EEG Power Spectral Analysis Research Articles

Neurophysiological correlates of trait and behavioral impulsivity across methamphetamine and gambling Addiction

Investigating neurophysiological markers linked to impulsivity in individuals with gambling and methamphetamine addiction using resting-state EEG data offers valuable insights into the underlying neurophysiological mechanisms associated with impulsivity in individuals with addiction. This study aims to use resting-state EEG to explore the connection between various types of addiction and different aspects of impulsivity. Participants from the methamphetamine, gambling, and healthy control groups (abbreviation: MA, GB, HC) underwent EEG recordings and completed measures of impulsivity. Group differences in trait scores and behavioral tendencies were analyzed. Abnormal connections with node linkage and importance changes were analyzed through the resting-state EEG power spectral and network analyses. Further, relationships between impulsivity scores and connectivity differences in groups were explored through correlation analysis. Finally, these abnormal connections related to impulsivity were tested for their effect of distinguishing individuals with addiction from healthy controls through the ROC analysis. Results revealed that GB displayed the highest trait impulsivity on the overall score, while MA exhibited greater attentional impulsivity. Variations in behavioral impulsivity were reflected in response times. Resting-state EEG analysis showed higher beta power in GB. Specific channel pairs demonstrated abnormal connections and altered connectivity patterns in the beta band, with MA displaying a less efficient network compared to GB. Correlation analyses uncovered associations between impulsivity scores and connectivity, which were influenced by group differences. Furthermore, resting-state EEG connections effectively differentiated individuals with addiction from healthy controls. Overall, this study contributes valuable insights into the neural mechanisms of addiction-related impulsivity, emphasizing the potential of resting-state EEG connections as an important neurophysiological correlate.

Differentiating types of cinematographic shot changes by cut through an EEG power spectral analysis.

Differentiating types of cinematographic shot changes by cut through an EEG power spectral analysis.

Brain electrical activity in female Major Depressive Disorder patients

Background: Quantitative EEG provides insight to the brain activity associated with depressive illness. Frontal asymmetry and changes of slow wave frequencies brain activity have been found as the characteristic features of Major Depressive Disorder (MDD). Objective: To assess the brain activity by power spectral analysis of EEG in female patients with MDD. Methods: This observational study was carried on 20 female MDD patients (age 20-40 years) enrolled from the Department of Psychiatry, Bangabandhu Sheikh Mujib Medical University, Shahbag, Dhaka. Twenty (20) healthy volunteers of the same age were considered the control group. For the study, EEG was recorded for 3 minutes in eye closed position by EEG data acquisition device, EEG Traveler BrainTech 32+ CMEEG-01, India. Power spectral analysis of EEG data was done by BT40 analysis software. For statistical analysis, the Mann-Whitney U test was done. Results: Significantly higher Absolute power of delta and theta brain wave, and lower alpha and beta brain wave activity was observed in female MDD patients compared to control in all most all electrodes in all cortical regions. Conclusion: MDD patients showed low excitable brain state and characteristic feature of high slow frequency wave and low fast frequency wave in MDD which can be diagnosed by quantitative EEG analysis. J Bangladesh Soc Physiol 2023;18(2): 53-62

GBA-AAV mitigates sleep disruptions and motor deficits in mice with REM sleep behavior disorder

Sleep disturbances, including rapid eye movement sleep behavior disorder (RBD), excessive daytime sleepiness, and insomnia, are common non-motor manifestations of Parkinson’s disease (PD). Little is known about the underlying mechanisms, partly due to the inability of current rodent models to adequately mimic the human PD sleep phenotype. Clinically, increasing studies have reported that variants of the glucocerebrosidase gene (GBA) increase the risk of PD. Here, we developed a mouse model characterized by sleep–wakefulness by injecting α-synuclein preformed fibronectin (PFF) into the sublaterodorsal tegmental nucleus (SLD) of GBA L444P mutant mice and investigated the role of the GBA L444P variant in the transition from rapid eye movement sleep behavior disorder to PD. Initially, we analyzed spectral correlates of REM and NREM sleep in GBA L444P mutant mice. Importantly, EEG power spectral analysis revealed that GBA L444P mutation mice exhibited reduced delta power during non-rapid eye movement (NREM) sleep and increased theta power (8.2–10 Hz) in active rapid eye movement (REM) sleep phases. Our study revealed that GBA L444P-mutant mice, after receiving PFF injections, exhibited increased sleep fragmentation, significant motor and cognitive dysfunctions, and loss of dopaminergic neurons in the substantia nigra. Furthermore, the over-expression of GBA-AAV partially improved these sleep disturbances and motor and cognitive impairments. In conclusion, we present the initial evidence that the GBA L444P mutant mouse serves as an essential tool in understanding the complex sleep disturbances associated with PD. This model further provides insights into potential therapeutic approaches, particularly concerning α-synuclein accumulation and its subsequent pathological consequences.

Power spectral analysis of resting-state EEG to monitor psychological resilience to stress

Psychological resilience refers to the capacity to adapt and recover from challenging situations, stress, or traumatic events. However, there is currently no universally accepted standard for assessing resilience in research, leading to heterogeneity in approaches and measures across different studies. Thus, the present study aimed to test the hypothesis that spectral analysis of the resting-state electroencephalograms (EEG) can be correlated to resilience scores, and ultimately used as the standard method of measuring psychological resilience of patients. We recorded the Perceived Stress Scale (PSS) and the Social Readjustment Rating Scale (SRRS) scores of 299 participants recruited at the Centre for Addiction and Mental Health. The PSS and SRRS scores were used to generate a regression model and residuals were utilized as a measure of resilience to stress. Resting-state EEG data were recorded from 55 healthy subjects extracted from the total sample, and the relative power spectrum of 8 EEG electrodes (F3, F4, C3, C4, P3, P4, O1, O2) for each frequency band (delta, theta, alpha, and beta) were calculated to compare with the resilience scores was tested using the Pearson coefficient. A significant positive correlation between PSS scores and SRRS scores was identified. The EEG power spectrum analysis did not yield any significant findings, except for a trend towards significance in the theta band at electrode P4 (p-value = 0.081). Therefore, the results provide a limited possibility of utilizing EEG to measure psychosocial resilience.

Effect of Atypical Sleep EEG Patterns on Weaning From Prolonged Mechanical Ventilation

Approximately one-third of acute ICU patients display atypical sleep patterns that cannot be interpreted by using standard EEG criteria for sleep. Atypical sleep patterns have been associated with poor weaning outcomes in acute ICUs. Do patients being weaned from prolonged mechanical ventilation experience atypical sleep EEG patterns, and are these patterns linked with weaning outcomes? EEG power spectral analysis during wakefulness and overnight polysomnogram were performed on alert, nondelirious patients at a long-term acute care facility. Forty-four patients had been ventilated for a median duration of 38days at the time of the polysomnogram study. Eleven patients (25%) exhibited atypical sleep EEG. During wakefulness, relative EEG power spectral analysis revealed higher relative delta power in patients with atypical sleep than in patients with usual sleep (53%vs41%; P< .001) and a higher slow-to-fast power ratio during wakefulness: 4.39 vs2.17 (P< .001). Patients with atypical sleep displayed more subsyndromal delirium (36%vs6%; P= .027) and less rapid eye movement sleep (4%vs11%total sleep time; P< .02). Weaning failure was more common in the atypical sleep group than in the usual sleep group: 91%vs45%(P= .013). This study provides the first evidence that patients in a long-term acute care facility being weaned from prolonged ventilation exhibit atypical sleep EEG patterns that are associated with weaning failure. Patients with atypical sleep EEG patterns had higher rates of subsyndromal delirium and slowing of the wakeful EEG, suggesting that these two findings represent a biological signal for brain dysfunction.

A novel electroencephalographic evaluation of noxious stimulation during isoflurane anesthesia in dogs.

In veterinary clinical medicine, evaluating the balance between nociception and antinociception presents a great challenge for anesthesiologists during canine surgeries. Heart rate (HR) and mean arterial pressure (MAP) are suitable indexes for monitoring noxious stimuli during anesthesia. Frontal electroencephalography (EEG) records, including processed parameters, are recommended for evaluating nociceptive balance in anesthetized unconscious human patients, which is unexplored in veterinary medicine. Therefore, the objective is to explore the response of processed EEG parameters to noxious stimulation and elucidate the impact of noxious stimulation on frontal cortical activity in dogs anesthetized with 1.5% isoflurane. Fourteen dogs were included and underwent frontal EEG monitoring, measuring the patient state index (PSI) and spectral edge frequency (SEF) before and after administering noxious stimulation using the towel clamp method on the tail of each 1.5% isoflurane-anesthetized dog. As the noxious stimulation was applied, there was a simultaneous increase in PSI, HR, and MAP, with PSI exhibiting a drastic response. SEF, especially on the left side, also increased with noxious stimulation. In EEG power spectral analysis, the delta band was decreased, and the alpha and beta bands showed an increase following noxious stimulation, with a more profound elevation of beta bands on the left side. This study suggests that noxious stimulation brings asymmetric frontal cortical arousal, changing brain activity by suppressing delta waves and augmenting alpha and beta waves. Consequently, PSI seems to be a potential indicator for detecting stimuli in canine isoflurane anesthesia.

Cognitive Network Changes After Exposure to Haptic Vibrotactile Trigger Technology: Results From The ENHANCE Study

The conceptual framework of cognitive networks, or cognits, represents a system of working memory, especially long-term memory arrays that are intrinsically designed to attain certain behavioral ends and that are activated by a neural structure. Despite the fact that cognitions can be used in a plethora of systems, current technologies allow manipulations of the central nervous system (CNS) to execute certain sensory and motor functions. Sensation and tactual perception by the skin are an innate mechanism for human survival and represent our adaptive somatosensorial ability to apprehend information via haptics—the active touch for object recognition and perception by higher centers of the brain. The somatosensation, which is identified by a set of channels and receptors sensitive to a variety of stimuli (thermal, tactile, and mechanical), is critical to survival, balance control, cognition, and pain modulation. Cognits are cutting-edge tools and modalities that provide a landscape of theoretical assets, evidencebased experimental protocols, computational intelligence schemes, and direct empirical modalities that facilitate the understanding of the complex functionalities of the human brain. By evaluating neuroimaging data after somatosensory stimulation and collected via electroencephalogram (EEG), cognition response and change can be obtained that allows researchers to gain a better understanding of emerging scientific approaches aimed at understanding human behavioral outcomes. An emerging technology, haptic vibrotactile trigger technology (VTT), incorporates somatosensory patterns in compression sleeves. eSmartr Smart Compression Sleeves (Srysty Holdings Inc., Mississauga, ON, Canada) with VTT and its Cognitive Boost Technology (CBT) pattern is designed to optimize neural communications for improved mindful wellness. This technology has also been incorporated into patches, braces, apparel (socks), wrist bands, and other routes of delivery. Mindful wellness is considered an outcome of somatosensory intervention that modulates the behavioral responses associated with cognitive networks. Currently, there is limited research exploring these modalities, exposing the need to study new technologies and their influence on somatosensory pathways and cognitive networks. The purpose of this IRB-approved study was to explore the effects of forearm VTT stimulation patterns on cognitive networks by comparing a baseline EEG to an EEG after placing a sleeve incorporating VTT on the right or left forearm of adult healthy individuals. Materials and methods: A baseline EEG was recorded over 5 minutes from 19 scalp locations on 20 subjects ranging in age from 17.6 years to 41.9 years (n=7 females, 13 males). The subject’s dominant arm was then fitted with the eSmartr Smart Compression Sleeve for 20 minutes and another 5-minute EEG was recorded. Both the LORETA (Low Resolution Electromagnetic Tomography Analysis) inverse solution and a power spectral analysis of the surface EEG were calculated. Additionally, for 10 distinct networks, the current sources from 88 Brodmann areas were computed. The variables were absolute power and absolute current density in 1 Hz increments in 10 frequency bands (delta, theta, alpha-1, alpha-2, beta-1, beta-2, beta-3, and hi-beta). Paired t-tests were computed for each individual for all EEG parameters, as well as group paired t-tests, between the baseline EEG and followup EEG. Results: The results showed statistically significant t-test differences (P &lt; 0.01) in both the surface EEG and the LORETA current sources between the baseline measurement and the follow-up ‘sleeve-on’ measurement. The largest differences were detected with a prominent downregulation of alpha and beta frequency powers at both the surface EEG and the LORETA current sources with the “sleeve-on,” as compared to baseline. In addition, the maximal effects of the “sleeve-on” condition were in the left frontal and left temporal surface EEGs and on the medial bank of the somatosensory cortex in the range of the alpha frequency. Changes in the default network and attention network were also prominent. Conclusions: Study results indicate that these non-pharmacologic, non-invasive, haptic vibrotactile trigger technology (VTT) patterned compression sleeves elicited a response in multiple cognitive networks. These networks play a key role in executive function, memory, attention, mood, and information flow. There was a prominent effect of the haptic vibrotactile trigger technology with the CBT- patterned sleeves on the EEG that was primarily located in alpha and beta frequency bands. The substantial impacts on the homuncular projection of the arm to the medial somatosensory cortex as well as the default network demonstrated activity influenced by the patterned sleeve. The mechanisms of action of the VTT sleeve on the brain, neuropathways, and the EEG spectrum are still being investigated. If results are confirmed with further research, this novel VTT technology could be a promising addition as a non-invasive and non-drug treatment approach for a variety of conditions and therapeutic applications.

The importance of REM sleep fragmentation in the effects of stress on sleep: Perspectives from preclinical studies

Psychological stress poses a risk for sleep disturbances. Importantly, trauma-exposed individuals who develop posttraumatic stress disorder (PTSD) frequently report insomnia and recurrent nightmares. Clinical studies have provided insight into the mechanisms of these sleep disturbances. We review polysomnographic findings in PTSD and identify analogous measures that have been made in animal models of PTSD. There is a rich empirical and theoretical literature on rapid eye movement sleep (REMS) substrates of insomnia and nightmares, with an emphasis on REMS fragmentation. For future investigations of stress-induced sleep changes, we recommend a focus on tonic, phasic and other microarchitectural REMS measures. Power spectral density analysis of the sleep EEG should also be utilized. Animal models with high construct validity can provide insight into gender and time following stressor exposure as moderating variables. Ultimately, preclinical studies with translational potential will lead to improved treatment for stress-related sleep disturbances.

P117 A pilot study of a novel electrode system for brainwave acquisition during sleep: Tripolar Concentric Ring Electrodes

Abstract Introduction Tri-concentric ring electrodes (TCRE) evaluate current density underlying each electrode rather than a voltage difference between two conventionally placed electroencephalography (EEG) electrodes. TCRE signals are more focal and show improved signal-to-noise with markedly reduced electromyographic interference compared to conventional EEG. This pilot study is the first to evaluate sleep using TCRE and power spectral analysis of TCRE versus conventional EEG emulated (eEEG) recordings obtained from TCRE and the outer rings of paired electrodes. Method Twenty healthy sleepers (8 men, mean±SD age 27.8±9.6 y) completed a single overnight sleep study with a 9-hr sleep opportunity. Participants were set up for polysomnography recording using TCRE for brain activity (18 sites) and conventional gold-cup electrodes for eye movements, muscle activity, and heart rate. A fast Fourier transform using multitaper-based estimation was applied in 5-s epochs to calculate relative powers in delta, alpha, theta, sigma and beta frequency bands for eEEG and TCRE signals throughout sleep. Results At the Cz position, TCRE showed greater relative delta power and reduced beta powers across sleep stages compared to eEEG. For example, TCRE had higher delta activity during NREM stage 2 sleep than eEEG (mean [SD]; 89% [5.7] vs 64% [6]) and lower beta activity during wake (3.4% [2] vs 17.3% [7.9]). Ongoing analyses will compare outcomes across electrode locations. Conclusions Brain activity acquisition via TCRE may reduce artefact interference and potentially identify new markers during sleep that are associated with sleep quality, health, and functioning.

EEG power spectral analysis and saccadic eye movement for true and false information

The purpose of this study was to examine the differences between the electroencephalography (EEG) power spectral analysis and saccadic eye movements (SEM)’s the response toward true and false information. The research method was conducted using an experimental design with true and false autobiographical information as stimuli. There were23 female participants aged between 19-24 years old (M=21,45; SD=1,5). The results showed a significant difference in the number of SEM between false information and true information. The EEG power is greater in the frontal, temporal and central areas for false information. Interestingly, we found a correlation between EEG power and SEM in detecting true and false information. Our result findings indicated evidence of multimodality by combining electroencephalography (EEG) and saccadic eye movement (SEM) to dissociate false and true information responses. The distinct dissociative process between true and false information can be used for memory studies and developing lie detectors.

A pilot study of machine learning of resting-state EEG and depression in Parkinson’s disease

IntroductionDepression is a non-motor symptom of Parkinson’s disease (PD). PD-related depression is difficult to diagnose, and the neurophysiological basis is poorly understood. Depression can markedly affect cortical function, which suggests that scalp electroencephalography (EEG) may be able to distinguish depression in PD. We conducted a pilot study of depression and resting-state EEG in PD. MethodsWe recruited 18 PD patients without depression, 18 PD patients with depression, and 12 demographically similar non-PD patients with clinical depression. All patients were on their usual medications. We collected resting-state EEG in all patients and compared cortical brain signal features between patients with and without depression. We used a machine learning algorithm that harnesses the entire power spectrum (linear predictive coding of EEG Algorithm for PD: LEAPD) to distinguish between groups. ResultsWe found differences between PD patients with and without depression in the alpha band (8–13 Hz) globally and in the beta (13–30 Hz) and gamma (30–50 Hz) bands in the central electrodes. From two minutes of resting-state EEG, we found that LEAPD-based machine learning could robustly distinguish between PD patients with and without depression with 97 % accuracy and between PD patients with depression and non-PD patients with depression with 100 % accuracy. We verified the robustness of our finding by confirming that the classification accuracy gracefully declines as data are randomly truncated. ConclusionsOur results suggest that resting-state EEG power spectral analysis has the potential to distinguish depression in PD accurately. We demonstrated the efficacy of the LEAPD algorithm in identifying PD patients with depression from PD patients without depression and controls with depression. Our data provide insight into cortical mechanisms of depression and could lead to novel neurophysiological markers for non-motor symptoms of PD.

Chronic Toxoplasma gondii infection and sleep-wake alterations in mice.

Aim Toxoplasma gondii (Tg) is an intracellular parasite infecting more than a third of the human population. Yet, the impact of Tg infection on sleep, a highly sensitive index of brain functions, remains unknown. We designed an experimental mouse model of chronic Tg infection to assess the effects on sleep‐wake states.MethodsMice were infected using cysts of the type II Prugniaud strain. We performed chronic sleep‐wake recordings and monitoring as well as EEG power spectral density analysis in order to assess the quantitative and qualitative changes of sleep‐wake states. Pharmacological approach was combined to evaluate the direct impact of the infection and inflammation caused by Tg.ResultsInfected mouse exhibited chronic sleep‐wake alterations over months, characterized by a marked increase (>20%) in time spent awake and in cortical EEG θ power density of all sleep‐wake states. Meanwhile, slow‐wave sleep decreased significantly. These effects were alleviated by an anti‐inflammatory treatment using corticosteroid dexamethasone.ConclusionWe demonstrated for the first time the direct consequences of Tg infection on sleep‐wake states. The persistently increased wakefulness and reduced sleep fit with the parasite's strategy to enhance dissemination through host predation and are of significance in understanding the neurodegenerative and neuropsychiatric disorders reported in infected patients.

Parametric Cortical Representations of Complexity and Preference for Artistic and Computer-Generated Fractal Patterns Revealed by Single-Trial EEG Power Spectral Analysis

Fractals are self-similar patterns that repeat at different scales, the complexity of which are expressed as a fractional Euclidean dimension D between 0 (a point) and 2 (a filled plane). The drip paintings of American painter Jackson Pollock (JP) are fractal in nature, and Pollock's most illustrious works are of the high-D (~1.7) category. This would imply that people prefer more complex fractal patterns, but some research has instead suggested people prefer lower-D fractals. Furthermore, research has suggested that parietal and frontal brain activity tracks the complexity of fractal patterns, but previous research has artificially binned fractals depending on fractal dimension, rather than treating fractal dimension as a parametrically varying value. We used white layers extracted from JP artwork as stimuli, and constructed statistically matched 2-dimensional random Cantor sets as control stimuli. We recorded the electroencephalogram (EEG) while participants viewed the JP and matched random Cantor fractal patterns. Participants then rated their subjective preference for each pattern. We used a single-trial analysis to construct within-subject models relating subjective preference to fractal dimension D, as well as relating D and subjective preference to single-trial EEG power spectra. Results indicated that participants preferred higher-D images for both JP and Cantor stimuli. Power spectral analysis showed that, for artistic fractal images, parietal alpha and beta power parametrically tracked complexity of fractal patterns, while for matched mathematical fractals, parietal power tracked complexity of patterns over a range of frequencies, but most prominently in alpha band. Furthermore, parietal alpha power parametrically tracked aesthetic preference for both artistic and matched Cantor patterns. Overall, our results suggest that perception of complexity for artistic and computer-generated fractal images is reflected in parietal-occipital alpha and beta activity, and neural substrates of preference for complex stimuli are reflected in parietal alpha band activity.

EEG Power Spectral Analysis of Abnormal Cortical Activations During REM/NREM Sleep in Obstructive Sleep Apnea.

Objective: To characterize electroencephalogram (EEG) power in different frequency bands during rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep in patients with obstructive sleep apnea (OSA).Methods: Retrospective data on 151 patients were collected and divided into three groups: primary snoring group (AHI < 5/h), mild-moderate OSA group (6 ≤ AHI < 30/h), and severe OSA group (AHI ≥ 30/h). EEG recordings in the frontal, central, and occipital regions were extracted from both REM and NREM sleep, to compute the normalized spectral power densities in the delta, theta, alpha, sigma, beta, and gamma frequency bands, using Fast Fourier Transform. Correlations between the computed EEG power and PSG parameters were analyzed.Results: In NREM sleep, elevated normalized power spectral density (PSD) in the delta band was observed in the severe OSA group compared to the other two groups. In contrast, the PSD of the other frequency bands showed a corresponding decrease in the severe OSA group. In REM sleep, similar changes were observed in the frontal region. Delta band PSD was positively correlated with Apnea Hypopnea Index (AHI) (r = 0.33), longest time of apnea, oxygen desaturation index (ODI) (r = 0.34), percent sleep time below 90% SaO2 (T90%) (r = 0.30), Arousal Index (ArI) (r = 0.29), and negatively correlated with N3%, minimum oxygen saturation (minSaO2).Conclusion: Our findings provide neurophysiological evidence for pathological cortical activation during REM/NREM sleep, which may be associated with the arousals and cognitive impairments in OSA. The technique of power spectral analysis could prove a potentially useful tool in complementing traditional PSG parameters in assessing disease burden to guide therapeutic decisions.

The Consciousness State of Traditional Nidrâ Yoga/Modern Yoga Nidra: Phenomenological Characterization and Preliminary Insights from an EEG Study.

Nidrâ yoga is an ancient yogic practice capable of inducing altered states of consciousness characterized by deep relaxation, strong concentration, acute self-awareness, and joy. In modern contemplative neuroscience language, it is known by the name yoga nidra, and few studies have investigated its phenomenological and psychophysiological effects. Six healthy volunteers (four females aged 31-74) performed 12 yoga nidra sessions guided by an expert during a 6-day retreat. Each session consisted of 10 minutes in a resting state (baseline) followed by 2 hours of yoga nidra. Psychometric data regarding dissociative experiences (Clinician Administered Dissociative States Scale) and the state of consciousness (Phenomenology of Consciousness Inventory) were collected after baseline and yoga nidra, while high-density EEG was recorded during the entire session. During nidra sessions, no sleep hallmarks (i.e., K-complexes and sleep spindles) were detected by the EEG in any subject. Psychometric data we re analyzed using a Wilcoxon signed-rank test corrected with the false discovery rate approach for multiple comparisons. Compared to baseline, yoga nidra practice was related to: (1) increased dissociative effects (p = 0.022); (2) perception of being in an altered state of consciousness (p = 0.026); (3) alterations in perceived body image (p = 0.022); (4) increased "meaningfulness" attributed to the experience (p = 0.026); (5) reduced rational thinking (p = 0.029); and (6) reduced volitional thought control (p = 0.026). First-person experience is discussed in relation to descriptive EEG power spectral density analysis, which was performed in one subject because of severe EEG artifacts in the other recordings; that subject showed, compared to baseline: (1) early increase of alpha and beta power, followed by a progressive widespread reduction; (2) widespread early increase of theta power, followed by a progressive reduction; and (3) widespread increase of gamma power in the latest stages. The present preliminary results enrich the knowledge of yoga nidra, elucidating its phenomenology and suggesting some psychophysiological correlates that future studies may address.

The Contribution of Astrocyte and Neuronal Panx1 to Seizures Is Model and Brain Region Dependent.

Pannexin1 (Panx1) is an ATP release channel expressed in neurons and astrocytes that plays important roles in CNS physiology and pathology. Evidence for the involvement of Panx1 in seizures includes the reduction of epileptiform activity and ictal discharges following Panx1 channel blockade or deletion. However, very little is known about the relative contribution of astrocyte and neuronal Panx1 channels to hyperexcitability. To this end, mice with global and cell type specific deletion of Panx1 were used in one in vivo and two in vitro seizure models. In the low-Mg2+ in vitro model, global deletion but not cell-type specific deletion of Panx1 reduced the frequency of epileptiform discharges. This reduced frequency of discharges did not impact the overall power spectra obtained from local field potentials. In the in vitro KA model, in contrast, global or cell type specific deletion of Panx1 did not affect the frequency of discharges, but reduced the overall power spectra. EEG recordings following KA-injection in vivo revealed that although global deletion of Panx1 did not affect the onset of status epilepticus (SE), SE onset was delayed in mice lacking neuronal Panx1 and accelerated in mice lacking astrocyte Panx1. EEG power spectral analysis disclosed a Panx1-dependent cortical region effect; while in the occipital region, overall spectral power was reduced in all three Panx1 genotypes; in the frontal cortex, the overall power was not affected by deletion of Panx1. Together, our results show that the contribution of Panx1 to ictal activity is model, cell-type and brain region dependent.

EEG power spectral analysis reveals tandospirone improves anxiety symptoms in patients with Alzheimer's disease: a prospective cohort study.

BackgroundTo study the efficacy of tandospirone citrate in treating Alzheimer’s disease (AD) patients with anxiety.MethodsThirty mild-to-moderate AD patients with anxiety symptoms were randomly divided into a monotherapy group (donepezil) and a combination therapy group (donepezil and tandospirone). The treatment lasted for 12 weeks. Drug efficacy was regularly assessed using psychological assessment scales and quantitative pharmaco-electroencephalogram (QPEEG) power spectral analysis.ResultsAfter 12 weeks of treatment, the mean Hamilton Anxiety Scale (HAMA) score and mean Neuropsychiatric Inventory (NPI) score of the combination therapy group were 5.13±4.18 and 4.2±5.0, respectively, which was significantly lower compared to baseline and the monotherapy group (all P<0.05). The mean attention score on the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-Cog) was 0.07±0.26 for the combination group, which was significantly lower than that of the monotherapy group (P<0.05). QPEEG revealed that the power values of the δ wave in the right prefrontal lobe, left middle temporal lobe and right posterior temporal lobe decreased in the combination therapy group but not in the monotherapy group. Similarly, the power values of the α2 wave in the right parietal, right posterior temporal and left middle temporal lobes, and the β1 wave power values of left middle temporal and left posterior temporal lobes were also significantly decreased in the combination therapy group, but not in the monotherapy group.ConclusionsTandospirone citrate can significantly improve anxiety symptoms and attention in patients with mild to moderate AD. QPEEG examination might provide a objective way for the efficacy of the tandospirone in anxiety symptoms of the patients with Alzheimer’s disease.

Patterns of Intrahemispheric EEG Asymmetry in Insomnia Sufferers: An Exploratory Study.

Individuals with insomnia present unique patterns of electroencephalographic (EEG) asymmetry between homologous regions of each brain hemisphere, yet few studies have assessed asymmetry within the same hemisphere. Increase in intrahemispheric asymmetry during rapid eye movement (REM) sleep in good sleepers (GS) and disruption of REM sleep in insomnia sufferers (INS) both point out that this activity may be involved in the pathology of insomnia. The objective of the present exploratory study was to evaluate and quantify patterns of fronto-central, fronto-parietal, fronto-occipital, centro-parietal, centro-occipital and parieto-occipital intrahemispheric asymmetry in GS and INS, and to assess their association with sleep-wake misperception, daytime anxiety and depressive symptoms, as well as insomnia severity. This paper provides secondary analysis of standard EEG recorded in 43 INS and 19 GS for three nights in a sleep laboratory. Asymmetry measures were based on EEG power spectral analysis within 0.3–60 Hz computed between pairs of regions at frontal, central, parietal and occipital derivations. Repeated-measures ANOVAs were performed to assess group differences. Exploratory correlations were then performed on asymmetry and sleep-wake misperception, as well as self-reported daytime anxiety and depressive symptoms, and insomnia severity. INS presented increased delta and theta F3/P3 asymmetry during REM sleep compared with GS, positively associated with depressive and insomnia complaints. INS also exhibited decreased centro-occipital (C3/O1, C4/O2) and parieto-occipital (P3–O1, P4/O2) theta asymmetry during REM. These findings suggest that INS present specific patterns of intrahemispheric asymmetry, partially related to their clinical symptoms. Future studies may investigate the extent to which asymmetry is related to sleep-wake misperception or memory impairments.

Neuro-Cognitive Profile of Morning and Evening Chronotypes at Different Times of Day.

Background:Chronotype is the circadian time preference for sleep–wake timings. However, its impact on cognitive performance is least explored.Objective:The present study investigated the effect of chronotype (morning “M” vs. evening “E”) on cognitive measures as a function of time of the day. In addition, the correlation between electroencephalogram (EEG) waves and subjective/objective cognitive measures were investigated.Method:Cognitive status of 28 adult male subjects (15 “M” and 13 “E”) was assessed objectively through event-related potential (ERP) by administering visual odd ball paradigm test and subjectively through Montreal Cognitive Assessment questionnaire. In addition, 20 to 30 min of resting EEG was recorded. Recordings were done from 8 to 10 am and from 4 to 6 pm on a single day. Power spectral analysis of EEG for alpha and beta waves at PZ and FZ cortical sites was done after subjecting selected epochs to fast Fourier transformation. Also, latency and amplitude of P300 potential from event-related potential record were measured. Appropriate statistical tests were applied for analysis.Results:Higher alpha and beta power was observed in “E” at PZ in the evening. “M” showed increased P300 latency and amplitude during evening session for frequent and rare stimuli and vice versa in “E.”’ Significant negative correlation was seen between latency of rare stimuli and alpha and beta power at FZ site during evening in “E” chronotype only.Conclusion:Result indicates better attention and alertness during evening hours in evening chronotypes and vice versa in morning chronotypes. The findings could be implemented to schedule the mental performance/cognitive load according to individual chronotype.