The utility of wearable headband electroencephalography and pulse photoplethysmography to assess cortical and physiological arousal in individuals with stress-related mental disorders.

Several stress-related mental disorders are characterised by disturbed sleep, but objective sleep biomarkers are not routinely examined in psychiatric patients. We examined the use of wearable-based sleep biomarkers in a psychiatric sample with headband electroencephalography (EEG) including pulse photoplethysmography (PPG), with an additional focus on microstructural elements as especially the shift from low to high frequencies appears relevant for several stress-related mental disorders. We analysed 371 nights of sufficient quality from 83 healthy participants and those with a confirmed stress-related mental disorder (anxiety-affective spectrum). The median value of macrostructural, microstructural (spectral slope fitting), and heart rate variables was calculated across nights and analysed at the individual level (N = 83). The headbands were accepted well by patients and the data quality was sufficient for most nights. The macrostructural analyses revealed trends for significance regarding sleep continuity but not sleep depth variables. The spectral analyses yielded no between-group differences except for a group × age interaction, with the normal age-related decline in the low versus high frequency power ratio flattening in the patient group. The PPG analyses showed that the mean heart rate was higher in the patient group in pre-sleep epochs, a difference that reduced during sleep and dissipated at wakefulness. Wearable devices that record EEG and/or PPG could be used over multiple nights to assess sleep fragmentation, spectral balance, and sympathetic drive throughout the sleep-wake cycle in patients with stress-related mental disorders and healthy controls, although macrostructural and spectral markers did not differ between the two groups.

Cognitive function and quantitative electroencephalogram analysis in subjects recovered from COVID-19 infection.

BACKGROUND & OBJECTIVES: Objective assessment of post-COVID-19 cognitive dysfunction is highly warranted. This study aimed to evaluate the cognitive dysfunction of COVID-19 survivors with cognitive complaints, both clinically and neurophysiologically, using Quantitative Electroencephalogram (QEEG). METHODS: This case-control study was conducted on 50 recovered subjects from COVID-19 infection with cognitive complaints and 50 age, sex, and educational-matched healthy controls. Both groups were subjected to the following neurocognitive tests: Paired associate learning Test (PALT) and Paced Auditory Serial Addition Test (PASAT). The neurophysiological assessment was also done for both groups using QEEG. RESULTS: COVID-19 survivors had significantly lower PALT scores than controls (P < 0.001). QEEG analysis found significantly higher levels of Theta / Beta ratio in both central and parietal areas in patients than in the controls (P < 0.001 for each). The interhemispheric coherence for the frontal, central, and parietal regions was also significantly lower in patients than in the control group regarding alpha and beta bands. There were statistically significant lower scores of PALT and PASAT among cases with severe COVID-19 infection (P = 0.011, 0.005, respectively) and those who needed oxygen support (P = 0.04, 0.01, respectively). On the other hand, a statistically significantly lower mean of frontal alpha inter-hemispheric coherence among patients with severe COVID-19 infection (P = 0.01) and those needing mechanical ventilation support (P = 0.04). CONCLUSION: Episodic memory deficit is evident in COVID-19 survivors with subjective cognitive complaints accompanied by lower inter-hemispheric coherence in frontal regions. These clinical and neurophysiological changes are associated with hypoxia and COVID-19 severity.

Quantitative electroencephalography (qEEG), apolipoprotein A-I (APOA-I), and apolipoprotein epsilon 4 (APOE ɛ4) alleles for the diagnosis of mild cognitive impairment and Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is the most common type of dementia. Amnestic mild cognitive impairment (aMCI), a pre-dementia stage is an important stage for early diagnosis and intervention. This study aimed to investigate the diagnostic value of qEEG, APOA-I, and APOE ɛ4 allele in aMCI and AD patients and found the correlation between qEEG (Delta + Theta)/(Alpha + Beta) ratio (DTABR) and different cognitive domains. METHODS: All participants were divided into three groups: normal controls (NCs), aMCI, and AD, and all received quantitative electroencephalography (qEEG), neuropsychological scale assessment, apolipoprotein epsilon 4 (APOE ɛ4) alleles, and various blood lipid indicators. Different statistical methods were used for different data. RESULTS: The cognitive domains except executive ability were all negatively correlated with DTABR in different brain regions while executive ability was positively correlated with DTABR in several brain regions, although without statistical significance. The consequences confirmed that the DTABR of each brain area were related to MMSE, MoCA, instantaneous memory, and the language ability (p < 0.05), and the DTABR in the occipital area was relevant to all cognitive domains (p < 0.01) except executive function (p = 0.272). Also, occipital DTABR was most correlated with language domain when tested by VFT with a moderate level (r = 0.596, p < 0.001). There were significant differences in T3, T5, and P3 DTABR between both AD and NC and aMCI and NCs. As for aMCI diagnosis, the maximum AUC was achieved when using T3 combined with APOA-I and APOE ε4 (0.855) and the maximum AUC was achieved when using T5 combined with APOA-I and APOE ε4 (0.889) for AD diagnosis. CONCLUSION: These findings highlight that APOA-I, APOE ɛ4, and qEEG play an important role in aMCI and AD diagnosis. During AD continuum, qEEG DTABR should be taken into consideration for the early detection of AD risk.

Effect of intra-operative Magnesium sulphate on the occurrence of post-operative delirium and insomnia in patients undergoing lumbar fixation: a randomized controlled trial.

BACKGROUND: Over the last two decades, a large body of literature has focused on studying the prevalence and outcome of the postoperative delirium and sleep disturbance. The aim of this work was to evaluate the effect of intraoperative administration of Magnesium sulphate on the occurrence of post-operative delirium and insomnia in patients undergoing lumbar fixation. METHODS: This prospective randomized controlled trial was carried out on 80 patients indicated for lumbar fixation; 40 of them received conventional general anesthesia with extra administration of intraoperative magnesium sulphate (Mg sulphate group), and the other 40 received conventional general anesthesia only (control group). Both groups were submitted to pre-operative assessment of depression using Beck Depression inventory (BDI) scale, pre-operative assessment of fatigue using a fatigue questionnaire, pre- and post-operative assessment of insomnia using Insomnia severity index (ISI), post-operative assessment of delirium using Memorial delirium assessment scale (MDAS), post-operative assessment of pain using Visual Analogue Scale (VAS), and pre- and post-operative Quantitative electroencephalography (QEEG). RESULTS: Mg sulphate administration, age, pre-operative BDI, pre-operative ISI, and post-operative VAS were independent predictors of post-operative ISI (P-value < 0.001, 0.047, 0.021, < 0.001, and < 0.001 respectively). Age and post-operative VAS were independent predictors of post-operative MDAS (P-value = 0.008, 0.013 respectively). Mg sulphate administration and pre-operative ISI were independent predictors of post-operative VAS (P-value = 0.010, 0.006 respectively). CONCLUSION: There was a significant relationship between intraoperative Mg sulphate administration and both post-operative insomnia and pain in unadjusted and adjusted analysis.

Neurofeedback and epilepsy: Renaissance of an old self-regulation method?

Neurofeedback is a brain-computer interface tool enabling the user to self-regulate their neuronal activity, and ultimately, induce long-term brain plasticity, making it an interesting instrument to cure brain disorders. Although this method has been used successfully in the past as an adjunctive therapy in drug-resistant epilepsy, this approach remains under-explored and deserves more rigorous scientific inquiry. In this review, we present early neurofeedback protocols employed in epilepsy and provide a critical overview of the main clinical studies. We also describe the potential neurophysiological mechanisms through which neurofeedback may produce its therapeutic effects. Finally, we discuss how to innovate and standardize future neurofeedback clinical trials in epilepsy based on evidence from recent research studies.

Use of Some Relevant Parameters for Primary Prediction of Brain Activity in Idiopathic Tinnitus Based on a Machine Learning Application.

INTRODUCTION: Tinnitus is one of the most common complaints, distressing about 15-24% of the adult population. Because of its pathophysiology heterogeneity, no curable treatment has been attained yet. Even though a neuromodulation management technique based on the tinnitus network model is currently being developed, it has not yet worked because the most involved brain areas still remain unpredictable from the patient's individual clinical and functional profile. A remarkable correlation between tinnitus network activity and the subjective measures of tinnitus like perceived loudness and annoyance and functional handicap is well established. Therefore, this study aimed to develop software for predicting the involved brain areas in the tinnitus network based on the subjective characteristics and clinical profile of patients using a supervised machine-learning method. METHODS: The involved brain areas of 30 tinnitus patients ranging from 6 to 80 months in duration were recognized by using QEEG and sLORETA software. There was a correlation between subjective information and those areas of activities in all rhythms by which we wrote our software. RESULTS: For verification and validation of the software, we compared and analyzed the results with SPSS data and the receiver operating characteristic (ROC) curves. CONCLUSIONS: The findings of this study confirmed the effectiveness of the software in predicting the brain activity in tinnitus subjects; however, some other important parameters can be added to the model to strengthen its reliability and feasibility in clinical use.

Contemplating on the Nature of Selfhood in DoC Patients: Neurophenomenological Perspective.

Medical well-regarded policy recommendations for patients with disorders of consciousness (DoC) are almost exclusively relied on behavioural examination and evaluation of higher-order cognition, and largely disregard the patients' self. This is so because practically establishing the presence of self-awareness or Selfhood is even more challenging than evaluating the presence of consciousness. At the same time, establishing the potential (actual physical possibility) of Selfhood in DoC patients is crucialy important from clinical, ethical, and moral standpoints because Selfhood is the most central and private evidence of being an independent and free agent that unites intention, embodiment, executive functions, attention, general intelligence, emotions and other components within the intra-subjective frame (first-person givenness). The importance of Selfhood is supported further by the observation that rebooting of self-awareness is the first step to recovery after brain damage. It seems that complex experiential Selfhood can be plausibly conceptualized within the Operational Architectonics (OA) of brain-mind functioning and reliably measured by quantitative electroencephalogram (qEEG) operational synchrony.

An Attempt to Develop a Model of Brain Waves Using Quantitative Electroencephalography with Closed Eyes in K1 Kickboxing Athletes-Initial Concept.

BACKGROUND: Brain injuries are a common problem in combat sports, especially in disciplines such as kickboxing. Kickboxing is a combat sport that has several variations of competition, with the most contact-oriented fights being carried out under the format of K-1 rules. While these sports require a high level of skill and physical endurance, frequent micro-traumas to the brain can have serious consequences for the health and well-being of athletes. According to studies, combat sports are one of the riskiest sports in terms of brain injuries. Among the sports disciplines with the highest number of brain injuries, boxing, mixed martial arts (MMA), and kickboxing are mentioned. METHODS: The study was conducted on a group of 18 K-1 kickboxing athletes who demonstrate a high level of sports performance. The subjects were between the ages 18 and 28. QEEG (quantitative electroencephalogram) is a numeric spectral analysis of the EEG record, where the data is digitally coded and statistically analysed using the Fourier transform algorithm. Each examination of one person lasts about 10 min with closed eyes. The wave amplitude and power for specific frequencies (Delta, Theta, Alpha, Sensorimotor Rhythm (SMR), Beta 1, and Beta2) were analysed using 9 leads. RESULTS: High values were shown in the Alpha frequency for central leads, SMR in the Frontal 4 (F4 lead), Beta 1 in leads F4 and Parietal 3 (P3), and Beta2 in all leads. CONCLUSIONS: The high activity of brainwaves such as SMR, Beta and Alpha can have a negative effect on the athletic performance of kickboxing athletes by affecting focus, stress, anxiety, and concentration. Therefore, it is important for athletes to monitor their brainwave activity and use appropriate training strategies to achieve optimal results.

Preliminary Development of a Brainwave Model for K1 Kickboxers Using Quantitative Electroencephalography (QEEG) with Open Eyes.

K1 kickboxing fighting is characterised by high injury rates due to the low restrictions of fighting rules. In recent years, much attention has been paid to research on changes in brain function among athletes, including those in combat sports. One of the tools that are likely to help diagnose and assess brain function is quantitative electroencephalography (QEEG). Therefore, the aim of the present study was an attempt to develop a brainwave model using quantitative electroencephalography in competitive K1 kickboxers. A total of thirty-six male individuals were purposefully selected and then comparatively divided into two groups. The first group consisted of specialised K1 kickboxing athletes exhibiting a high level of sports performance (experimental group, n = 18, mean age: 29.83 ± 3.43), while the second group comprised healthy individuals not training competitively (control group, n = 18, mean age: 26.72 ± 1.77). Body composition assessment was performed in all participants before the main measurement process. Measurements were taken for kickboxers during the de-training period, after the sports competition phase. Quantitative electroencephalography of Delta, Theta, Alpha, sensimotor rhytm (SMR), Beta1 and Beta2 waves was performed using electrodes placed on nine measurement points (frontal: FzF3F4, central: CzC3C4, and parietal: PzP3P4) with open eyes. In the course of the analyses, it was found that the level of brain activity among the study population significantly differentiated the K1 formula competitors compared with the reference standards and the control group in selected measurement areas. For kickboxers, all results of the Delta amplitude activity in the area of the frontal lobe were significantly above the normative values for this wave. The highest value was recorded for the average value of the F3 electrode (left frontal lobe), exceeding the norm by 95.65%, for F4 by 74.45% and Fz by 50.6%, respectively. In addition, the Alpha wave standard value for the F4 electrode was exceeded by 14.6%. Normative values were found for the remaining wave amplitudes. Statistically significant differentiation of results, with a strong effect (d = 1.52-8.41), was shown for the activity of Delta waves of the frontal area and the central part of the parietal area (Fz,F3,F4,Cz-p < 0.001), Theta for the frontal area as well as the central and left parietal lobes (Fz,F3,F4-p < 0.001, Cz-p = 0.001, C3-p = 0.018; d = 1.05-3.18), Alpha for the frontal, parietal and occipital areas (for: Fz,F3-p < 0.001, F4-p = 0.036, Cz-p < 0.001, C3-p = 0.001, C4-p = 0.025, Pz-p = 0.010, P3-p < 0.001, P4-p = 0.038; d = 0.90-1.66), SMR for the central parietal and left occipital lobes (Cz-p = 0.043; d = 0.69, P3-p < 0.001; d = 1.62), Beta for the frontal area, occipital and central lobes and left parietal segment (Fz,F3-p < 0.001, F4-p = 0.008, Cz, C3, Pz, P3,P4-p < 0.001; d = 1.27-2.85) and Beta 2 for all measurement areas (Fz, F3, F4, Cz, C3, C4, Pz, P3, P4-p < 0.001; d = 1.90-3.35) among the study groups. Significantly higher results were shown in the kickboxer group compared to the control. In addition to problems with concentration or over-stimulation of neural structures, high Delta waves, with elevated Alpha, Theta and Beta 2 waves, can cause disorders in the limbic system and problems in the cerebral cortex.

Early protein energy malnutrition impacts life-long developmental trajectories of the sources of EEG rhythmic activity.

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.

Pathophysiological insight into transient global amnesia from quantitative electroencephalography.

Transient global amnesia (TGA) is recognized as a benign memory disorder, with characteristic clinical and imaging features. However, the pathophysiology of TGA remains elusive. This study aims to elucidate the pathophysiological changes underlying TGA by exploring the brain activities. In total, 215 patients with TGA (age: 61.8 ± 7.8 years; women: 146) with MRI (within 7 days) and EEG studies (within 90 days) were recruited. Quantitative EEG (QEEG) power spectra and network analysis were performed by the artificial intelligence EEG analysis platform (iSyncBrain®). Subgroup analyses were conducted for different clinical groups, based on symptom duration, EEG timing after onset, and cytotoxic lesions on the MRI. Compared with 252 age- and sex-matched subjects (age: 64.5 ± 8.3 years, women: 182), TGA patients showed a global decrease in absolute power in all band waves, a relative decrease in alpha waves, a relative increase in theta waves, and atypical compensation activity. These QEEG changes were observed regardless of having cytotoxic lesions in MRI and they were significant up to 1 week after symptom onset. Network analysis showed that TGA was more activated than normal controls in alpha1 band-waves, exhibiting a compensatory process. TGA results in prolonged and widespread alterations of brain activity and connectivity. QEEG provide insight into pathophysiology of TGA.

EEG power spectral responses to wind farm compared with road traffic noise during sleep: A laboratory study.

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.

Comparative analysis of background EEG activity based on MRI findings in neonatal hypoxic-ischemic encephalopathy: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study.

BACKGROUND: It is important to assess the degree of brain injury and predict long-term outcomes in neonates diagnosed with hypoxic-ischemic encephalopathy (HIE). However, routine studies, including magnetic resonance imaging (MRI) and conventional encephalography (EEG) or amplitude-integrated EEG (aEEG), have their own limitations in terms of availability and accuracy of evaluation. Recently, quantitative EEG (qEEG) has been shown to improve the predictive reliability of neonatal HIE and has been further refined with brain mapping techniques. METHODS: We investigated background EEG activities in 29 neonates with HIE who experienced therapeutic hypothermia, via qEEG using a distributed source model. MRI images were evaluated and classified into two groups (normal-to-mild injury vs moderate-to-severe injury), based on a scoring system. 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 the two groups. RESULTS: Electrical neuronal activities were significantly lower in the moderate-to-severe injury group compared with the normal-to-mild injury group. Background EEG activities in moderate-to-severe HIE were most significantly reduced in the temporal and parietal lobes. Quantitative EEG also revealed a decrease in background activity at all frequency bands, with a maximum in decrease in the delta component. The maximum difference in current density was found in the inferior parietal lobule of the right parietal lobe for the delta frequency band. CONCLUSIONS: Our study demonstrated quantitative and topographical changes in EEG in moderate-to-severe neonatal HIE. They also suggest possible implementation and evaluation of conventional EEG and aEEG in neonatal HIE. The findings have implications as biomarkers in the assessment of neonatal HIE.

Comparative analysis of background EEG activity in juvenile myoclonic epilepsy during valproic acid treatment: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study.

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.

The impact of nutritive and non-nutritive sweeteners on the central nervous system: preliminary study.

BACKGROUND: Human consumption of food and beverages containing added nutritive or non-nutritive sweeteners has increased worldwide. OBJECTIVE: The present study evaluated the possible impact of frequent sweetener consumption on human CNS activity and functions through neuropsychological testing and EEG/qEEG analysis. METHODS: A sample of 23 women and 16 men, aged 18-35, with a body mass index between 18 and 24.9 kg/m2 was evaluated. Participants underwent a 1-week washout period in which food with added sugars or sweeteners was restricted from their diet. Initial assessment of cognitive functions was performed with a validated neuropsychological test and EEG/qEEG analysis, prior to supplementation. Sucrose, sucralose, or steviol glycosides, in commercially available presentations, were randomly assigned to three experimental groups of 13 participants each. Sweeteners were supplemented in fixed amounts, daily, for six weeks. After supplementation, neurological tests were repeated and the initial and final results were compared. RESULTS: The results show no significant changes between final and initial measures in the steviol glycosides group. However, a significant decrease in encoding memory was found in the sucrose group in the final evaluation. Strikingly, the sucralose group showed a significant decrease in overall memory, encoding memory, and executive functions after supplementation. Furthermore, qEEG analysis showed an increase in theta wave absolute and relative power at the final evaluation in the same group. CONCLUSION: These data show that frequent consumption of specific sweeteners is accompanied by measurable changes in EEG/qEEG activity and neuropsychological test performance in humans.

N-Pep-12 supplementation after ischemic stroke positively impacts frequency domain QEEG.

BACKGROUND: N-Pep-12 is a dietary supplement with neuroprotective and pro-cognitive effects, as shown in experimental models and clinical studies on patients after ischemic stroke. We tested the hypothesis that N-Pep-12 influences quantitative electroencephalography (QEEG) parameters in patients with subacute to chronic supratentorial ischemic lesions. METHODS: We performed secondary data analysis on an exploratory clinical trial (ISRCTN10702895), assessing the efficacy and safety of 90 days of once-daily treatment with 90 mg N-Pep-12 on neurocognitive function and neurorecovery outcome in patients with post-stroke cognitive impairment against a control group. All participants performed two 32-channel QEEG in resting and active states at baseline (30-120 days after stroke) and 90 days later. Power spectral density on the alpha, beta, theta, delta frequency bands, delta/alpha power ratio (DAR), and (delta+theta)/(alpha+beta) ratio (DTABR) were computed and compared across study groups using means comparison and descriptive methods. Secondarily, associations between QEEG parameters and available neuropsychological tests were explored. RESULTS: Our analysis showed a statistically significant main effect of EEG segments (p<0.001) in alpha, beta, delta, theta, DA, and DTAB power spectral density. An interaction effect between EEG segments and time was noticed in the alpha power. There was a significant difference in theta spectral power between patients with N-Pep-12 supplementation versus placebo at 0.05 alpha level (p=0.023), independent of time points. CONCLUSION: A 90-day, 90 mg daily administration of N-Pep-12 had significant impact on some QEEG indicators in patients after supratentorial ischemic stroke, confirming possible enhancement of post-stroke neurorecovery. Further research is needed to consolidate our findings.

Comparison of QEEG Findings before and after Onset of Post-COVID-19 Brain Fog Symptoms.

Previous research and clinical reports have shown that some individuals after COVID-19 infection may demonstrate symptoms of so-called brain fog, manifested by cognitive impairment and disorganization in behavior. Meanwhile, in several other conditions, related to intellectual function, a specific pattern of changes in electric brain activity, as recorded by quantitative electroencephalography (QEEG) has been documented. We hypothesized, that in post-COVID brain fog, the subjective complaints may be accompanied by objective changes in the QEEG profile. In order to test this hypothesis, we have performed an exploratory study on the academic staff of our University with previous records of QEEG originating in the pre-COVID-19 era. Among them, 20 subjects who revealed neurological problems in the cognitive sphere (confirmed as covid fog/brain fog by a clinical specialist) after COVID-19 infection were identified. In those individuals, QEEG was performed. We observed, that opposite to baseline QEEG records, increased Theta and Alpha activity, as well as more intensive sensimotor rhythm (SMR) in C4 (right hemisphere) in relation to C3 (left hemisphere). Moreover, a visible increase in Beta 2 in relation to SMR in both hemispheres could be documented. Summarizing, we could demonstrate a clear change in QEEG activity patterns in individuals previously not affected by COVID-19 and now suffering from post-COVID-19 brain fog. These preliminary results warrant further interest in delineating their background. Here, both neuroinflammation and psychological stress, related to Sars-CoV2-infection may be considered. Based on our observation, the relevance of QEEG examination as a supportive tool for post-COVID clinical workup and for monitoring the treatment effects is also to be explored.

Towards personalised antidepressive medicine based on "big data": an up-to-date review on robust factors affecting treatment response.

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).

Atypical resting-state gamma band trajectory in adult attention deficit/hyperactivity disorder.

Decreased gamma activity has been reported both in children and adults with attention deficit/hyperactivity disorder (ADHD). However, while ADHD is a lifelong neurodevelopmental disorder, our insight into the associations of spontaneous gamma band activity with age is limited, especially in adults. Therefore, we conducted an explorative study to investigate trajectories of resting gamma activity in adult ADHD patients (N = 42) versus matched healthy controls (N = 59). We investigated the relationship of resting gamma activity (30-48 Hz) with age in four right hemispheric electrode clusters where diminished gamma power in ADHD had previously been demonstrated by our group. We found significant non-linear association between resting gamma power and age in the lower frequency gamma1 range (30-39 Hz) in ADHD as compared to controls in all investigated locations. Resting gamma1 increased with age and was significantly lower in ADHD than in control subjects from early adulthood. We found no significant association between gamma activity and age in the gamma2 range (39-48 Hz). Alterations of gamma band activity might reflect altered cortical network functioning in adult ADHD relative to controls. Our results reveal that abnormal gamma power is present at all ages, highlighting the lifelong nature of ADHD. Nonetheless, longitudinal studies are needed to confirm our results.

Electroencephalogram in dementia with Lewy bodies: a systematic review.

Dementia with Lewy bodies (DLB) belongs to the spectrum of Lewy body dementia (LBD) that also encompasses Parkinson's disease dementia (PDD). It is a common neurodegenerative disorder characterized by memory decline, cognitive fluctuations, visual hallucinations, autonomic nervous system disturbance, REM sleep behavior disorder, and parkinsonism. Definite diagnosis can be established only through neuropathological confirmation of Lewy bodies' presence in brain tissue. Probable or possible diagnosis relies upon clinical features, imaging, polysomnography, and electroencephalogram (EEG) findings. Potential neurophysiological biomarkers for the diagnosis, management, and evaluation of treatment-response in DLB should be affordable and widely available outside academic centers. Increasing evidence supports the use of quantitative EEG (qEEG) as a potential DLB biomarker, with promising results in discriminating DLB from other dementias and in identifying subjects who are on the trajectory to develop DLB. Several studies evaluated the diagnostic value of EEG in DLB. Visual analysis and qEEG techniques have been implemented, showing a superiority of the last in terms of sensitivity and objectivity. In this systematic review, we attempt to provide a general synthesis of the current knowledge on EEG application in DLB. We review the findings from original studies and address the issues remaining to be further clarified.