Electrophysiological changes during adolescence: A review

Trajectories of working memory and decision making abilities along juvenile development in mice

Rodents commonly serve as model organisms for the investigation of human mental disorders by capitalizing on behavioral commonalities. However, our understanding of the developmental dynamics of complex cognitive abilities in rodents remains incomplete. In this study, we examined spatial working memory as well as odor-and texture-based decision making in mice using a delayed non-match to sample task and a two-choice set-shifting task, respectively. Mice were investigated during different stages of development: pre-juvenile, juvenile, and young adult age. We show that, while working memory abilities in mice improve with age, decision making performance peaks during juvenile age by showing a sex-independent trajectory. Moreover, cFos expression, as a first proxy for neuronal activity, shows distinct age-and brain area-specific changes that relate to task-specific behavioral performance. The distinct developmental trajectories of working memory and decision making in rodents resemble those previously reported for humans.

Disruption of functional network development in children with prenatal Zika virus exposure revealed by resting-state EEG

Children born to mothers infected by Zika virus (ZIKV) during pregnancy are at increased risk of adverse neurodevelopmental outcomes including microcephaly, epilepsy, and neurocognitive deficits, collectively known as Congenital Zika Virus Syndrome. To study the impact of ZIKV on infant brain development, we collected resting-state electroencephalography (EEG) recordings from 28 normocephalic ZIKV-exposed children and 16 socio-demographically similar but unexposed children at 23-27 months of age. We assessed group differences in frequency band power and brain synchrony, as well as the relationship between these metrics and age. A significant difference (p < 0.05, Bonferroni corrected) in Inter-Site Phase Coherence was observed: median Pearson correlation coefficients were 0.15 in unexposed children and 0.07 in ZIKV-exposed children. Results showed that functional brain networks in the unexposed group were developing rapidly, in part by strengthening distal high-frequency and weakening proximal lower frequency connectivity, presumably reflecting normal synaptic growth, myelination and pruning. These maturation patterns were attenuated in the ZIKV-exposed group, suggesting that ZIKV exposure may contribute to neurodevelopmental vulnerabilities that can be detected and quantified by resting-state EEG.

Bayesian covariance regression in functional data analysis with applications to functional brain imaging

Function on scalar regression models relate functional outcomes to scalar predictors through the conditional mean function. With few and limited exceptions, many functional regression frameworks operate under the assumption that covariate information does not affect patterns of covariation. In this manuscript, we address this disparity by developing a Bayesian functional regression model, providing joint inference for both the conditional mean and covariance functions. Our work hinges on basis expansions of both the functional evaluation domain and covariate space, to define flexible non-parametric forms of dependence. To aid interpretation, we develop novel low-dimensional summaries, which indicate the degree of covariate-dependent heteroskedasticity. The proposed modeling framework is motivated and applied to a case study in functional brain imaging through electroencephalography, aiming to elucidate potential differentiation in the neural development of children with autism spectrum disorder.

Unveiling the hidden electroencephalographical rhythms during development: Aperiodic and Periodic activity in healthy subjects

OBJECTIVE

The study analyzes power spectral density (PSD) components, aperiodic (AP) and periodic (P) activity, in resting-state EEG of 240 healthy subjects from 6 to 29 years old, divided into 4 groups.

METHODS

We calculate AP and P components using the (Fitting Oscillations and One-Over-f (FOOOF)) plugging in EEGLAB. All PSD components were calculated from 1-45 Hz. Topography analysis, Spearman correlations, and regression analysis with age were computed for all components.

RESULTS

AP and P activity show different topography across frequencies and age groups. Age-related decreases in AP exponent and offset parameters lead to reduced power, while P power decreases (1-6 Hz) and increases (10-15 Hz) with age.

CONCLUSIONS

We support the distinction between the AP and P components of the PSD and its possible functional changes with age. AP power is dominant in the configuration of the canonical EEG rhythms topography, although P contribution to topography is embedded in the canonical EEG topography. Some EEG canonical characteristics are similar to those of the P component, as topographies of EEG rhythms (embedded) and increases in oscillatory frequency with age.

SIGNIFICANCE

We support that spectral power parameterization improves the interpretation and neurophysiological and functional accuracy of brain processes.

Interactive effects of social media use and puberty on resting-state cortical activity and mental health symptoms

Adolescence is a period of profound biopsychosocial development, with pubertally-driven neural reorganization as social demands increase in peer contexts. The explosive increase in social media access has fundamentally changed peer interactions among youth, creating an urgent need to understand its impact on neurobiological development and mental health. Extant literature indicates that using social media promotes social comparison and feedback seeking (SCFS) behaviors in youth, which portend increased risk for mental health disorders, but little is known about its impact on neurobiological development. We assessed social media behaviors, mental health symptoms, and spontaneous cortical activity using magnetoencephalography (MEG) in 80 typically developing youth (8-16 years) and tested how self-reported pubertal stage moderates their relationship. More mature adolescents who engaged in more SCFS showed weaker fusiform/parahippocampal alpha and medial prefrontal beta activity, and increased symptoms of anxiety and attention problems. Engaging in SCFS on social media during adolescence may thus relate to developmental differences in brain regions that undergo considerable development during puberty. These results are consistent with works indicating altered neurodevelopmental trajectories within association cortices surrounding the onset of many mental health disorders. Importantly, later pubertal stages may be most sensitive to the detrimental effects of social media use.

Childhood trauma is associated with developmental trajectories of EEG coherence, alcohol-related outcomes, and PTSD symptoms

BACKGROUND

Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

METHODS

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

RESULTS

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = -0.07, p = 0.02) and PFI (ß = -0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = -0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = -1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

CONCLUSIONS

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

A longitudinal study of breastmilk feeding duration, EEG power and early academic skills

BACKGROUND

The cognitive benefits of breastfeeding are widely recognized; however, its effects on brain development and later academic skills require further examination. This study aimed to examine the longitudinal relations between breastmilk feeding, neurophysiological changes, and early academic skills.

METHODS

In the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort, breastmilk feeding practices were collected every 3 months from 3 weeks to 18 months postpartum. Resting electroencephalography (EEG) was recorded at 18 months and power spectral density was derived. The outcomes were a set of early academic assessments administered at age 4 (n = 810). Structural equation modelling was used to investigate EEG power as a mediator between breastmilk duration and early academic skills.

RESULTS

Breastmilk feeding for ≥12 months was associated with better general knowledge, numeracy, and language at age 4 compared to shorter durations of breastmilk feeding (Cohen's d: 1.53-17.44). Linear regression showed that breastmilk duration was negatively and positively associated with low- (i.e., delta, theta) and high-frequency power (i.e., gamma), respectively (Cohen's f2: 0.03-0.09). After adjusting for demographic and child baseline covariates, a decrease in absolute and relative delta, as well as relative theta was associated with better general knowledge and numeracy (Cohen's f2: 0.16-0.25). Relative delta power provided an indirect path between breastmilk duration and early academic skills (x2: 18.390, p = 0.010; CFI: 0.978; TLI: 0.954; RMSEA: 0.040).

CONCLUSIONS

Extended breastmilk feeding is associated with reduced low-frequency power and better early academic skills, suggesting benefits to brain development. Additional research to confirm this finding is warranted.

The development of aperiodic and periodic resting-state power between early childhood and adulthood: New insights from optically pumped magnetometers

Neurophysiological signals, comprised of both periodic (e.g., oscillatory) and aperiodic (e.g., non-oscillatory) activity, undergo complex developmental changes between childhood and adulthood. With much of the existing literature primarily focused on the periodic features of brain function, our understanding of aperiodic signals is still in its infancy. Here, we are the first to examine age-related changes in periodic (peak frequency and power) and aperiodic (slope and offset) activity using optically pumped magnetometers (OPMs), a new, wearable magnetoencephalography (MEG) technology that is particularly well-suited for studying development. We examined age-related changes in these spectral features in a sample (N=65) of toddlers (1-3 years), children (4-5 years), young adults (20-26 years), and adults (27-38 years). Consistent with the extant literature, we found significant age-related decreases in the aperiodic slope and offset, and changes in peak frequency and power that were frequency-specific; we are the first to show that the effect sizes of these changes also varied across brain regions. This work not only adds to the growing body of work highlighting the advantages of using OPMs, especially for studying development, but also contributes novel information regarding the variation of neurophysiological changes with age across the brain.

From Infancy to Childhood: A Comprehensive Review of Event- and Task-Related Brain Oscillations

Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications.

Age-related changes in brain oscillatory patterns during an n-back task in children and adolescents

The development of brain oscillatory responses and their possible role in the working memory (WM) performance of children, adolescents and young adults was investigated. A set of 0- and 1-back tasks with letter stimuli were administered to a final sample of 131 subjects (between 6 and 20 years of age). A decrease in response times (RTs) and an increase of the sensitivity index d-prime (d') were seen with increased age. RTs increased and d' decreased with load, indicating higher difficulty for higher loads. Event-related synchronization (ERS) and event-related desynchronization (ERD) were obtained by the convolution of Morlet wavelets on the recorded EEG. Statistical analyses were performed of the absolute and relative power of brain oscillations defined by topography, frequency and latency. Posterior alpha and beta ERD, and frontocentral theta ERS, were induced by the stimuli presented during the n-back task. While relative theta ERS increased with age, absolute theta ERS, absolute and relative alpha and, absolute beta ERD, decreased with age. Age-related improvement in behavioral performance was mediated by relative theta. Alpha and beta ERD were more pronounced for the most difficult task (1-back) and for the target condition. Globally, there was high consistency of the effects of target type and task load across development. Theta ERS maturation is a crucial step for improving WM performance during development, while alpha and beta ERD maturation seem to be less critical for behavioral performance improvement with age, possibly due to a sufficient level of alpha-beta ERD for good performance in young children.

Late positive potential reveals sustained threat contingencies despite extinction in adolescents but not adults

BACKGROUND

Major theories link threat learning processes to anxiety symptoms, which typically emerge during adolescence. While this developmental stage is marked by substantial maturation of the neural circuity involved in threat learning, research directly examining adolescence-specific patterns of neural responding during threat learning is scarce. This study compared adolescents and adults in acquisition and extinction of conditioned threat responses assessed at the cognitive, psychophysiological, and neural levels, focusing on the late positive potential (LPP), an event-related potential (ERP) component indexing emotional valence.

METHOD

Sixty-five adults and 63 adolescents completed threat acquisition and extinction, 24 h apart, using the bell conditioning paradigm. Self-reported fear, skin conductance responses (SCR), and ERPs were measured.

RESULTS

Developmental differences emerged in neural and psychophysiological responses during threat acquisition, with adolescents displaying heightened LPP responses to threat and safety cues as well as heightened threat-specific SCR compared to adults. During extinction, SCR suggested comparable reduction in conditioned threat responses across groups, while LPP revealed incomplete extinction only among adolescents. Finally, age moderated the link between anxiety severity and LPP-assessed extinction, whereby greater anxiety severity was associated with reduced extinction among younger participants.

CONCLUSIONS

In line with developmental theories, adolescence is characterized by a specific age-related difficulty adapting to diminishing emotional significance of prior threats, contributing to heightened vulnerability to anxiety symptoms. Further, LPP appears to be sensitive to developmental differences in threat learning and may thus potentially serve as a useful biomarker in research on adolescents, threat learning, and anxiety.

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence

BACKGROUND

During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described.

METHODS

The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults.

RESULTS

Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults.

CONCLUSION

Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review

The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.

Sex-specific Differences in Resting Oscillatory Dynamics in Children with Prenatal Alcohol Exposure

At rest children with prenatal alcohol exposure (PAE) exhibit impaired static and dynamic functional connectivity, along with decreased alpha oscillations. Sex-specific information regarding the impact of PAE on whole-brain resting-state gamma spectral power remains unknown. Eyes-closed and eyes-open MEG resting-state data were examined in 83 children, ages 6-13 years of age. Using a matched design, the sample consisted of 42 typically developing children (TDC) (22 males/20 females) and 41 children with PAE and/or a fetal alcohol spectrum disorders (FASD) diagnosis (21 males/20 females). Whole-brain source resting-state spectral power was examined to determine group and sex specific relationships. Within gamma, we found sex and group specific changes such that female participants with PAE/FASD had increased gamma power when compared to female TDC and male participants with PAE/FASD. These differences were detected in most source regions analyzed during both resting-states, and were observed across the age spectrum examined. Within delta, we found sex and group specific changes such that female participants with PAE/FASD had decreased delta power when compared to female TDC and male participants with PAE/FASD. The reduced delta oscillations in female participants with PAE/FASD were detected in several source regions during eyes-closed rest and were evident at younger ages. These results indicate PAE alters neural oscillations during rest in a sex-specific manner, with females with PAE/FASD showing the largest perturbations. These results further demonstrate PAE has global effects on resting-state spectral power and connectivity, creating long-term consequences by potentially disrupting the excitation/inhibition balance in the brain, interrupting normative neurodevelopment.

Delta-Beta Coupling in Adolescents with Depression: A Preliminary Examination of Associations with Age, Symptoms, and Treatment Outcomes

Cognitive behavioral therapy (CBT) is effective in treating adolescent depressive symptoms but with variable treatment response. Heterogeneity in treatment outcome may be due in part to individual differences in cognitive and emotional processes in depressed adolescents, and there is a need to identify biomarkers associated with symptoms and treatment outcomes. There has been growing interest in leveraging electroencephalography (EEG) data to examine correspondence between multiple frequency bands, and delta-beta coupling in particular is thought to underlie emotion regulation and offers a promising biomarker in adolescent depression. In the present study, clinically depressed adolescents aged 14-18 years old (N=54) completed 6-minutes of EEG at rest before and after a 16-session group CBT program. Analyses were focused on associations of pre- and post-treatment delta-beta coupling power with age, depressive symptoms and clinician-rated severity at baseline and the end of treatment, and clinician-rated improvement. Results indicated that older adolescents showed lower delta-beta coupling than younger adolescents and girls showed higher coupling post-treatment. Greater delta-beta coupling before and after treatment was associated with greater clinician-rated severity. Surprisingly, greater pre-treatment delta-beta coupling was associated with lower self-reported depressive symptoms with treatment. These results suggest that elevated delta-beta coupling, potentially reflecting more difficulty regulating emotions, is associated with gender and age in adolescents with depression and may be related to greater severity and poorer treatment outcomes, but replication in larger samples is needed.

Reorganization of adolescent prefrontal cortex circuitry is required for mouse cognitive maturation

Most cognitive functions involving the prefrontal cortex emerge during late development. Increasing evidence links this delayed maturation to the protracted timeline of prefrontal development, which likely does not reach full maturity before the end of adolescence. However, the underlying mechanisms that drive the emergence and fine-tuning of cognitive abilities during adolescence, caused by circuit wiring, are still unknown. Here, we continuously monitored prefrontal activity throughout the postnatal development of mice and showed that an initial activity increase was interrupted by an extensive microglia-mediated breakdown of activity, followed by the rewiring of circuit elements to achieve adult-like patterns and synchrony. Interfering with these processes during adolescence, but not adulthood, led to a long-lasting microglia-induced disruption of prefrontal activity and neuronal morphology and decreased cognitive abilities. These results identified a nonlinear reorganization of prefrontal circuits during adolescence and revealed its importance for adult network function and cognitive processing.

Longitudinal Stability of Neural Correlates of Pediatric Attention Deficit Hyperactivity Disorder: A Pilot Study of Event Related Potentials and Electroencephalography

OBJECTIVE

Stability and developmental effects of electroencephalography (EEG) and event related potential (ERP) correlates of ADHD are understudied. This pilot study examined stability and developmental changes in ERP and EEG metrics of interest.

METHODS

Thirty-seven 7 to 11-year-old children with ADHD and 15 typically developing (TD) children completed EEG twice, 11 to 36 months apart. A series of mixed effects linear models were run to examine stability and developmental effects of EEG and ERP metrics.

RESULTS

Stability and developmental effects of EEG and ERP correlates of ADHD varied considerably across metrics. P3 amplitude was stable over time and showed diverging developmental trajectories across groups. Developmental differences were apparent in error related ERPs and resting aperiodic exponent. Theta-beta ratio was stable over time among all children.

CONCLUSIONS

Developmental trajectories of EEG and ERP correlates of ADHD are candidate diagnostic markers. Replication with larger samples is needed.

The emergence of the EEG dominant rhythm across the first year of life

The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.

Mapping neurodevelopment with sleep macro- and micro-architecture across multiple pediatric populations

Profiles of sleep duration and timing and corresponding electroencephalographic activity reflect brain changes that support cognitive and behavioral maturation and may provide practical markers for tracking typical and atypical neurodevelopment. To build and evaluate a sleep-based, quantitative metric of brain maturation, we used whole-night polysomnography data, initially from two large National Sleep Research Resource samples, spanning childhood and adolescence (total N = 4,013, aged 2.5 to 17.5 years): the Childhood Adenotonsillectomy Trial (CHAT), a research study of children with snoring without neurodevelopmental delay, and Nationwide Children's Hospital (NCH) Sleep Databank, a pediatric sleep clinic cohort. Among children without neurodevelopmental disorders (NDD), sleep metrics derived from the electroencephalogram (EEG) displayed robust age-related changes consistently across datasets. During non-rapid eye movement (NREM) sleep, spindles and slow oscillations further exhibited characteristic developmental patterns, with respect to their rate of occurrence, temporal coupling and morphology. Based on these metrics in NCH, we constructed a model to predict an individual's chronological age. The model performed with high accuracy (r = 0.93 in the held-out NCH sample and r = 0.85 in a second independent replication sample - the Pediatric Adenotonsillectomy Trial for Snoring (PATS)). EEG-based age predictions reflected clinically meaningful neurodevelopmental differences; for example, children with NDD showed greater variability in predicted age, and children with Down syndrome or intellectual disability had significantly younger brain age predictions (respectively, 2.1 and 0.8 years less than their chronological age) compared to age-matched non-NDD children. Overall, our results indicate that sleep architectureoffers a sensitive window for characterizing brain maturation, suggesting the potential for scalable, objective sleep-based biomarkers to measure neurodevelopment.

Changes in Behavior and Neural Dynamics across Adolescent Development

Adolescence is an important developmental period, during which substantial changes occur in brain function and behavior. Several aspects of executive function, including response inhibition, improve during this period. Correspondingly, structural imaging studies have documented consistent decreases in cortical and subcortical gray matter volume, and postmortem histologic studies have found substantial (∼40%) decreases in excitatory synapses in prefrontal cortex. Recent computational modeling work suggests that the change in synaptic density underlie improvements in task performance. These models also predict changes in neural dynamics related to the depth of attractor basins, where deeper basins can underlie better task performance. In this study, we analyzed task-related neural dynamics in a large cohort of longitudinally followed subjects (male and female) spanning early to late adolescence. We found that age correlated positively with behavioral performance in the Eriksen Flanker task. Older subjects were also characterized by deeper attractor basins around task related evoked EEG potentials during specific cognitive operations. Thus, consistent with computational models examining the effects of excitatory synaptic pruning, older adolescents showed stronger attractor dynamics during task performance.SIGNIFICANCE STATEMENT There are well-documented changes in brain and behavior during adolescent development. However, there are few mechanistic theories that link changes in the brain to changes in behavior. Here, we tested a hypothesis, put forward on the basis of computational modeling, that pruning of excitatory synapses in cortex during adolescence changes neural dynamics. We found, consistent with the hypothesis, that variability around event-related potentials shows faster decay dynamics in older adolescent subjects. The faster decay dynamics are consistent with the hypothesis that synaptic pruning during adolescent development leads to stronger attractor basins in task-related neural activity.

Developmental changes in endogenous testosterone have sexually-dimorphic effects on spontaneous cortical dynamics

The transition from childhood to adolescence is associated with an influx of sex hormones, which not only facilitates physical and behavioral changes, but also dramatic changes in neural circuitry. While previous work has shown that pubertal hormones modulate structural and functional brain development, few of these studies have focused on the impact that such hormones have on spontaneous cortical activity, and whether these effects are modulated by sex during this critical developmental window. Herein, we examined the effect of endogenous testosterone on spontaneous cortical activity in 71 typically-developing youth (ages 10-17 years; 32 male). Participants completed a resting-state magnetoencephalographic (MEG) recording, structural MRI, and provided a saliva sample for hormone analysis. MEG data were source-reconstructed and the power within five canonical frequency bands (delta, theta, alpha, beta, and gamma) was computed. The resulting power spectral density maps were analyzed via vertex-wise ANCOVAs to identify spatially specific effects of testosterone and sex by testosterone interactions, while covarying out age. We found robust sex differences in the modulatory effects of testosterone on spontaneous delta, beta, and gamma activity. These interactions were largely confined to frontal cortices and exhibited a stark switch in the directionality of the correlation from the low (delta) to high frequencies (beta/gamma). For example, in the delta band, greater testosterone related to lower relative power in prefrontal cortices in boys, while the reverse pattern was found for girls. These data suggest testosterone levels are uniquely related to the development of spontaneous cortical dynamics during adolescence, and such levels are associated with different developmental patterns in males and females within regions implicated in executive functioning.

Analysis of EEG features and study of automatic classification in first-episode and drug-naïve patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis.

OBJECTIVE

This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning.

METHODS

Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD.

RESULTS

Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region.

CONCLUSIONS

Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.

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

Objective

This study compares the complementary information from semi-quantitative EEG (sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect the life-long effects of early childhood malnutrition on the brain.

Methods

Resting-state EEGs (N = 202) from the Barbados Nutrition Study (BNS) were used to examine the effects of protein-energy malnutrition (PEM) on childhood and middle adulthood outcomes. sqEEG analysis was performed on Grand Total EEG (GTE) protocol, and a single latent variable, the semi-quantitative Neurophysiological State (sqNPS) was extracted. A univariate linear mixed-effects (LME) model tested the dependence of sqNPS and nutritional group. sqEEG was compared with scores on the Montreal Cognitive Assessment (MoCA). Stable sparse classifiers (SSC) also measured the predictive power of sqEEG, spectral-qEEG, and a combination of both. Multivariate LME was applied to assess each EEG modality separately and combined under longitudinal settings.

Results

The univariate LME showed highly significant differences between previously malnourished and control groups (p < 0.001); age (p = 0.01) was also significant, with no interaction between group and age detected. Childhood sqNPS (p = 0.02) and adulthood sqNPS (p = 0.003) predicted MoCA scores in adulthood. The SSC demonstrated that spectral-qEEG combined with sqEEG had the highest predictive power (mean AUC 0.92 ± 0.005). Finally, multivariate LME showed that the combined spectral-qEEG+sqEEG models had the highest log-likelihood (-479.7).

Conclusion

This research has extended our prior work with spectral-qEEG and the long-term impact of early childhood malnutrition on the brain. Our findings showed that sqNPS was significantly linked to accelerated cognitive aging at 45-51 years of age. While sqNPS and spectral-qEEG produced comparable results, our study indicated that combining sqNPS and spectral-qEEG yielded better performance than either method alone, suggesting that a multimodal approach could be advantageous for future investigations.

Significance

Based on our findings, a semi-quantitative approach utilizing GTE could be a valuable diagnostic tool for detecting the lasting impacts of childhood malnutrition. Notably, sqEEG has not been previously explored or reported as a biomarker for assessing the longitudinal effects of malnutrition. Furthermore, our observations suggest that sqEEG offers unique features and information not captured by spectral quantitative EEG analysis and could lead to its improvement.

Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition

This study analyses the spontaneous electroencephalogram (EEG) brain activity of 14 children diagnosed with Autism Spectrum Disorder (ASD) compared to 18 children with normal development, aged 5-11 years. (i) Power Spectral Density (PSD), (ii) variability across trials (coefficient of variation: CV), and (iii) complexity (multiscale entropy: MSE) of the brain signal analysis were computed on the resting state EEG. PSD (0.5-45 Hz) and CV were averaged over different frequency bands (low-delta, delta, theta, alpha, low-beta, high-beta and gamma). MSE were calculated with a coarse-grained procedure on 67 time scales and divided into fine, medium and coarse scales. In addition, significant neurophysiological variables were correlated with behavioral performance data (Kaufman Brief Intelligence Test (KBIT) and Autism Spectrum Quotient (AQ)). Results show increased PSD fast frequency bands (high-beta and gamma), higher variability (CV) and lower complexity (MSE) in children with ASD when compared to typically developed children. These results suggest a more variable, less complex and, probably, less adaptive neural networks with less capacity to generate optimal responses in ASD children.

Resting-state EEG alpha rhythm spectral power in children with specific language impairment: a cross-sectional study

PURPOSE

This study investigated EEG alpha rhythm spectral power in children with Specific Language Impairment (SLI) and compared it to typically developing children to better understand the electrophysiological characteristics of this disorder. Specifically, we explored resting-state EEG, because there are studies that point to it being linked to speech and language development.

METHODS

EEG recordings of 30 children diagnosed with specific language impairment and 30 typically developing children, aged 4.0-6.11 years, were carried out under eyes closed and eyes open conditions. Differences in alpha rhythm spectral power in relation to brain topography and experimental conditions were calculated.

RESULTS

In the eyes closed condition, alpha rhythm spectral power was statistically significantly lower in children with specific language impairment in the left temporal (T5) and occipital electrodes (O1, O2) than in typically developing children. In the eyes open condition, children with SLI showed significantly lower alpha rhythm spectral power in the left temporal (T3, T5), parietal (P3, Pz), and occipital electrodes (O1, O2). There were no statistically significant differences between the groups in relation to the relative change (the difference between average alpha rhythm spectral power during eyes closed condition and average alpha rhythm spectral power during eyes open condition divided by average alpha rhythm spectral power during eyes closed condition) in the alpha rhythm spectral power between the conditions.

CONCLUSION

Lower alpha rhythm spectral power in the left temporal, left, midline parietal, and occipital brain regions could be a valuable electrophysiological marker in children with SLI. Further investigation is needed to examine the connection between EEG alpha spectral power and general processing and memory deficits in patients with SLI.

Aberrant oscillatory activity in neurofibromatosis type 1: an EEG study of resting state and working memory

BACKGROUND

Neurofibromatosis type 1 (NF1) is a genetic neurodevelopmental disorder commonly associated with impaired cognitive function. Despite the well-explored functional roles of neural oscillations in neurotypical populations, only a limited number of studies have investigated oscillatory activity in the NF1 population.

METHODS

We compared oscillatory spectral power and theta phase coherence in a paediatric sample with NF1 (N = 16; mean age: 13.03 years; female: n = 7) to an age/sex-matched typically developing control group (N = 16; mean age: 13.34 years; female: n = 7) using electroencephalography measured during rest and during working memory task performance.

RESULTS

Relative to typically developing children, the NF1 group displayed higher resting state slow wave power and a lower peak alpha frequency. Moreover, higher theta power and frontoparietal theta phase coherence were observed in the NF1 group during working memory task performance, but these differences disappeared when controlling for baseline (resting state) activity.

CONCLUSIONS

Overall, results suggest that NF1 is characterised by aberrant resting state oscillatory activity that may contribute towards the cognitive impairments experienced in this population.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03310996 (first posted: October 16, 2017).

Multiscale entropy of ADHD children during resting state condition

This present study aims to investigate neural mechanisms underlying ADHD compared to healthy children through the analysis of the complexity and the variability of the EEG brain signal using multiscale entropy (MSE), EEG signal standard deviation (SDs), as well as the mean, standard deviation (SDp) and coefficient of variation (CV) of absolute spectral power (PSD). For this purpose, a sample of children diagnosed with attention-deficit/hyperactivity disorder (ADHD) between 6 and 17 years old were selected based on the number of trials and diagnostic agreement, 32 for the open-eyes (OE) experimental condition and 25 children for the close-eyes (CE) experimental condition. Healthy control subjects were age- and gender-matched with the ADHD group. The MSE and SDs of resting-state EEG activity were calculated on 34 time scales using a coarse-grained procedure. In addition, the PSD was averaged in delta, theta, alpha, and beta frequency bands, and its mean, SDp, and CV were calculated. The results show that the MSE changes with age during development, increases as the number of scales increases and has a higher amplitude in controls than in ADHD. The absolute PSD results show CV differences between subjects in low and beta frequency bands, with higher variability values in the ADHD group. All these results suggest an increased EEG variability and reduced complexity in ADHD compared to controls.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09869-0.

Age-related differences in transient gamma band activity during working memory maintenance through adolescence

Adolescence is a stage of development characterized by neurodevelopmental specialization of cognitive processes. In particular, working memory continues to improve through adolescence, with increases in response accuracy and decreases in response latency continuing well into the twenties. Human electroencephalogram (EEG) studies indicate that gamma oscillations (35-65 Hz) during the working memory delay period support the maintenance of mnemonic information guiding subsequent goal-driven behavior, which decrease in power with development. Importantly, recent electrophysiological studies have shown that gamma events, more so than sustained activity, may underlie working memory maintenance during the delay period. However, developmental differences in gamma events during working memory have not been studied. Here, we used EEG in conjunction with a novel spectral event processing approach to investigate age-related differences in transient gamma band activity during a memory guided saccade (MGS) task in 164 10- to 30-year-olds. Total gamma power was found to significantly decrease through adolescence, replicating prior findings. Results from the spectral event pipeline showed age-related decreases in the mean power of gamma events and trial-by-trial power variability across both the delay period and fixation epochs of the MGS task. In addition, we found that while event number decreased with age during the fixation period, the developmental decrease during the delay period was more dramatic, resulting in an increase in event spiking from fixation to delay in adolescence but not adulthood. While average power of the transient gamma events was found to mediate age-related differences in total gamma power in the fixation and delay periods, the number of gamma events was related to total power in only the delay period, suggesting that the power of gamma events may underlie the sustained gamma activity seen in EEG literature while the number of events may directly support age-related improvements in working memory maintenance. Our findings provide compelling new evidence for mechanistic changes in neural processing characterized by refinements in neural function as behavior becomes optimized in adulthood.

Does the Frontal Brain Electrical Activity Mediate the Effect of Home Executive Function Environment and Screen Time on Children's Executive Function?

Executive functions play an important role in various developmental aspects of children; however, environmental factors influencing individual differences in children's executive function and their neural substructures, particularly in middle childhood, are rarely investigated. Therefore, the current study aimed to investigate the relationship between the home executive function environment (HEFE) and screen time with the executive function of children aged 8-12 years by employing the mediating variables of alpha, beta, and theta waves. The parents of 133 normal children completed Barkley Deficits in Executive Functioning, HEFE, and Screen Time Scales. Alpha, beta, and theta brain waves were also measured. Data were examined using correlational and path analysis. The results suggested a positive and significant relationship between home executive functions and the executive functions of children. Furthermore, the results indicated an inverse and significant relationship between screen time and executive function. The results also proved the mediating role of alpha, beta, and theta brain waves in the relationship between screen time and the children's executive function. Environmental factors (such as home environment and screen time) affect the function of brain waves and, thus, the daily executive function of children.

Development is in the details: Event-related theta oscillations reveal children and adults verify multiplication facts differently

When verifying the correctness of single-digit multiplication problems, children and adults show a robust ERP correctness effect thought to reflect similar cognitive processes across groups. Recent studies suggest that this effect is instead a modulation of the negative-going N400 component in children, reflecting access to semantic memory, and the positive-going P300 component in adults, reflecting stimulus categorization. However, the relative difference in ERP amplitude is the same for both components, more positive for correct than incorrect solutions, presenting a challenge to ascertaining the appropriate interpretation. Time-frequency analysis (TFA) of the N400/P300 window provides an objective approach to dissociating these effects. TFA measured from solution onset during single-digit multiplication verification revealed significant modulations of event-related as theta power (3-6 Hz) in both groups. Correct trials elicit less power in children (9-12 years) and more power in adults relative to incorrect trials. These findings are consistent with modulations of the N400 and P300, respectively, where opposite effects were predicted for spectral power. The ERP results further support a reinterpretation of the multiplication correctness effect. In contrast, TFA of the N400 effect elicited to a word-picture verification task revealed the same event-related theta effect in both groups, with increased power for mismatched than matched pictures. Together, these findings provide evidence for a developmental shift in cognitive processing specific to the multiplication task. Models of arithmetic should account for this overlooked difference in cognitive processing between children and adults.

Age-related trends in aperiodic EEG activity and alpha oscillations during early- to middle-childhood

Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age). Power spectra were extracted from baseline EEG recordings (eyes closed, eyes open) for each participant and parameterized into aperiodic activity to derive the offset and exponent parameters and periodic alpha oscillatory activity to derive the alpha peak frequency and the associated power estimates. Multilevel models were run to investigate age-related trends and condition-dependent changes for each of these measures. We found quadratic age-related effects for both the aperiodic offset and exponent. In addition, we observed increases in periodic alpha peak frequency as a function of age. Aperiodic measures and periodic alpha power were larger in magnitude during eyes closed compared to the eyes open baseline condition. Taken together, these results advance our understanding of the maturational patterns/trajectories of brain development during early- to middle-childhood.

Child and adolescent development of the brain oscillatory activity during a working memory task

The developmental trajectories of brain oscillations during the encoding and maintenance phases of a Working Memory (WM) task were calculated. The Delayed-Match-to-Sample Test (DMTS) was applied to 239 subjects of 6-29 years, while EEG was recorded. The Event-Related Spectral Perturbation (ERSP) was obtained in the range between 1 and 25 Hz during the encoding and maintenance phases. Behavioral parameters of reaction times (RTs) and response accuracy were simultaneously recorded. The results indicate a myriad of transient and sustained bursts of oscillatory activity from low frequencies (1 Hz) to the beta range (up to 19 Hz). Beta and Low-frequency ERSP increases were prominent in the encoding phase in all age groups, while low-frequency ERSP indexed the maintenance phase only in children and adolescents, but not in late adolescents and young adults, suggesting an age-dependent neural mechanism of stimulus trace maintenance. While the latter group showed Beta and Alpha indices of anticipatory attention for the retrieval phase. Mediation analysis showed an important role of early Delta-Theta and late Alpha oscillations for mediation between age and behavioral responses performance. In conclusion, the results show a complex pattern of oscillatory bursts during the encoding and maintenance phases with a consistent pattern of developmental changes.

Theta band brainwaves in human resting EEG modulated by mobile phone radiofrequency

PURPOSE

Wireless communication has become an integral part of our lives. The growing number of antennas in our environment and the expanding use of mobile phones (MPs) are increasing the population's exposure to electromagnetic fields. The present study aimed to examine the potential impact of MPs radiofrequency electromagnetic fields (RF-EMF) exposure on the brainwaves of the resting electroencephalogram (EEG) in humans.

MATERIALS AND METHODS

Twenty-one healthy volunteers were exposed to Global System for Mobile communications (GSM) signal at 900 MHz MP RF-EMF. The maximum specific absorption rate (SAR) of the MP averaged on 10 g tissue and 1 g tissue were measured at 0.49 W/kg, 0.70 W/kg, respectively.

RESULTS

Results showed that while delta and beta rhythms of resting EEG were not affected, theta brainwaves were significantly modulated during exposure to RF-EMF related to MPs. For the first time, it was shown that this modulation is dependent on the eye condition, i.e. closed or open.

CONCLUSIONS

This study strongly suggests that acute exposure to RF-EMF alters the EEG theta rhythm at rest. Long-term exposure studies are required to explore the effect of this disruption in high-risk or sensitive populations.

Time-frequency neural dynamics of ADHD children and adolescents during a Working Memory task

The present report analyzed the time-frequency changes in Event-Related Spectral perturbations (ERSP) in a sample of ADHD children and adolescents compared to a normodevelopment (ND) sample. A delayed match-to-sample (DMTS) test of working memory (WM) was presented to a group of ADHD subjects (N = 29) and compared with ND group (N = 34) with ages between 6 and 17 years old. Time-frequency decomposition was computed through wavelets. ADHD subjects presented higher Reaction Time (RT), Standard Deviation of RT (Std of RT), and a reduced percentage of correct responses. The results showed a complex pattern of oscillatory bursts during the encoding, maintenance, and recognition phases with similar dynamics in both groups. ADHD children presented a reduced Event-Related Synchronization (ERS) in the Theta range during the encoding phase, and also a reduced Alpha ERS during the late period of the maintenance phase. S1 Early theta ERS was positively correlated with Std of RT. Behavioral data, early Theta, and late Alpha ERS classified correctly above 70 % of ADHD and ND subjects when a linear discriminant analysis was applied. The reduced encoding and maintenance impaired brain dynamics of ADHD subjects would justify the poorer performance of this group of subjects.

Longitudinal change of inhibitory control functional connectivity associated with the development of heavy alcohol drinking

Introduction

Heavy drinking (HD) prevalent pattern of alcohol consumption among adolescents, particularly concerning because of their critical vulnerability to the neurotoxic effects of ethanol. Adolescent neurodevelopment is characterized by critical neurobiological changes of the prefrontal, temporal and parietal regions, important for the development of executive control processes, such as inhibitory control (IC). In the present Magnetoencephalography (MEG) study, we aimed to describe the relationship between electrophysiological Functional Connectivity (FC) during an IC task and HD development, as well as its impact on functional neuromaturation.

Methods

We performed a two-year longitudinal protocol with two stages. In the first stage, before the onset of HD, we recorded brain electrophysiological activity from a sample of 67 adolescents (mean age = 14.6 ± 0.7) during an IC task. Alcohol consumption was measured using the AUDIT test and a semi-structured interview. Two years later, in the second stage, 32 of the 67 participants (mean age 16.7 ± 0.7) completed a similar protocol. As for the analysis in the first stage, the source-space FC matrix was calculated, and then, using a cluster-based permutation test (CBPT) based on Spearman's correlation, we calculated the correlation between the FC of each cortical source and the number of standard alcohol units consumed two years later. For the analysis of longitudinal change, we followed a similar approach. We calculated the symmetrized percentage change (SPC) between FC at both stages and performed a CBPT analysis, analyzing the correlation between FC change and the level of alcohol consumed in a regular session.

Results

The results revealed an association between higher beta-band FC in the prefrontal and temporal regions and higher consumption years later. Longitudinal results showed that greater future alcohol consumption was associated with an exacerbated reduction in the FC of the same areas.

Discussion

These results underline the existence of several brain functional differences prior to alcohol misuse and their impact on functional neuromaturation.

Longitudinal investigation in children and adolescents with ADHD and healthy controls: A 2-year ERP study

Cross-sectional group comparisons have shown altered neurocognitive and neurophysiological profiles in individuals with attention-deficit/hyperactivity disorder (ADHD). We report a two-year longitudinal observational study of ADHD children and adolescents (N = 239) regarding ADHD symptoms, behavioral metrics, and event-related potentials (ERP) and compared them to healthy controls (N = 91). The participants were assessed up to five times with a cued Go/NoGo task while ERPs were recorded. We fitted the trajectories of our variables of interest with univariate and bivariate latent growth curve models. At baseline, the ADHD group had increased reaction time variability, higher number of omission and commission errors, and attenuated CNV and P3d amplitudes compared to controls. The task performance in terms of behavioral metrics improved in both groups over two years; however, with differential patterns: the decrease in reaction time and omission errors were stronger in the control group, and the reduction of commission errors was more substantial in the ADHD group. The cueP3, CNV, and N2d amplitudes changed slightly over two years, with negligible differences between both groups. Furthermore, the parent-rated symptom burden in the ADHD group decreased by 22 % (DSM-5-based questionnaire). We did not identify any associations between the changes in symptoms and the changes in the behavioral or neurophysiological metrics. The lack of association between the changes in symptoms and the behavioral or ERP metrics supports the trait liability hypothesis, which claims that the neurocognitive deficits are independent of symptom alleviation. Furthermore, the change in symptom burden was substantial, questioning the stability of the reported ADHD symptoms.

Inhibitory Control Development: A Network Neuroscience Perspective

As one of the core executive functions, inhibition plays an important role in human life through development. Inhibitory control is defined as the ability to suppress actions when they are unlikely to accomplish valuable results. Contemporary neuroscience has investigated the underlying neural mechanisms of inhibitory control. The controversy started to arise, which resulted in two schools of thought: a modulatory and a network account of inhibitory control. In this systematic review, we survey developmental mechanisms in inhibitory control as well as neurodevelopmental diseases related to inhibitory dysfunctions. This evidence stands against the modulatory perspective of inhibitory control: the development of inhibitory control does not depend on a dedicated region such as the right inferior frontal gyrus (rIFG) but relies on a more broadly distributed network.

Decreased resting-state alpha peak frequency in children and adolescents with fetal alcohol spectrum disorders or prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can result in long-lasting changes to physical, behavioral, and cognitive functioning in children. PAE might result in decreased white matter integrity, corticothalamic tract integrity, and alpha cortical oscillations. Previous investigations of alpha oscillations in PAE/fetal alcohol spectrum disorder (FASD) have focused on average spectral power at specific ages; therefore, little is known about alpha peak frequency (APF) or its developmental trajectory making this research novel. Using resting-state MEG data, APF was determined from parietal/occipital regions in participants with PAE/FASD or typically developing controls (TDC). In total, MEG data from 157 infants, children, and adolescents ranging in age from 6 months to 17 years were used, including 17 individuals with PAE, 61 individuals with an FASD and 84 TDC. In line with our hypothesis, we found that individuals with PAE/FASD had significantly reduced APF relative to TDC. Both age and group were significantly related to APF with differences between TDC and PAE/FASD persisting throughout development. We did not find evidence that sex or socioeconomic status had additional impact on APF. Reduced APF in individuals with an FASD/PAE may represent a long-term deficit and demonstrates the detrimental impact prenatal alcohol exposure can have on neurophysiological processes.

Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome

Association between familial loading for alcohol use disorders (AUD) and event-related potentials (ERPs) suggests a genetic basis for these oscillations though much less is known about epigenetic pathways influenced by environmental variation. Early life adversity (ELA) influences negative outcomes much later in life. The stress-activated neuropeptide corticotropin-releasing hormone (CRH) contributes to the deleterious effects of ELA on brain structure and function in animals. Accordingly, we hypothesized that ELA would be related to cortical thickness and electrophysiological characteristics through an epigenetic effect on CRH receptor type-1 (CRHR1) methylation. A total of 217 adolescent and young adult participants from either multiplex alcohol dependence or control families were scanned using magnetic resonance imaging (MRI) at 3T and cortical thickness was determined. Longitudinal follow-up across childhood, adolescence, and young adulthood provided developmental ERP data and measures of adversity. Blood samples for genetic and epigenetic analyses were obtained in childhood. Cortical thickness and visual ERP components were analyzed for their association and tested for familial risk group differences. Visual P300 amplitude at Pz and cortical thickness of the left lateral orbitofrontal region (LOFC), were significantly related to risk group status. LOFC cortical thickness showed a negative correlation with CRHR1 methylation status and with childhood total stress scores from the Life Stressors and Social Resources Inventory (LISRES). Stress scores were also significantly related to P300 amplitude recorded in childhood. The present results suggest that early life adversity reflected in greater total LISRES stress scores in childhood can impact the methylation of the CRHR1 gene with implications for brain development as seen in cortical thickness and electrophysiological signals emanating from particular brain regions.

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development

BACKGROUND

Assessing brain activity during rest has become a widely used approach in developmental neuroscience. Extant literature has measured resting brain activity both during eyes-open and eyes-closed conditions, but the difference between these conditions has not yet been well characterized. Studies, limited to fMRI and EEG, have suggested that eyes-open versus -closed conditions may differentially impact neural activity, especially in visual cortices.

METHODS

Spontaneous cortical activity was recorded using MEG from 108 typically developing youth (9-15 years-old; 55 female) during separate sessions of eyes-open and eyes-closed rest. MEG source images were computed, and the strength of spontaneous neural activity was estimated in the canonical delta, theta, alpha, beta, and gamma bands, respectively. Power spectral density maps for eyes-open were subtracted from eyes-closed rest, and then submitted to vertex-wise regression models to identify spatially specific differences between conditions and as a function of age and sex.

RESULTS

Relative alpha power was weaker in the eyes-open compared to -closed condition, but otherwise eyes-open was stronger in all frequency bands, with differences concentrated in the occipital cortex. Relative theta power became stronger in the eyes-open compared to the eyes-closed condition with increasing age in frontal cortex. No differences were observed between males and females.

CONCLUSIONS

The differences in relative power from eyes-closed to -open conditions are consistent with changes observed in task-based visual sensory responses. Age differences occurred in relatively late developing frontal regions, consistent with canonical attention regions, suggesting that these differences could be reflective of developmental changes in attention processes during puberty. Taken together, resting-state paradigms using eyes-open versus -closed produce distinct results and, in fact, can help pinpoint sensory related brain activity.

Decomposing the role of alpha oscillations during brain maturation

Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body of literature investigated accompanying neurophysiological changes, focusing on the most dominant feature of the human EEG signal: the alpha oscillation. Recent developments in EEG signal-processing show that conventional measures of alpha power are confounded by various factors and need to be decomposed into periodic and aperiodic components, which represent distinct underlying brain mechanisms. It is therefore unclear how each part of the signal changes during brain maturation. Using multivariate Bayesian generalized linear models, we examined aperiodic and periodic parameters of alpha activity in the largest openly available pediatric dataset (N=2529, age 5-22 years) and replicated these findings in a preregistered analysis of an independent validation sample (N=369, age 6-22 years). First, the welldocumented age-related decrease in total alpha power was replicated. However, when controlling for the aperiodic signal component, our findings provided strong evidence for an age-related increase in the aperiodic-adjusted alpha power. As reported in previous studies, also relative alpha power revealed a maturational increase, yet indicating an underestimation of the underlying relationship between periodic alpha power and brain maturation. The aperiodic intercept and slope decreased with increasing age and were highly correlated with total alpha power. Consequently, earlier interpretations on age-related changes of total alpha power need to be reconsidered, as elimination of active synapses rather links to decreases in the aperiodic intercept. Instead, analyses of diffusion tensor imaging data indicate that the maturational increase in aperiodic-adjusted alpha power is related to increased thalamocortical connectivity. Functionally, our results suggest that increased thalamic control of cortical alpha power is linked to improved attentional performance during brain maturation.

Impulsivity Moderates the Effect of Neurofeedback Training on the Contingent Negative Variation in Autism Spectrum Disorder

Background

The contingent negative variation (CNV) is a well-studied indicator of attention- and expectancy-related processes in the human brain. An abnormal CNV amplitude has been found in diverse neurodevelopmental psychiatric disorders. However, its role as a potential biomarker of successful clinical interventions in autism spectrum disorder (ASD) remains unclear.

Methods

In this randomized controlled trial, we investigated how the CNV changes following an intensive neurofeedback training. Therefore, twenty-one adolescents with ASD underwent 24 sessions of slow cortical potential (SCP) neurofeedback training. Twenty additional adolescents with ASD formed a control group and received treatment as usual. CNV waveforms were obtained from a continuous performance test (CPT), which all adolescents performed before and after the corresponding 3-month long training period. In order to utilize all available neural time series, trial-based area under the curve values for all four electroencephalogram (EEG) channels were analyzed with a hierarchical Bayesian model. In addition, the model included impulsivity, inattention, and hyperactivity as potential moderators of change in CNV.

Results

Our model implies that impulsivity moderates the effects of neurofeedback training on CNV depending on group. In the control group, the average CNV amplitude decreased or did not change after treatment as usual. In the experimental group, the CNV changed depending on the severity of comorbid impulsivity symptoms. The average CNV amplitude of participants with low impulsivity scores decreased markedly, whereas the average CNV amplitude of participants with high impulsivity increased.

Conclusion

The degree of impulsivity seems to play a crucial role in the changeability of the CNV following an intensive neurofeedback training. Therefore, comorbid symptomatology should be recorded and analyzed in future EEG-based brain training interventions.

Clinical Trial Registration

https://www.drks.de, identifier DRKS00012339.

Abnormal phase-amplitude coupling characterizes the interictal state in epilepsy

OBJECTIVE

 Diagnosing epilepsy still requires visual interpretation of electroencephalography and magnetoencephalography (MEG) by specialists, which prevents quantification and standardization of diagnosis. Previous studies proposed automated diagnosis by combining various features from electroencephalography and MEG, such as relative power (Power) and functional connectivity. However, the usefulness of interictal phase-amplitude coupling (PAC) in diagnosing epilepsy is still unknown. We hypothesized that resting-state PAC would be different for patients with epilepsy in the interictal state and for healthy participants such that it would improve discrimination between the groups.

METHODS

 We obtained resting-state MEG and magnetic resonance imaging in 90 patients with epilepsy during their preoperative evaluation and in 90 healthy participants. We used the cortical currents estimated from MEG and magnetic resonance imaging to calculate Power in the δ (1-3 Hz), θ (4-7 Hz), α (8-13 Hz), β (13-30 Hz), low γ (35-55 Hz), and high γ (65-90 Hz) bands and functional connectivity in the θ band. PAC was evaluated using the synchronization index (SI) for eight frequency band pairs: the phases of δ, θ, α, and β and the amplitudes of low and high γ. First, we compared the mean SI values for the patients with epilepsy and the healthy participants. Then, using features such as PAC, Power, functional connectivity, and features extracted by deep learning individually or combined, we tested whether PAC improves discrimination accuracy for the two groups.

RESULTS

 The mean SI values were significantly different for the patients with epilepsy and the healthy participants. The SI value difference was highest for θ/low γ in the temporal lobe. Discrimination accuracy was the highest, at 90%, using the combination of PAC and deep learning.

SIGNIFICANCE

 Abnormal PAC characterized the patients with epilepsy in the interictal state compared with the healthy participants, potentially improving the discrimination of epilepsy.

Altered spontaneous cortical activity predicts pain perception in individuals with cerebral palsy

Cerebral palsy is the most common paediatric neurological disorder and results in extensive impairment to the sensorimotor system. However, these individuals also experience increased pain perception, resulting in decreased quality of life. In the present study, we utilized magnetoencephalographic brain imaging to examine whether alterations in spontaneous neural activity predict the level of pain experienced in a cohort of 38 individuals with spastic diplegic cerebral palsy and 67 neurotypical controls. Participants completed 5 min of an eyes closed resting-state paradigm while undergoing a magnetoencephalography recording. The magnetoencephalographic data were then source imaged, and the power within the delta (2–4 Hz), theta (5–7 Hz), alpha (8–12 Hz), beta (15–29 Hz), low gamma (30–59 Hz) and high gamma (60–90 Hz) frequency bands were computed. The resulting power spectral density maps were analysed vertex-wise to identify differences in spontaneous activity between groups. Our findings indicated that spontaneous cortical activity was altered in the participants with cerebral palsy in the delta, alpha, beta, low gamma and high gamma bands across the occipital, frontal and secondary somatosensory cortical areas (all p_FWE < 0.05). Furthermore, we also found that the altered beta band spontaneous activity in the secondary somatosensory cortices predicted heightened pain perception in the individuals with cerebral palsy (P = 0.039). Overall, these results demonstrate that spontaneous cortical activity within individuals with cerebral palsy is altered in comparison to their neurotypical peers and may predict increased pain perception in this patient population. Potentially, changes in spontaneous resting-state activity may be utilized to measure the effectiveness of current treatment approaches that are directed at reducing the pain experienced by individuals with cerebral palsy.

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.

Electrocorticography to Investigate Age-Related Brain Lateralization on Pediatric Motor Inhibition

Response inhibition refers to the ability to suppress inappropriate actions that interfere with goal-driven behavior. The inferior frontal gyrus (IFG) is known to be associated with inhibition of a motor response by assuming executive control over motor cortex outputs. This study aimed to evaluate the pediatric development of response inhibition through subdural electrocorticography (ECoG) recording. Subdural ECoG recorded neural activities simultaneously during a Go/No-Go task, which was optimized for children. Different frequency power [theta: 4–8 Hz; beta: 12–40 Hz; high-gamma (HG): 70–200 Hz] was estimated within the IFG and motor cortex. Age-related analysis was computed by each bandpass power ratio between Go and No-Go conditions, and phase-amplitude coupling (PAC) over IFG by using the modulating index metric in two conditions. For all the eight pediatric patients, HG power was more activated in No-Go trials than in Go trials, in either right- or left-side IFG when available. In the IFG region, the power over theta and HG in No-Go conditions was higher than those in Go conditions, with significance over the right side (p < 0.05). The age-related lateralization from both sides to the right side was observed from the ratio of HG power and PAC value between the No-Go and Go trials. In the pediatric population, the role of motor inhibition was observed in both IFG, with age-related lateralization to the right side, which was proved in the previous functional magnetic resonance imaging studies. In this study, the evidence correlation of age and response inhibition was observed directly by the evidence of cortical recordings.

Neurophysiological correlates of interference control and response inhibition processes in children and adolescents engaging in open- and closed-skill sports

BACKGROUND

Accumulating evidence suggests that sports participation promotes the development of inhibitory control, but the influences of the sports category and inhibition type still remain unclear. The categorization of sports based on the open-skill (externally paced) and closed-skill (self-paced) continuum allows for the integration of the environment as a factor contributing to sports-related benefits for inhibitory control.

METHODS

Cross-sectional data from different studies were combined (n = 184) to examine the association between open- and closed-skill sports and cognitive control processes related to interference control and response inhibition. Participants (aged 9-14 years) filled in 7-day physical activity recall protocols and completed a Stroop Color-Word or a Go/NoGo task. The N200, N450, and P300 components of event-related potentials elicited by these tasks were recorded using electroencephalography.

RESULTS

Partial correlations supported the belief that time spent in open-skill sports was related to higher performance on inhibition trials. Additionally, path analyses revealed an association between this sports type and a greater negativity in the N200 and N450 amplitudes in both the full sample and group-level analyses. In contrast, no relation was found between sports type and P300 amplitude.

CONCLUSION

The findings suggest that only the engagement in open-skill sports is associated with more effective conflict monitoring and higher performance on tasks demanding inhibitory control.

Developmental trajectory of MEG resting-state oscillatory activity in children and adolescents: a longitudinal reliability study

Neural oscillations may be sensitive to aspects of brain maturation such as myelination and synaptic density changes. Better characterization of developmental trajectories and reliability is necessary for understanding typical and atypical neurodevelopment. Here, we examined reliability in 110 typically developing children and adolescents (aged 9-17 years) across 2.25 years. From 10 min of magnetoencephalography resting-state data, normalized source spectral power and intraclass correlation coefficients were calculated. We found sex-specific differences in global normalized power, with males showing age-related decreases in delta and theta, along with age-related increases in beta and gamma. Females had fewer significant age-related changes. Structural magnetic resonance imaging revealed that males had more total gray, subcortical gray, and cortical white matter volume. There were significant age-related changes in total gray matter volume with sex-specific and frequency-specific correlations to normalized power. In males, increased total gray matter volume correlated with increased theta and alpha, along with decreased gamma. Split-half reliability was excellent in all frequency bands and source regions. Test-retest reliability ranged from good (alpha) to fair (theta) to poor (remaining bands). While resting-state neural oscillations can have fingerprint-like quality in adults, we show here that neural oscillations continue to evolve in children and adolescents due to brain maturation and neurodevelopmental change.

Sound omission related brain responses in children

Action is an important way for children to learn about the world. Recent theories suggest that action is inherently accompanied by the sensory prediction of its effects. Such predictions can be revealed by rarely omitting the expected sensory consequence of the action, resulting in an omission response that is observable in the EEG. Although prediction errors play an important role in models of learning and development, little is known about omission-related brain responses in children. This study used a motor-auditory omission paradigm, testing a group of 6-8-year-old children and an adult group (N = 31 each). In an identity-specific condition, the sound coupled to the motor action was predictable, while in an identity unspecific condition the sound was unpredictable. Results of a temporal principal component analysis revealed that sound-related brain responses underlying the N1-complex differed considerably between age groups. Despite these developmental differences, omission responses (oN1) were similar between age groups. Two subcomponents of the oN1 were differently affected by specific and unspecific predictions. Results demonstrate that children, independent from the maturation of sound processing mechanisms, can implement specific and unspecific predictions as flexibly as adults. This supports theories that regard action and prediction error as important drivers of cognitive development.