Relations between frontal EEG maturation and inhibitory control in preschool in the prediction of children's early academic skills

Linking caregiving quality during infancy to brain activity in early childhood and later executive function

There is no relationship more vital than the one a child shares with their primary caregivers early in development. Yet many children worldwide are raised in settings that lack the warmth, connection, and stimulation provided by a responsive primary caregiver. In this study, we used data from the Bucharest Early Intervention Project (BEIP), a longitudinal study of institutionally-reared and family-reared children, to test how caregiving quality during infancy is associated with average EEG power over the first 3.5 years of life in alpha, beta, and theta frequency bands, and associations with later executive function (EF) at age 8 years. The sample comprised 189 children (129 institutionally-reared; 60 family-reared) who contributed data on observed caregiving quality during infancy (baseline; average age of 22 months), resting EEG power at baseline, 30, and 42 months, and performance-based data on a series of EF tasks at 8 years. Using Bayesian estimation, observed caregiving quality at baseline was marginally linked with higher average alpha and beta power, and lower theta power, from baseline to 42 months. In turn, higher average beta power and lower average theta power were marginally associated with higher EF at 8 years. In indirect effects models, higher caregiving quality at baseline was associated with higher EF at 8 years, with a marginal indirect effect through average theta power from baseline to 42 months. Variation in the quality of the early caregiving environment may be associated with later executive function, which is partially underpinned by individual differences in brain activity during early childhood. RESEARCH HIGHLIGHTS: Examined associations between caregiving quality during infancy, brain activity during early childhood, and executive function during mid-childhood in sample of never-institutionalized and institutionally-reared children. Significant associations between higher quality caregiving during infancy and higher executive function during middle childhood. Marginal associations between caregiving quality during infancy and brain activity during early childhood. Marginal associations between brain activity during early childhood and executive function during mid-childhood.

Personalized virtual reality exposure for panic disorder and agoraphobia: A preliminary neurophysiological study

BACKGROUND

Personalization is considered an important principle in virtual reality (VR) exposure therapy. We aimed to identify whether personalized VR exposure could provoke increased anxiety in patients with panic disorder and agoraphobia as it is considered the first step in successful treatment for anxiety.

METHODS

We performed a double-arm, one-day preliminary study among 28 patients with panic disorder and agoraphobia. Three sessions of VR exposure, including a theater, train, and elevator scenario, were conducted in two groups. In the personalized group (n = 14), the brightness and crowd density were customized based on a pre-assessment. In the control group (n = 14), these conditions were fully randomized. Self-reported anxiety, heart rate, skin conductance, and electroencephalography were measured before, during, and after the VR sessions.

RESULTS

In the later VR sessions, higher self-reported anxiety levels measured by the Visual Analogue Scale were observed in the personalized exposure group. Increased heart rates during and after the VR sessions were observed in the personalized group. The changes in skin conductance peaks were not significantly different between the groups, but the increase in skin conductance was associated with the participants' perception of presence. The electroencephalogram showed widespread increases in alpha waves in the frontal and temporal areas of the brain in the personalized group than in the control group.

CONCLUSION

Personalized VR exposure elicits stronger anxiogenic effects in patients with panic disorder and agoraphobia as suggested by self-report and neurophysiological data. Personalization of VR exposure has the potential for effective behavioral therapy.

Early development of electrophysiological activity: Contribution of periodic and aperiodic components of the EEG signal

Brain function rapidly changes in the first 2 years of life. In the last decades, resting-state EEG has been widely used to explore those changes. Previous studies have focused on the relative power of the signal in established frequency bands (i.e., theta, alpha, and beta). However, EEG power is a mixture of a 1/f-like background power (aperiodic) in combination with narrow peaks that appear over that curve (periodic activity, e.g., alpha peak). Therefore, it is possible that relative power captures both, aperiodic and periodic brain activity, contributing to changes in electrophysiological activity observed in infancy. For this reason, we explored the early developmental trajectory of the relative power in theta, alpha, and beta frequency bands from infancy to toddlerhood and compared it with changes in periodic activity in a longitudinal study with three waves at age 6, 9, and 16 to 18 months. Finally, we tested the contribution of periodic activity and aperiodic components of the EEG to age changes in relative power. We found that relative power and periodic activity trajectories differed in this period in all the frequency bands but alpha. Furthermore, aperiodic EEG activity flattened between 6 and 18 months. More importantly, only alpha relative power was exclusively related to periodic activity, whereas aperiodic components of the signal significantly contributed to the relative power of activity in theta and beta bands. Thus, relative power in these frequencies is influenced by developmental changes of the aperiodic activity, which should be considered for future studies.

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.

Microstate analysis in infancy

BACKGROUND

Microstate analysis is an emerging method for investigating global brain connections using electroencephalography (EEG). Microstates have been colloquially referred to as the "atom of thought," meaning that from these underlying networks comes coordinated neural processing and cognition. The present study examined microstates at 6-, 8-, and 10-months of age. It was hypothesized that infants would demonstrate distinct microstates comparable to those identified in adults that also parallel resting-state networks using fMRI. An additional exploratory aim was to examine the relationship between microstates and temperament, assessed via parent reports, to further demonstrate microstate analysis as a viable tool for examining the relationship between neural networks, cognitive processes as well as emotional expression embodied in temperament attributes.

METHODS

The microstates analysis was performed with infant EEG data when the infant was either 6- (n = 12), 8- (n = 16), or 10-months (n = 6) old. The resting-state task involved watching a 1-minute video segment of Baby Einstein while listening to the accompanying music. Parents completed the IBQ-R to assess infant temperament.

RESULTS

Four microstate topographies were extracted. Microstate 1 had an isolated posterior activation; Microstate 2 had a symmetric occipital to prefrontal orientation; Microstate 3 had a left occipital to right frontal orientation; and Microstate 4 had a right occipital to left frontal orientation. At 10-months old, Microstate 3, thought to reflect auditory/language processing, became activated more often, for longer periods of time, covering significantly more time across the task and was more likely to be transitioned into. This finding is interpreted as consistent with language acquisition and phonological processing that emerges around 10-months. Microstate topographies and parameters were also correlated with differing temperament broadband and narrowband scales on the IBQ-R.

CONCLUSION

Three microstates emerged that appear comparable to underlying networks identified in adult and infant microstate literature and fMRI studies. Each of the temperament domains was related to specific microstates and their parameters. These networks also correspond with auditory and visual processing as well as the default mode network found in prior research and can lead to new investigations examining differences across stimulus presentations to further explain how infants begin to recognize, respond to, and engage with the world around them.

Longitudinal investigation of executive function development employing task-based, teacher reports, and fNIRS multimethodology in 4- to 5-year-old children

Increased focus on resting-state functional connectivity (rsFC) and the use and accessibility of functional near-infrared spectroscopy (fNIRS) have advanced knowledge on the interconnected nature of neural substrates underlying executive function (EF) development in adults and clinical populations. Less is known about the relationship between rsFC and developmental changes in EF during preschool years in typically developing children, a gap the present study addresses employing task-based assessment, teacher reports, and fNIRS multimethodology. This preregistered study contributes to our understanding of the neural basis of EF development longitudinally with 41 children ages 4-5. Changes in prefrontal cortex (PFC) rsFC utilizing fNIRS, EF measured with a common task-based assessment (Day-Night task), and teacher reports of behavior (BRIEF-P) were monitored over multiple timepoints: Initial Assessment, 72 h follow-up, 1 Month Follow-up, and 4 Month Follow-up. Measures of rsFC were strongly correlated 72 h apart, providing evidence of high rsFC measurement reliability using fNIRS with preschool-aged children. PFC rsFC was positively correlated with performance on task-based and report-based EF assessments. Children's PFC functional connectivity at rest uniquely predicted later EF, controlling for verbal IQ, age, and sex. Functional connectivity at rest using fNIRS may potentially show the rapid changes in EF development in young children, not only neurophysiologically, but also as a correlate of task-based EF performance and ecologically-relevant teacher reports of EF in a classroom context.

Self-regulation and frontal EEG alpha activity during infancy and early childhood: A multilevel meta-analysis

Integrating behavioral and neurophysiological measures has created new and advanced ways to understand the development of self-regulation. Electroencephalography (EEG) has been used to examine how self-regulatory processes are related to frontal alpha power during infancy and early childhood. However, findings across previous studies have been inconsistent. To address this issue, the current meta-analysis synthesized all prior literature examining associations between individual differences in self-regulation and frontal EEG alpha power (baseline and/or task). In total, 23 studies consisting of 1275 participants between 1 month and 6 years of age were included, which yielded 149 effect sizes. Findings of the three-level meta-analytic model demonstrated a non-significant overall association between self-regulation and frontal alpha power. Yet, significant moderating effects were found for self-regulation construct (emotion regulation, effortful control, executive function), self-regulation measurement (behavioral task, computer assessment, lab observation, questionnaire), and children's mean age. Self-regulation was only significantly correlated with frontal alpha power when studies focused on the executive functioning construct. Moreover, the use of behavioral tasks or questionnaires and a higher mean age of the children resulted in small but significant effect size estimates. Higher frontal alpha power values were related to higher order top-down mechanisms of self-regulation, indicating that these mechanisms might become stronger when the frontal cortex is sufficiently developed. The findings of the current meta-analysis highlight the importance of longitudinal analyses and multimethod approaches in future work to reach a more comprehensive understanding of the role of frontal EEG alpha activity in the etiology of individual differences in early self-regulation. RESEARCH HIGHLIGHTS: The first meta-analysis of individual differences in self-regulation and frontal EEG alpha power during infancy and early childhood demonstrated a non-significant overall association. Moderation analyses revealed that variations in frontal alpha power were significantly associated with executive function, but not with effortful control and emotion regulation. Frontal alpha power was related to variations in self-regulation when measured by behavioral tasks and questionnaires, but not via computer assessments and lab observations. The association between individual differences in self-regulation and frontal alpha power becomes significantly stronger with age.

HAPPILEE: HAPPE In Low Electrode Electroencephalography, a standardized pre-processing software for lower density recordings

Lower-density Electroencephalography (EEG) recordings (from 1 to approximately 32 electrodes) are widely-used in research and clinical practice and enable scalable brain function measurement across a variety of settings and populations. Though a number of automated pipelines have recently been proposed to standardize and optimize EEG pre-processing for high-density systems with state-of-the-art methods, few solutions have emerged that are compatible with lower-density systems. However, lower-density data often include long recording times and/or large sample sizes that would benefit from similar standardization and automation with contemporary methods. To address this need, we propose the HAPPE In Low Electrode Electroencephalography (HAPPILEE) pipeline as a standardized, automated pipeline optimized for EEG recordings with lower density channel layouts of any size. HAPPILEE processes task-free (e.g., resting-state) and task-related EEG (including event-related potential data by interfacing with the HAPPE+ER pipeline), from raw files through a series of processing steps including filtering, line noise reduction, bad channel detection, artifact correction from continuous data, segmentation, and bad segment rejection that have all been optimized for lower density data. HAPPILEE also includes post-processing reports of data and pipeline quality metrics to facilitate the evaluation and reporting of data quality and processing-related changes to the data in a standardized manner. Here the HAPPILEE steps and their optimization with both recorded and simulated EEG data are described. HAPPILEE's performance is then compared relative to other artifact correction and rejection strategies. The HAPPILEE pipeline is freely available as part of HAPPE 2.0 software under the terms of the GNU General Public License at: https://github.com/PINE-Lab/HAPPE.

Inhibitory Control in Children 4-10 Years of Age: Evidence From Functional Near-Infrared Spectroscopy Task-Based Observations

Executive function (EF) is essential to child development, with associated skills beginning to emerge in the first few years of life and continuing to develop into adolescence and adulthood. The prefrontal cortex (PFC), which follows a neurodevelopmental timeline similar to EF, plays an important role in the development of EF. However, limited research has examined prefrontal function in young children due to limitations of currently available neuroimaging techniques such as functional resonance magnetic imaging (fMRI). The current study developed and applied a multimodal Go/NoGo task to examine the EF component of inhibitory control in children 4-10 years of age. Cortical activity was measured using a non-invasive and child-friendly neuroimaging technique - functional near-infrared spectroscopy (fNIRS). Children's response accuracy and reaction times were captured during the fNIRS session and compared with responses obtained using the standardized assessments from NIH Toolbox cognition battery. Results showed significant correlations between the behavioral measures during the fNIRS session and the standardized EF assessments, in line with our expectations. Results from fNIRS measures demonstrated a significant, age-independent effect of inhibitory control (IC) in the right PFC (rPFC), and an age-dependent effect in the left orbitofrontal cortex (lOFC), consistent with results in previous studies using fNIRS and fMRI. Thus, the new task designed for fNIRS was suitable for examining IC in young children, and results showed that fNIRS measures can reveal prefrontal IC function.

The development of theta and alpha neural oscillations from ages 3 to 24 years

Intrinsic, unconstrained neural activity exhibits rich spatial, temporal, and spectral organization that undergoes continuous refinement from childhood through adolescence. The goal of this study was to investigate the development of theta (4-8 Hertz) and alpha (8-12 Hertz) oscillations from early childhood to adulthood (years 3-24), as these oscillations play a fundamental role in cognitive function. We analyzed eyes-open, resting-state EEG data from 96 participants to estimate genuine oscillations separately from the aperiodic (1/f) signal. We examined age-related differences in the aperiodic signal (slope and offset), as well as the peak frequency and power of the dominant posterior oscillation. For the aperiodic signal, we found that both the aperiodic slope and offset decreased with age. For the dominant oscillation, we found that peak frequency, but not power, increased with age. Critically, early childhood (ages 3-7) was characterized by a dominance of theta oscillations in posterior electrodes, whereas peak frequency of the dominant oscillation in the alpha range increased between ages 7 and 24. Furthermore, theta oscillations displayed a topographical transition from dominance in posterior electrodes in early childhood to anterior electrodes in adulthood. Our results provide a quantitative description of the development of theta and alpha oscillations.

The development of brain rhythms at rest and its impact on vocabulary acquisition

A long-standing question in developmental science is how the neurodevelopment of the brain influences cognitive functions. Here, we examined the developmental change of resting EEG power and its links to vocabulary acquisition in school-age children. We further explored what mechanisms may mediate the relation between brain rhythm maturation and vocabulary knowledge. Eyes-opened resting-state EEG data were recorded from 53 typically-developing Chinese children every 2 years between the ages of 7 and 11. Our results showed first that delta, theta, and gamma power decreased over time, whereas alpha and beta power increased over time. Second, after controlling for general cognitive abilities, age, home literacy environment, and phonological skills, theta decreases explained 6.9% and 14.4% of unique variance in expressive vocabulary at ages 9 and 11, respectively. We also found that beta increase from age 7 to 9 significantly predicted receptive vocabulary at age 11. Finally, theta decrease predicted expressive vocabulary through the effects of phoneme deletion at age 9 and tone discrimination at age 11. These results substantiate the important role of brain oscillations at rest, especially theta rhythm, in language development. The developmental change of brain rhythms could serve as sensitive biomarkers for vocabulary development in school-age children, which would be of great value in identifying children at risk of language impairment.

The relationship of resting-state EEG oscillations to executive functions in middle childhood

Executive functions (EFs) play important roles in children's development, but their neural mechanisms are rarely investigated, especially for the different components of EFs in middle childhood. Therefore, this study aimed to explore the links between resting-state EEG in the frontal scalp region and EFs in children aged 7-9 years. Fifty-nine typically developing children from the second and third grades performed two core EF tasks, i.e., inhibition and working memory, and a high-level EF task, i.e., planning, followed by the recording of EEG signals during eyes-open and eyes-closed resting states. The results showed that distinct EEG activities in the frontal scalp region predicted different EF components. More specifically, after controlling for age and verbal ability, alpha to theta power ratio (ATR) and beta to theta power ratio (BTR) during the eyes-open resting state positively predicted inhibition, and beta to theta power ratio (BTR) during the eyes-open resting state positively predicted planning. However, we did not find any EEG features related to working memory. Our results contributed to the understanding of inter-individual differences in EFs and provided insights into the regulation of corresponding EEG activities through EEG neurofeedback for enhancing children's EFs.