Default mode network aberrance in subjects of alcohol and opioid use disorders during working memory task: An exploratory EEG microstates study.

Background: Aberrance in switching from default mode network (DMN) to fronto-parietal network (FPN) is proposed to underlie working memory deficits in subjects with substance use disorders, which can be studied using neuro-imaging techniques during cognitive tasks. The current study used EEG to investigate pre-stimulus microstates during the performance of Sternberg's working memory task in subjects with substance use disorders. Methods: 128-channel EEG was acquired and processed in ten age and gender-matched subjects, each with alcohol use disorder, opioid use disorder, and controls while they performed Sternberg's task. Behavioral parameters, pre-stimulus EEG microstate, and underlying sources were analyzed and compared between subjects with substance use disorders and controls. Results: Both alcohol and opioid use disorder subjects had significantly lower accuracy (P < 0.01), while reaction times were significantly higher only in subjects of alcohol use disorder compared to controls (P < 0.01) and opioid use disorder (P < 0.01), reflecting working memory deficits of varying degrees in subjects with substance use disorders. Pre-stimulus EEG microstate revealed four topographic Maps 1-4: subjects of alcohol and opioid use disorder showing significantly lower mean duration of Map 3 (visual processing) and Map 2 (saliency and DMN switching), respectively, compared to controls (P < 0.05). Conclusion: Reduced mean durations in Map 3 and 2 in subjects of alcohol and opioid use disorder can underlie their poorer performance in Sternberg's task. Furthermore, cortical sources revealed higher activity in both groups of substance use disorders in the parahippocampal gyrus- a hub of DMN; superior and middle temporal gyri associated with impulsivity; and insula that maintains balance between executive reflective system and impulsive system. EEG microstates can be used to envisage neural underpinnings implicated for working memory deficits in subjects of alcohol and opioid use disorders, reflected by aberrant switching between neural networks and information processing mechanisms.

Aberrance in default mode and executive network activity underlie working memory deficits in addictive disorders: A preliminary, exploratory case-control study.

BACKGROUND: Addiction can alter neural processes during rest and cognitive performance. Subjects with addictive disorders exhibit preoccupation and anticipation for the psychoactive substance when idle and cognitive deficits, during tasks. METHODS: 128 channel EEG was recorded in sixty subjects (30, with alcohol, opioid and internet addiction; 30 controls) during rest and while performing working memory task to ascertain underlying differences in cortical activity between the groups while at rest and during performance of the task. Artifactually clean data was then subjected to source analysis using sLORETA software in both the groups. RESULTS: EEG cortical source analysis in subjects with addictive disorders showed significant activation of areas of Default Mode Network (DMN) and reduced activation in dorsolateral prefrontal cortices (DLPFC), an area known to be involved in executive function, during performance of task. However, control subjects demonstrated significantly reduced activation in areas of DMN; and increased activation of DLPFC during task performance. CONCLUSION: Inability to suppress DMN inhibits reallocation of neural resources to areas of executive functioning leading to working memory deficits in subjects with addictive disorder.

Global Effect on Cortical Activity in Young Indian Males in Response to "OM" Chanting: A High-Density Quantitative Electro-Encephalography Study.

Background: Meditation using the "OM" mantra is the most widely used practice in India. Though reports have been published about the relaxation effect during both verbal "OM" chanting and listening to "OM" chanting, there is a paucity of literature concerning the cortical areas activated/deactivated after verbal "OM" chanting and listening to "OM" chanting using quantitative electro-encephalography (qEEG). Purpose: The objective of this study was to compare the effects of verbal "OM" chanting and listening to "OM" chanting on cortical sources as compared to baseline, as assessed by qEEG. Method: Twenty adult male subjects with a mean age of 27.5 ± 7.5 years and no past or present history of psychiatric, neurological, or auditory disorders or previous exposure to yoga and meditation were recruited from the undergraduate and postgraduate student population of AIIMS, New Delhi. Subjects were given a paradigm designed using E-prime for both verbal and listening to "OM" chanting of 5 min each and a 5-min relaxation period in between the tasks. Electroencephalography recording was done using a 128-channel geodesic sensor net with band-pass filtered at 1-70 Hz, and 20-sec data of eyes-closed condition, post-verbal "OM", and post-listening to "OM" chanting were segmented and pre-processed. Further, source analysis was performed on the data using standardized low-resolution electromagnetic tomography. Result: The pre (baseline) versus post-verbal "OM" (p < .05) and post-listening to "OM" (p < .05) chanting showed significant differences in similar cortical areas in both verbal "OM" and listening to "OM" chanting except the three areas, that is, the orbital gyrus, the rectal gyrus, and the sub-callosal gyrus, which were additionally activated post-listening to "OM" chanting. Both verbal and listening to "OM" chanting induced activation of similar cortical areas, which were classified as the nodes/hubs of specific resting-state networks (RSNs) such as the attentional network, frontoparietal control network, and default mode network. Conclusion: The study results suggest that "OM" chanting could facilitate flexible switching between various RSNs to induce a relaxed state and could improve attention simultaneously.Both verbal and listening to "OM" chanting induced common activated areas that are classified into frontoparietal, dorsal attention, and default mode network areas. And it is hypothesized that flexible switching between these RSNs could induce a relaxed state and improve attention simultaneously with the possible role of the frontoparietal network.

Longitudinal Outcomes of Neurofeedback and Hyperbaric Oxygen Therapy in Treating a Traumatic Brain Injury Patient: A Case Report.

Severe Traumatic Brain Injury (TBI) is a significant health issue, with neurofeedback and Hyperbaric Oxygen Therapy (HBOT) as potentially effective treatments. Neurofeedback uses operant conditioning for real-time psychological and physiological awareness, and HBOT increases blood oxygen levels, potentially enhancing cognitive abilities and the body's innate healing processes and reducing symptoms. On July 30, 2018, a 33-year-old female runner was hit by a car going 40 mph and thrown 30 feet, resulting in a severe TBI and a seven-week coma. After seven months of intensive rehabilitation, she started HBOT and neurofeedback treatments in November 2021, as recommended by her neuropsychiatrist. These treatments led to noticeable improvements in her cognition, sleep, conversation skills, emotional control, and relationships by January 2022. By December 2023, after 195 neurofeedback and over 300 HBOT sessions, she reported further improvements in various cognitive and emotional aspects and daily activities like feeding, toileting, grooming, and communication. Post-treatment quantitative electroencephalogram (qEEG) results in June 2024 showed moderate to large effects on her brain's average frequency band parameters (g = .612) and small to moderate average effects on 19 scalp electrode placement sites outcomes (uV2 g=.339 and Hz g=.333). This indicates significant progress in her recovery journey over a 31-month treatment period. This patient's case demonstrated noteworthy improvements in cognitive variables, namely, feeding (p=0.046), toileting (p=0.046), grooming (p=0.046), and communication abilities (p=0.046) per the objective measures, Disability Rating Scale (DRS) and the Glasgow Outcome Scale Extended (GOSE). Based on the qEEG effect sizes, DRS, and GOSE results from the pretest (2021) and posttest (2024), the patient has made noteworthy gains in brain recovery and overall quality of life.

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.

QEEG indices in traumatic brain injury - insights from the CAPTAIN RTMS trial.

This secondary analysis of the CAPTAIN-RTMS trial data focused on the significance of quantitative electroencephalography (qEEG) indices as indicators of recovery in patients with traumatic brain injury (TBI). By focusing on the delta alpha ratio (DAR), delta theta/alpha beta ratio (DTABR), and theta beta ratio (TBR), this study explored the shifts in brainwave activity as a response to an integrative treatment regimen of repetitive transcranial magnetic stimulation (rTMS) combined with the neurotrophic agent Cerebrolysin. Findings revealed significant increases in DAR and DTABR, suggesting changes in neurophysiological dynamics after treatment. However, variations in TBR were inconclusive in providing clear electrophysiological insights. These results indicate that further research is necessary to describe and understand the underlying mechanisms of brain recovery and to develop refined treatment frameworks for patients with TBI.

Novel biomarkers derived from the Maintenance of Wakefulness Test as predictors of sleepiness and response to treatment.

The Maintenance of Wakefulness Test (MWT) is a widely accepted objective test used to evaluate daytime somnolence and is commonly used in clinical studies evaluating novel therapeutics for excessive daytime sleepiness. In the latter, sleep onset latency (SOL) is typically the sole MWT endpoint. Here, we explored microsleeps, sleep probability measures derived from automated sleep scoring, and quantitative electroencephalography (qEEG) features as additional MWT biomarkers of daytime sleepiness, using data from a phase 1B trial of the selective orexin receptor 2 agonist danavorexton (TAK-925) in people with narcolepsy type 1 (NT1) or type 2 (NT2). Danavorexton treatment reduced the rate and duration of microsleeps during the MWT in NT1 (days 1 and 7; p ≤ 0.005) and microsleep rate in NT2 (days 1 and 7; p < 0.0001). Use of an EEG-sleep-staging-derived measure to determine the probability of wakefulness for each minute revealed a novel metric to track changes in daytime sleepiness, which were consistent with the θ/α ratio, a known biomarker of drowsiness. The slopes of line-fits to both the log-transformed sleepiness score or log-transformed θ/α ratio correlated well to (inverse) MWT SOL for NT1 (R = 0.93 and R = 0.83, respectively) and NT2 (R = 0.97 and R = 0.84, respectively), suggesting that individuals with narcolepsy have increased sleepiness immediately after lights-off. These analyses demonstrate that novel EEG-based biomarkers can augment SOL as predictors of sleepiness and its response to treatment and provide a novel framework for the analysis of wake EEG in hypersomnia disorders.

Combined EEG-tDCS approach in resting state to reduce comorbid anxiety and depressive symptoms in affective disorders: A sham-controlled pilot study.

Continuous challenges have been imposed on mental health science by Anxiety and Depression disorders as the most prevalent and debilitating psychiatric conditions worldwide. Pharmacologic and cognitive behavioral therapies, either alone or in combination, have been considered as the first-line therapies, however, resistant symptomatology is prevalent in comorbid conditions with symptoms remaining after interventions. The demand for new therapeutic solutions has given space to the development of non-invasive brain stimulation techniques (NIBS), and the transmagnetic direct current stimulation (tDCS) has been reported as a safe and well-tolerated technique for the treatment of several mental health conditions, including Anxiety and Depression disorders. Relying on quantitative electroencephalography(qEEG)- tDCS approach, the current study aims to inspect the effect of tDCS intervention on patients who suffer from anxiety-depression comorbidity, in particular, the impact of tDCS intervention on qEEG spectral power activity and resting-state connectivity organization during eyes closed and eyes open protocols. QEEG data were acquired from eight patients suffering from moderate to severe anxiety-depression comorbid symptoms along with poor coping skills to manage stress and negative affect. Twelve control subjects allocated in the control group exhibiting low to moderate symptoms in both anxiety and depression conditions went also through the qEEG data acquisition. In addition, a sham-controlled study was conducted, and the patient group went through resting-state qEEG-tDCS neuromodulation once a week for ten weeks. Various-stage qEEG recordings were performed to inspect the efficacy of tDCS treatment during the modulation of brain regions involved in the regulation of affective responses. Our results demonstrated that after tDCS neuromodulation, the patients' groups exhibited decreased absolute power abnormalities over the left anterior cingulate cortex and reduced abnormal activity in the alpha band over posterior regions; improved functional connectivity indexes; decreased anxiety and depressive scores while positive affect score was improved. Besides the promising improvements, our study did not find a significant tDCS effect on perceived stress and negative affect scores. Consistently, significant differences in absolute spectral power over the left anterior cingulate cortex were detected among the patient group, as compared to the controls, as expected. Therefore, our study offers preliminary data to understand the neuroplasticity changes that potentially result from the manipulation of cortical excitability during affective regulation protocols followed by the consequent decrease of comorbid anxiety and depressive symptomatology. The pilot study was followed by prospective registration with ChiCTR2200062142.

Remediation of Learning Difficulty Utilizing School-Based Cognitive Behavioral Intervention Measured by EEG Theta-Alpha and Theta-Beta Ratio During Resting and Cognitive Task Performance Conditions.

Background. EEG is an effective tool due to its ability to capture and interpret the changes in brain activity under different situations. Quantitative EEG (qEEG) can be essential in evaluating and treating children's learning problems. Methods and procedure. Fifty school-going children with difficulty in learning were studied. Analysis of the difference between pre-intervention and postintervention EEG power ratio of frequency bands, including Theta to Beta and Theta to Alpha, while eyes-closed, eyes-open, hyperventilation, writing, and reading conditions and the values for relative powers were calculated. The study correlated postintervention theta/beta ratio (TBR) and theta/alpha ratio (TAR) values with behavioral measures. Results. The findings suggested that there was a significant difference in pre-intervention and postintervention relative TAR and TBR power values. A significant increase of TAR and TBR power values was observed in eyes-closed (resting), hyperventilation, writing, and reading task conditions, indicative of a state of arousal at FP1FP2, T3T4, and O1O2 scalp locations. During eye open conditions, the TAR and TBR were significantly low at all 3 scalp locations, indicating a relaxed, conscious, and aware state of mind. Postintervention TAR and TBR values were significantly correlated with behavioral measures during 5 task conditions on several scalp locations. Conclusion. These quantitative electroencephalogram findings in children with learning problems indicate that with the increased complexity of the cognitive tasks, TAR and TBR increase, while postintervention, children could attain a relaxed and conscious state of mind during eyes-open condition.

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.

Quantitative EEG for the Monitoring of Walking Recovery in Chronic Stroke Patients Receiving Action Observation Training.

The current study aimed to evaluate the effects of action observation on the walking ability and oscillatory brain activity of chronic stroke patients. Fourteen chronic stroke patients were allocated randomly to the action observation (AO) or sham observation (SO) groups. Both groups received 12 sessions of intervention. Each session composed of 12 min of observational training, which depicted exercises for the experimental group but nature pictures for the sham group and 40 min of occupational therapy, which was the same for the both groups. Walking ability was assessed by a motion analysis system and brain activity was monitored using quantitative electroencephalography (QEEG) before and after the intervention. Brain asymmetry at alpha frequency, the percentage of stance phase, and step length showed significant changes in the AO group. Only the change in global alpha power was significantly correlated with the change in velocity after the intervention in AO group. Despite more improvements in walking and brain activity of patients in the AO group, our study failed to show significant correlations between the brain activity changes and functional improvements after the intervention, which might be mainly due to the small sample size in our study. Trial registration: IRCT20181014041333N1.

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.

A nomogram based on quantitative EEG to predict the prognosis of nontraumatic coma patients in the neuro-intensive care unit.

OBJECTIVE: We aimed to establish a quantitative electroencephalography-based prognostic prediction model specifically tailored for nontraumatic coma patients to guide clinical work. METHODS: This retrospective study included 126 patients with nontraumatic coma admitted to the First Affiliated Hospital of Chongqing Medical University from December 2020 to December 2022. Six in-hospital deaths were excluded. The Glasgow Outcome Scale assessed the prognosis at 3 months after discharge. The least absolute shrinkage and selection operator regression analysis and stepwise regression method were applied to select the most relevant predictors. We developed a predictive model using binary logistic regression and then presented it as a nomogram. We assessed the predictive effectiveness and clinical utility of the model. RESULTS: After excluding six deaths that occurred within the hospital, a total of 120 patients were included in this study. Three predictor variables were identified, including APACHE II score [39.129 (1.4244-1074.9000)], sleep cycle [OR: 0.006 (0.0002-0.1808)], and RAV [0.068 (0.0049-0.9500)]. The prognostic prediction model showed exceptional discriminative ability, with an AUC of 0.939 (95 % CI: 0.899-0.979). CONCLUSION: A lack of sleep cycles, smaller relative alpha variants, and higher APACHE II scores were associated with a poor prognosis of nontraumatic coma patients in the neurointensive care unit at 3 months after discharge. CLINICAL IMPLICATION: This study presents a novel methodology for the prognostic assessment of nontraumatic coma patients and is anticipated to play a significant role in clinical practice.

qEEG in the Diagnosis and Prognosis of a Case with Delusional Infestation.

Stroke can have neuropsychological consequences, such as poststroke psychosis. One aspect of poststroke psychosis is delusional infestation (DI), also known as delusional parasitosis. Patients with DI have fixed sensations that they get infested by lice. Some explanations of DI indicate that striatal and fronto-cortical structural and functional abnormalities are related to DI symptomatology. In this case report, we present a patient with DI due to right intracarotid artery occlusion, which is detected radiologically. Before treatment with escitalopram and risperidone, the case had a frontal slowing in quantitative electroencephalography activity, which was normalized after 2 weeks of treatment. At the end of treatment, psychotic symptoms and OCD symptoms evaluated by the Yale-Brown Obsessive Compulsive Scale, the Scale for the Assessment of Positive Symptoms, were remarkably reduced. These results revealed the role of brain imaging studies in the diagnosis and prognosis of DI.

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.

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.

Quantitative electroencephalography in children with attention deficit hyperactivity disorder and healthy children: Behavioral and age correlates.

This pilot study aimed to identify quantitative electroencephalographic (qEEG) biomarkers for children and adolescents with attention deficit hyperactivity disorder (ADHD). We examined whether qEEG power correlates with the behavioral symptoms. We included 89 children with ADHD and 77 healthy children as a control group. We conducted EEG spectral analysis in the eyes-closed and eyes-opened conditions and compared the findings with a normative database (Human Brain Index). We measured behavioral parameters by using scales proposed by Barkley. The findings revealed an age-dependent decrease in qEEG power in children with ADHD. We found significant discrimination between children with ADHD and healthy children in the theta/beta ratio and theta activity in the frontal area. We found a notable increasing trend in beta activity across two age groups (6-10 years and > 10 years). Correlation analysis showed an association between qEEG power and hyperactivity in younger children with ADHD, while theta activity in the frontal region correlated positively with hyperactivity. The qEEG power of children with ADHD decreased gradually as age increased, and these changes were related to their symptoms. This pilot study suggests that qEEG differences between children with ADHD and healthy children may serve as a sensitive diagnostic tool, depending on the child's age. Further research building upon these findings could deepen our understanding of ADHD and its neural correlates.

Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions.

Introduction: A majority of published studies comparing quantitative EEG (qEEG) in typically developing (TD) children and children with neurodevelopmental or psychiatric disorders have used a control group (e.g., TD children) that combines boys and girls. This suggests a widespread supposition that typically developing boys and girls have similar brain activity at all locations and frequencies, allowing the data from TD boys and girls to be aggregated in a single group. Methods: In this study, we have rigorously challenged this assumption by performing a comprehensive qEEG analysis on EEG recoding of TD boys (n = 84) and girls (n = 62), during resting state eyes-open and eyes-closed conditions (EEG recordings from Child Mind Institute's Healthy Brain Network (HBN) initiative). Our qEEG analysis was performed over narrow-band frequencies (e.g., separating low α from high α, etc.), included sex, age, and head size as covariates in the analysis, and encompassed computation of a wide range of qEEG metrics that included both absolute and relative spectral power levels, regional hemispheric asymmetry, and inter- and intra-hemispheric magnitude coherences as well as phase coherency among cortical regions. We have also introduced a novel compact yet comprehensive visual presentation of the results that allows comparison of the qEEG metrics of boys and girls for the entire EEG locations, pairs, and frequencies in a single graph. Results: Our results show there are wide-spread EEG locations and frequencies where TD boys and girls exhibit differences in their absolute and relative spectral powers, hemispheric power asymmetry, and magnitude coherence and phase synchrony. Discussion: These findings strongly support the necessity of including sex, age, and head size as covariates in the analysis of qEEG of children, and argue against combining data from boys and girls. Our analysis also supports the utility of narrow-band frequencies, e.g., dividing α, ß, and γ band into finer sub-scales. The results of this study can serve as a comprehensive normative qEEG database for resting state studies in children containing both eyes open and eyes closed paradigms.

Effects of deep brain stimulation on quantitative sleep electroencephalogram during non-rapid eye movement in Parkinson's disease.

Introduction: Sleep dysfunction is frequently experienced by people with Parkinson's disease (PD) and negatively influences quality of life. Although subthalamic nucleus (STN) deep brain stimulation (DBS) can improve sleep in PD, sleep microstructural features such as sleep spindles provide additional insights about healthy sleep. For example, sleep spindles are important for better cognitive performance and for sleep consolidation in healthy adults. We hypothesized that conventional STN DBS settings would yield a greater enhancement in spindle density compared to OFF and low frequency DBS. Methods: In a previous within-subject, cross-sectional study, we evaluated effects of low (60 Hz) and conventional high (≥130 Hz) frequency STN DBS settings on sleep macroarchitectural features in individuals with PD. In this post hoc, exploratory analysis, we conducted polysomnography (PSG)-derived quantitative electroencephalography (qEEG) assessments in a cohort of 15 individuals with PD who had undergone STN DBS treatment a median 13.5 months prior to study participation. Fourteen participants had unilateral DBS and 1 had bilateral DBS. During three nonconsecutive nights of PSG, the participants were assessed under three different DBS conditions: DBS OFF, DBS LOW frequency (60 Hz), and DBS HIGH frequency (≥130 Hz). The primary objective of this study was to investigate the changes in sleep spindle density across the three DBS conditions using repeated-measures analysis of variance. Additionally, we examined various secondary outcomes related to sleep qEEG features. For all participants, PSG-derived EEG data underwent meticulous manual inspection, with the exclusion of any segments affected by movement artifact. Following artifact rejection, sleep qEEG analysis was conducted on frontal and central leads. The measures included slow wave (SW) and spindle density and morphological characteristics, SW-spindle phase-amplitude coupling, and spectral power analysis during non-rapid eye movement (NREM) sleep. Results: The analysis revealed that spindle density was significantly higher in the DBS HIGH condition compared to the DBS LOW condition. Surprisingly, we found that SW amplitude during NREM was significantly higher in the DBS LOW condition compared to DBS OFF and DBS HIGH conditions. However, no significant differences were observed in the other sleep qEEG features during sleep at different DBS conditions. Conclusion: This study presents preliminary evidence suggesting that conventional HIGH frequency DBS settings enhance sleep spindle density in PD. Conversely, LOW frequency settings may have beneficial effects on increasing slow wave amplitude during sleep. These findings may inform mechanisms underlying subjective improvements in sleep quality reported in association with DBS. Moreover, this work supports the need for additional research on the influence of surgical interventions on sleep disorders, which are prevalent and debilitating non-motor symptoms in PD.

Spectral quantitative and semi-quantitative EEG provide complementary information on the life-long effects of early childhood malnutrition on cognitive decline.

Objective: This study compares the complementary information from semi-quantitative EEG (sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect the life-long effects of early childhood malnutrition on the brain. Methods: Resting-state EEGs (N = 202) from the Barbados Nutrition Study (BNS) were used to examine the effects of protein-energy malnutrition (PEM) on childhood and middle adulthood outcomes. sqEEG analysis was performed on Grand Total EEG (GTE) protocol, and a single latent variable, the semi-quantitative Neurophysiological State (sqNPS) was extracted. A univariate linear mixed-effects (LME) model tested the dependence of sqNPS and nutritional group. sqEEG was compared with scores on the Montreal Cognitive Assessment (MoCA). Stable sparse classifiers (SSC) also measured the predictive power of sqEEG, spectral-qEEG, and a combination of both. Multivariate LME was applied to assess each EEG modality separately and combined under longitudinal settings. Results: The univariate LME showed highly significant differences between previously malnourished and control groups (p < 0.001); age (p = 0.01) was also significant, with no interaction between group and age detected. Childhood sqNPS (p = 0.02) and adulthood sqNPS (p = 0.003) predicted MoCA scores in adulthood. The SSC demonstrated that spectral-qEEG combined with sqEEG had the highest predictive power (mean AUC 0.92 ± 0.005). Finally, multivariate LME showed that the combined spectral-qEEG+sqEEG models had the highest log-likelihood (-479.7). Conclusion: This research has extended our prior work with spectral-qEEG and the long-term impact of early childhood malnutrition on the brain. Our findings showed that sqNPS was significantly linked to accelerated cognitive aging at 45-51 years of age. While sqNPS and spectral-qEEG produced comparable results, our study indicated that combining sqNPS and spectral-qEEG yielded better performance than either method alone, suggesting that a multimodal approach could be advantageous for future investigations. Significance: Based on our findings, a semi-quantitative approach utilizing GTE could be a valuable diagnostic tool for detecting the lasting impacts of childhood malnutrition. Notably, sqEEG has not been previously explored or reported as a biomarker for assessing the longitudinal effects of malnutrition. Furthermore, our observations suggest that sqEEG offers unique features and information not captured by spectral quantitative EEG analysis and could lead to its improvement.