EEG functional connectivity in infants at elevated familial likelihood for autism spectrum disorder.

BACKGROUND: Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy. METHODS: We used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between cortical sources of EEG during video watching using the corrected imaginary part of phase-locking values. RESULTS: Our main analysis found no significant association between functional connectivity and ASD, showing only significant effects for age, sex, age-sex interaction, and site. Given these null results, we performed an exploratory analysis and observed, at 12 months, a negative correlation between functional connectivity and ADOS calibrated severity scores for restrictive and repetitive behaviors (RRB). LIMITATIONS: The small sample of ASD participants inherent to sibling studies limits diagnostic group comparisons. Also, results from our secondary exploratory analysis should be considered only as potential relationships to further explore, given their increased vulnerability to false positives. CONCLUSIONS: These results are inconclusive concerning an association between EEG functional connectivity and ASD in infancy. Exploratory analyses provided preliminary support for a relationship between RRB and functional connectivity specifically, but these preliminary observations need corroboration on larger samples.

EEG functional connectivity in infants at elevated familial risk for autism spectrum disorder.

Background: Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, relatively little is known about the development of these differences in infancy and on how trajectories may vary between sexes. Methods: We used the International Infant EEG Platform (EEG-IP), a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6, 12, and 18 months of age at typical (N=97) or high familial risk for ASD (N=98), determined by the presence of an older sibling with a confirmed ASD diagnosis. We computed the functional connectivity between cortical EEG sources during video watching using the corrected imaginary part of phase-locking values. Results: Our findings showed low regional specificity for group differences in functional connectivity but revealed different sex-specific trajectories between females and males in the group of high-risk infants. Specifically, functional connectivity was negatively correlated with ADOS calibrated severity scores, particularly at 12 months for the social affect score for females and for the restrictive and repetitive behaviors for males. Limitations: This study has been limited mostly due to issues related to the relatively small effective sample size inherent in sibling studies, particularly for diagnostic group comparisons. Conclusions: These results are consistent with sex differences in ASD observed in previous research and provide further insights into the role of functional connectivity in these differences.

Developmental trajectories of sensitivity to threat in children and adolescents predict larger medial frontal theta differentiation during response inhibition.

Sensitivity to threat (ST) is thought to be a hallmark of the onset and maintenance of anxiety, which often manifests behaviorally as withdrawal, increased arousal and hypervigilant monitoring of performance. The current study investigated whether longitudinal trajectories of ST were linked to medial frontal (MF) theta power dynamics, a robust marker of performance monitoring. Youth (N = 432, Mage = 11.96 years) completed self-report measures of threat sensitivity annually for 3 years. A latent class growth curve analysis was used to identify distinct profiles of threat sensitivity over time. Participants also completed a GO/NOGO task while electroencephalography was recorded. We identified three threat sensitivity profiles: (i) high (n = 83), (ii) moderate (n = 273) and (iii) low ( n= 76). Participants in the high threat sensitivity class had greater levels of MF theta power differentiation (NOGO-GO) compared to participants in the low threat sensitivity class, indicating that consistently high threat sensitivity is associated with neural indicators of performance monitoring. Of concern, both hypervigilant performance monitoring and threat sensitivity have been associated with anxiety; thus, youth with high threat sensitivity may be at risk for the development of anxiety.

Modeling brain dynamics and gaze behavior: Starting point bias and drift rate relate to frontal midline theta oscillations.

Frontal midline theta oscillatory dynamics have been implicated as an important neural signature of inhibitory control. However, most proactive cognitive control studies rely on behavioral tasks where individual differences are inferred through button presses. We applied computational modeling to further refine our understanding of theta dynamics in a cued anti-saccade task with gaze-contingent eye tracking. Using a drift diffusion model, increased frontal midline theta power during high-conflict, relative to low-conflict, trials predicted a more conservative style of responding through the starting point (bias). During both high- and low-conflict trials, increases in frontal midline theta also predicted improvements in response efficiency (drift rate). Regression analyses provided support for the importance of the starting point bias, which was associated with frontal midline theta over the course of the task above-and-beyond both drift rate and mean reaction time. Our findings provide a more thorough understanding of proactive gaze control by linking trial-by-trial increases of frontal midline theta to a shift in starting point bias facilitating a more neutral style of responding.

Inter-trial theta phase consistency during face processing in infants is associated with later emerging autism.

A growing body of research suggests that consistency in cortical activity may be a promising neurophysiological marker of autism spectrum disorder (ASD). In the current study we examined inter-trial coherence, a measure of phase consistency across trials, in the theta range (t-ITC: 3-6 Hz), as theta has been implicated in the processing of social and emotional stimuli in infants and adults. The sample included infants who had an older sibling with a confirmed ASD diagnosis and typically developing (TD) infants with no family history of ASD. The data were collected as part of the British Autism Study of Infant Siblings (BASIS) study. Infants between 6 and 10 months of age (Mage = 7.34, SDage = 1.21) performed a visual face processing task that included faces and scrambled, "face noise", stimuli. Follow-up assessments in higher likelihood infants were completed at 24 and again at 36 months to determine diagnostic outcomes. Analysis focused on posterior t-ITC during early (0-200 ms) and late (200-500 ms) visual processing stages commonly investigated in infant studies. t-ITC over posterior scalp regions during late stage face processing was significantly higher in TD and higher likelihood infants without ASD (HRA-), indicating reduced consistency in theta-band responses in higher likelihood infants who eventually receive a diagnosis of ASD (HRA+). These findings indicate that the temporal dynamics of theta during face processing relate to ASD outcomes. Reduced consistency of oscillatory dynamics at basic levels of infant sensory processing could have downstream effects on learning and social communication. LAY SUMMARY: We examined the consistency in brain responses to faces in infants at lower or higher familial likelihood for autism. Our results show that the consistency of EEG responses was lower during face processing in higher likelihood infants who eventually received a diagnosis of autism. These findings highlight that reduced consistency in brain activity during face processing in the first year of life is related to emerging autism.

A developmental examination of medial frontal theta dynamics and inhibitory control.

Medial frontal theta-band oscillations are a robust marker of action-outcome monitoring. In a large developmental sample (n = 432, 9-16 years), we examined whether phase and non-phase locked medial frontal theta power were related to inhibitory control among children and adolescents. Our results showed that the well-established increase in medial frontal theta power during inhibitory control was captured largely by non-phase locked dynamics, which partially mediated the positive effect of age on task performance. A person-centered approach also revealed latent classes of individuals based on their multivariate theta power dynamics (phase locked/non-phase locked, GO/NOGO). The class of individuals showing low phase locked and high non-phase locked medial frontal theta were significantly older, had better inhibitory control, scored higher on measures of general cognitive function, and were more efficient in their behavioural responses. The functional significance of phase and non-phase locked theta dynamics, and their potential changes, could have important implications for action-outcome monitoring and cognitive function in both typical and atypical development, as well as related psychopathology .

As they wait: Anticipatory neural response to evaluative peer feedback varies by pubertal status and social anxiety.

Adolescence is a developmental period characterized by substantial biological, neural, behavioral, and social changes. Learning to navigate the complex social world requires adaptive skills. Although anticipation of social situations can serve an adaptive function, providing opportunity to adjust behavior, socially anxious individuals may engage in maladaptive anticipatory processing. Importantly, elevated social anxiety often coincides with adolescence. This study investigated cortical electroencephalogram (EEG) responses during anticipation of evaluative feedback in 106 healthy adolescents aged 12-17 years. We examined differences in anticipatory event-related potentials (i.e., stimulus preceding negativity [SPN]) in relation to social anxiety levels and pubertal maturation. As expected, the right frontal SPN was more negative during feedback anticipation, particularly for adolescents with higher social anxiety and adolescents who were at a more advanced pubertal stage. Effects for the left posterior SPN were the opposite of those for the right frontal SPN consistent with a dipole. Anticipatory reactivity in adolescence was related to social anxiety symptom severity, especially in females, and pubertal maturation in a social evaluative situation. This study provides evidence for the development of social anticipatory processes in adolescence and potential mechanisms underlying maladaptive anticipation in social anxiety.

An ERP investigation of children and adolescents' sensitivity to wins and losses during a peer observation manipulation.

The purpose of this ERP P3 study was to test a peer observation manipulation (being observed by a peer versus being alone) on neural markers of attention to reward (win-feedback) and punishment (loss-feedback) during the Balloon Analogue Risk Task. Participants (126 children, 53 % male, 8-10 years; 196 early adolescents, 50 % male, 11-13 years; and 121 mid-adolescents, 52 % male, 14-16 years) were assessed by age group and pubertal status. Individual differences in how participants felt about being observed by a peer, and self-report personality factors, also were examined. Findings indicated that early and mid-adolescents (and individuals in mid-puberty and late-puberty) were sensitive to peer observation as both groups showed larger neural responses to loss-feedback in the peer condition than in the alone condition. Conversely, children (and individuals in pre- and early-puberty) were unaffected by peer observation. In addition, there clearly were individual differences in how rewarding versus anxiety-provoking participants found the peer experience. Early adolescents and mid-adolescents (and individuals in mid- and late-puberty) who reported feeling more anxious about the peer observation elicited larger neural responses to loss-feedback, and individuals in mid- and late-puberty in particular reported higher worry and lower sensation-seeking scores than those who reported a positive experience.

Association between spectral electroencephalography power and autism risk and diagnosis in early development.

Autism spectrum disorder (ASD) has its origins in the atypical development of brain networks. Infants who are at high familial risk for, and later diagnosed with ASD, show atypical activity in multiple electroencephalography (EEG) oscillatory measures. However, infant-sibling studies are often constrained by small sample sizes. We used the International Infant EEG Data Integration Platform, a multi-site dataset with 432 participants, including 222 at high-risk for ASD, from whom repeated measurements of EEG were collected between the ages of 3-36 months. We applied a latent growth curve model to test whether familial risk status predicts developmental trajectories of spectral power across the first 3 years of life, and whether these trajectories predict ASD outcome. Change in spectral EEG power in all frequency bands occurred during the first 3 years of life. Familial risk, but not a later diagnosis of ASD, was associated with reduced power at 3 months, and a steeper developmental change between 3 and 36 months in nearly all absolute power bands. ASD outcome was not associated with absolute power intercept or slope. No associations were found between risk or outcome and relative power. This study applied an analytic approach not used in previous prospective biomarker studies of ASD, which was modeled to reflect the temporal relationship between genetic susceptibility, brain development, and ASD diagnosis. Trajectories of spectral power appear to be predicted by familial risk; however, spectral power does not predict diagnostic outcome above and beyond familial risk status. Discrepancies between current results and previous studies are discussed. LAY SUMMARY: Infants with an older sibling who is diagnosed with ASD are at increased risk of developing ASD themselves. This article tested whether EEG spectral power in the first year of life can predict whether these infants did or did not develop ASD.

Use of Empirical Mode Decomposition in ERP Analysis to Classify Familial Risk and Diagnostic Outcomes for Autism Spectrum Disorder.

Event-related potentials (ERPs) activated by faces and gaze processing are found in individuals with autism spectrum disorder (ASD) in the early stages of their development and may serve as a putative biomarker to supplement behavioral diagnosis. We present a novel approach to the classification of visual ERPs collected from 6-month-old infants using intrinsic mode functions (IMFs) derived from empirical mode decomposition (EMD). Selected features were used as inputs to two machine learning methods (support vector machines and k-nearest neighbors (k-NN)) using nested cross validation. Different runs were executed for the modelling and classification of the participants in the control and high-risk (HR) groups and the classification of diagnosis outcome within the high-risk group: HR-ASD and HR-noASD. The highest accuracy in the classification of familial risk was 88.44%, achieved using a support vector machine (SVM). A maximum accuracy of 74.00% for classifying infants at risk who go on to develop ASD vs. those who do not was achieved through k-NN. IMF-based extracted features were highly effective in classifying infants by risk status, but less effective by diagnostic outcome. Advanced signal analysis of ERPs integrated with machine learning may be considered a first step toward the development of an early biomarker for ASD.

Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity.

Endogenous cortical fluctuations captured by electroencephalograms (EEGs) reflect activity in large-scale brain networks that exhibit dynamic patterns over multiple time scales. Developmental changes in the coordination and integration of brain function leads to greater complexity in population level neural dynamics. In this study we examined multiscale entropy, a measure of signal complexity, in resting-state EEGs in a large (N = 405) cross-sectional sample of children and adolescents (9-16 years). Our findings showed consistent age-dependent increases in EEG complexity that are distributed across multiple temporal scales and spatial regions. Developmental changes were most robust as the age gap between groups increased, particularly between late childhood and adolescence, and were most prominent over fronto-central scalp regions. These results suggest that the transition from late childhood to adolescence is characterized by age-dependent changes in the underlying complexity of endogenous brain networks.

12-Month peak alpha frequency is a correlate but not a longitudinal predictor of non-verbal cognitive abilities in infants at low and high risk for autism spectrum disorder.

Although studies of PAF in individuals with autism spectrum disorder (ASD) report group differences and associations with non-verbal cognitive ability, it is not known how PAF relates to familial risk for ASD, and whether similar associations with cognition in are present in infancy. Using a large multi-site prospective longitudinal dataset of infants with low and high familial risk for ASD, metrics of PAF at 12 months were extracted and growth curves estimated for cognitive development between 12-36 months. Analyses tested whether PAF 1) differs between low and high risk infants, 2) is associated with concurrent non-verbal/verbal cognitive ability and 3) predicts developmental change in non-verbal/verbal ability. Moderation of associations between PAF and cognitive ability by familial risk status was also tested. No differences in 12-month PAF were found between low and high risk infants. PAF was associated with concurrent non-verbal cognitive ability, but did not predict change in non-verbal cognitive over development. No associations were found between PAF and verbal ability, along with no evidence of moderation. PAF is not related to familial risk for ASD, and is a neural marker of concurrent non-verbal cognitive ability, but not verbal ability, in young infants at low and high risk for ASD.

EEG Integrated Platform Lossless (EEG-IP-L) pre-processing pipeline for objective signal quality assessment incorporating data annotation and blind source separation.

BACKGROUND: The methods available for pre-processing EEG data are rapidly evolving as researchers gain access to vast computational resources; however, the field currently lacks a set of standardized approaches for data characterization, efficient interactive quality control review procedures, and large-scale automated processing that is compatible with High Performance Computing (HPC) resources. NEW METHOD: In this paper we describe an infrastructure for the development of standardized procedures for semi and fully automated pre-processing of EEG data. Our pipeline incorporates several methods to isolate cortical signal from noise, maintain maximal information from raw recordings and provide comprehensive quality control and data visualization. In addition, batch processing procedures are integrated to scale up analyses for processing hundreds or thousands of data sets using HPC clusters. RESULTS: We demonstrate here that by using the EEG Integrated Platform Lossless (EEG-IP-L) pipeline's signal quality annotations, significant increase in data retention is achieved when applying subsequent post-processing ERP segment rejection procedures. Further, we demonstrate that the increase in data retention does not attenuate the ERP signal. CONCLUSIONS: The EEG-IP-L state provides the infrastructure for an integrated platform that includes long-term data storage, minimal data manipulation and maximal signal retention, and flexibility in post processing strategies.

EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.

BACKGROUND: Establishing reliable predictive and diganostic biomarkers of autism would enhance early identification and facilitate targeted intervention during periods of greatest plasticity in early brain development. High impact research on biomarkers is currently limited by relatively small sample sizes and the complexity of the autism phenotype. METHODS: EEG-IP is an International Infant EEG Data Integration Platform developed to advance biomarker discovery by enhancing the large scale integration of multi-site data. Currently, this is the largest multi-site standardized dataset of infant EEG data. RESULTS: First, multi-site data from longitudinal cohort studies of infants at risk for autism was pooled in a common repository with 1382 EEG longitudinal recordings, linked behavioral data, from 432 infants between 3- to 36-months of age. Second, to address challenges of limited comparability across independent recordings, EEG-IP applied the Brain Imaging Data Structure (BIDS)-EEG standard, resulting in a harmonized, extendable, and integrated data state. Finally, the pooled and harmonized raw data was preprocessed using a common signal processing pipeline that maximizes signal isolation and minimizes data reduction. With EEG-IP, we produced a fully standardized data set, of the pooled, harmonized, and pre-processed EEG data from multiple sites. CONCLUSIONS: Implementing these integrated solutions for the first time with infant data has demonstrated success and challenges in generating a standardized multi-site data state. The challenges relate to annotation of signal sources, time, and ICA analysis during pre-processing. A number of future opportunities also emerge, including validation of analytic pipelines that can replicate existing findings and/or test novel hypotheses.

The glass is half empty: Negative self-appraisal bias and attenuated neural response to positive self-judgment in adolescence.

Substantial changes in cognitive-affective self-referential processing occur during adolescence. We studied the behavioral and ERP correlates of self-evaluation in healthy male and female adolescents aged 12-17 (N = 109). Participants completed assessments of depression symptoms and puberty as well as a self-referential encoding task while 128-channel high-density EEG data were collected. Depression symptom severity was associated with increased endorsement of negative words and longer reaction times. In an extreme group analysis, a negative appraisal-bias subsample (n = 28) displayed decreased frontal P2 amplitudes to both positive and negative word stimuli, reflecting reduced early attentional processing and emotional salience. Compared to the positive appraisal-bias subsample (n = 27), the negative appraisal-bias subsample showed reduced LPP to positive words but not negative words, suggesting attenuated sustained processing of positive self-relevant stimuli. Findings are discussed in terms of neural processes associated with ERPs during negative versus positive self-appraisal bias, and developmental implications.

An inactive control of the 'Trier Social Stress Test' for Youth 10-17 years: Neuroendocrine, cardiac, and subjective responses.

The Trier Social Stress Test for children (TSST-C) adapted from TSST is one of the most commonly used laboratory paradigms for investigating the effects of stress on cognitive, affective and physiological responses in children and adolescents. Considering that laboratory procedures generate a significant amount of stress to children and adolescents, even in the absence of a stress paradigm, it is important to validate TSST-C against an inactive control condition in which the stress components were absent. Using a randomized design, we tested an inactive control condition, which replaced the TSST-C with a benign video clip (nature scenes viewed while standing), thus removing the stress associated components of the TSST-C. Eighty-eight youth between the ages of 10 and 17 years were randomly assigned to complete the TSST-C or the Inactive Control (IC). Subjective anxiety rating, salivary cortisol, systolic and diastolic blood pressure, and heart rate were collected at eight time points. Subjects in the Inactive Control condition showed no significant changes in blood pressure and heart rate, and decreased anxiety rating and salivary cortisol level throughout the study. Subjects in the stress condition (TSST-C) showed increased anxiety ratings, salivary cortisol, systolic and diastolic blood pressure, and heart rate immediately following TSST-C stress induction. Our findings validated that the TSST-C induced a systemic stress response, and that the Inactive Control can be a promising standardized control condition for the TSST-C and a tool for future psychobiological research. Our results also showed that anxiety reactivity decreased with age while HR reactivity increased with age. Cortisol reactivity did not fall in a linear relationship with age but rather via a quadratic curve, suggesting the mid-age adolescents had the highest cortisol responses to stress compared to their younger and older peers, potentially due to a dual factor of pubertal development and self-control and emotion regulation capacity.

One-Month Stability of Cyberball Post-Exclusion Ostracism Distress in Adolescents.

We examined one-month reliability, internal consistency, and validity of ostracism distress (Need Threat Scale) to simulated social exclusion during Cyberball. Thirty adolescents (13-18 yrs.) completed the Cyberball task, ostracism distress ratings, and measures of related clinical symptoms, repeated over one month. Need Threat Scale ratings of ostracism distress showed adequate test-retest reliability and internal consistency at both occasions. Construct validity was demonstrated via relationships with closely related constructs of anxiety, anxiety sensitivity, and emotion dysregulation, and weaker associations with more distal constructs of state paranoia and subclinical psychosis-like experiences. While ratings of ostracism distress and anxiety were significantly attenuated at retest, most participants continued to experience post-Cyberball ostracism distress at one-month follow-up, which indicates that the social exclusion induction of Cyberball persisted despite participants' familiarity with the paradigm. Overall, results suggest that the primary construct of ostracism distress is preserved over repeated administration of Cyberball, with reliability sufficient for usage in longitudinal research. These findings have important implications for translating this laboratory simulation of social distress into developmental and clinical intervention studies.

Sleep Disturbances in Child and Adolescent Mental Health Disorders: A Review of the Variability of Objective Sleep Markers.

Sleep disturbances are often observed in child and adolescent mental health disorders. Although previous research has identified consistent subjective reports of sleep disturbances, specific objective sleep markers have not yet been identified. We evaluated the current research on subjective and objective sleep markers in relation to attention deficit hyperactivity disorders, autism spectrum disorders, anxiety and depressive disorders. Subjective sleep markers are more consistent than objective markers of actigraphy, polysomnography, and circadian measures. We discuss the causes of variability in objective sleep findings and suggest future directions for research.

Medial frontal theta dissociates unsuccessful from successful avoidance and is modulated by lack of perseverance.

Medial frontal activity in the EEG is enhanced following negative feedback and varies in relation to dimensions of impulsivity. In 22 undergraduate students (Mage = 18.92 years, range 18-22 years), we employed a probabilistic negative reinforcement learning paradigm in which choices to avoid were followed by cues indicating successful or unsuccessful avoidance of an impending aversive noise. Our results showed that medial frontal theta power was enhanced following a cue that signaled avoidance was unsuccessful. In addition, self-reported lack of perseverance, a dimension of impulsivity characterized by an inability to maintain focus and determination during a challenging task, was negatively correlated with medial frontal theta elicited to an unsuccessful avoidance cue. We also observed robust differences in alpha attenuation and beta modulation following unsuccessful avoidance cue presentation. To our knowledge, this is the first study in humans to show a functional relation between medial frontal theta modulation and avoidance success. We discuss our findings in the context of frontal theta and self-regulation, negative reinforcement, and anxiety.

STATSLAB: An open-source EEG toolbox for computing single-subject effects using robust statistics.

Research on robust statistics during the past half century provides concrete evidence that classical hypothesis tests that rely on the sample mean and variance are problematic. Even seemingly minor departures from normality are now known to create major problems in terms of increased error rates and decreased power. Fortunately, numerous robust estimation techniques have been developed that circumvent the need for strict assumptions of normality and equal variances, leading to increased power and accuracy when testing hypotheses. Two robust methods that have been shown to have practical value across a wide range of applied situations are the trimmed mean and percentile bootstrap test. To facilitate the uptake of robust methods into the behavioural sciences, especially when dealing with trial-based data such as EEG, we introduce STATSLAB: An open-source EEG toolbox for computing single-subject effects using robust statistics. With the STATSLAB toolbox users can apply the percentile bootstrap test, with trimmed means, to a variety of neural signals including voltages, global field amplitude, and spectral features for both scalp channels and independent components. The toolbox offers a range of analytical strategies and is packaged with a fully functional graphical user interface that includes documentation.