Brain maturation in adolescence: concurrent changes in neuroanatomy and neurophysiology

Beta-band power modulation in the human amygdala during a delayed reach task

INTRODUCTION

The amygdala is mostly known for its roles in emotional processing and social behavior. In recent years, it has been implicated in voluntary motor control due to its structural and functional connectivity with the motor cortex. By investigating whether the amygdala modulates during movement preparation, we can further examine its contributions to motor processing.

OBJECTIVE

We utilized a delayed reach task to measure beta-band (13-30 Hz) modulation in the amygdala during movement preparation. We hypothesized that we would see decreases in beta-band power during the Delay and Response phases of this task.

METHODS

Eleven subjects diagnosed with drug-resistant epilepsy (DRE), who were implanted with stereoelectroencephalographic (SEEG) electrodes, were recruited to this study. The beta-band power was recorded through a delayed reach task. We calculated the beta-band Power Spectral Density (PSD) using multi-taper spectral analysis and compared the trial-averaged PSD using a cluster-based permutation test to determine the significance of beta-band power differences between task phases.

RESULTS

100 % of participants and 44.8 % of gray matter contacts in the amygdala (n = 58) exhibited significantly decreased beta-band power during the Delay phase. During the Response phase, 90.9 % of participants and 58.6 % of gray matter contacts (n = 58) showed significantly decreased beta-band power. We also found a difference in the proportion of amygdala contacts showing beta-band modulation between those implanted in gray vs. white matter (p = 0.0035) but found no difference between contralateral vs. ipsilateral contacts (p = 0.17) and male vs. female participants (p = 0.34).

CONCLUSION

This study is the first to demonstrate beta-band power decreases in the amygdala during the Delay and Response phases of a delayed reach task. These findings demonstrate that the amygdala undergoes neural modulation prior to movement initiation and during movement execution.

Physical and neurophysiological maturation associated with ADHD among previously institutionalized children: a randomized controlled trial

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental outcome among children with a history of early institutional care. Prior research on institutionalized children suggested that accelerated physical growth in childhood is a risk factor for ADHD outcomes.

METHODS

The current study examined physical and neurophysiological growth trajectories among institutionalized children randomized to foster care treatment (n = 59) or care as usual (n = 54), and never institutionalized children (n = 64) enrolled in the Bucharest Early Intervention Project (NCT00747396, clinicaltrials.gov). Participants completed physical and electroencephalography (EEG) assessments at six time points from infancy through adolescence, as well as structured diagnostic interviews at the 54-month and 12-year time points. A series of multilevel growth models and cross-lagged path models were estimated to examine associations among physical and neurophysiological maturation, treatment group, age of foster care placement, and ADHD diagnostic outcomes.

RESULTS

Twenty-seven percent of the institutionalized children met research criteria for ADHD at one or both time points. Slowed, prolonged growth of height and head circumference were associated with both ADHD and delayed foster care placement. Placement in foster care versus care as usual, but not ADHD, was associated with maturation of the peak alpha frequency. Among children randomized to foster care, average theta-beta ratio was lower among those with ADHD. There was no evidence that rapid physical maturation led to atypical cortical activity.

CONCLUSIONS

Delayed, prolonged physical growth and atypical neurophysiology from infancy through adolescence is associated with ADHD among institutionalized children, over and above the protective effects of foster care.

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.

Family study of the error-related negativity in adolescent and young adult females and their parents

The error-related negativity (ERN) has been identified as a potential endophenotype of psychopathology. However, there is limited research investigating familial transmission of the ERN, particularly across developmental phases that are associated with increased risk for psychopathology. The present study included a sample of one hundred thirty-one adolescent and young adult females (Mage = 17.77, SD = 1.84) and their biological parents at a first assessment and 75 females (Mage = 20.48, SD = 1.75) and their biological parents at a second assessment. Participants and their parents completed a flanker task while electroencephalography was recorded to examine parent-daughter associations of the ERN, correct response negativity (CRN), and ΔERN (i.e., ERN-CRN) at two assessments that were separated by approximately 3 years (Myears = 2.84, SD = 0.60). The daughters also completed self-report measures of generalized anxiety and depression symptoms. Results indicated that the ΔERN, but not the ERN or CRN, was positively correlated between parents and their daughters at both assessments. Furthermore, the parent-daughter correlation strength did not differ between assessments. Finally, both daughter and parent ∆ERNs were associated with daughter generalized anxiety and depression symptoms. The present study suggests that, like psychiatric disorders, the ERN runs in families and is associated with both concurrent and familial psychopathology, supporting its conceptualization as an endophenotype of psychopathology.

Prefrontal excitation/inhibition balance supports adolescent enhancements in circuit signal to noise ratio

The development and refinement of neuronal circuitry allow for stabilized and efficient neural recruitment, supporting adult-like behavioral performance. During adolescence, the maturation of PFC is proposed to be a critical period (CP) for executive function, driven by a break in balance between glutamatergic excitation and GABAergic inhibition (E/I) neurotransmission. During CPs, cortical circuitry fine-tunes to improve information processing and reliable responses to stimuli, shifting from spontaneous to evoked activity, enhancing the SNR, and promoting neural synchronization. Harnessing 7 T MR spectroscopy and EEG in a longitudinal cohort (N = 164, ages 10-32 years, 283 neuroimaging sessions), we outline associations between age-related changes in glutamate and GABA neurotransmitters and EEG measures of cortical SNR. We find developmental decreases in spontaneous activity and increases in cortical SNR during our auditory steady state task using 40 Hz stimuli. Decreases in spontaneous activity were associated with glutamate levels in DLPFC, while increases in cortical SNR were associated with more balanced Glu and GABA levels. These changes were associated with improvements in working memory performance. This study provides evidence of CP plasticity in the human PFC during adolescence, leading to stabilized circuitry that allows for the optimal recruitment and integration of multisensory input, resulting in improved executive function.

Adolescent brain maturation associated with environmental factors: a multivariate analysis

Human adolescence marks a crucial phase of extensive brain development, highly susceptible to environmental influences. Employing brain age estimation to assess individual brain aging, we categorized individuals (N = 7,435, aged 9-10 years old) from the Adolescent Brain and Cognitive Development (ABCD) cohort into groups exhibiting either accelerated or delayed brain maturation, where the accelerated group also displayed increased cognitive performance compared to their delayed counterparts. A 4-way multi-set canonical correlation analysis integrating three modalities of brain metrics (gray matter density, brain morphological measures, and functional network connectivity) with nine environmental factors unveiled a significant 4-way canonical correlation between linked patterns of neural features, air pollution, area crime, and population density. Correlations among the three brain modalities were notably strong (ranging from 0.65 to 0.77), linking reduced gray matter density in the middle temporal gyrus and precuneus to decreased volumes in the left medial orbitofrontal cortex paired with increased cortical thickness in the right supramarginal and bilateral occipital regions, as well as increased functional connectivity in occipital sub-regions. These specific brain characteristics were significantly more pronounced in the accelerated brain aging group compared to the delayed group. Additionally, these brain regions exhibited significant associations with air pollution, area crime, and population density, where lower air pollution and higher area crime and population density were correlated to brain variations more prominently in the accelerated brain aging group.

The development of aperiodic neural activity in the human brain

The neurophysiological mechanisms supporting brain maturation are fundamental to attention and memory capacity across the lifespan. Human brain regions develop at different rates, with many regions developing into the third and fourth decades of life. Here, in this preregistered study (https://osf.io/gsru7), we analyzed intracranial EEG (iEEG) recordings from widespread brain regions in a large developmental cohort. Using task-based (i.e., attention to-be-remembered visual stimuli) and task-free (resting-state) data from 101 children and adults (5.93 - 54.00 years, 63 males; n electrodes = 5691), we mapped aperiodic (1/ƒ-like) activity, a proxy of excitation:inhibition (E:I) balance with steeper slopes indexing inhibition and flatter slopes indexing excitation. We reveal that aperiodic slopes flatten with age into young adulthood in both association and sensorimotor cortices, challenging models of early sensorimotor development based on brain structure. In prefrontal cortex (PFC), attentional state modulated age effects, revealing steeper task-based than task-free slopes in adults and the opposite in children, consistent with the development of cognitive control. Age-related differences in task-based slopes also explained age-related gains in memory performance, linking the development of PFC cognitive control to the development of memory. Last, with additional structural imaging measures, we reveal that age-related differences in gray matter volume are differentially associated with aperiodic slopes in association and sensorimotor cortices. Our findings establish developmental trajectories of aperiodic activity in localized brain regions and illuminate the development of PFC inhibitory control during adolescence in the development of attention and memory.

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.

Prefrontal Excitation/ Inhibition Balance Supports Adolescent Enhancements in Circuit Signal to Noise Ratio

The development and refinement of neuronal circuitry allow for stabilized and efficient neural recruitment, supporting adult-like behavioral performance. During adolescence, the maturation of PFC is proposed to be a critical period (CP) for executive function, driven by a break in balance between glutamatergic excitation and GABAergic inhibition (E/I) neurotransmission. During CPs, cortical circuitry fine-tunes to improve information processing and reliable responses to stimuli, shifting from spontaneous to evoked activity, enhancing the SNR, and promoting neural synchronization. Harnessing 7T MR spectroscopy and EEG in a longitudinal cohort (N = 164, ages 10-32 years, 283 neuroimaging sessions), we outline associations between age-related changes in glutamate and GABA neurotransmitters and EEG measures of cortical SNR. We find developmental decreases in spontaneous activity and increases in cortical SNR during our auditory steady state task using 40 Hz stimuli. Decreases in spontaneous activity were associated with glutamate levels in DLPFC, while increases in cortical SNR were associated with more balanced Glu and GABA levels. These changes were associated with improvements in working memory performance. This study provides evidence of CP plasticity in the human PFC during adolescence, leading to stabilized circuitry that allows for the optimal recruitment and integration of multisensory input, resulting in improved executive function.

Connectivity study on resting-state EEG between motor imagery BCI-literate and BCI-illiterate groups

Objective.Although motor imagery-based brain-computer interface (MI-BCI) holds significant potential, its practical application faces challenges such as BCI-illiteracy. To mitigate this issue, researchers have attempted to predict BCI-illiteracy by using the resting state, as this was found to be associated with BCI performance. As connectivity's significance in neuroscience has grown, BCI researchers have applied connectivity to it. However, the issues of connectivity have not been considered fully. First, although various connectivity metrics exist, only some have been used to predict BCI-illiteracy. This is problematic because each metric has a distinct hypothesis and perspective to estimate connectivity, resulting in different outcomes according to the metric. Second, the frequency range affects the connectivity estimation. In addition, it is still unknown whether each metric has its own optimal frequency range. Third, the way that estimating connectivity may vary depending upon the dataset has not been investigated. Meanwhile, we still do not know a great deal about how the resting state electroencephalography (EEG) network differs between BCI-literacy and -illiteracy.Approach.To address the issues above, we analyzed three large public EEG datasets using three functional connectivity and three effective connectivity metrics by employing diverse graph theory measures. Our analysis revealed that the appropriate frequency range to predict BCI-illiteracy varies depending upon the metric. The alpha range was found to be suitable for the metrics of the frequency domain, while alpha + theta were found to be appropriate for multivariate Granger causality. The difference in network efficiency between BCI-literate and -illiterate groups was constant regardless of the metrics and datasets used. Although we observed that BCI-literacy had stronger connectivity, no other significant constructional differences were found.Significance.Based upon our findings, we predicted MI-BCI performance for the entire dataset. We discovered that combining several graph features could improve the prediction's accuracy.

Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model

The spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unknown. Here, we assess the developmental maturation of electroencephalogram spectra via Bayesian model inversion of the spectral graph model, a parsimonious whole-brain model of spatiospectral neural activity derived from linearized neural field models coupled by the structural connectome. Simulation-based inference was used to estimate age-varying spectral graph model parameter posterior distributions from electroencephalogram spectra spanning the developmental period. This model-fitting approach accurately captures observed developmental electroencephalogram spectral maturation via a neurobiologically consistent progression of key neural parameters: long-range coupling, axonal conduction speed, and excitatory:inhibitory balance. These results suggest that the spectral maturation of macroscopic neural activity observed during typical development is supported by age-dependent functional adaptations in localized neural dynamics and their long-range coupling across the macroscopic structural network.

Effects of topology on the controllability of brain connectomes through sparsity promoting control

The fundamental mechanisms underlying the brain's ability to switch between dynamic (or physiological) states in response to cognitive demands are elusive, and have not been systematically correlated with the topology of neural circuits, particularly in underdeveloped brains. We used a sparsity promoting closed-loop control framework, large datasets of resting-state connectomes from early adolescents and synthetic graphs, to investigate the role of graph topology on regional (node) controllability and control action on the connectome. Feedback costs were examined in ranges corresponding to nodes becoming self-controlled, losing their control action, or remaining self-controlled. Their associations with node connectedness and strength, and network modularity, fragility and resilience were assessed. Highly connected nodes that were central to the network became self-controlled and maintained their control action on the network under high feedback cost, suggesting that brain regions with such properties may play critical roles in the connectome's controllability. In addition, nodes in more modular, fragile and less resilient networks were self-controlled under overall higher feedback costs.

Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Theta activity and cognitive functioning: Integrating evidence from resting-state and task-related developmental electroencephalography (EEG) research

The theta band is one of the most prominent frequency bands in the electroencephalography (EEG) power spectrum and presents an interesting paradox: while elevated theta power during resting state is linked to lower cognitive abilities in children and adolescents, increased theta power during cognitive tasks is associated with higher cognitive performance. Why does theta power, measured during resting state versus cognitive tasks, show differential correlations with cognitive functioning? This review provides an integrated account of the functional correlates of theta across different contexts. We first present evidence that higher theta power during resting state is correlated with lower executive functioning, attentional abilities, language skills, and IQ. Next, we review research showing that theta power increases during memory, attention, and cognitive control, and that higher theta power during these processes is correlated with better performance. Finally, we discuss potential explanations for the differential correlations between resting/task-related theta and cognitive functioning, and offer suggestions for future research in this area.

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.

The Necessity of Taking Culture and Context into Account When Studying the Relationship between Socioeconomic Status and Brain Development

Decades of research has revealed a relationship between childhood socioeconomic status (SES) and brain development at the structural and functional levels. Of particular note is the distinction between income and maternal education, two highly correlated factors which seem to influence brain development through distinct pathways. Specifically, while a families' income-to-needs ratio is linked with physiological stress and household chaos, caregiver education influences the day-to-day language environment a child is exposed to. Variability in either one of these environmental experiences is related to subsequent brain development. While this work has the potential to inform public policies in a way that benefits children, it can also oversimplify complex factors, unjustly blame low-SES parents, and perpetuate a harmful deficit perspective. To counteract these shortcomings, researchers must consider sociodemographic differences in the broader cultural context that underlie SES-based differences in brain development. This review aims to address these issues by (a) identifying how sociodemographic mechanisms associated with SES influence the day-to-day experiences of children, in turn, impacting brain development, while (b) considering the broader cultural contexts that may differentially impact this relationship.

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.

Aperiodic EEG and 7T MRSI evidence for maturation of E/I balance supporting the development of working memory through adolescence

Adolescence has been hypothesized to be a critical period for the development of human association cortex and higher-order cognition. A defining feature of critical period development is a shift in the excitation: inhibition (E/I) balance of neural circuitry, however how changes in E/I may enhance cortical circuit function to support maturational improvements in cognitive capacities is not known. Harnessing ultra-high field 7 T MR spectroscopy and EEG in a large, longitudinal cohort of youth (N = 164, ages 10-32 years old, 347 neuroimaging sessions), we delineate biologically specific associations between age-related changes in excitatory glutamate and inhibitory GABA neurotransmitters and EEG-derived measures of aperiodic neural activity reflective of E/I balance in prefrontal association cortex. Specifically, we find that developmental increases in E/I balance reflected in glutamate:GABA balance are linked to changes in E/I balance assessed by the suppression of prefrontal aperiodic activity, which in turn facilitates robust improvements in working memory. These findings indicate a role for E/I-engendered changes in prefrontal signaling mechanisms in the maturation of cognitive maintenance. More broadly, this multi-modal imaging study provides evidence that human association cortex undergoes physiological changes consistent with critical period plasticity during adolescence.

The neurodevelopmental trajectory of beta band oscillations: an OPM-MEG study

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - Optically Pumped Magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Ketamine ameliorates activity-based anorexia of adolescent female mice through changes in GluN2B-containing NMDA receptors at postsynaptic cytoplasmic locations of pyramidal neurons and interneurons of medial prefrontal cortex

Anorexia nervosa (AN) is a mental illness with high rates of mortality and relapse, and no approved pharmacotherapy. Using the activity-based anorexia (ABA) model of AN, we previously showed that a single sub-anesthetic intraperitoneal injection of ketamine (30 mg/kg-KET, but not 3 mg/kg-KET), has an immediate and long-lasting effect of reducing anorexia-like behavior among adolescent female mice. We also showed previously that excitatory outflow from medial prefrontal cortex (mPFC) engages hunger-evoked hyperactivity, leading to the ABA condition of severe weight loss. Ketamine is known to target GluN2B-containing NMDARs (NR2B). Might synaptic plasticity involving NR2B in mPFC contribute to ketamine's ameliorative effects? We addressed this question through electron microscopic immunocytochemical quantification of GluN2B at excitatory synapses of pyramidal neurons (PN) and GABAergic interneurons (IN) in mPFC layer 1 of animals that underwent recovery from a second ABA induction (ABA2), 22 days after ketamine injection during the first ABA induction. The 30 mg/kg-KET evoked synaptic plasticity that differed for PN and IN, with changes revolving the cytoplasmic reserve pool of NR2B more than the postsynaptic membrane pool. Those individuals that suppressed hunger-evoked wheel running the most and increased food consumption during recovery from ABA2 the most showed the greatest increase of NR2B at PN and IN excitatory synapses. We hypothesize that 30 mg/kg-KET promotes long-lasting changes in the reserve cytoplasmic pool of NR2B that enables activity-dependent rapid strengthening of mPFC circuits underlying the more adaptive behavior of suppressed running and enhanced food consumption, in turn supporting better weight restoration.

Hearing loss in juvenile rats leads to excessive play fighting and hyperactivity, mild cognitive deficits and altered neuronal activity in the prefrontal cortex

Background

In children, hearing loss has been associated with hyperactivity, disturbed social interaction, and risk of cognitive disturbances. Mechanistic explanations of these relations sometimes involve language. To investigate the effect of hearing loss on behavioral deficits in the absence of language, we tested the impact of hearing loss in juvenile rats on motor, social, and cognitive behavior and on physiology of prefrontal cortex.

Methods

Hearing loss was induced in juvenile (postnatal day 14) male Sprague-Dawley rats by intracochlear injection of neomycin under general anesthesia. Sham-operated and non-operated hearing rats served as controls. One week after surgery auditory brainstem response (ABR) measurements verified hearing loss or intact hearing in sham-operated and non-operated controls. All rats were then tested for locomotor activity (open field), coordination (Rotarod), and for social interaction during development in weeks 1, 2, 4, 8, 16, and 24 after surgery. From week 8 on, rats were trained and tested for spatial learning and memory (4-arm baited 8-arm radial maze test). In a final setting, neuronal activity was recorded in the medial prefrontal cortex (mPFC).

Results

In the open field deafened rats moved faster and covered more distance than sham-operated and non-operated controls from week 8 on (both p < 0.05). Deafened rats showed significantly more play fighting during development (p < 0.05), whereas other aspects of social interaction, such as following, were not affected. Learning of the radial maze test was not impaired in deafened rats (p > 0.05), but rats used less next-arm entries than other groups indicating impaired concept learning (p < 0.05). In the mPFC neuronal firing rate was reduced and enhanced irregular firing was observed. Moreover, oscillatory activity was altered, both within the mPFC and in coherence of mPFC with the somatosensory cortex (p < 0.05).

Conclusions

Hearing loss in juvenile rats leads to hyperactive behavior and pronounced play-fighting during development, suggesting a causal relationship between hearing loss and cognitive development. Altered neuronal activities in the mPFC after hearing loss support such effects on neuronal networks outside the central auditory system. This animal model provides evidence of developmental consequences of juvenile hearing loss on prefrontal cortex in absence of language as potential confounding factor.

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.

Development of EEG connectivity from preschool to school-age children

Introduction

Many studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, rather, on the interaction between different brain regions. In this regard studying the connectivity between brain regions is of great importance towards understanding higher cognitive functions and its underlying mechanisms.

Methods

In this study, EEG data of children (N = 253; 3-10 years old; 113 females, 140 males) from pre-school to schoolage was collected, and the weighted phase delay index and directed transfer function method was used to find the electrophysiological indicators of both functional connectivity and effective connectivity. A general linear model was built between the indicators and age, and the change trend of electrophysiological indicators analyzed for age.

Results

The results showed an age trend for the functional and effective connectivity of the brain of children.

Discussion

The results are of importance in understanding normative brain development and in defining those conditions that deviate from typical growth trajectories.

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.

Brain functional connectivity in children with a mild traumatic brain injury: A scoping review

INTRODUCTION

The occurrence of mild traumatic brain injury(mTBI) is estimated at 0,2-0,3% cases annually. Following a mTBI, some children experience persistent symptoms, and functional connectivity(FC) changes may be implicated. However, characteristics of FC have not been widely described in this population. This scoping review aimed to identify and understand the impacts of mTBI on EEG-measured FC in children, provide an overview of the available literature, detail analysis techniques, and describe gaps in the research.

METHODS

PubMed, Web of Science, Medline, Embase, ProQuest and CINAHL were searched up to June 25, 2023, with the terms child, mTBI, EEG, FC, and their synonyms. Ten studies were identified.

RESULTS

Five studies reported significant differences between the mTBI group and controls. In addition to group differences, six studies reported significant variation over time. Brain Network Analysis(BNA), utilized in seven studies, was the primary FC analysis recorded. Two of the five studies that reported significant differences following mTBI utilized the BNA. The other three applied alternative analysis methods.

DISCUSSION

FC assessment based on EEG can identify some differences in children with mTBI. BNA was more useful in following changes over time. Further research is suggested, considering the limited age range and number of retrieved studies.

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.

Early Age- and Sex-Dependent Regulation of Astrocyte-Mediated Glutamatergic Synapse Elimination in the Rat Prefrontal Cortex: Establishing an Organotypic Brain Slice Culture Investigating Tool

Clinical and pre-clinical studies of neuropsychiatric (NP) disorders show altered astrocyte properties and synaptic networks. These are refined during early postnatal developmental (PND) stages. Thus, investigating early brain maturational trajectories is essential to understand NP disorders. However, animal experiments are highly time-/resource-consuming, thereby calling for alternative methodological approaches. The function of MEGF10 in astrocyte-mediated synapse elimination (pruning) is crucial to refine neuronal networks during development and adulthood. To investigate the impact of MEGF10 during PND in the rat prefrontal cortex (PFC) and its putative role in brain disorders, we established and validated an organotypic brain slice culture (OBSC) system. Using Western blot, we characterized the expression of MEGF10 and the synaptic markers synaptophysin and PSD95 in the cortex of developing pups. We then combined immunofluorescent-immunohistochemistry with Imaris-supported 3D analysis to compare age- and sex-dependent astrocyte-mediated pruning within the PFC in pups and OBSCs. We thereby validated this system to investigate age-dependent astrocyte-mediated changes in pruning during PND. However, further optimizations are required to use OBSCs for revealing sex-dependent differences. In conclusion, OBSCs offer a valid alternative to study physiological astrocyte-mediated synaptic remodeling during PND and might be exploited to investigate the pathomechanisms of brain disorders with aberrant synaptic development.

Spatial-Temporal EEG Fusion Based on Neural Network for Major Depressive Disorder Detection

In view of the major depressive disorder characteristics such as high mortality as well as high recurrence, it is important to explore an objective and effective detection method for major depressive disorder. Considering the advantages complementary of different machine learning algorithms in information mining process, as well as the fusion complementary of different information, in this study, the spatial-temporal electroencephalography fusion framework using neural network is proposed for major depressive disorder detection. Since electroencephalography is a typical time series signal, we introduce recurrent neural network embedded in long short-term memory unit for extract temporal domain features to solve the problem of long-distance information dependence. To reduce the volume conductor effect, the temporal electroencephalography data are mapping into a spatial brain functional network using phase lag index, then the spatial domain features were extracted from brain functional network using 2D convolutional neural networks. Considering the complementarity between different types of features, the spatial-temporal electroencephalography features are fused to achieve data diversity. The experimental results show that spatial-temporal features fusion can improve the detection accuracy of major depressive disorder with a highest of 96.33%. In addition, our research also found that theta, alpha, and full frequency band in brain regions of left frontal, left central, right temporal are closely related to MDD detection, especially theta frequency band in left frontal region. Only using single-dimension EEG data as decision basis, it is difficult to fully explore the valuable information hidden in the data, which affects the overall detection performance of MDD. Meanwhile, different algorithms have their own advantages for different application scenarios. Ideally, different algorithms should use their respective advantages to jointly address complex problems in engineering fields. To this end, we propose a computer-aided MDD detection framework based on spatial-temporal EEG fusion using neural network, as shown in Fig. 1. The simplified process is as follows: (1) Raw EEG data acquisition and preprocessing. (2) The time series EEG data of each channel are input as recurrent neural network (RNN), and RNN is used to process and extract temporal domain (TD) features. (3) The BFN among different EEG channels is constructed, and CNN is used to process and extract the spatial domain (SD) features of the BFN. (4) Based on the theory of information complementarity, the spatial-temporal information is fused to realize efficient MDD detection. Fig. 1 MDD detection framework based on spatial-temporal EEG fusion.

Development of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children

Electroencephalographic peak alpha frequency (PAF) is a marker of neural maturation that increases with age throughout childhood. Distinct maturation of PAF is observed in children with autism spectrum disorder such that PAF does not increase with age and is instead positively associated with cognitive ability. The current study clarifies and extends previous findings by characterizing the effects of age and cognitive ability on PAF between diagnostic groups in a sample of children and adolescents with and without autism spectrum disorder. Resting EEG data and behavioral measures were collected from 45 autistic children and 34 neurotypical controls aged 8 to 18 years. Utilizing generalized additive models to account for nonlinear relations, we examined differences in the joint effect of age and nonverbal IQ by diagnosis as well as bivariate relations between age, nonverbal IQ, and PAF across diagnostic groups. Age was positively associated with PAF among neurotypical children but not among autistic children. In contrast, nonverbal IQ but not age was positively associated with PAF among autistic children. Models accounting for nonlinear relations revealed different developmental trajectories as a function of age and cognitive ability based on diagnostic status. Results align with prior evidence indicating that typical age-related increases in PAF are absent in autistic children and that PAF instead increases with cognitive ability in these children. Findings suggest the potential of PAF to index distinct trajectories of neural maturation in autistic children.

Resting brain activity in early childhood predicts IQ at 18 years

Resting brain activity has been widely used as an index of brain development in neuroscience and clinical research. However, it remains unclear whether early differences in resting brain activity have meaningful implications for predicting long-term cognitive outcomes. Using data from the Bucharest Early Intervention Project (Zeanah et al., 2003), we examined the impact of institutional rearing and the consequences of early foster care intervention on 18-year IQ. We found that higher resting theta electroencephalogram (EEG) power, reflecting atypical neurodevelopment, across three assessments from 22 to 42 months predicted lower full-scale IQ at 18 years, providing the first evidence that brain activity in early childhood predicts cognitive outcomes into adulthood. In addition, both institutional rearing and later (vs. earlier) foster care intervention predicted higher resting theta power in early childhood, which in turn predicted lower IQ at 18 years. These findings demonstrate that experientially-induced changes in brain activity early in life have profound impact on long-term cognitive development, highlighting the importance of early intervention for promoting healthy development among children living in disadvantaged environments.

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.

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events

Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here, we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while the participants rested with their eyes closed. A total of 289 good-quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: individual alpha frequency (IAF) increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.

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.

The maturation of aperiodic EEG activity across development reveals a progressive differentiation of wakefulness from sleep

During development, the brain undergoes radical structural and functional changes following a posterior-to-anterior gradient, associated with profound changes of cortical electrical activity during both wakefulness and sleep. However, a systematic assessment of the developmental effects on aperiodic EEG activity maturation across vigilance states is lacking, particularly regarding its topographical aspects. Here, in a population of 160 healthy infants, children and teenagers (from 2 to 17 years, 10 subjects for each year), we investigated the development of aperiodic EEG activity in wakefulness and sleep. Specifically, we parameterized the shape of the aperiodic background of the EEG Power Spectral Density (PSD) by means of the spectral exponent and offset; the exponent reflects the rate of exponential decay of power over increasing frequencies and the offset reflects an estimate of the y-intercept of the PSD. We found that sleep and development caused the EEG-PSD to rotate over opposite directions: during wakefulness the PSD showed a flatter decay and reduced offset over development, while during sleep it showed a steeper decay and a higher offset as sleep becomes deeper. During deep sleep (N2, N3) only the spectral offset decreased over age, indexing a broad-band voltage reduction. As a result, the difference between values in deep sleep and those in both light sleep (N1) and wakefulness increased with age, suggesting a progressive differentiation of wakefulness from sleep EEG activity, most prominent over the frontal regions, the latest to complete maturation. Notably, the broad-band spectral exponent values during deep sleep stages were entirely separated from wakefulness values, consistently across developmental ages and in line with previous findings in adults. Concerning topographical development, the location showing the steepest PSD decay and largest offset shifted from posterior to anterior regions with age. This shift, particularly evident during deep sleep, paralleled the migration of sleep slow wave activity and was consistent with neuroanatomical and cognitive development. Overall, aperiodic EEG activity distinguishes wakefulness from sleep regardless of age; while, during development, it reveals a postero-anterior topographical maturation and a progressive differentiation of wakefulness from sleep. Our study could help to interpret changes due to pathological conditions and may elucidate the neurophysiological processes underlying the development of wakefulness and sleep.

A Cross-Sectional Study: Structural and Related Functional Connectivity Changes in the Brain: Stigmata of Adverse Parenting in Patients with Major Depressive Disorder?

Background: There is a high correlation between the risk of major depressive disorder (MDD) and adverse childhood experiences (ACEs) such as adverse parenting (AP). While there appears to be an association between ACEs and changes in brain structure and function, there have yet to be multimodal neuroimaging studies of associations between parenting style and brain developmental changes in MDD patients. To explore the effect of AP on brain structure and function. Methods: In this cross-sectional study, 125 MDD outpatients were included in the study and divided into the AP group and the optimal parenting (OP) group. Participants completed self-rating scales to assess depressive severity, symptoms, and their parents' styles. They also completed magnetic resonance imaging within one week of filling out the instruments. The differences between groups of gender, educational level, and medications were analyzed using the chi-squared test and those of age, duration of illness, and scores on scales using the independent samples t-test. Differences in gray matter volume (GMV) and resting-state functional connectivity (RS-FC) were assessed between groups. Results: AP was associated with a significant increase in GMV in the right superior parietal lobule (SPL) and FC between the right SPL and the bilateral medial superior frontal cortex in MDD patients. Limitations: The cross-cultural characteristics of AP will result in the lack of generalizability of the findings. Conclusions: The results support the hypothesis that AP during childhood may imprint the brain and affect depressive symptoms in adulthood. Parents should pay attention to the parenting style and avoid a style that lacks warmth.

Is structural connectivity different in child and adolescent relatives of patients with bipolar disorder? A narrative review according to studies with DTI

INTRODUCTION

Bipolar disorder (BD) has been associated with a decrease in white matter integrity. Diffusion tensor imaging (DTI) studies have enabled these changes to be elucidated with higher quality. Due to BD's high heritability, some studies have been conducted in relatives of BD patients looking at white matter integrity, and have found that structural connectivity may also be affected. This alteration has been proposed as a potential BD biomarker of vulnerability. However, there are few studies in children and adolescents.

OBJECTIVE

To conduct a review of the literature on changes in white matter integrity determined by DTI in high-risk children and adolescents.

RESULTS

Brain structural connectivity in the paediatric population is described in studies using DTI. Changes in the myelination process from its evolution within normal neurodevelopment to the findings in fractional anisotropy (FA) in BD patients and their high-risk relatives are also described.

CONCLUSIONS

Studies show that both BD patients and their at-risk relatives present a decrease in FA in specific brain regions. Studies in children and adolescents with a high risk of BD, indicate a reduced FA in axonal tracts involved in emotional and cognitive functions. Decreased FA can be considered as a vulnerability biomarker for BD.

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.

Relationship Between Central Auditory Processing Abilities and Working Memory During Adolescence

Purpose

Adolescence is a period of transformation in humans with changes in the neural physiology at subcortical and cortical levels. However, its significance on auditory processing skills and working memory skills and their association is yet to be well understood. Hence, the current study was designed to evaluate and establish the association between auditory processing skills and working memory abilities in adolescents.

Method

A total of 125 adolescents within the age range of 10 to 15 years participated in the current study. All of them had normal hearing sensitivity and no associated obvious peripheral or central deficits. All the participants underwent auditory closure ability assessment using quick speech perception in noise test in Kannada, binaural integration ability assessment using dichotic CV test, and temporal processing assessment using gap detection test. Auditory working memory abilities were assessed using auditory digit span and digit sequencing.

Results

Spearman correlation was done to assess the correlation between auditory processing skills and working memory abilities. Results revealed a significant negative correlation between most of the central auditory processing abilities and all the working memory spans.

Conclusions

Findings of the current study indicate that individuals with poor working memory abilities have difficulty in auditory processing abilities.

Ketamine ameliorates activity-based anorexia of adolescent female mice through changes in the prevalence of NR2B-containing NMDA receptors at excitatory synapses that are in opposite directions for of pyramidal neurons versus GABA interneurons In medial prefrontal cortex

A previous study showed that a single sub-anesthetic dose of ketamine (30 mg/kg-KET, IP) has an immediate and long-lasting (>20 days) effect of reducing maladaptive behaviors associated with activity-based anorexia (ABA) among adolescent female mice. This study sought to determine whether synaptic plasticity involving NR2B-containing NMDA receptors (NR2B) at excitatory synapses in the prelimbic region of medial prefrontal cortex (mPFC) contributes to this ameliorative effect. To this end, quantitative electron microscopic analyses of NR2B-subunit immunoreactivity at excitatory synapses of pyramidal neurons (PN) and GABAergic interneurons (GABA-IN) were conducted upon layer 1 of mPFC of the above-described mice that received a single efficacious 30 mg/kg-KET (N=8) versus an inefficacious 3 mg/kg-KET (N=8) dose during the food-restricted day of the first ABA induction (ABA1). Brain tissue was collected after these animals underwent recovery from ABA1, then of recovery from a second ABA induction (ABA2), 22 days after the ketamine injection. For all three parameters used to quantify ABA resilience (increased food consumption, reduced wheel running, body weight gain), 30 mg/kg-KET evoked synaptic plasticity in opposite directions for PN and GABA-IN, with changes at excitatory synapses on GABA-IN dominating the adaptive behaviors more than on PN. The synaptic changes were in directions consistent with changes in the excitatory outflow from mPFC that weaken food consumption-suppression, strengthen wheel running suppression and enhance food consumption. We hypothesize that 30 mg/kg-KET promotes these long-lasting changes in the excitatory outflow from mPFC after acutely blocking the hunger and wheel-access activated synaptic circuits underlying maladaptive behaviors during ABA.

A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.

Analysis of functional connectivity in depression based on a weighted hyper-network method

Objective. Brain connectivity network is a vital tool to reveal the interaction between different brain regions. Currently, most functional connectivity methods can only capture pairs of information to construct brain networks which ignored the high-order correlations between brain regions.Approach. Therefore, this study proposed a weighted connectivity hyper-network based on resting-state EEG data, and then applied to depression identification and analysis. The hyper-network model was build based on least absolute shrinkage and selection operator sparse regression method to effectively represent the higher-order relationships of brain regions. On this basis, by integrating the correlation-based weighted hyper-edge information, the weighted hyper-network is constructed, and the topological features of the network are extracted for classification.Main results. The experimental results obtained an optimal accuracy compared to the traditional coupling methods. The statistical results on network metrics proved that there were significant differences between depressive patients and normal controls. In addition, some brain regions and electrodes were found and discussed to highly correlate with depression by analyzing of the critical nodes and hyper-edges.Significance. These may help discover disease-related biomarkers important for depression diagnosis.

Development of network oscillations through adolescence in male and female rats

The primary aim of this research was to study the developmental trajectory of oscillatory synchronization in neural networks of normal healthy rats during adolescence, corresponding to the vulnerable age of schizophrenia prodrome in human. To monitor the development of oscillatory networks through adolescence we used a "pseudo-longitudinal" design. Recordings were performed in terminal experiments under urethane anesthesia, every day from PN32 to PN52 using rats-siblings from the same mother, to reduce individual innate differences between subjects. We found that hippocampal theta power decreased and delta power in prefrontal cortex increased through adolescence, indicating that the oscillations in the two different frequency bands follow distinct developmental trajectories to reach the characteristic oscillatory activity found in adults. Perhaps even more importantly, theta rhythm showed age-dependent stabilization toward late adolescence. Furthermore, sex differences was found in both networks, more prominent in the prefrontal cortex compared with hippocampus. Delta increase was stronger in females and theta stabilization was completed earlier in females, in postnatal days PN41-47, while in males it was only completed in late adolescence. Our finding of a protracted maturation of theta-generating networks in late adolescence is overall consistent with the findings of longitudinal studies in human adolescents, in which oscillatory networks demonstrated a similar pattern of maturation.

Electroencephalographic characteristics of children and adolescents with chronic musculoskeletal pain

Introduction

The pathophysiology of pediatric musculoskeletal (MSK) pain is unclear, contributing to persistent challenges to its management.

Objectives

This study hypothesizes that children and adolescents with chronic MSK pain (CPs) will show differences in electroencephalography (EEG) features at rest and during thermal pain modalities when compared with age-matched controls.

Methods

One hundred forty-two CP patients and 45 age-matched healthy controls (HCs) underwent a standardized thermal tonic heat and cold stimulations, while a 21-electrode headset collected EEG data. Cohorts were compared with respect to their EEG features of spectral power, peak frequency, permutation entropy, weight phase-lag index, directed phase-lag index, and node degree at 4 frequency bands, namely, delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz), at rest and during the thermal conditions.

Results

At rest, CPs showed increased global delta (P = 0.0493) and beta (P = 0.0002) power in comparison with HCs. These findings provide further impetus for the investigation and prevention of long-lasting developmental sequalae of early life chronic pain processes. Although no cohort differences in pain intensity scores were found during the thermal pain modalities, CPs and HCs showed significant difference in changes in EEG spectral power, peak frequency, permutation entropy, and network functional connectivity at specific frequency bands (P < 0.05) during the tonic heat and cold stimulations.

Conclusion

This suggests that EEG can characterize subtle differences in heat and cold pain sensitivity in CPs. The complementation of EEG and evoked pain in the clinical assessment of pediatric chronic MSK pain can better detect underlying pain mechanisms and changes in pain sensitivity.

Habitual night waking associates with dynamics of waking cortical theta power in infancy

The implications of the substantial individual differences in infant sleep for early brain development remain unclear. Here, we examined whether night sleep quality relates to daytime brain activity, operationalized through measures of EEG theta power and its dynamic modulation, which have been previously linked to later cognitive development. For this longitudinal study, 76 typically developing infants were studied (age: 4-14 months, 166 individual study visits) over the course of 6 months with one, two, three, or four lab visits. Habitual sleep was measured with a 7-day sleep diary and actigraphy, and the Brief Infant Sleep Questionnaire. Twenty-channel EEG was recorded while infants watched multiple rounds of videos of women singing nursery rhymes; oscillatory power in the theta band was extracted. Key metrics were average theta across stimuli and the slope of change in theta within the first novel movie. Both objective and subjective sleep assessment methods showed a relationship between more night waking and higher overall theta power and reduced dynamic modulation of theta over the course of the novel video stimuli. These results may indicate altered learning and consolidation in infants with more disrupted night sleep, which may have implications for cognitive development.