression was used to compare the two groups and identify seizure detection risk factors. ResultsOf 2227 patients (mean age 59.4 years) who met the inclusion criteria, 882 (50% females) underwent cEEG for AMS and 1345(51% females) for SLE. SLE patients were younger(OR: 0.988, CI: 0.98–0.99, p < 0.001), had longer monitoring(OR:1.04, CI:1.00–1.07, p = 0.033), were more likely to have epilepsy-related-breakthrough seizures(OR:25.9, CI:0.5.89–115, p < 0.001), psychogenic non-epileptic spells (OR:6.85, CI:1.60–29.3, p = 0.008), were more awake (p < 0.001) and more likely to be on anti-seizure medications(OR:1.60, CI:1.29–1.98, p < 0.001). On multivariable analysis, SLE was an independent predictor of seizure detection (OR: 2.60, CI: 1.77–3.88, p < 0.001). SignificanceOur findings highlight the differences in patients undergoing cEEG for AMS vs. SLE. SLE as a cEEG indication represents an independent predictor of seizures on cEEG and, therefore, deserves special attention. Future multicenter studies are needed to validate our findings.

Changes in Electroencephalogram (EEG) After Foot Stimulation with Embedded Haptic Vibrotactile Trigger Technology: Neuromatrix and Pain Modulation Considerations

Background: Globally, pain and pain-related diseases are the leading causes of disability and disease burden. In the United States, pain is the most common reason patients consult primary care providers. An estimated 100 million people live with chronic or recurrent pain. Existing pharmacological treatments for pain include anti-inflammatory agents, opioids, and other oral and topical analgesics. Many of these have been associated with troublesome and potentially harmful adverse effects. Understanding the complex pain neuromatrix may help in identifying alternative, non-invasive strategies and treatment approaches to address pain severity, interference, and improve patient outcomes. The neuromatrix of pain is a network of neuronal pathways and circuits responding to sensory (nociceptive) stimulation. Research has suggested that the output patterns of the body-self neuromatrix are responsible for causing or triggering perceptual, homeostatic, and behavioral programs following traumatic injury, other pathology, or chronic stress. As such, pain can be considered a product of the output of a widely distributed neural network within the brain instead of a sequential result of sensory inputs triggered by injury, inflammation, or other pathology. For over a century, the Brodmann Areas remain the most widely known and frequently cited cytoarchitectural organization of the human cortex. Certain Brodmann areas of the brain have been associated with the current understanding of the neuromatrix of pain. The areas expands well beyond the thalamus and anterior cingulate, and primary (S1) and secondary (S2) somatosensory cortices to include the midbrain region of the periaqueductal gray (PAG) and the lenticular complex as well as the insula, orbitofrontal (Brodmann's area [BA] 11, 47), prefrontal (BA 9, 10, 44-46), motor (BA 6, Supplementary motor area, and M1), inferior parietal (BA 39, 40), and anterior cingulate (BA 24, 25) cortices (ACCs). Treatments that are non-invasive and non-pharmacological and target both central and peripheral nociceptive mechanisms that are identified as having an impact on the Brodmann areas associated with the neuromatrix of pain may potentially be considered a beneficial pain management option for patients. Haptic vibrotactile trigger technology targets the nociceptive pathways and is theorized to disrupt the neuromatrix of pain. The technology has been incorporated into non-pharmacological patches and other non-invasive routes of delivery such as apparel (socks), braces, wristbands, and compression sleeves. The purpose of this minimal risk study was to compare electroencephalogram (EEG) patterns in areas of the brain that have been associated with the neuromatrix for pain in subjects wearing socks that were embedded with haptic vibrotactile trigger technology with those patients that wore socks that were not embedded with the technology. Methods: This IRB-approved study compared electroencephalogram (EEG) patterns in subjects wearing cloth socks embedded with haptic vibrotactile trigger technology (Superneuro VTT Enhanced Socks (Srysty Holding Co., Toronto, Canada) with those patients that wore cloth socks that were not embedded with the technology. Baseline EEG data from 19 scalp locations were recorded in sixty (60) adult subjects (36 females and 24 males) ranging from ages 14 to 83 wearing standard store-purchased cloth socks on their feet. The subject’s standard socks were then removed and replaced with the Superneuro VTT enhanced socks on the subject’s feet. A second EEG recording was then obtained. Both eyes-closed and eyes-open data were recorded. Results: The results showed statistically significant t-test differences (P &lt; .01) in 59 out of 60 subjects in absolute power and 60 out of 60 subjects showed statistically significant differences in coherence and phase difference. The largest differences were in the alpha1 and beta2 frequency bands and especially in central scalp locations. Paired t-tests of LORETA current source densities between socks on and socks off demonstrated statistically significant differences in 60 out of 60 subjects. The largest effects of Superneuro VTT enhanced socks on were on the medial bank of the somatosensory cortex as well as in the left frontal lobes in the theta and alpha frequency. Conclusions: Study results indicate that foot stimulation with embedded haptic vibrotactile trigger technology showed significant modulation in the Brodmann areas that have been shown to be associated with the neuromatrix for pain in the human brain. Further research is suggested to evaluate if this technology has a positive impact on pain severity, pain interference, and quality of life and to be considered as a potentially beneficial pain management strategy and as part of a multi-modal treatment approach.

Decreased Electroencephalographic Alpha Power During Anesthesia Induction Is Associated With EEG Discontinuity in Human Infants.

Electroencephalogram (EEG) discontinuity can occur at high concentrations of anesthetic drugs, reflecting suppression of electrocortical activity. This EEG pattern has been reported in children and reflects a deep state of anesthesia. Isoelectric events on the EEG, a more extreme degree of voltage suppression, have been shown to be associated with worse long-term neurologic outcomes in neonates undergoing cardiac surgery. However, the clinical significance of EEG discontinuities during pediatric anesthesia for noncardiac surgery is not yet known and merits further research. In this study, we assessed the incidence of EEG discontinuity during anesthesia induction in neurologically normal infants and the clinical factors associated with its development. We hypothesized that EEG discontinuity would be associated with sevoflurane-induced alpha (8-12 Hz) power during the period of anesthesia induction in infants. We prospectively recorded 26 channels of EEG during anesthesia induction in an observational cohort of 54 infants (median age, 7.6 months; interquartile range [IQR] [4.9-9.8 months]). We identified EEG discontinuity, defined as voltage amplitude <25 microvolts for >2 seconds, and assessed its association with sevoflurane-induced alpha power using spectral analysis and multivariable logistic regression adjusting for clinically important variables. EEG discontinuity was observed in 20 of 54 subjects (37%), with a total of 25 discrete events. Sevoflurane-induced alpha power in the posterior regions of the head (eg, parietal or occipital regions) was significantly lower in the EEG discontinuity group (midline parietal channel on the electroencephalogram, International 10-20 System [Pz]; 8.3 vs 11.2 decibels [dBs]; P = .004), and this association remained after multivariable adjustment (adjusted odds ratio [aOR] = 0.51 per dB increase in alpha power [95% CI, 0.30-0.89]; P = .02). There were no differences in the baseline (unanesthetized) EEG between groups in alpha power or power in any other frequency band. We demonstrate that EEG discontinuity is common during anesthesia induction and is related to the level of sevoflurane-induced posterior alpha power, a putative marker of cortical-thalamic circuit development in the first year of life. This association persisted even after adjusting for age and propofol coadministration. The fact that this difference was only observed during anesthesia and not in the baseline EEG suggests that otherwise hidden brain circuit properties are unmasked by general anesthesia. These neurophysiologic markers observed during anesthesia may be useful in identifying patients who may have a greater chance of developing discontinuity.

On the Statistical Normality Rate of EEG Ambient Signal of Healthy Subjects and Its Dependence on Data-Observation Duration

Determination of whether or not the electroencephalography (EEG) ambient signal is Gaussian-distributed is important for a variety of engineering applications, such as cognitive studies and cortical source localization, as well as for a theoretical understanding of the brain’s physiology. The statistical normality of EEG ambient signals has variably been affirmed/negated in the research literature. Therefore, in light of the evolving applications of EEG, one prime objective of this work is to statistically characterize the baseline EEG signal obtained from healthy subjects to be used as a reference in future studies that involve EEG signals. In addition, this present work will critically examine the alleged normality trend by introducing more appropriately rigorous statistical techniques to reveal/characterize the statistical normality of EEG datasets. Then, this work will apply these statistical tools quantitatively to a dataset collected from healthy subjects using high-density EEG recordings with over an order-of-magnitude more electrodes compared to previously reported works. The analysis results show that the maximal data-observation duration is found to be at most 0.2 seconds for a normality-test positivity rate of 98%; for 95%, 90%, 85%, and 80%, the respective ceilings can relax, respectively, to 0.3, 1.0, 1.6, and 2.9 seconds.

Evaluation of nociception in unconscious critically ill patients using a multimodal approach

This prospective observational study included 80 adults (>18 years) patients admitted to the intensive care unit who were unconscious (Glasgow Coma Scale [GCS] score <9 with a motor response <5) and receiving mechanical ventilation. A tetanic stimulation was used to assess nociception; automated pupillometry (Algiscan, ID-MED, France) was used to compute the pupillary pain index score (PPI), with a PPI > 4 considered as nociception. Concomitantly, the number of skin conductance fluctuations (NSCF) per second, measured using a Skin Conductance Algesimeter (SCA, MEDSTORM Innovation AS, Norway; > 0.27 fluctuations/sec indicating nociception), and the instantaneous Analgesia Nociception Index (iANI, MDoloris Medical Systems, France; <50 indicating nociception) were collected.Tetanic stimulation resulted in a median pupillary dilation of 16 [6–25]% and a PPI of 5 [2–7]. According to the PPI assessment, 44 patients (55%) had nociception, whereas 23 (29%) and 18 (23%) showed nociception according to the algesimeter and iANI assessment, respectively. No significant changes in measured physiologic variables were observed after the tetanic stimulation. There were no correlations between PPI, post-stimulation iANI, and SCA-derived variables. There were no differences in PPI, iANI, and SCA variables in patients with low and normal baseline EEG power at baseline. PerspectivesDetection of nociception varies across different devices in unconscious critically ill patients. Further studies are required to understand which method to implement for analgesic administration in this patient population.

Baseline Electroencephalogram and Its Evolution after Activation of Dopaminergic System by Apomorphine in Middle-Aged 5XFAD Transgenic Mice, a Model of Alzheimer’s Disease

Aging and Alzheimer’s disease (AD) are characterized by common pathological features associated with alterations in neuronal connections. These inevitably affect the functioning of specific brain areas and their interrelations, leading to questions about neuronal plasticity and the compensatory mechanisms associated with dopaminergic (DA) mediation. In this study on twelve-month-old freely moving 5XFAD-transgenic mice, serving as a model of AD, and their wild-type (WT) littermates, we analyze electroencephalograms (EEGs) from the motor cortex (MC), putamen (Pt) and the DA-producing ventral tegmental area (VTA) and substantia nigra (SN). Baseline EEGs in the transgenic mice were characterized by delta 2 activity enhancements in VTA and alpha attenuation in VTA and SN. In contrast to WT mice, which lack differences in EEG from these brain areas, 5XFAD mice showed theta–alpha attenuation and delta 2 and beta 2 enhancements in EEG from both VTA and SN vs. MC. In 5XFAD mice, a DA mimetic, apomorphine, lowered (vs. saline) the theta oscillations in Pt, VTA and SN and enhanced alpha in MC, Pt, VTA and beta 1 in all brain areas. These results and those obtained earlier in younger (six-month-old) mice suggest that the age-related characteristics of cerebral adaptive mechanisms affected by AD might be associated with modification of dopaminergic mediation in the mechanisms of intracerebral dynamic interrelations between different brain areas.

Psychophysiological restorative potential in cancer patients by virtual reality (VR)-based perception of natural environment.

The positive significance of nature to human’ self-reported well-being has been widely confirmed, but less attention has been paid to the study of cancer patients, as well as the role of time on the restorative effects. Therefore, using virtual reality (VR) and the inclusion of patients with esophageal and gastrointestinal cancer as participants, this study conducted indoor experiments to explore patients’ psychophysiological recovery through the perception of five different environmental types with three to five interventions per week. There were 63 participants selected from the People’s Hospital in Shaanxi Province. Depending on their psychophysiological state, they would participate in three to five interventions in a week to compare the number of interventions needed to achieve maximum restoration. The five environmental types utilized varied in land cover, vegetation structure, and landscape characteristics, and were identified as blue space (BS), open green space (OGS), semi-open green space (SOS), closed green space (CGS), and gray space (GrS). Before and after viewing landscapes, the changes of psychophysiological indicators were measured to explore the influence of different environmental types on participants. The results showed that the participants preferred and received the highest perceived restorative potentials in BS and lastly, GrS. The green and blue spaces measurably increased positive emotions and perceived restoration while a decreasing negative emotions and the heart rate (HR) compared with the GrS. Participants had the highest level of relaxation while their eyes were closed in the EEG baseline stage. Moreover, participants received the most relaxation when they contacted with nature three times a week, which indicated that excessive natural participation may not be conducive to the sustained development of cancer patients’ psychophysiological health. Instead of field appreciation, VR could be utilized to increase the access of cancer patients to nature and then be used as an approach to landscape interaction.

Simultaneous measurement of DC-EEG and transcutaneous pCO2

Abstract DC potential shifts are the shifts observed in the EEG baseline which can last from seconds to minutes. The significance of these low-frequency components in healthy as well as pathological states of human physiology is getting more and more attention not only in scientific research but also in clinical applications. In this paper, we present our novel multimodal measurement setup for simultaneously investigating DC potential shifts in EEG (DC-EEG) and the changes in noninvasive transcutaneous pCO2 measurements. We present preliminary results of our measurements during hyperventilation and apnea, which are two commonly used activation methods for changes in pCO2.

SPECIAL ISSUE: Do Biofeedback, Neurofeedback, and Neuromeditation Have a Role in Psychedelic-Assisted Therapies?

SPECIAL ISSUE: Do Biofeedback, Neurofeedback, and Neuromeditation Have a Role in Psychedelic-Assisted Therapies?

Electroencephalogram microstates and functional connectivity of cybersickness.

Virtual reality (VR) is a rapidly developing technology that simulates the real world. However, for some cybersickness-susceptible people, VR still has an unanswered problem—cybersickness—which becomes the main obstacle for users and content makers. Sensory conflict theory is a widely accepted theory for cybersickness. It proposes that conflict between afferent signals and internal models can cause cybersickness. This study analyzes the brain states that determine cybersickness occurrence and related uncomfortable feelings. Furthermore, we use the electroencephalogram (EEG) microstates and functional connectivity approach based on the sensory conflict theory. The microstate approach is a time–space analysis method that allows signals to be divided into several temporarily stable states, simultaneously allowing for the exploration of short- and long-range signals. These temporal dynamics can show the disturbances in mental processes associated with neurological and psychiatric conditions of cybersickness. Furthermore, the functional connectivity approach gives us in-depth insight and relationships between the sources related to cybersickness. We recruited 40 males (24.1 ± 2.3 years), and they watched a VR video on a curved computer monitor for 10 min to experience cybersickness. We recorded the 5-min resting state EEG (baseline condition) and 10-min EEG while watching the VR video (task condition). Then, we performed a microstate analysis, focusing on two temporal parameters: mean duration and global explained variance (GEV). Finally, we obtained the functional connectivity data using eLoreta and lagged phase synchronization (LPS). We discovered five sets of microstates (A–E), including four widely reported canonical microstates (A–D), during baseline and task conditions. The average duration increased in microstates A and B, which is related to the visual and auditory networks. The GEV and duration decreased in microstate C, whereas those in microstate D increased. Microstate C is related to the default mode network (DMN) and D to the attention network. The temporal dynamics of the microstate parameters are from cybersickness disturbing the sensory, DMN, and attention networks. In the functional connectivity part, the LPS between the left and right parietal operculum (OP) significantly decreased (p < 0.05) compared with the baseline condition. Furthermore, the connectivity between the right OP and V5 significantly decreased (p < 0.05). These results also support the disturbance of the sensory network because a conflict between the visual (V5) and vestibular system (OP) causes cybersickness. Changes in the microstates and functional connectivity support the sensory conflict theory. These results may provide additional information in understanding brain dynamics during cybersickness.

Quantitative electroencephalographic analysis as a potential biomarker of response to treatment with cannabidiol

PurposePharmaceutical grade cannabidiol (CBD) is one of the newest anti-seizure medications for refractory epilepsy, and the effects of CBD on EEG have not been fully described. MethodsPatients enrolled in a CBD expanded access study had EEGs prior to and 12 weeks after initiation of CBD treatment for their refractory epilepsy. In addition to evaluating the clinical EEG reports, a nonbiased quantitative EEG (qEEG) analysis of background EEG was performed to determine whether consistent changes occur in the EEG in response to administration of CBD. ResultsNo significant qualitative changes were seen, nor changes in quantitative markers of EEG amplitude (RMS amplitude, standard deviation of the amplitude, skewness, or kurtosis), frequency (relative delta, theta, or alpha power), Spearman correlation, or coherence between brain regions. However, relative beta power and 1/f slope, a measure of signal noise increased with the addition of CBD. When patients were separated into responders and nonresponders based on seizure reduction with CBD, responders also had decreased Spearman correlation between the frontopolar and occipital regions after addition of CBD, suggesting that responders may have quantitatively improved EEG background organization after CBD initiation. The differences in beta and 1/f slope were also seen more robustly in CBD responders compared with nonresponders after CBD initiation. These differences disappeared when analyzing only patients not taking benzodiazepines, suggesting that the effect of CBD on seizures was related to the ability of the brain to further increase beta in response to CBD in patients already taking benzodiazepines.We noted that even before initiation of CBD, 1/f slope was also significantly different in responders compared to nonresponders. Therefore, to explore the baseline EEG in responders and nonresponders, we utilized a variable selection procedure to identify baseline EEG features that could predict whether a patient’s seizures would improve with CBD. In the optimal multivariable logistic model, baseline coherence, Spearman correlation, and patient sex jointly predicted whether a patient in this cohort would respond to CBD (defined as a seizure reduction of 40% or greater) with 74% accuracy. This model performed less well on a data set of reduced duration and variability, highlighting the importance of real-world testing of any clinically relevant model. ConclusionThese results suggest that there are subtle changes in certain metrics detected by qEEG even at baseline that may not be perceived during qualitative EEG analysis and that could be used in the future as a biomarker to predict a patient’s clinical response to CBD administration. Development of such a predictive EEG biomarker, especially before the initiation of a medication trial, could reduce unnecessary ASM exposure and improve outcomes for patients with epilepsy facing new medication selection.

Evaluation of EEG biomarkers of Comprehensive Behavioral Intervention for Tics in children with Tourette syndrome

ObjectiveComprehensive Behavioral Intervention for Tics (CBIT) is a first-line treatment of Tourette syndrome (TS). However, the brain mechanisms involved in CBIT are poorly understood. Enhanced frontomesial EEG coherence during a Go/NoGo task has been suggested as a mechanism involved in voluntary tic control. In the current study, we conducted a randomized controlled trial to assess whether EEG coherence during a Go/NoGo task was associated with CBIT outcome. MethodsThirty-two children with TS were randomly assigned to CBIT or to treatment-as-usual (TAU). Treatment outcome was assessed by a blinded evaluator with the Yale Global Tic Severity Scale (YGTSS) and the Clinical Global Impression – Improvement Scale (CGI-I). EEG was recorded during a Go/NoGo task at baseline and endpoint. EEG coherence was computed in the alpha frequency band between a priori selected channel pairs spanning the frontal and motor areas. ResultsTic severity decreased significantly in the CBIT group. However, CBIT did not impact EEG coherence and baseline EEG coherence did not predict treatment outcome. ConclusionsAlthough CBIT was superior to TAU on blinded clinical outcomes, EEG coherence during the Go/NoGo task was not associated with change in tic severity. SignificanceThe brain processes involved in the inhibition of motor responses do not appear to be involved in CBIT.

Cognitive Decline Risk Stratification in People with Late-Onset Epilepsy of Unknown Etiology: An Electroencephalographic Connectivity and Graph Theory Pilot Study.

Although people with late onset epilepsy of unknown etiology (LOEU) are at higher risk of cognitive decline compared to the general population, we still lack affordable tools to predict and stratify their risk of dementia. This pilot-study investigates the potential application of electroencephalography (EEG) network small-world (SW) properties in predicting cognitive decline among patients with LOEU. People diagnosed with LOEU and normal cognitive examination at the time of epilepsy diagnosis were included. Cerebrospinal fluid biomarkers, brain imaging, and neuropsychological assessment were performed at the time of epilepsy diagnosis. Baseline EEG was analyzed for SW properties. Patients were followed-up over time with neuropsychological testing to define the trajectory of cognitive decline. Over 5.1 years of follow-up, among 24 patients diagnosed with LOEU, 62.5% were female, mean age was 65.3 years, thirteen developed mild cognitive impairment (MCI), and four developed dementia. Patients with LOEU developing MCI had lower values of SW coefficients in the delta (p = 0.03) band and higher SW values in the alpha frequency bands (p = 0.02) compared to patients having normal cognition at last follow-up. The two separate ANOVAs, for low and alpha bands, confirmed an interaction between SW and cognitive decline at follow-up. A similar gradient was confirmed for patients developing dementia compared to those with normal cognitive function as well as to those developing MCI. Baseline EEG analysis through SW is worth investigating as an affordable, widely available tool to stratify LOEU patients for their risk of cognitive decline.

An investigation of the multi-dimensional (1D vs. 2D vs. 3D) analyses of EEG signals using traditional methods and deep learning-based methods

Electroencephalographic (EEG) signals are electrical signals generated in the brain due to cognitive activities. They are non-invasive and are widely used to assess neurodegenerative conditions, mental load, and sleep patterns. In this work, we explore the utility of representing the inherently single dimensional time-series in different dimensions such as 1D-feature vector, 2D-feature maps, and 3D-videos. The proposed methodology is applied to four diverse datasets: 1) EEG baseline, 2) mental arithmetic, 3) Parkinson’s disease, and 4) emotion dataset. For a 1D analysis, popular 1D features hand-crafted from the time-series are utilized for classification. This performance is compared against the data-driven approach of using raw time-series as the input to the deep learning framework. To assess the efficacy of 2D representation, 2D feature maps that utilize a combination of the Feature Pyramid Network (FPN) and Atrous Spatial Pyramid Pooling (ASPP) is proposed. This is compared against an approach utilizing a composite feature set consisting of 2D feature maps and 1D features. However, these approaches do not exploit spatial, spectral, and temporal characteristics simultaneously. To address this, 3D EEG videos are created by stacking spectral feature maps obtained from each sub-band per time frame in a temporal domain. The EEG videos are the input to a combination of the Convolution Neural Network (CNN) and Long–Short Term Memory (LSTM) for classification. Performances obtained using the proposed methodologies have surpassed the state-of-the-art for three of the classification scenarios considered in this work, namely, EEG baselines, mental arithmetic, and Parkinson’s disease. The video analysis resulted in 92.5% and 98.81% peak mean accuracies for the EEG baseline and EEG mental arithmetic, respectively. On the other hand, for distinguishing Parkinson’s disease from controls, a peak mean accuracy of 88.51% is achieved using traditional methods on 1D feature vectors. This illustrates that 3D and 2D feature representations are effective for those EEG data where topographical changes in brain activation regions are observed. However, in scenarios where topographical changes are not consistent across subjects of the same class, these methodologies fail. On the other hand, the 1D analysis proves to be significantly effective in the case involving changes in the overall activation of the brain due to varying degrees of deterioration.

A clinical trial of a patient-customized virtual reality intervention for tinnitus

Virtual reality (VR) has recently been used as a clinical treatment because it can efficiently simulate situations that are difficult to control in real-world settings. In our study, we assessed the potential of VR in patients with chronic subjective tinnitus. An evaluation of its clinical benefits was performed based on analyses of patient electroencephalograms (EEGs) and by questionnaire responses after 6–8 weeks of patient involvement in our VR-based alleviation program. Clinical trials were performed at a tertiary academic hospital. Nineteen patients (aged 33–64 years) who visited our hospital with chronic subjective tinnitus over 3 months were enrolled in the study. The intervention consisted of trashing the tinnitus avatar in VR. We expected that the patients would have the subjective feeling of controlling tinnitus through our intervention. The VR environment comprised four different sessions in four different settings: a bedroom, a living room, a restaurant, and a city street. We analyzed changes in the source activities of the prefrontal regions related to tinnitus in these patients using standardized low-resolution brain electromagnetic tomography. The Tinnitus Handicap Inventory (THI), the total score (from 50.11 to 44.21, P = 0.046) and the grade (from 3.16 to 2.79, P = 0.035) were significantly improved after the VR-based tinnitus treatment program (P < 0.05). The Pittsburgh Sleep Quality Index also showed improved outcomes (P = 0.025). On the other hand, a Tinnitus Handicap Questionnaire, Quality of Life Assessment (WHO-QOL), Hospital Anxiety and Depression Scale, Profile of Mood States revealed no significant change after the intervention. The baseline EEG data showed that brain activity in the orbitofrontal cortex significantly increased in the alpha and theta frequency bands. Furthermore, patients who showed a THI score improvement after the intervention showed specific increases in brain activity for the theta and high beta bands in the orbitofrontal cortex. Our findings suggest that the virtual reality-based program, as in parts of cognitive behavioral treatment, may help to alleviate tinnitus-related distress in patients with chronic subjective tinnitus.

The Role of Serial Follow-up and Sleep Deprivation Methods in Improving Electroencephalography Diagnostic Yield in a Cohort of Omanis Aged 13 Years and Above: A Clinical Audit Study

ABSTRACT The aim of this audit study was to establish the utility of follow-up and sleep-deprived electroencephalography testing to improve the detection of interictal abnormalities in a tertiary referral center in Oman. As part of our ongoing auditing process, a total of 3010 EEGs were included in this study. All EEGs were routinely performed for Omanis aged 13 years and above, who were referred for possible diagnosis of seizure disorders. Each EEG was performed over an average period of 20–30 minutes. Of the 3010 EEGs, there were 553 follow-up and sleep-deprived EEGs, including initial baseline EEG studies which were analyzed for this study. The total progressive yield of serial follow-up EEGs to detect overall EEG changes was 53.5%, distributed as 8.8%, 11.4%, 0%, and 33.3% for the second, third, fourth, and fifth serial EEG studies, respectively. For the sleep deprivation EEG group, the yield was 6.5% for detecting overall EEG changes compared to the initial EEG studies. A limitation in this study was the small sample size in the subsequent follow-up and sleep deprivation EEGs. In conclusion, we found a minimal contribution of serial follow-up and sleep deprivation methods in improving the EEG abnormality detection in our study. National guidelines and an increase in awareness among physicians are required to increase the benefit of these well-established, yet not optimally utilized EEG methods.

Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study.

Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide—a chloride-regulating agent—improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8–21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC.Clinical Trial RegistrationEU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

Electrographic Features of Epilepsy With Eyelid Myoclonia With Photoparoxysmal Responses.

Epilepsy with eyelid myoclonia (EMA) is characterized by eyelid myoclonia, eyelid closure sensitivity, and photosensitivity. EEG may manifest with frontal-predominant (FPEDs) or occipital-predominant epileptiform discharges (OPEDs). Data on clinical and electrographic features of these two subtypes are lacking. The purpose of our research was to look at baseline electroclinical features of EMA subtypes and to study electrographic findings of patients with EMA during intermittent photic stimulation (IPS). We retrospectively identified all patients who had photoparoxysmal responses on EEGs performed at Cleveland clinic between January 01, 2012, and December 31, 2019. Patients who met diagnostic criteria for EMA were studied further. Of the 249 patients with photoparoxysmal responses, 70 (28.1%) had EMA (62 [88.6%] female; the mean age of epilepsy onset: 7.0 ± 7.9 years). Patients with EMA had either FPEDs or OPEDs. Eleven patients with EMA (15.7%) had seizures (4 absence, 5 myoclonic and 2 bilateral tonic-clonic) during IPS. Patients with OPEDs were more likely to have drug-resistant epilepsy; occipital focal IEDs and other focal IEDs (other than frontal/occipital) on baseline EEG; and generalized IEDs with occipital predominance, generalized IEDs with no predominance, or focal IEDs during IPS. Predictors of seizure occurrence during photic stimulation included the presence of focal occipital IEDs on baseline EEG, generalized IEDs with frontal predominance during IPS, and photoparoxysmal response outlasting the stimulus. Our study provides evidence that EMA has two distinct subtypes, which differ in clinical characteristics, baseline EEG, and EEG during photic stimulation. We highlight diagnostic and prognostic implications of these findings. Our study also details EEG characteristics of patients with EMA during IPS.

Human ARHGEF9 intellectual disability syndrome is phenocopied by a mutation that disrupts collybistin binding to the GABAA receptor α2 subunit

Intellectual disability (ID) is a common neurodevelopmental disorder that can arise from genetic mutations ranging from trisomy to single nucleotide polymorphism. Mutations in a growing number of single genes have been identified as causative in ID, including ARHGEF9. Evaluation of 41 ARHGEF9 patient reports shows ubiquitous inclusion of ID, along with other frequently reported symptoms of epilepsy, abnormal baseline EEG activity, behavioral symptoms, and sleep disturbances. ARHGEF9 codes for the Cdc42 Guanine Nucleotide Exchange Factor 9 collybistin (Cb), a known regulator of inhibitory synapse function via direct interaction with the adhesion molecule neuroligin-2 and the α2 subunit of GABAA receptors. We mutate the Cb binding motif within the large intracellular loop of α2 replacing it with the binding motif for gephyrin from the α1 subunit (Gabra2-1). The Gabra2-1 mutation causes a strong downregulation of Cb expression, particularly at cholecystokinin basket cell inhibitory synapses. Gabra2-1 mice have deficits in working and recognition memory, as well as hyperactivity, anxiety, and reduced social preference, recapitulating the frequently reported features of ARHGEF9 patients. Gabra2-1 mice also have spontaneous seizures during postnatal development which can lead to mortality, and baseline abnormalities in low-frequency wavelengths of the EEG. EEG abnormalities are vigilance state-specific and manifest as sleep disturbance including increased time in wake and a loss of free-running rhythmicity in the absence of light as zeitgeber. Gabra2-1 mice phenocopy multiple features of human ARHGEF9 mutation, and reveal α2 subunit-containing GABAA receptors as a druggable target for treatment of this complex ID syndrome.

Abstract WMP46: Quantitative Electroencephalogram To Assess Neurovascular Coupling Post Endovascular Thrombectomy

Introduction: Persistent neurovascular uncoupling may be associated with poor outcome in patients with ischemic stroke after successful recanalization. Quantitative electroencephalography (EEG) can be used to assess neuronal function. We assessed relation between degree of recanalization post-endovascular thrombectomy (EVT), quantitative EEG based parameters and severity of neurological deficits. Methods: Patients with acute ischemic stroke with large vessel occlusion in anterior circulation were enrolled. EEG was recorded using a modified Muse headband (InteraXon) before, immediately after and at 24 hours post-EVT. Pairwise-derived brain symmetry index (pdBSI) and delta-to-alpha ratio (DAR) were computed using Fitting Oscillation &amp; one-over F (FOOOF) MATLAB wrapper. Results: A total of six patients with mean age 73.6±11.6 years and baseline median (IQR) NIHSS of 13.5 (11-15) were included. Expanded thrombolysis in cerebral infarction (eTICI) scores were 2b67 in one, 2c in two and 3 in three cases. Baseline EEG was recorded at 75 minutes (60-100) from arrival, second at 255 minutes (90-420) after recanalization and third at 28.5 hours (27-31) after recanalization. Four patients with improvement in NIHSS of &gt;10 had 46.6±31.7% change in pdBSI at 24 h. One patient with NIHSS &lt;10 improvement had -25.3% change in pdBSI. One patient with low baseline NIHSS (9) had 90.9% change in pdBSI. There was linear correlation between baseline infarct volume on perfusion studies and change in pdBSI at 24 h (r=0.86, p&lt;0.0001, Figure 1). There was no difference in the DAR in the ipsilateral hemisphere pre-EVT, immediately post-EVT (p=0.6) and 24 h post-EVT (p=0.8). Conclusion: Preliminary data suggest return of neuronal function and clinical recovery may lag after successful recanalization, due to persistent neurovascular uncoupling. Higher baseline infarct volume may predict lower pdBSI change. Portable EEG may help characterise this novel treatment target.