Within-subject reliability and inter-session stability of EEG power and coherent activity in women evaluated monthly over nine months

Switching tinnitus on or off: An initial investigation into the role of the pregenual and rostral to dorsal anterior cingulate cortices

Research indicates that hearing loss significantly contributes to tinnitus, but it alone does not fully explain its occurrence, as many people with hearing loss do not experience tinnitus. To identify a secondary factor for tinnitus generation, we examined a unique dataset of individuals with intermittent chronic tinnitus, who experience fluctuating periods of tinnitus. EEGs of healthy controls were compared to EEGs of participants who reported perceiving tinnitus on certain days, but no tinnitus on other days.. The EEG data revealed that tinnitus onset is associated with increased theta activity in the pregenual anterior cingulate cortex and decreased theta functional connectivity between the pregenual anterior cingulate cortex and the auditory cortex. Additionally, there is increased alpha effective connectivity from the dorsal anterior cingulate cortex to the pregenual anterior cingulate cortex. When tinnitus is not perceived, differences from healthy controls include increased alpha activity in the pregenual anterior cingulate cortex and heightened alpha connectivity between the pregenual anterior cingulate cortex and auditory cortex. This suggests that tinnitus is triggered by a switch involving increased theta activity in the pregenual anterior cingulate cortex and decreased theta connectivity between the pregenual anterior cingulate cortex and auditory cortex, leading to increased theta-gamma cross-frequency coupling, which correlates with tinnitus loudness. Increased alpha activity in the dorsal anterior cingulate cortex correlates with distress. Conversely, increased alpha activity in the pregenual anterior cingulate cortex can transiently suppress the phantom sound by enhancing theta connectivity to the auditory cortex. This mechanism parallels chronic neuropathic pain and suggests potential treatments for tinnitus by promoting alpha activity in the pregenual anterior cingulate cortex and reducing alpha activity in the dorsal anterior cingulate cortex through pharmacological or neuromodulatory approaches.

Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

EEG coherence before and after giving birth

During pregnancy and the postpartum period, changes in brain volume and in motivational, sensory, cognitive, and emotional processes have been described. However, to date, longitudinal modifications of brain function have been understudied. To explore regional cortical coupling, in pregnancy and at 3 months postpartum, we analyzed resting-state electroencephalographic (EEG) coherence in the delta, theta, alpha1, alpha2, beta1, and beta2 frequency bands across frontal and parietal regions of the maternal brain (Fp1, Fp2, F3, F4, P3, and P4). We found that from pregnancy to the postpartum period, mothers showed less intrahemispheric EEG coherence between the frontal and parietal regions in the alpha1 and alpha2 bands, as well as greater interhemispheric EEG coherence between frontopolar regions in the beta2 band. These changes suggest decreased inhibition of neural circuits. These neurophysiological changes may represent an adaptive process characteristic of motherhood.

EEG functional connectivity after perinatal stroke

Impaired cognitive functioning after perinatal stroke has been associated with long-term functional brain network changes. We explored brain functional connectivity using a 64-channel resting-state electroencephalogram in 12 participants, aged 5-14 years with a history of unilateral perinatal arterial ischemic or haemorrhagic stroke. A control group of 16 neurologically healthy subjects was also included-each test subject was compared with multiple control subjects, matched by sex and age. Functional connectomes from the alpha frequency band were calculated for each subject and the differences in network graph metrics between the 2 groups were analyzed. Our results suggest that the functional brain networks of children with perinatal stroke show evidence of disruption even years after the insult and that the scale of changes appears to be influenced by the lesion volume. The networks remain more segregated and show a higher synchronization at both whole-brain and intrahemispheric level. Total interhemispheric strength was higher in children with perinatal stroke compared with healthy controls.

EEG signatures of low back and knee joint pain during movement execution: a short report

Chronic musculoskeletal pain has a high prevalence between European citizens, affecting their quality of life and their ability to work. The plastic changes associated with the occurrence of chronic musculoskeletal pain are still not fully understood. The current short report investigated the possible changes in brain activity caused by pain during movement in two of the most common musculoskeletal pain disorders in Denmark, knee pain and low back pain. Electroencephalography (EEG) was recorded from 20 participants (5 participants with knee pain, 5 with low back pain and 10 healthy controls). Participants with pain performed a movement that evoked pain in the area of interest, and the healthy controls performed the same movement. Electromyographic (EMG) signals were also collected to identify movement initiation. No differences were observed in brain activity of participants with pain and healthy controls during rest. During movement execution, though, participants with pain showed significantly higher event related synchronization in the alpha and beta bands compared to healthy controls. These changes could be related to higher cognitive processing, possibly due to the attempt of suppressing the pain. These results highlight the importance of assessing cortical activity during movement to reveal plastic changes due to musculoskeletal pain. This adds to our knowledge regarding plastic changes in cortical activity related to musculoskeletal pain in different locations. Such knowledge could help us identify neurophysiological markers for clinical changes and contribute to the development of new treatment approaches based on neuromodulation such as neurofeedback.

Reduced Resting-State EEG Power Spectra and Functional Connectivity after 24 and 36 Hours of Sleep Deprivation

Total sleep deprivation (TSD) leads to cognitive decline; however, the neurophysiological mechanisms underlying resting-state electroencephalogram (EEG) changes after TSD remain unclear. In this study, 42 healthy adult participants were subjected to 36 h of sleep deprivation (36 h TSD), and resting-state EEG data were recorded at baseline, after 24 h of sleep deprivation (24 h TSD), and after 36 h TSD. The analysis of resting-state EEG at baseline, after 24 h TSD, and after 36 h TSD using source localization analysis, power spectrum analysis, and functional connectivity analysis revealed a decrease in alpha-band power and a significant increase in delta-band power after TSD and impaired functional connectivity in the default mode network, precuneus, and inferior parietal lobule. The cortical activities of the precuneus, inferior parietal lobule, and superior parietal lobule were significantly reduced, but no difference was found between the 24 h and 36 h TSD groups. This may indicate that TSD caused some damage to the participants, but this damage temporarily slowed during the 24 h to 36 h TSD period.

Stability, change, and reliable individual differences in electroencephalography measures: a lifespan perspective on progress and opportunities

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

Age related changes and sex related differences of functional brain networks in childhood: A high-density EEG study

OBJECTIVE

The aim of this study was to explore functional network age-related changes and sex-related differences during the early lifespan with a high-density resting state electroencephalography (rs-EEG).

METHODS

We analyzed two data sets of high-density rs-EEG in healthy children and adolescents. We recorded a 64-channel EEG and calculated functional connectomes in 27 participants aged 5-18 years. To validate our results, we used publicly available data and calculated functional connectomes in another 86 participants aged 6-18 years from a 128-channel rs-EEG. We were primarily interested in alpha frequency band, but we also analyzed theta and beta frequency bands.

RESULTS

We observed age-related increase of characteristic path, clustering coefficient and interhemispheric strength in the alpha frequency band of both data sets and in the beta frequency band of the larger validation data set. Age-related increase of global efficiency was seen in the theta band of the validation data set and in the alpha band of the test data set. Increase in small worldness was observed only in the alpha frequency band of the test data set. We also observed an increase of individual peak alpha frequency with age in both data sets. Sex-related differences were only observed in the beta frequency band of the larger validation data set, with females having higher values than same aged males.

CONCLUSIONS

Functional brain networks show indices of higher segregation, but also increasing global integration with maturation. Age-related changes are most prominent in the alpha frequency band.

SIGNIFICANCE

To the best of our knowledge, our study was the first to analyze maturation related changes and sex-related differences of functional brain networks with a high-density EEG and to compare functional connectomes generated from two diverse high-density EEG data sets. Understanding the age-related changes and sex-related differences of functional brain networks in healthy children and adolescents is crucial for identifying network abnormalities in different neurologic and psychiatric conditions, with the aim to identify possible markers for prognosis and treatment.

Analyzing motivating functions of consumer behavior: Evidence from attention and neural responses to choices and consumption

Academia and business have shown an increased interest in using neurophysiological methods, such as eye-tracking and electroencephalography (EEG), to assess consumer motivation. The current research contributes to this literature by verifying whether these methods can predict the effects of antecedent events as motivating functions of attention, neural responses, choice, and consumption. Antecedent motivational factors are discussed, with a specific focus on deprivation as such a situational factor. Thirty-two participants were randomly assigned to the experimental and control conditions. Water deprivation of 11-12 h was used as an establishing operation to increase the reinforcing effectiveness of water. We designed three experimental sessions to capture the complexity of the relationship between antecedents and consumer behavior. Experimental manipulations in session 1 established the effectiveness of water for the experimental group and abolished it for the control group. Results from session 2 show that participants in the experimental group had significantly higher average fixation duration for the image of water. Their frontal asymmetry did not provide significant evidence of greater left frontal activation toward the water image. Session 3 demonstrated that choice and consumption behavior of the relevant reinforcer was significantly higher for participants in the experimental group. These early findings highlight the potential application of a multi-method approach using neurophysiological tools in consumer research, which provides a comprehensive picture of the functional relationship between motivating events, behavior (attention, neural responses, choice, and consumption), and consequences.

Reliability of Mental Workload Index Assessed by EEG with Different Electrode Configurations and Signal Pre-Processing Pipelines

BACKGROUND AND OBJECTIVE

Mental workload (MWL) is a relevant construct involved in all cognitively demanding activities, and its assessment is an important goal in many research fields. This paper aims at evaluating the reproducibility and sensitivity of MWL assessment from EEG signals considering the effects of different electrode configurations and pre-processing pipelines (PPPs).

METHODS

Thirteen young healthy adults were enrolled and were asked to perform 45 min of Simon's task to elicit a cognitive demand. EEG data were collected using a 32-channel system with different electrode configurations (fronto-parietal; Fz and Pz; Cz) and analyzed using different PPPs, from the simplest bandpass filtering to the combination of filtering, Artifact Subspace Reconstruction (ASR) and Independent Component Analysis (ICA). The reproducibility of MWL indexes estimation and the sensitivity of their changes were assessed using Intraclass Correlation Coefficient and statistical analysis.

RESULTS

MWL assessed with different PPPs showed reliability ranging from good to very good in most of the electrode configurations (average consistency > 0.87 and average absolute agreement > 0.92). Larger fronto-parietal electrode configurations, albeit being more affected by the choice of PPPs, provide better sensitivity in the detection of MWL changes if compared to a single-electrode configuration (18 vs. 10 statistically significant differences detected, respectively).

CONCLUSIONS

The most complex PPPs have been proven to ensure good reliability (>0.90) and sensitivity in all experimental conditions. In conclusion, we propose to use at least a two-electrode configuration (Fz and Pz) and complex PPPs including at least the ICA algorithm (even better including ASR) to mitigate artifacts and obtain reliable and sensitive MWL assessment during cognitive tasks.

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders

Background

The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.

Methods

We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.

Discussion

This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.

Trial registration

Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.

Enhanced effective connectivity from the middle frontal gyrus to the parietal lobe is associated with impaired mental rotation after total sleep deprivation: An electroencephalogram study

Sleep deprivation impairs cognitive functions, including attention, memory, and decision-making. Studies on the neuro-electro-physiological mechanisms underlying total sleep deprivation (TSD) that impairs spatial cognition are limited. Based on electroencephalogram (EEG) and Exact Low Resolution Brain Electromagnetic Tomography (eLORETA), this study focused on the effects of TSD on mental rotation and the cognitive neural mechanisms underlying its damage. Twenty-four healthy college students completed mental rotation tasks while resting and after 36 h of TSD; their EEG data were simultaneously recorded. The amplitude of P300 component associated with mental rotation was observed and localized through source reconstruction, while changes in effective connectivity between multiple brain regions associated with mental rotation cognitive processing were calculated using isolated effective coherence (iCoh) of eLORETA. Compared with the baseline before TSD, the amplitude of the P300 component related to mental rotation decreased. The task-state data of P300 were localized to the source of the difference in ERP current density, and it was found that the brain regions related to the difference in the decrease in P300 amplitude included the superior parietal lobule, precuneus, prefrontal lobe, and other related regions. Effective connectivity analysis found that TSD enhanced the effective connectivity from the left middle frontal gyrus to the left superior parietal lobule, left inferior parietal lobule, and left precuneus under the identical condition. Pearson correlation analysis showed a positive correlation between the decrease in accuracy of mental rotation and increase in effective connectivity. Thus, our study suggests that TSD impairs the ability of the mental rotation, showing a decrease in P300 amplitude and an enhanced effective connectivity between the middle frontal gyrus and the parietal lobe in the task state.

Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions

BACKGROUND

Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric.

NEW METHODS

We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity.

RESULTS

Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals.

CONCLUSIONS

The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.

Test-retest reproducibility comparison in resting and the mental task states: A sensor and source-level EEG spectral analysis

Previous test-retest analysis of EEG mostly focused on eyes open and eyes closed resting-state. However, less attention was paid to the EEG during the subject-driven mental imaginary task state. In the current study, we compared the test-retest reproducibility of EEG spectrum in three mental imaginary task states (i.e. performed mental arithmetic, recalled the events of their day, and silently sang lyrics) and two resting states (i.e. eyes open and closed) during three EEG sessions. The resting state with eyes closed has the highest reproducibility, while the resting state with eyes opened has the lowest reproducibility for the spectral features of EEG signals at the sensor level. However, the reproducibility during eyes-open ranked higher among the five states at the source level. Moreover, the mental arithmetic state has the highest reproducibility among all the three task states. And its reproducibility in certain rhythms (theta, gamma, etc) was higher than the resting states. The reproducibility of the EEG spectrum was also investigated from the perspective of large-scale brain networks. The dorsal attention network showed the highest reproducibility in a wide frequency range of the alpha and beta rhythms. Our study suggests the importance of task selection based on the target brain region and the target frequency band. This may provide some suggestions for future researchers to choose appropriate experimental paradigms and provide a guideline on EEG study for the basic and clinical applications.

Stimulus-induced narrowband gamma oscillations are test–retest reliable in human EEG

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20–35 Hz) and fast gamma (36–66 Hz) oscillations in subjects (n = 40) (age: 50–88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8–12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification.

EEG functional brain connectivity strengthens with age during attentional processing to faces in children

Studying functional connectivity may generate clues to the maturational changes that occur in children, expressed by the dynamical organization of the functional network assessed by electroencephalographic recordings (EEG). In the present study, we compared the EEG functional connectivity pattern estimated by linear cross-correlations of the electrical brain activity of three groups of children (6, 8, and 10 years of age) while performing odd-ball tasks containing facial stimuli that are chosen considering their importance in socioemotional contexts in everyday life. On the first task, the children were asked to identify the sex of faces, on the second, the instruction was to identify the happy expressions of the faces. We estimated the stable correlation pattern (SCP) by the average cross-correlation matrix obtained separately for the resting state and the task conditions and quantified the similarity of these average matrices comparing the different conditions. The accuracy improved with higher age. Although the topology of the SCPs showed high similarity across all ages, the two older groups showed a higher correlation between regions associated with the attentional and face processing networks compared to the youngest group. Only in the youngest group, the similarity metric decreased during the sex condition. In general, correlation values strengthened with age and during task performance compared to rest. Our findings indicate that there is a spatially extended stable brain network organization in children like that reported in adults. Lower similarity scores between several regions in the youngest children might indicate a lesser ability to cope with tasks. The brain regions associated with the attention and face networks presented higher synchronization across regions with increasing age, modulated by task demands.

Human resting-state EEG and radiofrequency GSM mobile phone exposure: the impact of the individual alpha frequency

PURPOSE

With the extensive use of mobile phone (MP), several studies have been realized to investigate the effects of radiofrequency electromagnetic fields (RF-EMF) exposure on brain activity at rest via electroencephalography (EEG), and the most consistent effect has been seen on the alpha band power spectral density (PSD). However, some studies reported an increase or a decrease of the PSD, while others showed no effect. It has been suggested that these differences might partly be due to a variability of the physiological state of the brain between subjects. So, the aim of this study was to investigate the alpha band modulation, exploring the impact of the alpha band frequency ranges applied in the PSD analysis.

MATERIALS AND METHODS

Twenty-one healthy volunteers took part to the study with a double-blind, randomized and counterbalanced crossover design, during which eyes-open (EO) and eyes-closed (EC) resting-state EEG was recorded. The exposure system was a sham or a real GSM (global system for mobile) 900 MHz MP (pulse modulated at 217 Hz, mean power of 250 mW and 2 W peak, with a maximum specific absorption rate of 0.70 W/kg on 1 g tissue). The experimental protocol presented a baseline recording phase without MP exposure, an exposure phase during which the exposure system was placed against the left ear, and the post-exposure phase without MP. EEG data from baseline and exposure phases were analyzed and PSD was computed for the alpha band in the fixed range of 8-12 Hz and for the individual alpha band frequency range (IAF).

RESULTS

Results showed a trend in decrease or increase of EEG power of both alpha oscillations during exposure in relation to EC and EO recording conditions, respectively, but not reaching statistical significance. Findings did not provide evidence for a different sensitivity to RF-EMF MP related to individual variability in the frequency of the alpha band.

CONCLUSION

In conclusion, these results did not show alpha band activity modulation during resting-state under RF-EMF. It might be argued the need of a delay after the exposure in order to appreciate an EEG spectral power modulation related to RF-EMF exposure.

Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales

Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.

Neural Dynamics of a Single Human with Long-Term, High Temporal Density Electroencephalography

We undertake a longitudinal study with high temporal recording density, capturing daily electroencephalograms (EEG) of an individual in an in-situ setting for 370 consecutive days. Resting-state EEG retains a high level of stability over the course of the year, and inter-session variability remains unchanged, whether the sessions are one day, one week, or one month apart. On the other hand, EEG for certain cognitive tasks experience a steady decline in similarity over the same time period. Clustering analysis reveals that days with low similarity scores should not be considered as outliers, but instead are part of a cluster of days with a consistent alternate spectral signature. This has methodological and design implications for the selection of baseline references or templates in fields ranging from neurophysiology to brain-computer interfaces (BCI) and neurobiometrics.

Development of Frontal EEG Differences Between Eyes-Closed and Eyes-Open Resting Conditions in Children: Data From a Single-Channel Dry-Sensor Portable Device

Changes in EEG when moving from an eyes-closed to an eyes-open resting condition result from bottom-up sensory processing and have been referred to as activation. In children, activation is characterized by a global reduction in alpha, frontally present reductions for delta and theta, and a frontal increase for beta. The present study aimed to replicate frontal EEG activation effects using single-channel, dry-sensor EEG, and to extend current understanding by examining developmental change in children. Frontal EEG was recorded using a single-channel, dry-sensor EEG device while 182 children aged 7 to 12 years completed eyes-closed resting (EC), eyes-open resting (EO), and focus (FO) tasks. Results indicated that frontal delta, theta, and alpha power were reduced, and frontal beta power was increased, in the EO compared with the EC condition. Exploratory analysis of a form of top-down activation showed that frontal beta power was increased in the FO compared with to the EO condition, with no differences for other bands. The activation effects were robust at the individual level. The bottom-up activation effects reduced with age for frontal delta and theta, increased for frontal alpha, with no developmental change for top-down or bottom-up frontal beta activation. These findings contribute further to validation of the single-channel, dry-sensor, frontal EEG and provide support for use in a range of medical, therapeutic, and clinical domains.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Aiding diagnosis of childhood attention-deficit/hyperactivity disorder of the inattentive presentation: Discriminant function analysis of multi-domain measures including EEG

INTRODUCTION

We developed a neurocognitive assessment tool (NCAT) in consultation with mental health professionals working with children with AD/HD as a diagnostic aid and screening tool. This study examines the predictive utility of NCAT in the classification of children with AD/HD Inattentive presentation.

METHOD

Fifty three children with AD/HD Inattentive presentation and 161 typically-developing children completed an NCAT assessment. Discriminant function analyses examined group membership prediction for separate components of NCAT and for the components combined.

RESULTS

The combined model correctly classified 93.4 % of participants, with 91.4 % sensitivity and 93.9 % specificity. Contributions to classification were from SNAP-IV, psychological needs satisfaction, self-regulation, executive function performance, and EEG. The combined model resulted in a 9.3 % increase in specificity and 5.9 % increase in sensitivity compared to SNAP-IV alone.

CONCLUSIONS

NCAT provides good discrimination between children with and without AD/HD of the Inattentive presentation, and further investigation including other subtypes and comorbidities is warranted.

Brain sources' activity in resting state before a visuo-motor task

Objective In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance. Approach The purpose of the present study was to investigate the brain rhythms characteristics of EEG recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the Global Spectra Power Density (GSPD) in the left and in the right hemisphere, and of an index of brain Laterality L. Main results The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated with L in the central areas in eyes closed condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open and eyes closed conditions. Significance The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance.

EEGs Vary Less Between Lab and Home Locations Than They Do Between People

Given the rapid development of light weight EEG devices which we have witnessed the past decade, it is reasonable to ask to which extent neuroscience could now be taken outside the lab. In this study, we have designed an EEG paradigm well suited for deployment “in the wild.” The paradigm is tested in repeated recordings on 20 subjects, on eight different occasions (4 in the laboratory, 4 in the subject's own home). By calculating the inter subject, intra subject and inter location variance, we find that the inter location variation for this paradigm is considerably less than the inter subject variation. We believe the paradigm is representative of a large group of other relevant paradigms. This means that given the positive results in this study, we find that if a research paradigm would benefit from being performed in less controlled environments, we expect limited problems in doing so.

Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG

INTRODUCTION

The global COVID-19 pandemic has affected the economy, daily life, and mental/physical health. The latter includes the use of electroencephalography (EEG) in clinical practice and research. We report a survey of the impact of COVID-19 on the use of clinical EEG in practice and research in several countries, and the recommendations of an international panel of experts for the safe application of EEG during and after this pandemic.

METHODS

Fifteen clinicians from 8 different countries and 25 researchers from 13 different countries reported the impact of COVID-19 on their EEG activities, the procedures implemented in response to the COVID-19 pandemic, and precautions planned or already implemented during the reopening of EEG activities.

RESULTS

Of the 15 clinical centers responding, 11 reported a total stoppage of all EEG activities, while 4 reduced the number of tests per day. In research settings, all 25 laboratories reported a complete stoppage of activity, with 7 laboratories reopening to some extent since initial closure. In both settings, recommended precautions for restarting or continuing EEG recording included strict hygienic rules, social distance, and assessment for infection symptoms among staff and patients/participants.

CONCLUSIONS

The COVID-19 pandemic interfered with the use of EEG recordings in clinical practice and even more in clinical research. We suggest updated best practices to allow safe EEG recordings in both research and clinical settings. The continued use of EEG is important in those with psychiatric diseases, particularly in times of social alarm such as the COVID-19 pandemic.

Long-term stability of resting state EEG-based linear and nonlinear measures

This preliminary study is aimed to evaluate the stability of various linear and nonlinear EEG measures over three years on healthy adults. The linear measures, relative powers of EEG frequency bands, interhemispheric (IHAS) and spectral (SASI) asymmetries plus nonlinear Higuchi's fractal dimension (HFD) and detrended fluctuation analyses (DFA), have been calculated from the resting state eyes closed EEG of 17 participants during two sessions separated over three years. Our results indicate that the stability is highest for the nonlinear (HFD and DFA) and the linear (relative powers of EEG frequency bands) EEG measures that use the signal from a single EEG channel and frequency band, followed by the SASI employing signals from a single channel and two frequency bands and lowest for the IHAS employing signals from two channels. The result support the prospect of using EEG-based measures in clinical practice.

Re-test reliability and internal consistency of EEG alpha-band oscillations in older adults with chronic knee pain

OBJECTIVE

Chronic pain studies investigating the ability to detect sensory processing differences related to thalamic gating using electroencephalographic (EEG) alpha have yielded conflicting results. Alpha's basic psychometric properties in pain populations requires further study. The present study reports on the test-retest reliability and internal consistency of EEG alpha power in older adults with chronic knee pain.

METHODS

Repeated EEG alpha power measurements were taken of older adults (N = 31) with chronic knee pain across two sessions separated by a ten-day period associated with a pilot clinical trial study. Recordings included resting periods (eyes open and eyes closed) as well as periods involving a pain management activity.

RESULTS

Most single alpha-power measures and all within-participant averages of alpha obtained within a session showed high internal consistency (Cronbach's α > 0.7) and satisfactory-to-excellent re-test reliability (Pearson's rs > 0.6) of both alpha power and alpha blocking (eyes closed minus eyes open) across repeated conditions.

CONCLUSIONS

EEG alpha power seems mostly reliable and consistent, particularly when participants' eyes are closed, after a period of habituation, and when alpha measures are averaged as within-participant estimates.

SIGNIFICANCE

This analysis suggests that within-subject averages of EEG alpha are the most reliable for developing indices of chronic knee pain.

Reproducibility of power spectrum, functional connectivity and network construction in resting-state EEG

BACKGROUND

Characteristics from resting-state electroencephalography (rsEEG) provides relevant information about individual differences in cognitive tasks and personality traits. Due to its increasing application, it is crucial to know the reproducibility of several analysis measures of rsEEG.

NEW METHOD

A new brain network construction method was proposed based on simplified forward model (SFM). In addition, we aimed to carry out an extensive examination of the reproducibility of the power spectrum and functional connectivity at both the sensor-level and the source-level. We systematically proposed multiple new pipelines by integration source imaging, time-course extraction and network reconstruction.

RESULTS/COMPARISON WITH EXISTING METHOD(S)

Our results revealed that the reproducibility of eyes-closed was slightly higher than that of eyes-open, and the relative power was more repeatable than the absolute power, especially in high-frequency bands. The reproducibility of the sensor-level was higher than that of the source-level, both for power and connectivity. Remarkably, connectivity measures could be separated into two classes according to their reproducibility. Notably, the reproducibility of power envelope correlation (PEC) was generally the highest among those connectivity measures which are insensitive to volume conduction effect. For the whole-brain network construction, single dipole modeling was better than the dimensionality reduction methods, such as mean or principal component analysis (PCA) of multiple dipoles of a region.

CONCLUSIONS

In conclusion, our results described the reproducibility of rsEEG power spectrum, connectivity measures, and network constructions, which could be considered in assessing inter-individual differences in brain-behavior relationships, as well as automatic biometric applications.

Role of kinaesthetic motor imagery in mirror-induced visual illusion as intervention in post-stroke rehabilitation

Mirror-induced visual illusion obtained through mirror therapy is widely used to facilitate motor recovery after stroke. Activation of primary motor cortex (M1) ipsilateral to the moving limb has been reported during mirror-induced visual illusion. However, the mechanism through which the mirror illusion elicits motor execution processes without movements observed in the mirrored limb remains unclear. This study aims to review evidence based on brain imaging studies for testing the hypothesis that neural processes associated with kinaesthetic motor imagery are attributed to ipsilateral M1 activation. Four electronic databases were searched. Studies on functional brain imaging, investigating the instant effects of mirror-induced visual illusion among stroke survivors and healthy participants were included. Thirty-five studies engaging 78 stroke survivors and 396 healthy participants were reviewed. Results of functional brain scans (n = 20) indicated that half of the studies (n = 10, 50%) reported significant changes in the activation of ipsilateral M1, which mediates motor preparation and execution. Other common neural substrates included primary somatosensory cortex (45%, kinaesthesia), precuneus (40%, image generation and self-processing operations) and cerebellum (20%, motor control). Similar patterns of ipsilateral M1 activations were observed in the two groups. These neural substrates mediated the generation, maintenance, and manipulation of motor-related images, which were the key processes in kinaesthetic motor imagery. Relationships in terms of shared neural substrates and mental processes between mirror-induced visual illusion and kinaesthetic motor imagery generate new evidence on the role of the latter in mirror therapy. Future studies should investigate the imagery processes in illusion training for post-stroke patients.

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence—a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

Pushing the Limits of EEG: Estimation of Large-Scale Functional Brain Networks and Their Dynamics Validated by Simultaneous fMRI

Functional magnetic resonance imaging (fMRI) is the technique of choice for detecting large-scale functional brain networks and to investigate their dynamics. Because fMRI measures brain activity indirectly, electroencephalography (EEG) has been recently considered a feasible tool for detecting such networks, particularly the resting-state networks (RSNs). However, a truly unbiased validation of such claims is still missing, which can only be accomplished by using simultaneously acquired EEG and fMRI data, due to the spontaneous nature of the activity underlying the RSNs. Additionally, EEG is still poorly explored for the purpose of mapping task-specific networks, and no studies so far have been focused on investigating networks' dynamic functional connectivity (dFC) with EEG. Here, we started by validating RSNs derived from the continuous reconstruction of EEG sources by directly comparing them with those derived from simultaneous fMRI data of 10 healthy participants, and obtaining an average overlap (quantified by the Dice coefficient) of 0.4. We also showed the ability of EEG to map the facial expressions processing network (FEPN), highlighting regions near the posterior superior temporal sulcus, where the FEPN is anchored. Then, we measured the dFC using EEG for the first time in this context, estimated dFC brain states using dictionary learning, and compared such states with those obtained from the fMRI. We found a statistically significant match between fMRI and EEG dFC states, and determined the existence of two matched dFC states which contribution over time was associated with the brain activity at the FEPN, showing that the dynamics of FEPN can be captured by both fMRI and EEG. Our results push the limits of EEG toward being used as a brain imaging tool, while supporting the growing literature on EEG correlates of (dynamic) functional connectivity measured with fMRI, and providing novel insights into the coupling mechanisms underlying the two imaging techniques.

Cognitive and spectral coherence of EEG alterations in resting state in children with chronic TBI

Introduction. TBI is associated with alterations in cortico-subcortical connectivity. However, little attention has been paid to its clinical characteristics and functional connectivity in pediatric patients with chronic TBI. Objective. To evaluate the cognitive performance and spectral coherence of a group of children with TBI in non-acute phase. Method. Cross-sectional study of 15 children with chronic TBI and 17 healthy children. The Neuropsychological Assessment of Children (Evaluación Neuropsicológica Infantil, ENI) was used and the resting activity of the EEG with eyes-closed was recorded. Offline, two-second epochs of the EEG of each participant were chosen and the spectral coherence was estimated in a range of 1.6 to 30 Hz. The cognitive performance between groups was compared with T-test/Mann-Whitney U Test and MANOVA for the coherence values. Results. The TBI group showed a lower performance (p ≤ 0.05) in metalinguistic, visuospatial skills, attention, memory, non-verbal flexibility, planning, and organization. Differences (p ≤ 0.000) were found both inter and intrahemispherically in the spectral coherence between the groups, particularly on F1-F3 (95% CI: 0.543 - 0.557) over the whole frequency range and F3-C3 (95% CI: 0.503 - 0.515) in delta, theta, alpha2, and beta frequencies. Discussion and conclusión. Our findings suggest alterations of hypo and hyper functional connectivity, particularly on the frontal and parietal lobes of both hemispheres, even after several years of a TBI. It is possible that a subtle difference in the degree of connectivity is crucial in the genesis or successful development of attentional, mnesic, executive, and visuospatial processes.

Cross-correlation task-related component analysis (xTRCA) for enhancing evoked and induced responses of event-related potentials

We propose an analysis method that extracts trial-reproducible (i.e., recurring) event-related spatiotemporal EEG patterns by optimizing a spatial filter as well as trial timings of task-related components in the time domain simultaneously in a unified manner. Event-related responses are broadly categorized into evoked and induced responses, but those are analyzed commonly in the time and the time-frequency domain, respectively. To facilitate a comparison of evoked and induced responses, a unified method for analyzing both evoked and induced responses is desired. Here we propose a method of cross-correlation task-related component analysis (xTRCA) as an extension of our previous method. xTRCA constructs a linear spatial filter and then optimizes trial timings of single trials based on trial reproducibility as an objective function. The spatial filter enhances event-related responses, and the temporal optimization compensates trial-by-trial latencies that are inherent to ERPs. We first applied xTRCA to synthetic data of induced responses whose phases varied from trial to trial, and found that xTRCA could realign the induced responses by compensating the phase differences. We then demonstrated with mismatch negativity data that xTRCA enhanced the event-related-potential waveform observed at a single channel. Finally, a classification accuracy was improved when trial timings were optimized by xTRCA, suggesting a practical application of the method for a brain computer interface. We conclude that xTRCA provides a unified framework to analyze and enhance event-related evoked and induced responses in the time domain by objectively maximizing trial reproducibility.

Automated Source Estimation of Scalp EEG Epileptic Activity Using eLORETA Kurtosis Analysis

OBJECTIVES

eLORETA (exact low-resolution brain electromagnetic tomography) is a technique created by Pascual-Marqui et al. [Int J Psychophysiol. 1994 Oct; 18(1): 49-65] for the 3-dimensional representation of current source density in the brain by electroencephalography (EEG) data. Kurtosis analysis allows for the identification of spiky activity in the brain. In this study, we focused on the evaluation of the reliability of eLORETA kurtosis analysis. For this purpose, the results of eLORETA kurtosis source localization of paroxysmal activity in EEG were compared with those of eLORETA current source density (CSD) analysis of EEG data in 3 epilepsy patients with partial seizures.

METHODS

EEG was measured using a digital EEG system with 19 channels. We set the bandpass filter at traditional frequency band settings (1-4, 4-8, 8-15, 15-30, and 30-60 Hz) and 5-10 and 20-70 Hz and performed eLORETA kurtosis to compare the source localization of paroxysmal activity with that of visual interpretation of EEG data and CSD analysis of eLORETA in focal epilepsy patients.

RESULTS

The eLORETA kurtosis analysis of EEG data preprocessed by bandpass filtering from 20 to 70 Hz and traditional frequency band settings did not show any discrete paroxysmal source activity compatible with the results of CSD analysis of eLORETA. In all 3 cases, eLORETA kurtosis analysis filtered at 5-10 Hz showed paroxysmal activities in the theta band, which were all consistent with the visual inspection results and the CSD analysis results.

DISCUSSION

Our findings suggested that eLORETA kurtosis analysis of EEG data might be useful for the identification of spiky paroxysmal activity sources in epilepsy patients. Since EEG is widely used in the clinical practice of epilepsy, eLORETA kurtosis analysis is a promising method that can be applied to epileptic activity mapping.

Characteristic Fluctuations Around Stable Attractor Dynamics Extracted from Highly Nonstationary Electroencephalographic Recordings

Since the discovery of electrical activity of the brain, electroencephalographic (EEG) recordings constitute one of the most popular techniques of brain research. However, EEG signals are highly nonstationary and one should expect that averages of the cross-correlation coefficient, which may take positive and negative values with equal probability, (almost) vanish when estimated over long data segments. Instead, we found that the average zero-lag cross-correlation matrix estimated with a running window over the whole night of sleep EEGs, or of resting state during eyes-open and eyes-closed conditions of healthy subjects shows a characteristic correlation pattern containing pronounced nonzero values. A similar correlation structure has already been encountered in scalp EEG signals containing focal onset seizures. Therefore, we conclude that this structure is independent of the physiological state. Because of its pronounced similarity across subjects, we believe that it depicts a generic feature of the brain dynamics. Namely, we interpret this pattern as a manifestation of a dynamical ground state of the brain activity, necessary to preserve an efficient operational mode, or, expressed in terms of dynamical system theory, we interpret it as a "shadow" of the evolution on (or close to) an attractor in phase space. Nonstationary dynamical aspects of higher cerebral processes should manifest in deviations from this stable pattern. We confirm this hypothesis through a correlation analysis of EEG recordings of 10 healthy subjects during night sleep, 20 recordings of 9 epilepsy patients, and 42 recordings of 21 healthy subjects in resting state during eyes-open and eyes-closed conditions. In particular, we show that the estimation of deviations from the stationary correlation structures provides a more significant differentiation of physiological states and more homogeneous results across subjects.

Changes in brain connectivity following exposure to bilateral eye movements

The present research assessed how engaging in bilateral eye movements influences brain activity. Participants had their resting-state brain activity recorded with electroencephalography (EEG) before and after they performed 30 s of bilateral eye movements or a center-control manipulation. We assessed differences in change scores for absolute power and coherence between the eye-movement and center-control conditions. A main effect for handedness was present for EEG power in the theta and beta frequency bands, with inconsistent-handed participants displaying a greater increase than consistent-handed participants in both frequency bands. For theta, the increase in power for inconsistent handers was specific to participants in the bilateral eye-movement condition, whose increase in theta power exceeded the increase in theta power for consistent-handed participants regardless of condition. In contrast, for coherence, a main effect for condition was present for the delta frequency band, with participants in the control condition exhibiting a significant drop in posterior delta coherence pre to post. We suggest that the maintenance of posterior delta coherence over time may be an important factor in sustaining attention. Further, the malleability of EEG power for inconsistent-handed participants reveals the importance of individual-differences variables in the potential for behavioral manipulations to change brain activity.

Directional information flow in patients with Alzheimer's disease. A source-space resting-state MEG study

In a recent magnetoencephalography (MEG) study, we found posterior-to-anterior information flow over the cortex in higher frequency bands in healthy subjects, with a reversed pattern in the theta band. A disruption of information flow may underlie clinical symptoms in Alzheimer's disease (AD). In AD, highly connected regions (hubs) in posterior areas are mostly disrupted. We therefore hypothesized that in AD the information flow from these hub regions would be disturbed. We used resting-state MEG recordings from 27 early-onset AD patients and 26 healthy controls. Using beamformer-based virtual electrodes, we estimated neuronal oscillatory activity for 78 cortical regions of interest (ROIs) and 12 subcortical ROIs of the AAL atlas, and calculated the directed phase transfer entropy (dPTE) as a measure of information flow between these ROIs. Group differences were evaluated using permutation tests and, for the AD group, associations between dPTE and general cognition or CSF biomarkers were determined using Spearman correlation coefficients. We confirmed the previously reported posterior-to-anterior information flow in the higher frequency bands in the healthy controls, and found it to be disturbed in the beta band in AD. Most prominently, the information flow from the precuneus and the visual cortex, towards frontal and subcortical structures, was decreased in AD. These disruptions did not correlate with cognitive impairment or CSF biomarkers. We conclude that AD pathology may affect the flow of information between brain regions, particularly from posterior hub regions, and that changes in the information flow in the beta band indicate an aspect of the pathophysiological process in AD.

Differences in Resting-state Quantitative Electroencephalography Patterns in Attention Deficit/Hyperactivity Disorder with or without Comorbid Symptoms

Objective

The aim of the present study was to evaluate the role of comorbid psychiatric symptoms on quantitative electroencephalogram (QEEG) activities in boys with the attention deficit/hyperactivity disorder (ADHD).

Methods

All participants were male students in the second, third or fourth grade in elementary school. Therefore, there were no significant differences in age or sex. Participants with ADHD were assigned to one of three groups: pure ADHD (n=22), ADHD with depressive symptoms (n=11), or ADHD with problematic internet use (n=19). The Korean version of the Children’s Depression Inventory and the Korean Internet Addiction Self-scale were used to assess depressive symptoms and problematic internet use, respectively. Resting-state EEG during eyes closed was recorded, and the absolute power of five frequency bands was analyzed: delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), and gamma (30–50 Hz).

Results

The ADHD with problematic internet use group showed decreased absolute theta power at the central and posterior region compared with the pure ADHD group. However, The ADHD with depressive symptoms group showed no significant differences compared with the other groups.

Conclusion

These findings will contribute to a better understanding of brain-based electrophysiological changes in children with ADHD in accordance with comorbid psychiatric symptoms.

Movement-related beta oscillations show high intra-individual reliability

Oscillatory activity in the beta frequency range (15-30Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic. Here, we used scalp electroencephalography (EEG) to evaluate intra-individual reliability of beta-band oscillations over six sessions, focusing on changes in beta activity during movement (Movement-Related Beta Desynchronization, MRBD) and after movement termination (Post-Movement Beta Rebound, PMBR). Subjects performed visually-cued unimanual wrist flexion and extension. We assessed Intraclass Correlation Coefficients (ICC) and between-session correlations for spectral power and peak frequency measures of movement-related and resting beta activity. Movement-related and resting beta power from both sensorimotor cortices was highly reliable across sessions. Resting beta power yielded highest reliability (average ICC=0.903), followed by MRBD (average ICC=0.886) and PMBR (average ICC=0.663). Notably, peak frequency measures yielded lower ICC values compared to the assessment of spectral power, particularly for movement-related beta activity (ICC=0.386-0.402). Our data highlight that power measures of movement-related beta oscillations are highly reliable, while corresponding peak frequency measures show greater intra-individual variability across sessions. Importantly, our finding that beta power estimates show high intra-individual reliability over time serves to validate the notion that these measures reflect meaningful individual differences that can be utilised in basic research and clinical studies.

Recent Advances in Resting-State Electroencephalography Biomarkers for Autism Spectrum Disorder-A Review of Methodological and Clinical Challenges

BACKGROUND

Electroencephalography (EEG) has been used for almost a century to identify seizure-related disorders in humans, typically through expert interpretation of multichannel recordings. Attempts have been made to quantify EEG through frequency analyses and graphic representations. These "traditional" quantitative EEG analysis methods were limited in their ability to analyze complex and multivariate data and have not been generally accepted in clinical settings. There has been growing interest in identification of novel EEG biomarkers to detect early risk of autism spectrum disorder, to identify clinically meaningful subgroups, and to monitor targeted intervention strategies. Most studies to date have, however, used quantitative EEG approaches, and little is known about the emerging multivariate analytical methods or the robustness of candidate biomarkers in the context of the variability of autism spectrum disorder.

METHODS

Here, we present a targeted review of methodological and clinical challenges in the search for novel resting-state EEG biomarkers for autism spectrum disorder.

RESULTS

Three primary novel methodologies are discussed: (1) modified multiscale entropy, (2) coherence analysis, and (3) recurrence quantification analysis. Results suggest that these methods may be able to classify resting-state EEG as "autism spectrum disorder" or "typically developing", but many signal processing questions remain unanswered.

CONCLUSIONS

We suggest that the move to novel EEG analysis methods is akin to the progress in neuroimaging from visual inspection, through region-of-interest analysis, to whole-brain computational analysis. Novel resting-state EEG biomarkers will have to evaluate a range of potential demographic, clinical, and technical confounders including age, gender, intellectual ability, comorbidity, and medication, before these approaches can be translated into the clinical setting.

Improving test-retest reliability of quantitative electroencephalography using different preprocessing approaches

This work aims to assess the effect of preprocessing approaches over test-retest reliability of quantitative electroencephalography measurements. Two electroencephalography sessions were recorded during an eyes-closed resting state condition in 15 young healthy individuals. The second session was 4 to 6 weeks after the first one. Clean recordings were obtained from the implementation of different preprocessing approaches commonly used in the literature. We then estimated the power spectrum density, for each individual and preprocessing approach, in six frequency bands: delta, theta, alpha1, alpha2, beta, and gamma. Test-retest reliability using the intraclass correlation coefficient was calculated for power spectrum in each methodology and frequency band. We found that the test-retest reliability varied considerably across frequency bands and preprocessing approaches. Reliability was higher for theta, alpha1, and alpha2 frequency bands. Also, the use of preprocessing approach that includes a robust reference to average and independent component analysis, can improve test-retest reliability in other bands such as beta and gamma. Results suggest that quantitative electroencephalography are test-retest reliable and can be used in longitudinal studies.