Curr Top Med Chem. 2022 May 9. doi: 10.2174/1568026622666220509155413. Online ahead of print.

ABSTRACT

Attention-deficit hyperactivity disorder is a neurodevelopmental disorder diagnosed primarily in children, although it is also present in adults. Patients present inattention, impulsivity, and hyperactivity symptoms that create difficulties in their daily lives. Pharmacological treatment with stimulants or non-stimulants is used most commonly to reduce ADHD symptoms. Although generally effective and safe, pharmacological treatments have different effects among patients, including lack of response and adverse reactions. The reasons for these differences are not fully understood, but they may derive from the highly diverse etiology of ADHD. Strategies to guide optimal pharmacological treatment selection on the basis of individual patients' physiological markers are being developed. In this review, we describe the main pharmacological ADHD treatments used and their main drawbacks. We present alternatives under study that would allow the customization of pharmacological treatments to overcome these drawbacks and achieve more reliable improvement of ADHD symptoms.

PMID:35579123 | DOI:10.2174/1568026622666220509155413

Brain Lang. 2022 May 13;230:105137. doi: 10.1016/j.bandl.2022.105137. Online ahead of print.

ABSTRACT

Spontaneous neural oscillatory activity reflects the brain's functional architecture and has previously been shown to correlate with perceptual, motor and executive skills. The current study used resting state electroencephalography to examine the relationship between spontaneous neural oscillatory activity and children's language skills. Participants in the study were 52 English-speaking children aged around 10-years. Language was assessed using a sentence repetition task. The main analysis revealed resting state theta power negatively correlated with this task. No significant correlations were found in the other studied frequency bands (delta, alpha, beta, gamma). As part of typical brain development, spontaneous theta power declines across childhood and adolescence. The negative correlation observed in this study may therefore be indicating children's language skills are related to the maturation of theta oscillations. More generally, the study provides further evidence that oscillatory activity in the developing brain, even at rest, is reliably associated with children's language skills.

PMID:35576738 | DOI:10.1016/j.bandl.2022.105137

Appl Neuropsychol Child. 2022 May 15:1-7. doi: 10.1080/21622965.2022.2074298. Online ahead of print.

ABSTRACT

Learning the subtype of dyslexia may help shorten the rehabilitation process and focus more on the relevant special education or diet for children with dyslexia. For this purpose, the resting-state eyes-open 2-min QEEG measurement data were collected from 112 children with dyslexia (84 male, 28 female) between 7 and 11 years old for 96 sessions per subject on average. The z-scores are calculated for each band power and each channel, and outliers are eliminated afterward. Using the k-Means clustering method, three different clusters are identified. Cluster 1 (19% of the cases) has positive z-scores for theta, alpha, beta-1, beta-2, and gamma-band powers in all channels. Cluster 2 (76% of the cases) has negative z-scores for theta, alpha, beta-1, beta-2, and gamma-band powers in all channels. Cluster 3 (5% of the cases) has positive z-scores for theta, alpha, beta-1, beta-2, and gamma-band powers at AF3, F3, FC5, and T7 channels and mostly negative z-scores for other channels. In Cluster 3, there is temporal disruption which is a typical description of dyslexia. In Cluster 1, there is a general brain inflammation as both slow and fast waves are detected in the same channels. In Cluster 2, there is a brain maturation delay and a mild inflammation. After Auto Train Brain training, most of the cases resemble more of Cluster 2, which may mean that inflammation is reduced and brain maturation delay comes up to the surface which might be the result of inflammation. Moreover, Cluster 2 center values at the posterior parts of the brain shift toward the mean values at these channels after 60 sessions. It means, Auto Train Brain training improves the posterior parts of the brain for children with dyslexia, which were the most relevant regions to be strengthened for dyslexia.

PMID:35575241 | DOI:10.1080/21622965.2022.2074298

Int J Environ Res Public Health. 2022 Apr 30;19(9):5480. doi: 10.3390/ijerph19095480.

ABSTRACT

In 2021, over 100,000 people died prematurely from opioid overdoses. Neuropsychiatric and cognitive impairments are underreported comorbidities of reward dysregulation due to genetic antecedents and epigenetic insults. Recent genome-wide association studies involving millions of subjects revealed frequent comorbidity with substance use disorder (SUD) in a sizeable meta-analysis of depression. It found significant associations with the expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. However, despite the rise in SUD and neuropsychiatric illness, there are currently no standard objective brain assessments being performed on a routine basis. The rationale for encouraging a standard objective Brain Health Check (BHC) is to have extensive data available to treat clinical syndromes in psychiatric patients. The BHC would consist of a group of reliable, accurate, cost-effective, objective assessments involving the following domains: Memory, Attention, Neuropsychiatry, and Neurological Imaging. Utilizing primarily PUBMED, over 36 years of virtually all the computerized and written-based assessments of Memory, Attention, Psychiatric, and Neurological imaging were reviewed, and the following assessments are recommended for use in the BHC: Central Nervous System Vital Signs (Memory), Test of Variables of Attention (Attention), Millon Clinical Multiaxial Inventory III (Neuropsychiatric), and Quantitative Electroencephalogram/P300/Evoked Potential (Neurological Imaging). Finally, we suggest continuing research into incorporating a new standard BHC coupled with qEEG/P300/Evoked Potentials and genetically guided precision induction of "dopamine homeostasis" to diagnose and treat reward dysregulation to prevent the consequences of dopamine dysregulation from being epigenetically passed on to generations of our children.

PMID:35564876 | PMC:PMC9099927 | DOI:10.3390/ijerph19095480

Front Neurol. 2022 Apr 11;13:704844. doi: 10.3389/fneur.2022.704844. eCollection 2022.

ABSTRACT

BACKGROUND: Following mild traumatic brain injury (mTBI), also known as concussion, many patients with chronic symptoms (>3 months post injury) receive conventional imaging such as computed tomography (CT) or magnetic resonance imaging (MRI). However, these modalities often do not show changes after mTBI. We studied the benefit of triaging patients with ongoing symptoms >3 months post injury by quantitative electroencephalography (qEEG) and then completing a brain single positron emission computed tomography (SPECT) to aid in diagnosis and early detection of brain changes.

METHODS: We conducted a retrospective case review of 30 outpatients with mTBI. The patients were assessed by a neurologist, consented, and received a qEEG, and if the qEEG was positive, they consented and received a brain SPECT scan. The cases and diagnostic tools were collectively reviewed by a multidisciplinary group of physicians in biweekly team meetings including neurology, nuclear medicine, psychiatry, neuropsychiatry, general practice psychotherapy, neuro-ophthalmology, and chiropractic providers. The team noted the cause of injury, post injury symptoms, relevant past medical history, physical examination findings, and diagnoses, and commented on patients' SPECT scans. We then analyzed the SPECT scans quantitatively using the 3D-SSP software.

RESULTS: All the patients had cerebral perfusion abnormalities demonstrated by SPECT that were mostly undetectable by conventional imaging (CT/MRI). Perfusion changes were localized primarily in the cerebral cortex, basal ganglia, and cingulate cortex, and correlated with the patients' symptoms and examination findings. Qualitative and quantitative analyses yielded similar results. Most commonly, the patients experienced persistent headache, memory loss, concentration difficulties, depression, and cognitive impairment post mTBI. Because of their symptoms, most of the patients were unable to return to their previous employment and activity level.

CONCLUSION: Our findings outline the physical basis of neurological and psychiatric symptoms experienced by patients with mTBI. Increased detection of mTBI can lead to development of improved targeted treatments for mTBI and its various sequelae.

PMID:35528740 | PMC:PMC9074759 | DOI:10.3389/fneur.2022.704844

Front Physiol. 2022 Apr 20;13:866844. doi: 10.3389/fphys.2022.866844. eCollection 2022.

ABSTRACT

Quantitative EEG (qEEG) delineates complex brain activities. Global field synchronization (GFS) is one multichannel EEG analysis that measures global functional connectivity through quantification of synchronization between signals. We hypothesized that preservation of global functional connectivity of brain activity might be a surrogate marker for good outcome in sudden cardiac arrest (SCA) survivors. In addition, we examined the relation of phase coherence and GFS in a mathematical approach. We retrospectively collected EEG data of SCA survivors in one academic medical center. We included 75 comatose patients who were resuscitated following in-hospital or out-of-hospital nontraumatic cardiac arrest between 2013 and 2017 in the intensive care unit (ICU) of National Taiwan University Hospital (NTUH). Twelve patients (16%) were defined as good outcome (GO) (CPC 1-2). The mean age in the GO group was low (51.6 ± 15.7 vs. 68.1 ± 12.9, p < 0.001). We analyzed standard EEG power, computed EEG GFS, and assessed the cerebral performance category (CPC) score 3 months after discharge. The alpha band showed the highest discrimination ability (area under curve [AUC] = 0.78) to predict GO using power. The alpha band of GFS showed the highest AUC value (0.8) to predict GO in GFS. Furthermore, by combining EEG power + GFS, the alpha band showed the best prediction value (AUC 0.86) in predicting GO. The sensitivity of EEG power + GFS was 73%, specificity was 93%, PPV was 0.67%, and NPV was 0.94%. In conclusion, by combining GFS and EEG power analysis, the neurological outcome of the nontraumatic cardiac arrest survivor can be well-predicted. Furthermore, we proved from a mathematical point of view that although both amplitude and phase contribute to obtaining GFS, the interference in phase variation drastically changes the possibility of generating a good GFS score.

PMID:35514330 | PMC:PMC9065675 | DOI:10.3389/fphys.2022.866844

Sci Rep. 2022 May 4;12(1):7293. doi: 10.1038/s41598-022-11196-7.

ABSTRACT

Neurocritical patients suffer from a substantial risk of extubation failure. The aim of this prospective study was to analyze if quantitative EEG (qEEG) monitoring is able to predict successful extubation in these patients. We analyzed EEG-monitoring for at least six hours before extubation in patients receiving mechanical ventilation (MV) on our neurological intensive care unit (NICU) between November 2017 and May 2019. Patients were divided in 2 groups: patients with successful extubation (SE) versus patients with complications after MV withdrawal (failed extubation; FE), including reintubation, need for non-invasive ventilation (NIV) or death. Bipolar six channel EEG was applied. Unselected raw EEG signal underwent automated artefact rejection and Short Time Fast Fourier Transformation. The following relative proportions of global EEG spectrum were analyzed: relative beta (RB), alpha (RA), theta (RT), delta (RD) as well as the alpha delta ratio (ADR). Coefficient of variation (CV) was calculated as a measure of fluctuations in the different power bands. Mann-Whitney U test and logistic regression were applied to analyze group differences. 52 patients were included (26 male, mean age 65 ± 17 years, diagnosis: 40% seizures/status epilepticus, 37% ischemia, 13% intracranial hemorrhage, 10% others). Successful extubation was possible in 40 patients (77%), reintubation was necessary in 6 patients (12%), 5 patients (10%) required NIV, one patient died. In contrast to FE patients, SE patients showed more stable EEG power values (lower CV) considering all EEG channels (RB: p < 0.0005; RA: p = 0.045; RT: p = 0.045) with RB as an independent predictor of weaning success in logistic regression (p = 0.004). The proportion of the EEG frequency bands (RB, RA RT, RD) of the entire EEG power spectrum was not significantly different between SE and FE patients. Higher fluctuations in qEEG frequency bands, reflecting greater fluctuation in alertness, during the hours before cessation of MV were associated with a higher rate of complications after extubation in this cohort. The stability of qEEG power values may represent a non-invasive, examiner-independent parameter to facilitate weaning assessment in neurocritical patients.

PMID:35508676 | PMC:PMC9068701 | DOI:10.1038/s41598-022-11196-7

Neuropsychopharmacol Hung. 2022 Mar 1;24(1):17-28.

ABSTRACT

Prescribing antidepressant medication is currently the most effective way of treating major depression, but only very few patients achieve permanent improvement. Therefore, it is important to identify objectively measurable markers for effective, personalized therapy. The aim of this review article is to collect all the markers that are robustly predictive of the outcome of therapy. We searched for systematic review articles that have simultaneously investigated the effects of as many different markers as possible on the response to antidepressant therapy in major depressive patients. From these we extracted markers that have been found to be significant by at least two independent review studies and that have proven replicable also within each of these reviews. A separate search was performed for meta-analyses of pharmacogenetic genome-wide association studies. Based on our results, onset time, symptom severity, presence of anhedonia, early treatment response, comorbid anxiety, alcohol consumption, frontal EEG theta activity, hippocampal volume, activity of anterior cingulate cortex, as well as a peripheral marker, serum BDNF levels have proven replicable predictors of antidepressant response. Pharmacogenomic studies to date have not yielded replicable results. Predictors identified as robust by our study may provide a starting point for future machine learning models within a 'big data' database of major depressive patients. (Neuropsychopharmacol Hung 2022; 24(1): 17-28).

PMID:35451589

Clin EEG Neurosci. 2022 Apr 21:15500594221095385. doi: 10.1177/15500594221095385. Online ahead of print.

ABSTRACT

Backgrounds. Deep Transcranial Magnetic Stimulation (dTMS) is a non-invasive treatment cleared by FDA as a safe and efficient intervention for the treatment of depression and obsessive-compulsive disorder (OCD). Objectives. In this retrospective single-center study, the effects of dTMS on the electrophysiological parameters and the clinical outcomes of patients with OCD were tested. Methods. Thirty sessions of dTMS were administered to 29 OCD patients (15 female and 14 male). Quantitative electroencephalography (QEEG) recordings and Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) were measured at baseline and endpoint. Paired sample t-test was used to measure the change in Y-BOCS scores and QEEG activity after dTMS practice. Results. All 29 patients responded to the dTMS intervention by indicating at least 35% reduction in Y-BOCS scores. QEEG recordings revealed a significant decrease in theta, alpha and the beta rhythms. The decrease in the severity of OCD symptoms correlated with the decrease in beta activity at left central region. Conclusions. Historically, excess fast oscillations in OCD are correlated with the unresponsiveness to selective serotonin reuptake inhibitor (SSRI) treatment. We hypothesize that the decrease in the power of beta bands by deep TMS is related to the mechanism of the therapeutic response.

PMID:35450452 | DOI:10.1177/15500594221095385

J Affect Disord. 2022 Jul 1;308:322-327. doi: 10.1016/j.jad.2022.04.076. Epub 2022 Apr 16.

ABSTRACT

BACKGROUND: Major depression and anxiety disorders represent a substantial burden of morbidity. Neither antidepressant medication nor psychological interventions are fully effective, the former beset with side effects, interactions and compliance issues, and the latter requiring patient engagement, effort and a degree of psychological mindedness. Both treatments are lengthy. TMS by contrast is virtually free of side effects and compliance issues, relatively brief, and requires no patient effort. Nevertheless, remission rates are only about 1 in 3 with standard left frontal rapid (rTMS) stimulation, and up to 30 treatment sessions may be required. Our aim was to improve the effectiveness of TMS treatment using bespoke as opposed to standard left frontal rTMS, including theta burst stimulation (TBS).

METHODS: 210 male and female patients were treated: regions and frequencies of TMS were guided by quantitative EEG analysis (qEEG) to elicit recognisable phenotypes, neuromarkers integral to the genesis of major depression and anxiety disorder, dictating treatment parameters.

RESULTS: 98 patients (47%) achieved at least 50% reduction in Hamilton depression rating scale scores, while a further 60 (29%) patients achieved a 30-50% reduction, over a mean of 7.03 ± 0.3 treatment sessions. Theta burst stimulation (TBS) almost halved treatment time within session compared to rTMS. The effect size (Cohen's d) for both treatments was large (>0.8) with rTMS at 1.43 (1.16-1.70) and TBS at 1.87 (1.48-2.25).

CONCLUSIONS: qEEG guided TMS treatment is a safe and effective treatment in depression and anxiety disorders.

PMID:35439465 | DOI:10.1016/j.jad.2022.04.076

J Healthc Eng. 2022 Apr 5;2022:3789516. doi: 10.1155/2022/3789516. eCollection 2022.

ABSTRACT

OBJECTIVES: Epilepsy is a chronic neurological disorder that is characterized by episodes of seizure.

METHODS: In this study, patients with status epilepticus in the Intensive Care Unit of the Department of Neurology of Qujing First People's Hospital were collected and treated with levetiracetam injection, continuous bedside EEG monitoring (cEEG) technology, and quantitative EEG (qEEG) technique. The inhibitory effects of different doses of levetiracetam injection and sodium valproate on abnormal discharge, the improvement of clinical symptoms, the incidence of adverse reactions, and prognosis were monitored, analyzed, and compared.

RESULTS: Compared with the experimental group of sodium valproate, 1000 mg/d levetiracetam group and 1500 mg/d levetiracetam group had a high probability of successful symptom control and a short control time. The patients had a low recurrence rate and a long recurrence time, and the probability of abnormal discharge in EEG was low.

CONCLUSIONS: The recording results showed that levetiracetam could significantly inhibit the abnormal discharge of patients. Compared with sodium valproate, high-dose levetiracetam is a drug with a rapid effect, good effect, and long action time.

PMID:35422974 | PMC:PMC9005289 | DOI:10.1155/2022/3789516

Neuroimage. 2022 Apr 7;256:119190. doi: 10.1016/j.neuroimage.2022.119190. Online ahead of print.

ABSTRACT

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

PMID:35398285 | DOI:10.1016/j.neuroimage.2022.119190

Neuroimage. 2022 Jul 1;254:119144. doi: 10.1016/j.neuroimage.2022.119144. Epub 2022 Mar 24.

ABSTRACT

Protein Energy Malnutrition (PEM) has lifelong consequences on brain development and cognitive function. We studied the lifelong developmental trajectories of resting-state EEG source activity in 66 individuals with histories of Protein Energy Malnutrition (PEM) limited to the first year of life and in 83 matched classmate controls (CON) who are all participants of the 49 years longitudinal Barbados Nutrition Study (BNS). qEEGt source z-spectra measured deviation from normative values of EEG rhythmic activity sources at 5-11 years of age and 40 years later at 45-51 years of age. The PEM group showed qEEGt abnormalities in childhood, including a developmental delay in alpha rhythm maturation and an insufficient decrease in beta activity. These profiles may be correlated with accelerated cognitive decline.

PMID:35342003 | DOI:10.1016/j.neuroimage.2022.119144

Brain Sci. 2022 Mar 2;12(3):339. doi: 10.3390/brainsci12030339.

ABSTRACT

Binaural beat (BB) stimulation, which has two different frequencies for each ear, is reportedly effective in reducing anxiety and controlling mood. This study aimed to evaluate the brain wave entrainment effect of binaural beats and to propose an effective and safe supplementary therapy for relieving the symptoms of insomnia. Subjects between 20 and 59 years of age with subclinical symptoms of insomnia were recruited from the community. Quantitative electroencephalography was measured twice, before and two weeks after the BB intervention. Participants used the apparatus with or without 6 Hz BB for 30 min before going to bed for two weeks. When music with BB was played, the relative theta power increased (occipital, p = 0.009). After two weeks of intervention with music, the theta power increased when listening to music with BB (parietal, p = 0.009). After listening to music with BB for two weeks, the decrease in the beta power was more noticeable than after using music-only devices when participants listened to music in the laboratory (occipital, p = 0.035). When BB were played, the entrapment of the theta wave appeared. Therefore, exposure to music with BB is likely to reduce the hyper-arousal state and contribute to sleep induction.

PMID:35326295 | PMC:PMC8945912 | DOI:10.3390/brainsci12030339

Clin Neurophysiol. 2022 May;137:92-101. doi: 10.1016/j.clinph.2022.02.022. Epub 2022 Mar 8.

ABSTRACT

OBJECTIVE: Quantitative Electroencephalography (qEEG) can capture changes in brain activity following stroke. qEEG metrics traditionally focus on oscillatory activity, however recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. We assessed neurophysiological alterations and recovery after mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD).

METHODS: Eighteen patients (n = 18) with mild to moderate mono-hemispheric Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n = 16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients.

RESULTS: At T0, stroke patients showed significantly more negative SE values than HC (p = 0.003), reflecting broad-band EEG slowing. Most important, in patients SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1. This SE renormalization significantly correlated with National Institute of Health Stroke Scale (NIHSS) improvement (R = 0.63, p = 0.005).

CONCLUSIONS: SE is a reliable readout of the neurophysiological and clinical alterations occurring after an ischaemic cortical lesion.

SIGNIFICANCE: SE promise to be a robust method to monitor and predict patients' functional outcome.

PMID:35303540 | DOI:10.1016/j.clinph.2022.02.022

Cureus. 2022 Feb 28;14(2):e22675. doi: 10.7759/cureus.22675. eCollection 2022 Feb.

ABSTRACT

Frontal alpha asymmetry (fAA) is purported to be a neurophysiological marker for anxiety and depression. Higher left frontal alpha EEG voltage is associated with lower left and higher right frontal cerebral cortical activation, indicative of right-sided fAA. This pilot study tests the hypothesis that greater left-sided frontal alpha voltage is associated with negative thoughts about oneself. A group of eight healthy 28-41-year-old right-handed male medical students were subjected to an extensive interactive self-report inventory (ISI) evaluating perceptions of their psychosocial interactions. Quantitative EEG (qEEG) was performed with eyes closed. Computations of fAA and related parameters were based on measurements in the alpha bandwidth (8-13 Hz) at the left frontal F7 and right frontal F8 scalp electrodes. fAA was the percent difference between mean voltages at F8 minus that at F7. Significance of associations between fAA and the ISI scores was determined by Pearson's product-moment correlation coefficient, at P≤0.05. "Depressed" scores were positively correlated with right-sided fAA (P=0.01). "Relaxed" (P=0.05), "regulated" (P=0.02), "cooperative" (P=0.05) and "dependent scores" (P=0.004) were negatively correlated with right-sided fAA. These findings imply that right-sided fAA may be associated with more perceptions of "depressed" psychosocial interactions involving negative thoughts about oneself, as well as, more reliance on others ("dependence" score), less sharing ("cooperative" ISI score), less trust ("regulated" ISI score) and less initiative ("relaxed" ISI score). These results support the hypothesis that right-sided fAA may identify individuals with a predilection for negative thoughts about themselves and other negatively-valenced perceptions of their psychosocial interactions.

PMID:35242485 | PMC:PMC8883328 | DOI:10.7759/cureus.22675

Front Immunol. 2022 Feb 15;13:845272. doi: 10.3389/fimmu.2022.845272. eCollection 2022.

ABSTRACT

OBJECTIVE: To establish the diagnostic biomarker of electroencephalogram (EEG) to distinguish between anti-N-methyl-d-aspartate receptor encephalitis (NMDARE) and other types of autoimmune encephalitis (other AEs).

METHODS: We reviewed the clinical records of 90 patients with acute encephalitis who were treated in our institution between January 2014 and October 2020. We enrolled the patients who fulfilled the diagnostic criteria for possible AE (pAE) defined by Graus et al. (pAE criteria) and then classified into definite NMDARE and other AEs. We investigated the main syndrome and analyzed all admission EEGs using EEG power value (PV). Statistical significance was tested using the Mann-Whitney U test or Fisher's exact test.

RESULTS: Twenty-five patients fulfilled the pAE criteria and were classified into 9 with definite NMDARE (median age: 21 years; 8 women) and 12 with other AEs (median age: 37.5 years; 6 women). Four were eventually excluded. Speech dysfunction (9/9 vs. 4/12, p = 0.005) and movement disorders (6/9 vs. 1/12, p = 0.016) were more frequent in NMDARE than in other AEs. The PV analyses revealed the novel quantitative EEG (qEEG) index, namely, fast slow ratio (FSR) (PV of total beta/PV of total theta + delta). The median FSR (0.139 vs. 0.029, p = 0.004) was higher for NMDARE than other AEs, and the receiver operating characteristic curve area of FSR was 0.86 (95% CI 0.70-1.00). A cutoff value of 0.047 yielded a specificity of 0.75 and a sensitivity of 1.00. Focusing on patients who did not meet the "probable NMDARE criteria" in Graus 2016 (proNMDARE criteria) (n = 10), the pretest probability of NMDAR antibody test was 0.30 (3/10), which increased in patients with an FSR greater than the cutoff (n = 5) to 0.60 (3/5).

CONCLUSIONS: The NMDARE group highlighted speech dysfunction and movement disorders, and a novel qEEG index FSR accurately distinguished the NMDARE patients from other AEs. The FSR is a promising diagnostic marker for NMDARE that indicates the positive results of NMDAR antibodies in patients with AE when combined with the proNMDARE criteria.

PMID:35242143 | PMC:PMC8885512 | DOI:10.3389/fimmu.2022.845272

J Neurosci Nurs. 2022 Apr 1;54(2):96-101. doi: 10.1097/JNN.0000000000000639.

ABSTRACT

BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.

PMID:35234185 | DOI:10.1097/JNN.0000000000000639

Int J Environ Res Public Health. 2022 Feb 21;19(4):2465. doi: 10.3390/ijerph19042465.

ABSTRACT

Quantitative electroencephalography (QEEG) is becoming an increasingly common method of diagnosing neurological disorders and, following the recommendations of The American Academy of Neurology (AAN) and the American Clinical Neurophysiology Society (ACNS), it can be used as a complementary method in the diagnosis of epilepsy, vascular diseases, dementia, and encephalopathy. However, few studies are confirming the importance of QEEG in the diagnosis of mental disorders and changes occurring as a result of therapy; hence, there is a need for analyses in this area. The aim of the study is analysis of the usefulness of QEEG in the diagnosis of people with generalized anxiety disorders. Our research takes the form of case studies. The paper presents an in-depth analysis of the QEEG results of five recently studied people with a psychiatric diagnosis: generalized anxiety disorder. The results show specific pattern amplitudes at C3 and C4. In all of the examined patients, two dependencies are repeated: low contribution of the sensorimotor rhythm (SMR) wave amplitudes and high beta2 wave amplitudes, higher or equal to the alpha amplitudes. The QEEG study provides important information about the specificity of brain waves of people with generalized anxiety disorder; therefore, it enables the preliminary and quick diagnosis of dysfunction. It is also possible to monitor changes due to QEEG, occurring as a result of psychotherapy, pharmacological therapy and EEG-biofeedback.

PMID:35206651 | PMC:PMC8879113 | DOI:10.3390/ijerph19042465

Clin Neurophysiol. 2022 Apr;136:182-190. doi: 10.1016/j.clinph.2022.01.131. Epub 2022 Feb 4.

ABSTRACT

OBJECTIVE: To investigate the influence of apolipoprotein E (APOE) gene polymorphism on regional cerebral oxygen saturation (rScO₂) and quantitative electroencephalogram (QEEG) at the early phase of adult traumatic brain injury (TBI).

METHODS: clinical data of TBI patients who were admitted to the neurosurgery intensive care unit (NICU) were retrospectively evaluated and studied, and data of healthy volunteers were recruited as control. The APOE genotypes were genotyped by quantitative fluorescent polymerase chain reaction (QF-PCR). The rScO₂ and brainelectricalactivityof all the participants involved in this research were measured by near-infrared spectroscopy (NIRS) and QEEG respectively.

RESULTS: The average rScO₂ of TBI patients was significantly lower than that of the normal controls (P < 0.0001). And the EEG of the TBI patients has showed more irregular slow-wave activities than that of the normal controls. Furthermore, the above changes were more significant in the APOE ε4 carriers in the early stage of TBI patients.

CONCLUSIONS: The APOE ε4 allele may be associated with poor rScO₂ and more slow-wave activities at the early stage of TBI.

SIGNIFICANCE: To clarify the effect of APOE gene polymorphism on the condition of patients with TBI may be helpful for the design and management of individualized treatment programs.

PMID:35193096 | DOI:10.1016/j.clinph.2022.01.131

J Alzheimers Dis. 2022;86(3):1399-1413. doi: 10.3233/JAD-215511.

ABSTRACT

BACKGROUND: Fosgonimeton (ATH-1017) is being developed as a first-in-class regenerative therapy for people with Alzheimer's disease (AD) and dementia; potentially improving dementia symptoms and altering disease progression by reversing synaptic disconnection and neuronal loss.

OBJECTIVE: This randomized, double-blind, placebo-controlled phase I trial (NCT03298672) evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of fosgonimeton.

METHODS: Fosgonimeton was administered once daily via subcutaneous injection to 88 subjects. The single ascending dose study enrolled healthy young male subjects (n = 48; age, 33.4±6.3 years; dose, 2, 6, 20, 40, 60, or 90 mg); the multiple ascending dose study enrolled healthy elderly subjects (n = 29; age, 63.8±4.0 years; dose, 20, 40, 60, or 80 mg; 9-day duration); and the fixed-dose study enrolled AD subjects (n = 11; age, 69.2±7.1 years; dose, 40 mg; 9-day duration). Quantitative electroencephalogram (qEEG) and event-related potential (ERP) P300 measured neurophysiological signals following fosgonimeton treatment, supporting brain penetration and target engagement.

RESULTS: Fosgonimeton and placebo were shown to be safe and well-tolerated across all doses. Pharmacokinetic results for fosgonimeton were dose-proportional, with no sex effect or accumulation over 9 days. The main effect of fosgonimeton on qEEG was acute and sustained gamma power induction. In AD subjects, there was a significant effect toward ERP P300 latency normalization compared with placebo (p = 0.027; n = 7 at 40 mg fosgonimeton versus n = 4 placebo).

CONCLUSION: These results support the continued development of fosgonimeton as a novel therapeutic for people with AD and dementia. The fast-onset normalization of ERP P300 latency in AD subjects suggests enhancement of synaptic function and potential procognitive effects.

PMID:35180125 | PMC:PMC9108585 | DOI:10.3233/JAD-215511

Front Hum Neurosci. 2022 Jan 27;15:795006. doi: 10.3389/fnhum.2021.795006. eCollection 2021.

ABSTRACT

Impaired neurodevelopmental outcome, in particular cognitive impairment, after neonatal hypoxic-ischemic encephalopathy is a major concern for parents, clinicians, and society. This study aims to investigate the potential benefits of using advanced quantitative electroencephalography analysis (qEEG) for early prediction of cognitive outcomes, assessed here at 2 years of age. EEG data were recorded within the first week after birth from a cohort of twenty infants with neonatal hypoxic-ischemic encephalopathy (HIE). A proposed regression framework was based on two different sets of features, namely graph-theoretical features derived from the weighted phase-lag index (WPLI) and entropies metrics represented by sample entropy (SampEn), permutation entropy (PEn), and spectral entropy (SpEn). Both sets of features were calculated within the noise-assisted multivariate empirical mode decomposition (NA-MEMD) domain. Correlation analysis showed a significant association in the delta band between the proposed features, graph attributes (radius, transitivity, global efficiency, and characteristic path length) and entropy features (Pen and SpEn) from the neonatal EEG data and the cognitive development at age two years. These features were used to train and test the tree ensemble (boosted and bagged) regression models. The highest prediction performance was reached to 14.27 root mean square error (RMSE), 12.07 mean absolute error (MAE), and 0.45 R-squared using the entropy features with a boosted tree regression model. Thus, the results demonstrate that the proposed qEEG features show the state of brain function at an early stage; hence, they could serve as predictive biomarkers of later cognitive impairment, which could facilitate identifying those who might benefit from early targeted intervention.

PMID:35153702 | PMC:PMC8830486 | DOI:10.3389/fnhum.2021.795006

BMC Neurol. 2022 Feb 9;22(1):48. doi: 10.1186/s12883-022-02577-6.

ABSTRACT

BACKGROUND: By definition, the background EEG is normal in juvenile myoclonic epilepsy (JME) patients and not accompanied by other developmental and cognitive problems. However, some recent studies using quantitative EEG (qEEG) reported abnormal changes in the background activity. QEEG investigation in patients undergoing anticonvulsant treatment might be a useful approach to explore the electrophysiology and anticonvulsant effects in JME.

METHODS: We investigated background EEG activity changes in patients undergoing valproic acid (VPA) treatment using qEEG analysis in a distributed source model. In 17 children with JME, non-parametric statistical analysis using standardized low-resolution brain electromagnetic tomography was performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions.

RESULTS: VPA reduced background EEG activity in the low-frequency (delta-theta) bands across the frontal, parieto-occipital, and limbic lobes (threshold log-F-ratio = ±1.414, p < 0.05; threshold log-F-ratio= ±1.465, p < 0.01). In the delta band, comparative analysis revealed significant current density differences in the occipital, parietal, and limbic lobes. In the theta band, the analysis revealed significant differences in the frontal, occipital, and limbic lobes. The maximal difference was found in the delta band in the cuneus of the left occipital lobe (log-F-ratio = -1.840) and the theta band in the medial frontal gyrus of the left frontal lobe (log-F-ratio = -1.610).

CONCLUSIONS: This study demonstrated the anticonvulsant effects on the neural networks involved in JME. In addition, these findings suggested the focal features and the possibility of functional deficits in patients with JME.

PMID:35139806 | PMC:PMC8827290 | DOI:10.1186/s12883-022-02577-6

Comput Math Methods Med. 2022 Jan 29;2022:9398551. doi: 10.1155/2022/9398551. eCollection 2022.

ABSTRACT

To analyze the application value of artificial intelligence model based on Visual Geometry Group- (VGG-) 16 combined with quantitative electroencephalography (QEEG) in cerebral small vessel disease (CSVD) with cognitive impairment, 72 patients with CSVD complicated by cognitive impairment were selected as the research subjects. As per Diagnostic and Statistical Manual (5th Edition), they were divided into the vascular dementia (VD) group of 34 cases and vascular cognitive impairment with no dementia (VCIND) group of 38 cases. The two groups were analyzed for the clinical information, neuropsychological test results, and monitoring results of QEEG based on intelligent algorithms for more than 2 hours. The accuracy rate of VGG was 84.27% and Kappa value was 0.7, while that of modified VGG (nVGG) was 88.76% and Kappa value was 0.78. The improved VGG algorithm obviously had higher accuracy. The test results found that the QEEG identified 8 normal, 19 mild, 10 moderate, and 0 severe cases in the VCIND group, while in the VD group, the corresponding numbers were 4, 13, 11, and 7; in the VCIND group, 7 cases had the normal QEEG, 11 cases had background changes, 9 cases had abnormal waves, and 11 cases had in both background changes and abnormal waves, and in the VD group, the corresponding numbers were 5, 2, 5, and 22, respectively; in the VCIND group, QEEG of 18 patients had no abnormal waves, QEEG of 11 patients had a few abnormal waves, and QEEG of 9 patients had many abnormal waves, and QEEG of 0 people had a large number of abnormal waves, and in the VD group, the corresponding numbers were 7, 6, 12, and 9. The above data were statistically different between the two groups (P < 0.05). Hence, QEEG based on intelligent algorithms can make a good assessment of CSVD with cognitive impairment, which had good clinical application value.

PMID:35132334 | PMC:PMC8817878 | DOI:10.1155/2022/9398551

Endocr Metab Immune Disord Drug Targets. 2022 Jan 31. doi: 10.2174/1871530322666220131120349. Online ahead of print.

ABSTRACT

BACKGROUND: Corticobasal degeneration (CBD) is a rare neurological disease caused by the pathological accumulation of tau protein. The primary pathological features of CBD include progressive neurodegenerative processes resulting in remarkable frontoparietal and basal ganglia atrophy.

OBJECTIVE: Like in many other neurodegenerative disorders, there is still no effective disease-modifying drug therapy in CBD. Therefore, the development of new treatment methods is of great importance. In this study, we aimed to assess the stimulating effects of high-frequency DLPFC rTMS on the motor, cognitive and behavioral disturbances in four CBD patients.

METHODS: Four (three females, one male) CBD patients who had been diagnosed as CBD were enrolled in this study. Patients were evaluated before and after the rTMS procedure regarding the motor, neuropsychometric and behavioral tests. The results of statistical analysis of behavioral and neuropsychometric evaluation were assessed via SPSS 18.0 package program. Data are expressed as mean, standard deviation. Before and after values of the groups were compared with the Wilcoxon sign rank test, and p<0.05 was considered significant.

RESULTS: We have provided strong preliminary evidence that the improvement in clinical parameters was associated with the normalizations of the theta activity and glucose metabolism.

CONCLUSION: Our current results are consistent with some previous trials showing a strong association between DLPFC targeted rTMS and electrophysiological normalizations in the left DLPFC.

PMID:35100961 | DOI:10.2174/1871530322666220131120349

Neurobiol Aging. 2022 Apr;112:87-101. doi: 10.1016/j.neurobiolaging.2021.11.009. Epub 2021 Dec 5.

ABSTRACT

Synaptic dysfunctions precede cognitive decline in Alzheimer's disease by decades, affect executive functions, and can be detected by quantitative electroencephalography (qEEG). We used quantitative electroencephalography combined with Stroop testing to identify changes of inhibitory controls in cognitively healthy individuals with an abnormal versus normal ratio of cerebrospinal fluid (CSF) amyloid/total-tau. We studied two groups of participants (60-94 years) with either normal (CH-NAT or controls, n = 20) or abnormal (CH-PAT, n = 21) CSF amyloid/tau ratio. We compared: alpha event-related desynchronization (ERD), alpha spectral entropy (SE), and their relationships with estimated cognitive reserve. CH-PATs had more negative occipital alpha ERD, and higher frontal and occipital alpha SE during low load congruent trials, indicating hyperactivity. CH-PATs demonstrated fewer frontal SE changes with higher load, incongruent Stroop testing. Correlations of alpha ERD with estimated cognitive reserve were significant in CH-PATs but not in CH-NATs. These results suggested compensatory hyperactivity in CH-PATs compared to CH-NATs. We did not find differences in alpha ERD comparisons with individual CSF amyloid(A), p-tau(T), total-tau(N) biomarkers.

PMID:35066324 | PMC:PMC8976735 | DOI:10.1016/j.neurobiolaging.2021.11.009

Brain Sci. 2021 Dec 27;12(1):29. doi: 10.3390/brainsci12010029.

ABSTRACT

Juvenile myoclonic epilepsy (JME) appears in adolescence with myoclonic, absence, and generalized tonic clonic (GTC) seizures with paroxysmal activity of polyspike and slow wave (PSW), or spike and wave (SW) complexes in EEG. Our aim was to analyze the clinical characteristics, background EEG activity, and paroxysmal events in 41 patients with JME. Background EEG activity was analyzed with visual, quantitative (QEEG), and neurometric parameters. Our JME patients started with absence seizures at 11.4 ± 1.5 years old, myoclonic seizures at 13.6 ± 2.5 years, and GTC seizures at 15.1 ± 0.8 years. The seizures presented in awakening at 7:39 h with sleep deprivation, alcoholic beverage intake, and stress as the most frequent precipitant factors. Paroxysmal activity was of PSW and fast SW complexes with 40.5 ± 62.6 events/hour and a duration of 1.7 s. Right asymmetric paroxysmal activity was present in 68.3% of patients. Background EEG activity was abnormal in 31.7% of patients with visual analysis. With QEEG beta AP (absolute power) increase and AP delta decrease were the most frequent abnormalities found. Spectral analysis showed that 48.7% of patients had normal results, and 26.83% and 24.4% had higher and lower frequencies than 10.156 Hz, respectively. We concluded that, with visual analysis, background EEG activity was abnormal in a few patients and the abnormalities increased when QEEG was used.

PMID:35053773 | PMC:PMC8773902 | DOI:10.3390/brainsci12010029

Front Aging Neurosci. 2022 Jan 3;13:804991. doi: 10.3389/fnagi.2021.804991. eCollection 2021.

ABSTRACT

Background: Quantitative electroencephalography (qEEG) has been suggested as a biomarker for cognitive decline in Parkinson's disease (PD). Objective: Determine if applying a wavelet-based qEEG algorithm to 21-electrode, resting-state EEG recordings obtained in a routine clinical setting has utility for predicting cognitive impairment in PD. Methods: PD subjects, evaluated by disease stage and motor score, were compared to healthy controls (N = 20 each). PD subjects with normal (PDN, MoCA 26-30, N = 6) and impaired (PDD, MoCA ≤ 25, N = 14) cognition were compared. The wavelet-transform based time-frequency algorithm assessed the instantaneous predominant frequency (IPF) at 60 ms intervals throughout entire recordings. We then determined the relative time spent by the IPF in the four standard EEG frequency bands (RTF) at each scalp location. The resting occipital rhythm (ROR) was assessed using standard power spectral analysis. Results: Comparing PD subjects to healthy controls, mean values are decreased for ROR and RTF-Beta, greater for RTF-Theta and similar for RTF-Delta and RTF-Alpha. In logistic regression models, arithmetic combinations of RTF values [e.g., (RTF-Alpha) + (RTF-Beta)/(RTF-Delta + RTF-Theta)] and RTF-Alpha values at occipital or parietal locations are most able to discriminate between PD and controls. A principal component (PC) from principal component analysis (PCA) using RTF-band values in all subjects is associated with PD status (p = 0.004, β = 0.31, AUC = 0.780). Its loadings show positive contribution from RTF-Theta at all scalp locations, and negative contributions from RTF-Beta at occipital, parietal, central, and temporal locations. Compared to cognitively normal PD subjects, cognitively impaired PD subjects have lower median RTF-Alpha and RTF-Beta values, greater RTF-Theta values and similar RTF-Delta values. A PC from PCA using RTF-band values in PD subjects is associated with cognitive status (p = 0.002, β = 0.922, AUC = 0.89). Its loadings show positive contributions from RTF-Theta at all scalp locations, negative contributions from RTF-Beta at central locations, and negative contributions from RTF-Delta at central, frontal and temporal locations. Age, disease duration and/or sex are not significant covariates. No PC was associated with motor score or disease stage. Significance: Analyzing standard EEG recordings obtained in a community practice setting using a wavelet-based qEEG algorithm shows promise as a PD biomarker and for predicting cognitive impairment in PD.

PMID:35046794 | PMC:PMC8761986 | DOI:10.3389/fnagi.2021.804991

J Alzheimers Dis. 2022;86(1):21-42. doi: 10.3233/JAD-215240.

ABSTRACT

The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.

PMID:35034899 | DOI:10.3233/JAD-215240

Clin EEG Neurosci. 2022 Jan 7:15500594211073390. doi: 10.1177/15500594211073390. Online ahead of print.

ABSTRACT

Skin picking disorder (SPD) characterized by repetitive compulsive scratching in the absence of a primary skin disease is strongly associated with psychiatric comorbidities, including obsessive-compulsive disorder (OCD) and depression (MDD). Selective serotonin reuptake inhibitors (SSRIs) have been used in the treatment of SPD with variable success. Nevertheless, the optimum treatment choice for SPD is an issue for clinicians. This case report presents a 32-year-old female SPD patient treated with four-week paroxetine monotherapy. Based upon the clinical interview and standardized questionnaires, the patient was diagnosed with OCD with depressive features and Skin Picking Disorder. In addition to symptom severity scales, quantitative electroencephalography (qEEG) was also applied. Paroxetine treatment was started (titrated from 5 to 40 mg/day) and doubled each week. After four-week paroxetine monotherapy, OCD symptoms were diminished, and skin lesions were completely regressed leaving solely post inflammatory hyperpigmentation. Post-treatment qEEG assessment also showed a normalization of frontal alpha power and amplitude asymmetry. It can be concluded that if OCD includes SPD with abnormal EEG patterns; then the treatment success using paroxetine will be very high.

PMID:34994223 | DOI:10.1177/15500594211073390

East Asian Arch Psychiatry. 2021 Jun;31(2):43-48. doi: 10.12809/eaap2024.

ABSTRACT

OBJECTIVES: To determine the associations of epilepsy spectrum disorder (ESD) with brain insult and certain quantitative electroencephalographic (QEEG) and clinico-demographic parameters in patients with depression.

METHODS: 21 right-handed patients aged 18 to 50 years with the diagnosis of depression and ESD (scored ≥70 in Iowa Interview for Partial seizure-like symptoms) were compared with 21 patients with depression but without ESD (scored <70) and 21 normal subjects with <3 positive scores on the 12-Item General Health Questionnaire. Their QEEG parameters such as power spectrum and coherence of five frequency bands in 11 regions were compared.

RESULTS: Patients with ESD had more minor traumatic brain injury along with more severe and multiple depressive episodes. Patients with ESD had significantly higher beta1 power over all regions on the left scalp than did normal subjects. Patients with ESD had significantly higher beta2 power over the left central region than did patients with no ESD and normal subjects.

CONCLUSIONS: For patients with severe recurrent depression, clinicians should systematically check for episodic partial seizure-like phenomena, especially when QEEG shows electrical disorganisation in the left side in those with mild traumatic brain injury.

PMID:34987117 | DOI:10.12809/eaap2024

Photobiomodul Photomed Laser Surg. 2022 Mar;40(3):205-210. doi: 10.1089/photob.2021.0048. Epub 2022 Jan 4.

ABSTRACT

Background: Currently treatment for prosopagnosia is limited. Methods: We report the reversal of acquired associative-type prosopagnosia (AAP) using quantitative electroencephalography (qEEG)-guided transcranial laser therapy (qGLT) in a subject with temporal lobe epilepsy (TLE) and mild cognitive impairment (MCI). Results: Objective and subjective measures of improvement in AAP, TLE, and MCI are presented. Additional improvement, measured through qEEG, was found 1-month post-treatment. Conclusions: There was no recurrence of AAP for 1 year. We conclude that further research into the utility of qGLT in the treatment of AAP is warranted.

PMID:34981964 | DOI:10.1089/photob.2021.0048

Front Neurosci. 2021 Dec 17;15:766781. doi: 10.3389/fnins.2021.766781. eCollection 2021.

ABSTRACT

We describe the utility of a standardized index (Z-score) in quantitative EEG (QEEG) capable of when referenced to a resting-state, sex- and age-differentiated QEEG normative database (ISB-NormDB). Our ISB-NormDB comprises data for 1,289 subjects (553 males, 736 females) ages 4.5 to 81 years that met strict normative data criteria. A de-noising process allowed stratification based on QEEG variability between normal healthy men and women at various age ranges. The ISB-NormDB data set that is stratified by sex provides a unique, highly accurate ISB-NormDB model (ISB-NormDB: ISB-NormDB-Male, ISB-NormDB-Female). To evaluate the trends and accuracy of the ISB-NormDB, we used actual data to compare Z-scores obtained through the ISB-NormDB with those obtained through a traditional QEEG normative database to confirm that basic trends are maintained in most bands and are sensitive to abnormal test data. Finally, we demonstrate the value of our standardized index of QEEG, and highlight it's capacity to minimize the confounding variables of sex and age in any analysis.

PMID:34975376 | PMC:PMC8718919 | DOI:10.3389/fnins.2021.766781

Front Neurol. 2021 Dec 8;12:724571. doi: 10.3389/fneur.2021.724571. eCollection 2021.

ABSTRACT

Background: We aimed to explore whether transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) can improve prognosis evaluation in patients with a large hemispheric infarction (LHI) and to establish an accurate prognosis prediction model. Methods: We prospectively assessed 90-day mortality in patients with LHI. Brain function was monitored using TCD-QEEG at the bedside of the patient. Results: Of the 59 (55.3 ± 10.6 years; 17 men) enrolled patients, 37 (67.3%) patients died within 90 days. The Cox regression analyses revealed that the Glasgow Coma Scale (GCS) score ≤ 8 [hazard ratio (HR), 3.228; 95% CI, 1.335-7.801; p = 0.009], TCD-terminal internal carotid artery as the offending vessel (HR, 3.830; 95% CI, 1.301-11.271; p = 0.015), and QEEG-a (delta + theta)/(alpha + beta) ratio ≥ 3 (HR, 3.647; 95% CI, 1.170-11.373; p = 0.026) independently predicted survival duration. Combining these three factors yielded an area under the receiver operating characteristic curve of 0.905 and had better predictive accuracy than those of individual variables (p < 0.05). Conclusion: TCD and QEEG complement the GCS score to create a reliable multimodal method for monitoring prognosis in patients with LHI.

PMID:34956039 | PMC:PMC8693413 | DOI:10.3389/fneur.2021.724571

J Pers Med. 2021 Dec 6;11(12):1315. doi: 10.3390/jpm11121315.

ABSTRACT

The results of quantitative electroencephalography (qEEG) studies on electroconvulsive therapy (ECT) have been inconsistent, and indicators of the efficacy of ECT have not been clearly identified. In this study, we examined whether qEEG could be used as an indicator of the effect of ECT by measuring it during the course of treatment. We analyzed qEEG data before and after acute-phase ECT in 18 patients with schizophrenia, mood disorders, and other psychiatric disorders. We processed the qEEG data and compared the spectral power between the data acquired before and after ECT. The spectral power increased significantly after ECT in the delta, theta, and alpha bands. There was a strong significant correlation between the increase in the spectral power of the alpha band after acute ECT and improvement in the Brief Psychiatric Rating Scale score. Our results suggest that an increase in the alpha-band spectral power may be useful as an objective indicator of the treatment effect of acute ECT.

PMID:34945787 | PMC:PMC8703644 | DOI:10.3390/jpm11121315

Basic Clin Neurosci. 2021 Mar-Apr;12(2):281-290. doi: 10.32598/bcn.12.2.2378.1. Epub 2021 Mar 1.

ABSTRACT

INTRODUCTION: Generalized Anxiety Disorder (GAD) is one of the most common anxiety disorders that has significant adverse effects on social functioning, occupational/academic performance, and daily living. This study aimed to evaluate the effect of Quantitative Electroencephalography (QEEG)-based Neurofeedback (NFB) therapy on anxiety, depression, and emotion regulation of people with GAD.

METHODS: This research is a quasi-experimental study with a pre-test/post-test/follow-up design and a control group. The study participants were 29 college students with GAD living in Zanjan City, Iran, who were selected using a convenience sampling method. Then, they were randomly divided into two groups of intervention (n=15) and control (n=14). The protocol of NFB therapy was designed based on the QEEG method. The intervention group received QEEG-based NFB therapy for 8 weeks (20 sessions, 2 sessions per week, each session for 45 min), while the control group received no intervention. The samples were surveyed and measured by using a 7-item GAD scale, Emotion Regulation Questionnaire (ERQ), 21-item Depression, Anxiety, and Stress Scale (DASS), and Structured Clinical Interview for DSM (SCID) before and after the intervention and then at a 3-month follow-up. The collected data were analyzed in SPSS software V. 22 using univariate ANCOVA and repeated measures ANOVA.

RESULTS: The within-subjects effect of time (pre-test, post-test, and follow-up) was statistically significant (P=0.031). The intervention group showed significant changes in the post-test and follow-up phases in comparison with the control group. The anxiety and depression levels of patients reduced significantly (P=0.001), and their emotion regulation improved (P=0.001) after the intervention, and they remained unchanged in the follow-up period.

CONCLUSION: QEEG-based NFB therapy can reduce anxiety and depression and improve emotion regulation in patients with GAD.

PMID:34925724 | PMC:PMC8672673 | DOI:10.32598/bcn.12.2.2378.1

Clin EEG Neurosci. 2021 Dec 20:15500594211064008. doi: 10.1177/15500594211064008. Online ahead of print.

ABSTRACT

Objective: Complexity analysis is a method employed to understand the activity of the brain. The effect of methylphenidate (MPH) treatment on neuro-cortical complexity changes is still unknown. This study aimed to reveal how MPH treatment affects the brain complexity of children with attention deficit hyperactivity disorder (ADHD) using entropy-based quantitative EEG analysis. Three embedding entropy approaches were applied to short segments of both pre- and post- medication EEG series. EEG signals were recorded for 25 boys with combined type ADHD prior to the administration of MPH and at the end of the first month of the treatment. Results: In comparison to Approximate Entropy (ApEn) and Sample Entropy (SampEn), Permutation Entropy (PermEn) provided the most sensitive estimations in investigating the impact of MPH treatment. In detail, the considerable decrease in EEG complexity levels were observed at six cortical regions (F3, F4, P4, T3, T6, O2) with statistically significant level (p < .05). As well, PermEn provided the most meaningful associations at central lobes as follows: 1) The largeness of EEG complexity levels was moderately related to the severity of ADHD symptom detected at pre-treatment stage. 2) The percentage change in the severity of opposition as the symptom cluster was moderately reduced by the change in entropy. Conclusion: A significant decrease in entropy levels in the frontal region was detected in boys with combined type ADHD undergoing MPH treatment at resting-state mode. The changes in entropy correlated with pre-treatment general symptom severity of ADHD and conduct disorder symptom cluster severity.

PMID:34923863 | DOI:10.1177/15500594211064008

Neuropsychopharmacol Rep. 2022 Mar;42(1):21-31. doi: 10.1002/npr2.12220. Epub 2021 Dec 10.

ABSTRACT

INTRODUCTION: Vortioxetine has a positive effect on cognitive function in patients with major depressive disorder (MDD). This study aimed to examine the changes in cognitive function and EEG (spectral power and mismatch negativity (MMN)) in patients with MDD pre- and postvortioxetine treatment.

METHODS: Thirty patients with MDD were included in the study. They were given vortioxetine (10-20mg po per day) for eight weeks. Depression and anxiety severities, social function (Korean version of the social adjustment scale (K-SAS)), and cognitive function (digit-symbol substitution Test (DSST), Korean version of the attentional control questionnaire (K-ACQ), and Korean version of the perceived deficits questionnaire for depression (K-PDQD)) were evaluated. Spectral power of EEG and MMN was also measured pre- and postvortioxetine treatment.

RESULTS: Depression and anxiety severity, social function, and cognitive functioning significantly improved after vortioxetine treatment. Also, there was a significant decrease in the right central delta band and an increase in the right central beta 2 band following vortioxetine treatment. The changes in EEG spectral power were not related to changes in cognitive functions. Baseline MMN significantly predicted changes in DSST score after controlling for the baseline clinical variables.

CONCLUSION: Vortioxetine treatment improved cognitive function and induced changes in EEG (decreased theta power and increased beta power) in patients with MDD. Our results suggest that greater negative MMN amplitude is associated with greater potential for cognitive improvement following vortioxetine treatment.

PMID:34894110 | PMC:PMC8919117 | DOI:10.1002/npr2.12220

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:997-1000. doi: 10.1109/EMBC46164.2021.9629946.

ABSTRACT

Electroencephalography (EEG) is an effective and non-invasive technique commonly used to monitor brain activity and assist in outcome prediction for comatose patients post cardiac arrest. EEG data may demonstrate patterns associated with poor neurological outcome for patients with hypoxic injury. Thus, both quantitative EEG (qEEG) and clinical data contain prognostic information for patient outcome. In this study we use machine learning (ML) techniques, random forest (RF) and support vector machine (SVM) to classify patient outcome post cardiac arrest using qEEG and clinical feature sets, individually and combined. Our ML experiments show RF and SVM perform better using the joint feature set. In addition, we extend our work by implementing a convolutional neural network (CNN) based on time-frequency images derived from EEG to compare with our qEEG ML models. The results demonstrate significant performance improvement in outcome prediction using non-feature based CNN compared to our feature based ML models. Implementation of ML and DL methods in clinical practice have the potential to improve reliability of traditional qualitative assessments for postanoxic coma patients.

PMID:34891456 | DOI:10.1109/EMBC46164.2021.9629946

Front Comput Neurosci. 2021 Nov 11;15:755499. doi: 10.3389/fncom.2021.755499. eCollection 2021.

ABSTRACT

The use of positron emission tomography (PET) as the initial or sole biomarker of β-amyloid (Aβ) brain pathology may inhibit Alzheimer's disease (AD) drug development and clinical use due to cost, access, and tolerability. We developed a qEEG-ML algorithm to predict Aβ pathology among subjective cognitive decline (SCD) and mild cognitive impairment (MCI) patients, and validated it using Aβ PET. We compared QEEG data between patients with MCI and those with SCD with and without PET-confirmed beta-amyloid plaque. We compared resting-state eyes-closed electroencephalograms (EEG) patterns between the amyloid positive and negative groups using relative power measures from 19 channels (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), divided into eight frequency bands, delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz) calculated by FFT and denoised by iSyncBrain^®. The resulting 152 features were analyzed using a genetic algorithm strategy to identify optimal feature combinations and maximize classification accuracy. Guided by gene modeling methods, we treated each channel and frequency band of EEG power as a gene and modeled it with every possible combination within a given dimension. We then collected the models that showed the best performance and identified the genes that appeared most frequently in the superior models. By repeating this process, we converged on a model that approximates the optimum. We found that the average performance increased as this iterative development of the genetic algorithm progressed. We ultimately achieved 85.7% sensitivity, 89.3% specificity, and 88.6% accuracy in SCD amyloid positive/negative classification, and 83.3% sensitivity, 85.7% specificity, and 84.6% accuracy in MCI amyloid positive/negative classification.

PMID:34867252 | PMC:PMC8632633 | DOI:10.3389/fncom.2021.755499

Neurol Clin Pract. 2021 Oct;11(5):420-428. doi: 10.1212/CPJ.0000000000001107.

ABSTRACT

OBJECTIVE: Our primary objective was to determine the performance of real-time neuroscience intensive care unit (neuro-ICU) nurse interpretation of quantitative EEG (qEEG) at the bedside for seizure detection. Secondary objectives included determining nurse time to seizure detection and assessing factors that influenced nurse accuracy.

METHODS: Nurses caring for neuro-ICU patients undergoing continuous EEG (cEEG) were trained using a 1-hour qEEG panel (rhythmicity spectrogram and amplitude-integrated EEG) bedside display. Nurses' hourly interpretations were compared with post hoc cEEG review by 2 neurophysiologists as the gold standard. Diagnostic performance, time to seizure detection compared with standard of care (SOC), and effects of other factors on nurse accuracy were calculated.

RESULTS: A total of 109 patients and 65 nurses were studied. Eight patients had seizures during the study period (7%). Nurse sensitivity and specificity for the detection of seizures were 74% and 92%, respectively. Mean nurse time to seizure detection was significantly shorter than SOC by 132 minutes (Cox proportional hazard ratio 6.96). Inaccurate nurse interpretation was associated with increased hours monitored and presence of brief rhythmic discharges.

CONCLUSIONS: This prospective study of real-time nurse interpretation of qEEG for seizure detection in neuro-ICU patients showed clinically adequate sensitivity and specificity. Time to seizure detection was less than that of SOC.

TRIAL REGISTRATION INFORMATION: Clinical trial registration number NCT02082873.

CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that neuro-ICU nurse interpretation of qEEG detects seizures in adults with a sensitivity of 74% and a specificity of 92% compared with traditional cEEG review.

PMID:34840869 | PMC:PMC8610554 | DOI:10.1212/CPJ.0000000000001107

Behav Sci Law. 2021 Oct;39(5):597-610. doi: 10.1002/bsl.2548. Epub 2021 Nov 20.

ABSTRACT

The main goals of the present study were to replicate and extend current knowledge related to paralimbic dysfunctions associated with psychopathy. The research evaluated the quantitative electroencephalography, current density (CD) source and synchronization likelihood analysis during the rest condition and structural magnetic resonance imaging images to compare volumetric and cortical thickness, in inmates recruited from two prisons located in Havana City. The Psychopathy Checklist-Revised (PCL-R) was used as a quantitative measure of psychopathy. This study showed most beta energy and less alpha activity in male psychopath offenders. Low-resolution electromagnetic tomography signified an increase of beta activity in psychopath offender groups within paralimbic regions. The superior temporal gyrus volume was associated with the F1 factor while the fusiform, anterior cingulate and associative occipital areas were primarily associated with the F2 factor of PCL-R scale. Cortical thickness in the left dorsal anterior cingulate cortex and the temporal pole was negatively associated with PCL-R total score.

PMID:34800344 | DOI:10.1002/bsl.2548

Clin EEG Neurosci. 2021 Nov 18:15500594211058260. doi: 10.1177/15500594211058260. Online ahead of print.

ABSTRACT

Background: Electroconvulsive therapy (ECT) is a clinically effective treatment for schizophrenia (SZD). However, studies have shown that only about 50 to 80% of patients show response to ECT. To identify the most suitable patients for ECT, developing biomarkers predicting ECT response remains an important goal. This study aimed to explore the quantitative electroencephalography (QEEG) biomarkers to predict ECT efficacy. Methods: Thirty patients who met DSM-5 criteria for SZD and had been assigned to ECT were recruited. 32-lead Resting-EEG recordings were collected one hour before the initial ECT treatment. Positive and negative symptoms scale (PANSS) was assessed at baseline and after the eighth ECT session. EEG data were analyzed using mutual information. Results: In the brain network density threshold range of 0.05 to 0.2, the assortativity of the right temporal, right parietal, and right occipital cortex in the response group was significantly higher than that in the non-response group (p < .05) in the beta band. In the theta band, the left frontal, parietal, right occipital cortex, and central area assortativity were higher in the response group than in the non-response group (p < .05). Conclusions: QEEG might be a useful approach to identify the candidate biomarker for ECT in clinical practice.

PMID:34792399 | DOI:10.1177/15500594211058260

Neurocrit Care. 2022 Jun;36(3):897-904. doi: 10.1007/s12028-021-01395-x. Epub 2021 Nov 17.

ABSTRACT

BACKGROUND: The objective of this study was to evaluate the accuracy of seizure burden in patients with super-refractory status epilepticus (SRSE) by using quantitative electroencephalography (qEEG).

METHODS: EEG recordings from 69 patients with SRSE (2009-2019) were reviewed and annotated for seizures by three groups of reviewers: two board-certified neurophysiologists using only raw EEG (gold standard), two neurocritical care providers with substantial experience in qEEG analysis (qEEG experts), and two inexperienced qEEG readers (qEEG novices) using only a qEEG trend panel.

RESULTS: Raw EEG experts identified 35 (51%) patients with seizures, accounting for 2950 seizures (3,126 min). qEEG experts had a sensitivity of 93%, a specificity of 61%, a false positive rate of 6.5 per day, and good agreement (κ = 0.64) between both qEEG experts. qEEG novices had a sensitivity of 98.5%, a specificity of 13%, a false positive rate of 15 per day, and fair agreement (κ = 0.4) between both qEEG novices. Seizure burden was not different between the qEEG experts and the gold standard (3,257 vs. 3,126 min), whereas qEEG novices reported higher burden (6066 vs. 3126 min).

CONCLUSIONS: Both qEEG experts and novices had a high sensitivity but a low specificity for seizure detection in patients with SRSE. qEEG could be a useful tool for qEEG experts to estimate seizure burden in patients with SRSE.

PMID:34791594 | DOI:10.1007/s12028-021-01395-x

J Sleep Res. 2022 Jun;31(3):e13517. doi: 10.1111/jsr.13517. Epub 2021 Nov 13.

ABSTRACT

Wind turbine noise is dominated by low frequencies for which effects on sleep relative to more common environmental noise sources such as road traffic noise remain unknown. This study examined the effect of wind turbine noise compared with road traffic noise on sleep using quantitative electroencephalogram power spectral analysis. Twenty-three participants were exposed to 3-min samples of wind turbine noise and road traffic noise at three sound pressure levels (33, 38 and 43 dBA) in randomised order during established sleep. Acute (0-30 s) and more sustained (30-180 s) effects of noise presentations during N2 and N3 sleep were examined using spectral analysis of changes in electroencephalogram power frequency ranges across time in 5-s intervals. Both noise types produced time- and sound pressure level-dependent increases in electroencephalogram power, but with significant noise type by sound pressure level interactions in beta, alpha, theta and delta frequency bands (all p < 0.05). Wind turbine noise showed significantly lower delta, theta and beta activity immediately following noise onset compared with road traffic noise (all p < 0.05). However, alpha activity was higher for wind turbine noise played at lower sound pressure levels (33 dBA [p = 0.001] and 38 dBA [p = 0.003]) compared with traffic noise during N2 sleep. These findings support that spectral analyses show subtle effects of noise on sleep and that electroencephalogram changes following wind turbine noise and road traffic noise onset differ depending on sound pressure levels; however, these effects were mostly transient and had little impact on conventionally scored sleep. Further studies are needed to establish if electroencephalogram changes associated with modest environmental noise exposures have significant impacts on sleep quality and next-day functioning.

PMID:34773428 | DOI:10.1111/jsr.13517

Front Hum Neurosci. 2021 Oct 8;15:741446. doi: 10.3389/fnhum.2021.741446. eCollection 2021.

ABSTRACT

Renal failure and diabetes can induce cerebral complications, including encephalopathy, for which attentional and cognitive impairment are common symptoms. It is possible that renal failure with comorbid diabetes may induce more severe encephalopathy due to multiple pathogenic mechanisms. This concept was supported by the main findings of this study, which showed that EEG background activity between end-stage renal disease with and without comorbid diabetes was significantly different in relative power of delta in the eyes-open condition in frontoparietal regions; theta in the eyes-closed condition in all regions; beta in the parieto-occipital regions in both eye conditions; the delta/theta ratio in both eye conditions in frontoparietal regions; and the theta/beta ratio in all regions in the eyes-closed condition. These findings may increase awareness of comorbid cerebral complications in clinical practice. Moreover, the delta/theta ratio is recommended as an optimal feature to possibly determine the severity of encephalopathy.

PMID:34690724 | PMC:PMC8531714 | DOI:10.3389/fnhum.2021.741446

J Stroke Cerebrovasc Dis. 2022 Jan;31(1):106158. doi: 10.1016/j.jstrokecerebrovasdis.2021.106158. Epub 2021 Oct 21.

ABSTRACT

BACKGROUND: Computer-assisted electroencephalography (EEG) systems may improve the likelihood of detecting abnormal EEGs in adult patients with severe disease.

CASE PRESENTATION: We implemented long-range EEG monitoring in a patient with large hemispheric infarction (LHI) and explored its real-time changes in reflecting the patient's brain function. The bands of Alpha, Beta, Delta, Theta, DAR (Delta/Alpha), DTABR (Delta+Theta/Alpha+Beta), and brain symmetry index (BSI) were calculated as a ratio of total power. The test results showed that this patient presents a progressive worsening trend and developed brain herniation. The sigh at the electrophysiological level of brain herniation could be seen 6 h in advance based on the quantitative EEG (QEEG) parameters test. We calculated QEEG at both C3 and C4, electrode locations simultaneously, and the results showed that the trend of QEEG at both electrodes was consistent with the global, affected, and unaffected side.

CONCLUSIONS: QEEG parameters can reflect the trend of LHI patients in real-time and may predict the occurrence of LHI brain herniation. For LHI patients, monitoring with fewer EEG electrodes can be tried to predict the changes in conditions.

PMID:34688212 | DOI:10.1016/j.jstrokecerebrovasdis.2021.106158

Acta Neurol Scand. 2022 Feb;145(2):239-248. doi: 10.1111/ane.13543. Epub 2021 Oct 22.

ABSTRACT

OBJECTIVES: To evaluate the usefulness of quantitative electroencephalography (qEEG) in the analysis of baseline activity in patients with temporal lobe epilepsy (TLE) and identify measures potentially associated with disease duration and drug resistance.

MATERIALS AND METHODS: Cross-sectional study of adult patients with TLE and controls who underwent video-EEG monitoring. Representative artifact-free resting wakefulness baseline EEG segments were selected for quantitative analysis. The fast Fourier transform (FFT) approach was used for the power spectral analysis, with computation of FFT power ratios and alpha-delta and alpha-theta ratios for both hemispheres. The resulting measures were compared between TLE patients and controls and their values as predictors of epilepsy duration and drug resistance analyzed.

RESULTS: Thirty-nine TLE patients and 23 controls were included. The TLE patients had a lower alpha-delta ratio in the posterior quadrant ipsilateral to the epileptic focus and a lower alpha-theta ratio in the ipsilateral anterior/posterior quadrants and temporal region. A younger age at onset and longer epilepsy duration correlated with a higher theta power ratio in the contralateral anterior and posterior quadrants and temporal region. No qEEG measures predicted drug resistance.

CONCLUSIONS: Quantitative electroencephalography background activity may contribute to the diagnosis of TLE and provide useful information on disease duration. A lower alpha-delta and alpha-theta ratio may be reliable baseline qEEG measures for identifying patients with TLE. A higher contralateral theta power ratio may be indicative of longer epilepsy duration.

PMID:34687043 | DOI:10.1111/ane.13543

Brain Sci. 2021 Oct 16;11(10):1359. doi: 10.3390/brainsci11101359.

ABSTRACT

The apolipoprotein E (APOE) ε4 allele is a risk factor for Alzheimer's disease (AD) that has been linked to changes in brain structure and function as well as to different biological subtypes of the disease. The present study aimed to investigate the association of APOE ε4 genotypes with brain functional impairment, as assessed by quantitative EEG (qEEG) in patients on the AD continuum. The study population included 101 amyloid positive patients diagnosed with mild cognitive impairment (MCI) (n = 50) and AD (n = 51) that underwent resting-state EEG recording and CSF Aβ42 analysis. In total, 31 patients were APOE ε4 non-carriers, 42 were carriers of one, and 28 were carriers of two APOE ε4 alleles. Quantitative EEG analysis included computation of the global field power (GFP) and global field synchronization (GFS) in conventional frequency bands. Amyloid positive patients who were carriers of APOE ε4 allele(s) had significantly higher GFP beta and significantly lower GFS in theta and beta bands compared to APOE ε4 non-carriers. Increased global EEG power in beta band in APOE ε4 carriers may represent a brain functional compensatory mechanism that offsets global EEG slowing in AD patients. Our findings suggest that decreased EEG measures of global synchronization in theta and beta bands reflect brain functional deficits related to the APOE ε4 genotype in patients that are on a biomarker-verified AD continuum.

PMID:34679423 | PMC:PMC8533770 | DOI:10.3390/brainsci11101359

Int J Psychophysiol. 2021 Dec;170:89-101. doi: 10.1016/j.ijpsycho.2021.10.004. Epub 2021 Oct 15.

ABSTRACT

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) represents a significant public health challenge given the presence of many unexplained patient symptoms. Research has shown that many features in ME/CFS may result from a dysfunctional autonomic nervous system (ANS). We explored the role of the cortical autonomic network (CAN) involved in higher-order control of ANS functioning in 34 patients with ME/CFS and 34 healthy controls under task-free conditions. All participants underwent resting-state quantitative electroencephalographic (qEEG) scalp recordings during an eyes-closed condition. Source analysis was performed using exact low-resolution electromagnetic tomography (eLORETA), and lagged coherence was used to estimate intrinsic functional connectivity between each node across 7 frequency bands: delta (1-3 Hz), theta (4-7 Hz), alpha-1 (8-10 Hz), alpha-2 (10-12 Hz), beta-1 (13-18 Hz), beta-2 (19-21 Hz), and beta-3 (22-30 Hz). Symptom ratings were measured using the DePaul Symptom Questionnaire and the Short Form (SF-36) health survey. Graph theoretical analysis of weighted, undirected connections revealed significant group differences in baseline CAN organization. Regression results showed that cognitive, affective, and somatomotor symptom cluster ratings were associated with alteration to CAN topology in patients, depending on the frequency band. These findings provide evidence for reduced higher-order homeostatic regulation and adaptability in ME/CFS. If confirmed, these findings address the CAN as a potential therapeutic target for managing patient symptoms.

PMID:34662673 | DOI:10.1016/j.ijpsycho.2021.10.004