Baseline EEG Research Articles

Eeg coherence in depressive female adolescents with different types of auto-aggressive behavior

IntroductionIntracortical interactions reflected in EEG coherence (Coh) play an important role in the control of behavior in both norm and mental disorders. EEG Coh in depression is less than in the norm. Non-suicidal self-injuries (NSSI) are widespread in adolescents and represent a significant risk factor for consequent suicidal attempts (SA).ObjectivesThe aim of the study was to identify the differences in EEG coherence between depressive female adolescents who have NSSI or NSSI and SA in their history compared with healthy controls.Methods75 depressive female adolescents (16–25 years old) were enrolled in the study and divided into two subgroups: NSSI (n=38) and NSSI+SA (n=37). The control group included 20 healthy subjects (HC) matched by age and gender. Baseline EEG was recorded, and EEG coherence was analyzed in 8 narrow frequency sub-bands.ResultsIn the NSSI subgroup, the number of “high coherent connections” (pairs of EEG leads with Coh>0.80) was the lowest in comparison with the NSSI+SA subgroup (intermediate values) and HC (the highest values) in theta-1 (4-6 Hz), theta-2 (6-8 Hz), alpha-1 (8-9 Hz) and alpha-2 (9-11 Hz) EEG frequency sub-bands, especially in frontal-central-parietal regions.ConclusionsThe lowest EEG coherence in the NSSI subgroup suggests that this subgroup is “more depressive” than the NSSI+SA subgroup, while the NSSI+SA subgroup is “more normal” but has increased suicidal risk. The results obtained suggested the use of EEG Coh data to clarify the degree of suicidal risk in depressive adolescents with different types of auto-aggressive behavior. The study supported by RBRF grant No.20-013-00129а.DisclosureNo significant relationships.

EEG features in depressive female adolescents with suicidal and non-suicidal auto-aggressive behavior

IntroductionIn adolescents, both non-suicidal self-injuries (NSSI) and previous suicidal attempts (SA) represent significant risk factors for future suicide. Thus, the search for EEG markers of these forms of auto-aggressive behavior seem to be an actual task.ObjectivesThe aim of the study was to reveal the differences of baseline EEG features in depressive female adolescents with auto-aggressive behavior such as NSSI or SA.MethodsThe study included 45 depressive female in-patients aged 16–25 years. 21 of them showed only NSSI (NSSI subgroup), 24 patients had a history of SA (SA subgroup). Subgroups did not differ in clinical and social-demographic parameters. Baseline EEG spectral power (SP) and its asymmetry were measured.ResultsSA subgroup had higher parietal-occipital alpha-2 (9-11 Hz) SP than NSSI subgroup. Its focus was located in the right hemisphere, and alpha-3 (11-13 Hz) SP was higher than alpha-1 (8-9 Hz). In contrary, in NSSI subgroup alpha-1 SP was higher than alpha-3; and foci of alpha-2 and alpha-3 SP were localized in the left hemisphere.ConclusionsSpatial distribution and the ratio of EEG alpha frequency components SP in the SA subgroup reflect greater activation of brain cortex, especially of the left hemisphere that is more typical for EEG of individuals with increased risk of suicide. In NSSI subgroup, the right hemisphere is relatively more activated that is more typical for EEG in depression without SA. The study supported by RBRF grant No.20-013-00129a.DisclosureNo significant relationships.

Associations between pre-stimulus alpha power, hearing level and performance in a digits-in-noise task

Objective Baseline electroencephalography (EEG) alpha power, i.e. that measured prior to stimulus presentation, is a potential objective predictor of task performance. Here we assessed the predictive power of EEG alpha on performance accuracy in a digits-in-noise recognition task, factoring in hearing thresholds and age. Design EEG alpha power, recorded while participants listened to target digits presented in a noise background, was analysed during two different baseline periods: i) a pre-stimulus baseline (pre-STIM) free from any acoustic stimulus, and ii) a pre-target baseline (pre-TARG) recorded in background noise only. Study sample Eighty-five participants with either normal hearing or aided hearing impairment (age range: 55–85 years old, 42 male). Results Hierarchical multiple regression analyses indicated that i) lower hearing thresholds and, to a lesser extent, higher pre-STIM alpha power were associated with improved performance accuracy ii) alpha power in pre-STIM and pre-TARG were highly correlated across individuals but pre-TARG alpha power was not a significant predictor of performance accuracy. Conclusion Investigations of baseline EEG alpha power as a predictor of speech-in-noise performance accuracy should control for associations between hearing thresholds and measures of EEG baseline periods.

Alterations in coordinated EEG activity precede the development of seizures in comatose children

ObjectiveWe aimed to test the hypothesis that computational features of the first several minutes of EEG recording can be used to estimate the risk for development of acute seizures in comatose critically-ill children. MethodsIn a prospective cohort of 118 comatose children, we computed features of the first five minutes of artifact-free EEG recording (spectral power, inter-regional synchronization and cross-frequency coupling) and tested if these features could help identify the 25 children who went on to develop acute symptomatic seizures during the subsequent 48 hours of cEEG monitoring. ResultsChildren who developed acute seizures demonstrated higher average spectral power, particularly in the theta frequency range, and distinct patterns of inter-regional connectivity, characterized by greater connectivity at delta and theta frequencies, but weaker connectivity at beta and low gamma frequencies. Subgroup analyses among the 97 children with the same baseline EEG background pattern (generalized slowing) yielded qualitatively and quantitatively similar results. ConclusionsThese computational features could be applied to baseline EEG recordings to identify critically-ill children at high risk for acute symptomatic seizures. SignificanceIf confirmed in independent prospective cohorts, these features would merit incorporation into a decision support system in order to optimize diagnostic and therapeutic management of seizures among comatose children.

Ten year cumulative incidence of dementia after late onset epilepsy of unknown etiology

Recent epidemiological studies suggest late life onset epilepsy of unknown etiology (LOEU) is a risk factor for future dementia. These studies rely on inclusion and exclusion of multiple diagnostic codes rather than structured data and neuroimaging findings, and thus challenging to interpret clinically. We assessed the cumulative incidence of dementia in patients with LOEU diagnosed through admission data and neuroimaging over a 10-year follow-up and compared baseline characteristics that distinguish group level incident dementia. We screened our hospital records for patients aged 55–69 with new epilepsy, admitted between 2000 and 2008, and excluded patients diagnosed with epilepsy from an underlying cause on medical records or neuroimaging. We used retrospective hospital data to follow patients for incident dementia or mortality at 10 years and compared baseline (demographics, depression or anxiety, vascular risk factors, results of electroencephalogram (EEG) studies, antidepressant use and type of ant seizure medication) and follow up (seizure recurrence, incident cerebrovascular disease) characteristics for patients with and without incident dementia.Fifty-four LOEU cases were screened, age at first seizure was 61 ± 5. The 10-year cumulative incidence of dementia was 22.20% (95% Confidence Interval 22.08–23.10%) and time to dementia diagnosis was 5.4 ± 3.9 years. Patients with incident dementia were more likely to be women (83% vs 38%, p = 0.002), have interictal epileptic form discharges (IED) on baseline EEG (70% vs 29%, p = 0.011) and depression or anxiety (50% vs 18%, p = 0.026). No differences were found in other baseline or follow up characteristics. Our results support recent findings of dementia incidence in LOEU. Prospective studies on LOEU should evaluate phenotypic determinants of individuals with late life epilepsy and the rate of progression to dementia.

The PDE10A Inhibitor TAK-063 Reverses Sound-Evoked EEG Abnormalities in a Mouse Model of Fragile X Syndrome.

Fragile X syndrome (FXS) is a genetic neurodevelopmental syndrome characterized by increased anxiety, repetitive behaviors, social communication deficits, delayed language development, and abnormal sensory processing. Recently, we have identified electroencephalographic (EEG) biomarkers that are conserved between the mouse model of FXS (Fmr1 KO mice) and humans with FXS. In this study, we test a specific candidate mechanism for engagement of multielectrode array (MEA) EEG biomarkers in the FXS mouse model. We administered TAK-063, a potent, selective, and orally active phosphodiesterase 10A (PDE10A) inhibitor, to Fmr1 KO mice, and examined its effects on MEA EEG biomarkers. We demonstrate significant dose-related amelioration of inter-trial phase coherence (ITPC) to temporally modulated auditory stimuli by TAK-063 in Fmr1 KO mice. Our data suggest that TAK-063 improves cortical auditory stimulus processing in Fmr1 KO mice, without significantly depressing baseline EEG power or causing any noticeable sedation or behavioral side effects. Thus, the PDE10A inhibitor TAK-063 has salutary effects on normalizing EEG biomarkers in a mouse model of FXS and should be pursued in further translational treatment development.

Seizure phenotype in CLN3 disease and its relation to other neurologic outcome measures.

CLN3 disease is a pediatric neurodegenerative condition wherein seizures are common. The most common disease-causing variant is an ~1-kb deletion in CLN3. We investigated seizure phenotype in relation to genotype and to adaptive behavior, MR spectroscopy and CSF biochemical markers in a CLN3 cohort. We performed seizure phenotyping using clinical history, EEG, and the Unified Batten Disease Rating Scale (UBDRS) seizure score. We assessed correlations of seizure severity with disease severity (UBDRS capability), adaptive behavior composite score (ABC; Vineland-3), glutamate+glutamine+GABA and N-acetylaspartate+N-acetylaspartyl glutamate (MR spectroscopy), and CSF neurofilament light chain (NEFL) levels. In 20 participants, median age was 10.7 years (IQR=7.8). Eighteen completed baseline EEG; 12 had a 1-year follow-up. Seizures were reported in 14 (8 1-kb deletion homozygotes), with median age at onset of 10.0 (IQR=6.8). Epileptiform discharges were noted in 15 (9 homozygotes). Bilateral tonic clonic (n=11) and nonmotor seizures (n=7) were most common. UBDRS seizure score correlated with age (rp=0.50; [0.08,0.77]; P=.02), UBDRS capability (rp=-0.57; [-0.81,-0.17]; P=.009) and ABC (rp=-0.66; [-0.85,-0.31]; P=.001) scores, glutamate+glutamine+GABA (rp=-0.54; [-0.80,-0.11]; P=.02) and N-acetylaspartate+N-acetylaspartyl glutamate (rp=-0.54; [-0.80,-0.11]; P=.02), and CSF NEFL (rp=0.65; [0.29,0.85]; P=.002) levels. After controlling for age, correlations with ABC and CSF NEFL remained significant. In our CLN3 cohort, seizures and epileptiform discharges were frequent and often started by age 10 years without significant difference between genotypes. ABC and CSF NEFL correlate with UBDRS seizure score, reflecting the role of seizures in the neurodegenerative process. Longitudinal evaluations in a larger cohort are needed to confirm these findings.

Abnormally Large Baseline P300 Amplitude Is Associated With Conversion to Psychosis in Clinical High Risk Individuals With a History of Autism: A Pilot Study.

Psychosis rates in autism spectrum disorder (ASD) are 5–35% higher than in the general population. The overlap in sensory and attentional processing abnormalities highlights the possibility of related neurobiological substrates. Previous research has shown that several electroencephalography (EEG)-derived event-related potential (ERP) components that are abnormal in schizophrenia, including P300, are also abnormal in individuals at Clinical High Risk (CHR) for psychosis and predict conversion to psychosis. Yet, it is unclear whether P300 is similarly sensitive to psychosis risk in help-seeking CHR individuals with ASD history. In this exploratory study, we leveraged data from the North American Prodrome Longitudinal Study (NAPLS2) to probe for the first time EEG markers of longitudinal psychosis profiles in ASD. Specifically, we investigated the P300 ERP component and its sensitivity to psychosis conversion across CHR groups with (ASD+) and without (ASD–) comorbid ASD. Baseline EEG data were analyzed from 304 CHR patients (14 ASD+; 290 ASD–) from the NAPLS2 cohort who were followed longitudinally over two years. We examined P300 amplitude to infrequent Target (10%; P3b) and Novel distractor (10%; P3a) stimuli from visual and auditory oddball tasks. Whereas P300 amplitude attenuation is typically characteristic of CHR and predictive of conversion to psychosis in non-ASD sample, in our sample, history of ASD moderated this relationship such that, in CHR/ASD+ individuals, enhanced – rather than attenuated - visual P300 (regardless of stimulus type) was associated with psychosis conversion. This pattern was also seen for auditory P3b amplitude to Target stimuli. Though drawn from a small sample of CHR individuals with ASD, these preliminary results point to a paradoxical effect, wherein those with both CHR and ASD history who go on to develop psychosis have a unique pattern of enhanced neural response during attention orienting to both visual and target stimuli. Such a pattern stands out from the usual finding of P300 amplitude reductions predicting psychosis in non-ASD CHR populations and warrants follow up in larger scale, targeted, longitudinal studies of those with ASD at clinical high risk for psychosis.

The electrophysiological footprint of CACNA1A disorders

ObjectivesCACNA1A variants underlie three neurological disorders: familial hemiplegic migraine type 1 (FHM1), episodic ataxia type 2 (EA2) and spinocerebellar ataxia type 6 (SCA6). EEG is applied to study their episodic manifestations, but findings in the intervals did not gain attention up to date.MethodsWe analyzed repeated EEG recordings performed between 1994 and 2019 in a large cohort of genetically confirmed CACNA1A patients. EEG findings were compared with those of CACNA1A-negative phenocopies. A review of the related literature was performed.Results85 EEG recordings from 38 patients (19 EA2, 14 FHM1, 5 SCA6) were analyzed. Baseline EEG was abnormal in 55% of cases (12 EA2, 9 FHM1). The most common finding was a lateralized intermittent slowing, mainly affecting the temporal region. Slowing was more pronounced after a recent attack but was consistently detected in the majority of patients also during the follow-up. Interictal epileptic discharges (IEDs) were detected in eight patients (7 EA2,1 FHM1). EEG abnormalities and especially IEDs were significantly associated with younger age at examination (16 ± 9 vs 43 ± 21 years in those without epileptic changes, p = 0.003) and with earlier onset of disease (1 (1–2) vs 12 (5–45) years, p = 0.0009). EEG findings in CACNA1A-negative phenocopies (n = 15) were largely unremarkable (p = 0.03 in the comparison with CACNA1A patients).ConclusionsEEG abnormalities between attacks are highly prevalent in episodic CACNA1A disorders and especially associated with younger age at examination and earlier disease onset. Our findings underpin an age-dependent effect of CACNA1A variants, with a more severe impairment when P/Q channel dysfunction manifests early in life.

Cortical and Striatal Electroencephalograms and Apomorphine Effects in the FUS Mouse Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of motor neurons resulting in muscle atrophy. In contrast to the lower motor neurons, the role of upper (cortical) neurons in ALS is yet unclear. Maturation of locomotor networks is supported by dopaminergic (DA) projections from substantia nigra to the spinal cord and striatum. To examine the contribution of DA mediation in the striatum-cortex networks in ALS progression. We studied electroencephalogram (EEG) from striatal putamen (Pt) and primary motor cortex (M1) in ΔFUS(1-359)-transgenic (Tg) mice, a model of ALS. EEG from M1 and Pt were recorded in freely moving young (2-month-old) and older (5-month-old) Tg and non-transgenic (nTg) mice. EEG spectra were analyzed for 30 min before and for 60 min after systemic injection of a DA mimetic, apomorphine (APO), and saline. In young Tg versus nTg mice, baseline EEG spectra in M1 were comparable, whereas in Pt, beta activity in Tg mice was enhanced. In older Tg versus nTg mice, beta dominated in EEG from both M1 and Pt, whereas theta and delta 2 activities were reduced. In younger Tg versus nTg mice, APO increased theta and decreased beta 2 predominantly in M1. In older mice, APO effects in these frequency bands were inversed and accompanied by enhanced delta 2 and attenuated alpha in Tg versus nTg mice. We suggest that revealed EEG modifications in ΔFUS(1-359)-transgenic mice are associated with early alterations in the striatum-cortex interrelations and DA transmission followed by adaptive intracerebral transformations.

Differential Effects of Up- and Down-Regulation of SMR Coherence on EEG Activity and Memory Performance: A Neurofeedback Training Study.

Modulating connectivity measures in EEG-based neurofeedback studies is assumed to be a promising therapeutic and training tool. However, little is known so far about its effects and trainability. In the present study, we investigated the effects of up- and down-regulating SMR (12–15 Hz) coherence by means of neurofeedback training on EEG activity and memory functions. Twenty adults performed 10 neurofeedback training sessions in which half of them tried to increase EEG coherence between Cz and CPz in the SMR frequency range, while the other half tried to down-regulate coherence. Up-regulation of SMR coherence led to between- and within-session changes in EEG coherence. SMR power increased across neurofeedback training sessions but not within training sessions. Cross-over training effects on baseline EEG measures were also observed in this group. Up-regulation of SMR coherence was also associated with improvements in memory functions when comparing pre- and post-test results. Participants were not able to down-regulate SMR coherence. This group did not show any changes in baseline EEG measures or memory functions comparing pre- and post-test. Our results provide insights in the trainability and effects of connectivity-based neurofeedback training and indications for its practical application.

The identification of mild cognitive impairment in Parkinson’s disease using EEG and machine learning

AbstractBackgroundElectroencephalography (EEG) is an inexpensive, non‐invasive and faster method to assess cognition in aging clinical groups. In this study, we are investigating the feasibility of using a ‘dry‐EEG’ mobile headset to assess cognitive impairment in Parkinson’s disease (PD) over a 12‐month period. Cognitive impairment is prevalent in PD with approximately 75% of patients developing dementia within 10 years (Aarsland and Kurz, 2010). The presence of mild cognitive impairment (PD‐MCI) has been associated with increased dementia risk (Pederson et al. 2013). Very little is known about the EEG correlates of PD‐MCI, however EEG has previously been used to predict outcomes in MCI associated with Alzheimer’s disease.Method50 Parkinson’s disease patients and 50 age and sex‐matched controls have completed a battery of baseline neuropsychological and EEG tasks. These tasks measured attention, language, memory, visuospatial and executive function domains. Resting state EEG was also recorded. Event‐related potential components and spectral analyses on the delta, theta and alpha oscillatory bands were computed. Differences between groups were assessed using randomisation tests with FDR‐corrected pairwise comparisons. Random forest, k‐nearest neighbours, support‐vector machine and logistic regression machine learning algorithms were also applied to these data. An identical 12‐month follow‐up assessment will be conducted.ResultFindings from the baseline assessments are presented. 52% of the Parkinson’s disease cohort fulfilled the criteria for MCI. There was no difference in age, education or pre‐morbid IQ between groups. Machine learning classifiers derived from EEG and neuropsychological test metrics discriminated between PD‐MCI, PD normal cognition (PD‐NC) and healthy controls with over 80% accuracy.ConclusionCognitive impairment is prevalent in PD. Our findings show that it is feasible to use dry‐EEG to profile cognition in PD and can differentially discriminate between cognitively normal and cognitively impaired PD patients at an early stage. The features selected are in agreement with the dual syndrome hypothesis of cognition (Kehagia et al., 2013) and those identified in a 10 year follow‐up study (Williams‐Grey et al., 2013). The stability of these features and their ability to predict cognitive status at 12 months will be investigated at a follow‐up assessment.

EEG education in neurology residency: background knowledge and focal challenges.

To assess the baseline EEG knowledge among adult neurology residents at our institution and their perspectives on EEG learning experience during residency. We evaluated baseline EEG knowledge and resident perception of EEG education utilizing an EEG quiz and an online EEG survey, respectively. The EEG quiz was divided in two parts, composed of normal (n=27) and abnormal (n=10) EEG examples. The EEG survey focused on the importance of EEG, EEG milestones and EEG education. Twenty-one residents completed the EEG quiz; all 21 completed the normal EEG part whereas 19 of these 21 completed the abnormal EEG part. The overall score (mean±SEM) was 42±4.5% for the normal EEG part and 44±5.5% for the abnormal EEG part. The EEG survey was completed by 28 residents. Forty-three percent of the respondents reported not being able to read EEGs even with supervision. The most commonly reported education barriers were insufficient exposure, insufficient responsibility to read EEGs, and inability to link EEG learning to direct patient care. On average, adult neurology residents were able to correctly identify less than half of normal and abnormal EEG findings. Almost half of residents reported not being able to read EEGs even with supervision.

Virtual reality–based mindfulness training, sensory activation and mental assessment in dementia care

AbstractBackgroundRecent studies underline the importance of cognitive reserve, which is supported by stress reduction, pleasure experience and meditation, for mental health. Mindfulness training is successfully applied to dementia and indicate a lasting positive effect on cognitive reserve, well‐being and motivation. The research project OpenSense investigated the potential of VR‐based intervention and assessment for dementia care in a proof‐of concept study. The VR‐based intervention was developed to foster mindfulness and sensory activation.MethodVR‐based intervention was applied in persons with dementia (PwD) with Alzheimer’s dementia (AD; n=12, age M=85.0 years, MMSE M=21.5) and healthy controls (n=12, age M=75.1 years, MMSE M=30) using 30 minutes of panoramic video‐based multi‐sensory experiences presenting stimuli that empower relaxation (body‐scanning, beach, forest) and activation (bakery, orchestra). EEG‐based alpha‐band signals (8‐12 Hz) associated with relaxation and inhibitory control were recorded before, during and after intervention and eye tracking was applied during intervention.ResultPre‐post EEG analysis showed significant increases in alpha power and brain connectivity for PwD with AD and controls (post > pre, p<.05). EEG baseline alpha power demonstrated higher values for healthy controls than for PwD (AD). Eye movement analysis demonstrated significant differences between PwD (AD) and controls: eye blink rate AD > controls, p=.004(**) from the observation of a 3 minutes video, and significant correlation (Rho=.607, p=.003(**); 3 minutes video) was achieved between eye movements and the Freiburg Mindfulness Inventory score.ConclusionThe potential of VR‐based intervention based on mindfulness and sensory activation is very promising: the study demonstrated significant increases of EEG alpha power and brain connectivity where PwD usually suffer from decline and gaze data acquired during intervention indicate potential for non‐invasive assessment for decision support. OpenSense anticipates numerous opportunities for novel VR‐based care services for empowering cognitive reserve, inducing sensory activation, raising awareness and motivation for self‐regulation, and as pervasive assessment tool.

Quantitative EEG Analysis in Angelman Syndrome: Candidate Method for Assessing Therapeutics.

The goal of these studies was to use quantitative (q)EEG techniques on data from children with Angelman syndrome (AS) using spectral power analysis, and to evaluate this as a potential biomarker and quantitative method to evaluate therapeutics. Although characteristic patterns are evident in visual inspection, using qEEG techniques has the potential to provide quantitative evidence of treatment efficacy. We first assessed spectral power from baseline EEG recordings collected from children with AS compared to age-matched neurotypical controls, which corroborated the previously reported finding of increased total power driven by elevated delta power in children with AS. We then retrospectively analyzed data collected during a clinical trial evaluating the safety and tolerability of minocycline (3 mg/kg/d) to compare pretreatment recordings from children with AS (4-12 years of age) to EEG activity at the end of treatment and following washout for EEG spectral power and epileptiform events. At baseline and during minocycline treatment, the AS subjects demonstrated increased delta power; however, following washout from minocycline treatment the AS subjects had significantly reduced EEG spectral power and epileptiform activity. Our findings support the use of qEEG analysis in evaluating AS and suggest that this technique may be useful to evaluate therapeutic efficacy in AS. Normalizing EEG power in AS therefore may become an important metric in screening therapeutics to gauge overall efficacy. As therapeutics transition from preclinical to clinical studies, it is vital to establish outcome measures that can quantitatively evaluate putative treatments for AS and neurological disorders with distinctive EEG patterns.

Association Between Lower Preoperative Cognition With Intraoperative Electroencephalographic Features Consistent With Deep States of Anesthesia in Older Patients: An Observational Cohort Study.

Patients with low cognitive performance are thought to have a higher risk of postoperative neurocognitive disorders. Here we analyzed the relationship between preoperative cognition and anesthesia-induced brain dynamics. We hypothesized that patients with low cognitive performance would be more sensitive to anesthetics and would show differences in electroencephalogram (EEG) activity consistent with a brain anesthesia overdose. This is a retrospective analysis from a previously reported observational study. We evaluated cognitive performance using the Montreal cognitive assessment (MoCA) test. All patients received general anesthesia maintained with sevoflurane or desflurane during elective major abdominal surgery. We analyzed the EEG using spectral, coherence, and phase-amplitude modulation analyses. Patients were separated into a low MoCA group (<26 points, n = 12) and a high MoCA group (n = 23). There were no differences in baseline EEG, nor end-tidal age-corrected minimum alveolar concentration (MACage). However, under anesthesia, the low MoCA group had lower α-β power (high MoCA: 2.9 [interquartile range {IQR}: 0.6-5.8 dB] versus low MoCA: -1.2 [IQR: -2.1 to 0.6 dB], difference 4.1 [1.0-5.7]) and a lower α peak frequency (high MoCA: 9.0 [IQR: 8.3-9.8 Hz] versus low MoCA: 7.5 [IQR: 6.3-9.0 Hz], difference 1.5 [0-2.3]) compared to the high MoCA group. The low MoCA group also had a lower α band coherence and a stronger peak-max phase-amplitude coupling (PAC). Finally, patients in the low MoCA group had longer emergence times (high MoCA 663 ± 345 seconds versus low MoCA: 960 ± 352 seconds, difference 297 [15-578]). Multiple linear regression shows up that both age and MoCA scores are independently associated with intraoperative α-β power. All these EEG features, together with a prolonged emergence time, are consistent with the possibility that older patients with low cognitive performance are receiving a brain anesthesia overdose compare to cognitive normal patients.

The Case for Incorporating EEG in Clinical TMS Practice

TMS psychiatrists are seeking methods to identify subtypes of clinically complex treatment-resistant depression (TRD), requiring rigorous, in-depth assessment. Advances in affordable neurotechnology and software have made it possible to record, process, and analyze EEGs within the clinic. Psychiatrists can learn to decipher the electroencephalograph (EEG) according to the EEG phenotype model developed by Johnston, Gunkelman, & Lunt (2005). We reviewed and processed raw EEG recordings, using WinEEG software, from 50 recent TRD TMS patients. Their primary diagnoses included: MDD recurrent (54%), MDD recurrent with mixed features (22%), bipolar 1 depression (4%), and bipolar 2 depression (20%). Secondary diagnoses included chronic PTSD (72%), dysthymia (32%), comorbid anxiety disorder (48%), OCD (6%), substance use disorder in full remission (18%), alcohol use disorder (6%), cannabis use disorder (4%), personality disorders (10%), and ADHD (12%). Baseline EEGs showed the following features, in ranking order: dysfunctional insular involvement seen in independent component analysis (80%), a marker of severity of depression; hypercoherent frontal alpha, reflecting diminished cognitive and emotional control (80%); excess alpha at right temporoparietal junction (76%), likely a marker relating to comorbid chronic PTSD; and tonic midline theta (38%), a marker of anterior cingulate involvement, often reflecting fear and dread, and excess beta abnormalities (80%) reflecting issues of overarousal. We currently use EEG data to inform medication choices and TMS protocol indications and contraindications. We believe these findings have helped guide successful treatment choices and hope to validate that observation with these and an additional 300 patients’ EEG, clinical, and TMS treatment response data.

Positive shyness and frontal EEG alpha/delta ratio in children: A pilot study

In two separate recent studies, researchers have reported an association between increases in children's shyness (i.e., social avoidance and inhibition) and decreases on frontal baseline electroencephalogram (EEG) alpha-to-delta ratio (ADR) scores (i.e., Schmidt & Poole, 2018, 2020). Here we attempted to extend these findings by examining whether different types of children's shyness were distinguishable on this same frontal ADR score, which is thought to be one electrocortical proxy of brain maturation. We coded expressions of positive shyness (i.e., co-occurrence of smiling and avoidance behaviors) versus non-positive shyness (i.e., avoidance behaviors) from direct observations during a social presentation speech in children (N = 63; Mage = 10.41 years) and examined these expressions of shyness in relation to the children's frontal baseline EEG ADR scores. We found preliminary evidence that children expressing positive shyness exhibited the lowest frontal baseline EEG ADR score (i.e., ostensibly less brain maturation) relative to children expressing non-positive shyness and low levels of shyness. We speculate that relatively less frontal brain maturation may be linked to some adaptive features of shyness.

Prediction of tinnitus masking benefit within a case series using a spiking neural network model.

Masking has been widely used as a tinnitus therapy, with large individual differences in its effectiveness. The basis of this variation is unknown. We examined individual tinnitus and psychological responses to three masking types, energetic masking (bilateral broadband static or rain noise [BBN]), informational masking (BBN with a notch at tinnitus pitch and 3-dimensional cues) and a masker combining both effects (BBN with spatial cues). Eleven participants with chronic tinnitus were followed for 12 months, each person used each masking approach for 3 months with a 1 month washout-baseline. The Tinnitus Functional Index (TFI), Tinnitus Rating Scales, Positive and Negative Affect Scale and Depression Anxiety Stress Scales, were measured every month of treatment. Electroencephalography (EEG) and psychoacoustic assessment was undertaken at baseline and following 3 months of each masking sound. The computational modeling of EEG data was based on the framework of brain-inspired Spiking Neural Network (SNN) architecture called NeuCube, designed for this study for mapping, learning, visualizing and classifying of brain activity patterns. EEG was related to clinically significant change in the TFI using the SNN model. The SNN framework was able to predict sound therapy responders (93% accuracy) from non-responders (100% accuracy) using baseline EEG recordings. The combination of energetic and informational masking was an effective treatment sound in more individuals than the other sounds used. Although the findings are promising, they are preliminary and require confirmation in independent and larger samples.

Detection of neurophysiological features in female R255X MeCP2 mutation mice

Rett syndrome (RTT) is a severe neurodevelopmental disorder (NDD) that is nearly always caused by loss of function mutations in Methyl-CpG-binding Protein 2 (MECP2) and shares many clinical features with other NDD. Genetic restoration of Mecp2 in symptomatic mice lacking MeCP2 expression can reverse symptoms, providing hope that disease modifying therapies can be identified for RTT. Effective and rapid clinical trial completion relies on well-defined clinical outcome measures and robust biomarkers of treatment responses. Studies on other NDD have found evidence of differences in neurophysiological measures that correlate with disease severity. However, currently there are no well-validated biomarkers in RTT to predict disease prognosis or treatment responses. To address this, we characterized neurophysiological features in a mouse model of RTT containing a knock-in nonsense mutation (p.R255X) in the Mecp2 locus. We found a variety of changes in heterozygous female Mecp2R255X/X mice including age-related changes in sleep/wake architecture, alterations in baseline EEG power, increased incidence of spontaneous epileptiform discharges, and changes in auditory evoked potentials. Furthermore, we identified association of some neurophysiological features with disease severity. These findings provide a set of potential non-invasive and translatable biomarkers that can be utilized in preclinical therapy trials in animal models of RTT and eventually within the context of clinical trials.