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

Presymptomatic Biological, Structural, and Functional Diagnostic Biomarkers of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder clinically diagnosed by persistent deficits in three areas of social communication and interaction, plus at least two of four types of restricted repetitive behaviors. ASD has been shown to be caused by genetic predisposition and environmental factors; however, the heterogeneity of ASD complicates its diagnosis and treatment. Early behavioral interventions have shown significant benefits, emphasizing the urgent need for reliable diagnostic biomarkers to enhance long-term outcomes. Here we provide a systematic review that outlines current findings on genetic and neurological biomarkers for presymptomatic ASD diagnoses, assessed prior to the observation of behavioral manifestations. Specifically, we offer insights into the mechanisms of presymptomatic neurological, biological, structural, and functional markers for ASD, compare outcomes across studies, and critically assess their limitations and implications. Recent findings highlight genotype-guided therapeutic strategies in animal models, such as dietary zinc supplementation for reversing ASD-associated behaviors by synaptic deficits. However, the differential efficacy based on underlying genotypes, along with challenges in identifying reliable genomic biomarkers prior to symptom onset, indicates the need for further research. Notably, recent advancements in imaging technologies like magnetic resonance imaging, electroencephalography, and pupillometry have shown promising markers in neonates, and at 3 and 9 months old, respectively. Newer developments in magnetoencephalography hardware can facilitate the much-needed infant ASD studies. It is important to note that many of these biomarker findings are preliminary, and further validation for clinical use is required. Continued research is needed to advance the practicality, reliability, and acceptability of these biomarkers to improve ASD diagnosis and treatment strategies.

White matter microstructure as a potential contributor to differences in resting state alpha activity between neurotypical and autistic children: a longitudinal multimodal imaging study

We and others have demonstrated the resting-state (RS) peak alpha frequency (PAF) as a potential clinical marker for young children with autism spectrum disorder (ASD), with previous studies observing a higher PAF in school-age children with ASD versus typically developing (TD) children, as well as an association between the RS PAF and measures of processing speed in TD but not ASD. The brain mechanisms associated with these findings are unknown. A few studies have found that in children more mature optic radiation white matter is associated with a higher PAF. Other studies have reported white matter and neural activity associations in TD but not ASD. The present study hypothesized that group differences in the RS PAF are due, in part, to group differences in optic radiation white matter and PAF associations. The maturation of the RS PAF (measured using magnetoencephalography(MEG)), optic radiation white matter (measured using diffusion tensor imaging(DTI)), and associations with processing speed were assessed in a longitudinal cohort of TD and ASD children. Time 1 MEG and DTI measures were obtained at 6-8 years old (59TD and 56ASD) with follow-up brain measures collected ~ 1.5 and ~ 3 years later. The parietal-occipital PAF increased with age in both groups by 0.13 Hz/year, with a main effect of group showing the expected higher PAF in ASD than TD (an average of 0.26 Hz across the 3 time points). Across age, the RS PAF predicted processing speed in TD but not ASD. Finally, more mature optic radiation white matter measures (FA, RD, MD, AD) were associated with a higher PAF in both groups. Present findings provide additional evidence supporting the use of the RS PAF as a brain marker in children with ASD 6-10 years old, and replicate findings of an association between the RS PAF and processing speed in TD but not ASD. The hypothesis that the RS PAF group differences (with ASD leading TD by about 2 years) would be explained by group differences in optic radiation white matter was not supported, with brain structure-function associations indicating that more mature optic radiation white matter is associated with a higher RS PAF in both groups.

Oscillatory But Not Aperiodic Frontal Brain Activity Predicts the Development of Executive Control From Infancy to Toddlerhood

Executive control (EC) emerges in the first year of life, with the ability to inhibit prepotent responses (inhibitory control [IC]) and to flexibly readapt (cognitive flexibility [CF]) steadily improving. Simultaneously, electrophysiological brain activity undergoes profound reconfiguration, which has been linked to individual variability in EC. However, most studies exploring this relationship have used relative/absolute power and tasks that combine different executive processes. In addition, brain activity conflates aperiodic and oscillatory activity, which hinders the interpretation of the relationship between power and cognition. In the current study, we used the Early Childhood Inhibitory Touchscreen Task (ECITT) to examine the development of EC skills from 9 to 16 months in a longitudinal sample, and related performance of the task to resting-state EEG (rs-EEG) power, separating oscillatory and aperiodic activity. Our results showed improvement in IC but not in CF with age. In addition, alpha and theta oscillatory activity were concurrent (9-mo.) and longitudinal predictors of CF in toddlerhood, whereas the aperiodic exponent of the EEG signal did not contribute to EC. These findings demonstrate the relevance of oscillatory brain activity for cognitive development and provide an early brain marker for the early development of EC.

Peak alpha frequency is linked to visual temporal attention in 6-month-olds

The temporal resolution of adults' visual attention has been linked to the frequency of alpha-band oscillations in electroencephalogram (EEG) signal, with higher Peak Alpha Frequency (PAF) being associated with better visual temporal processing skills. However, relatively less is known about neural mechanisms underlying individual differences in the temporal resolution of visual attention in infancy. This study investigated the role of PAF in visual temporal processing in early infancy. In a sample of 6-month-old infants (n = 62) we examined the relationship between PAF extracted from resting-state EEG, and saccadic latencies in a predictive cueing task where the appearance of a reward was predicted by higher or lower frequency of two flickering objects. Results showed that higher PAF was associated with shorter saccadic latencies in a condition with higher differences between the two flickering frequencies, speaking for the involvement of PAF in visual temporal attention in early development. Additionally, we found that infants were generally faster to orient to the reward in trials where both peripheral stimuli were flickering at relatively lower frequencies, roughly corresponding to the theta frequency band. Our findings support theoretical accounts highlighting the role of PAF in visual attention processing and extend this framework to early infancy.

Heterogeneity and convergence across seven neuroimaging modalities: a review of the autism spectrum disorder literature

Background

A growing body of literature classifies autism spectrum disorder (ASD) as a heterogeneous, complex neurodevelopmental disorder that often is identified prior to three years of age. We aim to provide a narrative review of key structural and functional properties that differentiate the neuroimaging profile of autistic youth from their typically developing (TD) peers across different neuroimaging modalities.

Methods

Relevant studies were identified by searching for key terms in PubMed, with the most recent search conducted on September 1, 2023. Original research papers were included if they applied at least one of seven neuroimaging modalities (structural MRI, functional MRI, DTI, MRS, fNIRS, MEG, EEG) to compare autistic children or those with a family history of ASD to TD youth or those without ASD family history; included only participants <18 years; and were published from 2013 to 2023.

Results

In total, 172 papers were considered for qualitative synthesis. When comparing ASD to TD groups, structural MRI-based papers (n = 26) indicated larger subcortical gray matter volume in ASD groups. DTI-based papers (n = 14) reported higher mean and radial diffusivity in ASD participants. Functional MRI-based papers (n = 41) reported a substantial number of between-network functional connectivity findings in both directions. MRS-based papers (n = 19) demonstrated higher metabolite markers of excitatory neurotransmission and lower inhibitory markers in ASD groups. fNIRS-based papers (n = 20) reported lower oxygenated hemoglobin signals in ASD. Converging findings in MEG- (n = 20) and EEG-based (n = 32) papers indicated lower event-related potential and field amplitudes in ASD groups. Findings in the anterior cingulate cortex, insula, prefrontal cortex, amygdala, thalamus, cerebellum, corpus callosum, and default mode network appeared numerous times across modalities and provided opportunities for multimodal qualitative analysis.

Conclusions

Comparing across neuroimaging modalities, we found significant differences between the ASD and TD neuroimaging profile in addition to substantial heterogeneity. Inconsistent results are frequently seen within imaging modalities, comparable study populations and research designs. Still, converging patterns across imaging modalities support various existing theories on ASD.

Oxytocin treatment rescues irritability-like behavior in Cc2d1a conditional knockout mice

Irritability, a state of excessive reactivity to negative emotional stimuli, is common in individuals with autism spectrum disorder (ASD). Although it has a significant negative impact of patients' disease severity and quality of life, the neural mechanisms underlying irritability in ASD remain largely unclear. We have previously demonstrated that male mice lacking the Coiled-coil and C2 domain containing 1a (Cc2d1a) in forebrain excitatory neurons recapitulate numerous ASD-like behavioral phenotypes, including impaired social behaviors and pronounced repetitive behaviors. Here, using the bottle-brush test (BBT) to trigger and evaluate aggressive and defensive responses, we show that Cc2d1a deletion increases irritability-like behavior in male but not female mice, which is correlated with reduced number of oxytocin (OXT)-expressing neurons in the paraventricular nucleus (PVN) of the hypothalamus. Intranasal OXT administration or chemogenetic activation of OXT neurons in the PVN rescues irritability-like behavior in Cc2d1a conditional knockout (cKO) mice. Administration of a selective melanocortin receptor 4 agonist, RO27-3225, which potentiates endogenous OXT release, also alleviates irritability-like behavior in Cc2d1a cKO mice, an effect blocked by a specific OXT receptor antagonist, L-368,899. We additionally identify a projection connecting the posterior ventral segment of the medial amygdala (MeApv) and ventromedial nucleus of the ventromedial hypothalamus (VMHvl) for governing irritability-like behavior during the BBT. Chemogenetic suppression of the MeApv-VMHvl pathway alleviates irritability-like behavior in Cc2d1a cKO mice. Together, our study uncovers dysregulation of OXT system in irritability-like behavior in Cc2d1a cKO mice during the BBT and provide translatable insights into the development of OXT-based therapeutics for clinical interventions.

Relationships between peak alpha frequency, age, and autistic traits in young children with and without autism spectrum disorder

Background

Atypical peak alpha frequency (PAF) has been reported in children with autism spectrum disorder (ASD); however, the relationships between PAF, age, and autistic traits remain unclear. This study was conducted to investigate and compare the resting-state PAF of young children with ASD and their typically developing (TD) peers using magnetoencephalography (MEG).

Methods

Nineteen children with ASD and 24 TD children, aged 5-7 years, underwent MEG under resting-state conditions. The PAFs in ten brain regions were calculated, and the associations between these findings, age, and autistic traits, measured using the Social Responsiveness Scale (SRS), were examined.

Results

There were no significant differences in PAF between the children with ASD and the TD children. However, a unique positive association between age and PAF in the cingulate region was observed in the ASD group, suggesting the potential importance of the cingulate regions as a neurophysiological mechanism underlying distinct developmental trajectory of ASD. Furthermore, a higher PAF in the right temporal region was associated with higher SRS scores in TD children, highlighting the potential role of alpha oscillations in social information processing.

Conclusions

This study emphasizes the importance of regional specificity and developmental factors when investigating neurophysiological markers of ASD. The distinct age-related PAF patterns in the cingulate regions of children with ASD and the association between right temporal PAF and autistic traits in TD children provide novel insights into the neurobiological underpinnings of ASD. These findings pave the way for future research on the functional implications of these neurophysiological patterns and their potential as biomarkers of ASD across the lifespan.

Abnormalities in both stimulus-induced and baseline MEG alpha oscillations in the auditory cortex of children with Autism Spectrum Disorder

The neurobiology of Autism Spectrum Disorder (ASD) is hypothetically related to the imbalance between neural excitation (E) and inhibition (I). Different studies have revealed that alpha-band (8-12 Hz) activity in magneto- and electroencephalography (MEG and EEG) may reflect E and I processes and, thus, can be of particular interest in ASD research. Previous findings indicated alterations in event-related and baseline alpha activity in different cortical systems in individuals with ASD, and these abnormalities were associated with core and co-occurring conditions of ASD. However, the knowledge on auditory alpha oscillations in this population is limited. This MEG study investigated stimulus-induced (Event-Related Desynchronization, ERD) and baseline alpha-band activity (both periodic and aperiodic) in the auditory cortex and also the relationships between these neural activities and behavioral measures of children with ASD. Ninety amplitude-modulated tones were presented to two groups of children: 20 children with ASD (5 girls, Mage = 10.03, SD = 1.7) and 20 typically developing controls (9 girls, Mage = 9.11, SD = 1.3). Children with ASD had a bilateral reduction of alpha-band ERD, reduced baseline aperiodic-adjusted alpha power, and flattened aperiodic exponent in comparison to TD children. Moreover, lower raw baseline alpha power and aperiodic offset in the language-dominant left auditory cortex were associated with better language skills of children with ASD measured in formal assessment. The findings highlighted the alterations of E / I balance metrics in response to basic auditory stimuli in children with ASD and also provided evidence for the contribution of low-level processing to language difficulties in ASD.

The importance of decomposing periodic and aperiodic EEG signals for assessment of brain function in a global context

Measures of early neuro-cognitive development that are suitable for use in low-resource settings are needed to enable studies of the effects of early adversity on the developing brain in a global context. These measures should have high acquisition rates and good face and construct validity. Here, we investigated the feasibility of a naturalistic electroencephalography (EEG) paradigm in a low-resource context during childhood. Additionally, we examined the sensitivity of periodic and aperiodic EEG metrics to social and non-social stimuli. We recorded simultaneous 20-channel EEG and eye-tracking in 72 children aged 4-12 years (45 females) while they watched videos of women singing nursery rhymes and moving toys, selected to represent familiar childhood experiences. These measures were part of a feasibility study that assessed the feasibility and acceptability of a follow-up data collection of the South African Safe Passage Study, which tracks environmental adversity and brain and cognitive development from before birth up until childhood. We examined whether data quantity and quality varied with child characteristics and the sensitivity of varying EEG metrics (canonical band power in the theta and alpha band and periodic and aperiodic features of the power spectra). We found that children who completed the EEG and eye-tracking assessment were, in general, representative of the full cohort. Data quantity was higher in children with greater visual attention to the stimuli. Out of the tested EEG metrics, periodic measures in the theta frequency range were most sensitive to condition differences, compared to alpha range measures and canonical and aperiodic EEG measures. Our results show that measuring EEG during ecologically valid social and non-social stimuli is feasible in low-resource settings, is feasible for most children, and produces robust indices of social brain function. This work provides preliminary support for testing longitudinal links between social brain function, environmental factors, and emerging behaviors.

Resting-State Activity in Children: Replicating and Extending Findings of Early Maturation of Alpha Rhythms in Autism Spectrum Disorder

Resting-state alpha brain rhythms provide a foundation for basic as well as higher-order brain processes. Research suggests atypical maturation of the peak frequency of resting-state alpha activity (= PAF) in autism spectrum disorder (ASD). The present study examined resting-state alpha activity in young school-aged children, obtaining magnetoencephalographic (MEG) eyes-closed resting-state data from 47 typically developing (TD) males and 45 ASD males 6.0 to 9.3 years old. Results confirmed a higher PAF in ASD versus TD, and demonstrated that alpha power differences between groups were linked to the shift of PAF in ASD. Additionally, a higher PAF was associated with better cognitive performance in TD but not ASD. Finding thus suggested functional consequences of group differences in resting-state alpha activity.

Evaluating early EEG correlates of restricted and repetitive behaviors for toddlers with or without autism

Background

Restricted and repetitive behaviors (RRB) are among the primary characteristics of autism spectrum disorder (ASD). Despite the potential impact on later developmental outcomes, our understanding of the neural underpinnings of RRBs is limited. Alterations in EEG alpha activity have been observed in ASD and implicated in RRBs, however, developmental changes within the alpha band requires careful methodological considerations when studying its role in brain-behavior relationships during infancy and early childhood. Novel approaches now enable the parameterization of the power spectrum into periodic and aperiodic components. This study aimed to characterize the neural correlates of RRBs in infancy by (1) comparing infant resting-state measures (periodic alpha and aperiodic activity) between infants who develop ASD, elevated likelihood infants without ASD, and low likelihood infants without ASD, and (2) evaluate whether these infant EEG measures are associated with frequency of RRBs measured at 24 months.

Methods

Baseline non-task related EEG data were collected from 12-to-14-month-old infants with and without elevated likelihood of autism (N=160), and periodic alpha activity (periodic alpha power, individual peak alpha frequency and amplitude), and aperiodic activity measures (aperiodic exponent) were calculated. Parent-reported RRBs were obtained at 24 months using the Repetitive Behavior Scale-Revised questionnaire. Group differences in EEG measures were evaluated using ANCOVA, and multiple linear regressions were conducted to assess relationships between EEG and RRB measures.

Results

No group-level differences in infant EEG measures were observed. Marginal effects analysis of linear regressions revealed significant associations within the ASD group, such that higher periodic alpha power, lower peak alpha frequency, and lower aperiodic exponent, were associated with elevated RRBs at 24 months. No significant associations were observed for non-ASD outcome groups.

Limitations

The sample size for ASD (N=19) was modest for examining brain-behavior relations. Larger sample sizes are needed to increase statistical power.

Conclusion

For infants with later ASD diagnoses, measures of alpha and aperiodic activity measured at 1-year of age were associated with later manifestation of RRBs at 2-years. Longitudinal studies are needed to elucidate whether the early trajectory of these EEG measures and their dynamic relations in development influence manifestations of RRBs in ASD.

EEG Biomarkers for Autism: Rational, Support, and the Qualification Process

In this chapter, we highlight the advantages, progress, and pending challenges of developing electroencephalography (EEG) and event-related potential (ERP) biomarkers for use in autism spectrum disorder (ASD). We describe reasons why global efforts towards precision treatment in ASD are utilizing EEG indices to quantify biological mechanisms. We overview common sensory processing and attention biomarkers and provide translational examples examining the genetic etiology of autism across animal models and human subgroups. We describe human-specific social biomarkers related to face perception, a complex social cognitive process that may prove informative of autistic social behaviors. Lastly, we discuss outstanding considerations for quantifying EEG biomarkers, the challenges associated with rigor and reproducibility, contexts of future use, and propose opportunities for combinatory multidimensional biomarkers.

Neural mechanisms of language development in infancy

Understanding the neural processes underpinning individual differences in early language development is of increasing interest, as it is known to vary in typical development and to be quite heterogeneous in neurodevelopmental conditions. However, few studies to date have tested whether early brain measures are indicative of the developmental trajectory of language, as opposed to language outcomes at specific ages. We combined recordings from two longitudinal studies, including typically developing infants without a family history of autism, and infants with increased likelihood of developing autism (infant-siblings) (N = 191). Electroencephalograms (EEG) were recorded at 6 months, and behavioral assessments at 6, 12, 18, 24 and 36 months of age. Using a growth curve model, we tested whether absolute EEG spectral power at 6 months was associated with concurrent language abilities, and developmental change in language between 6 and 36 months. We found evidence of an association between 6-month alpha-band power and concurrent, but not developmental change in, expressive language ability in both infant-siblings and control infants. The observed association between 6-month alpha-band power and 6-month expressive language was not moderated by group status, suggesting some continuity in neural mechanisms.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

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

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

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

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

The Value of Brain Imaging and Electrophysiological Testing for Early Screening of Autism Spectrum Disorder: A Systematic Review

Given the significance of validating reliable tests for the early detection of autism spectrum disorder (ASD), this systematic review aims to summarize available evidence of neuroimaging and neurophysiological changes in high-risk infants to improve ASD early diagnosis. We included peer-reviewed, primary research in English published before May 21, 2021, involving the use of magnetic resonance imaging (MRI), electroencephalogram (EEG), or functional near-infrared spectroscopy (fNIRS) in children with high risk for ASD under 24 months of age. The main exclusion criteria includes diagnosis of a genetic disorder and gestation age of less the 36 weeks. Online research was performed on PubMed, Web of Science, PsycINFO, and CINAHL. Article selection was conducted by two reviewers to minimize bias. This research was funded by Massachusetts General Hospital Sundry funding. IRB approval was not submitted as it was deemed unnecessary. We included 75 primary research articles. Studies showed that high-risk infants had divergent developmental trajectories for fractional anisotropy and regional brain volumes, increased CSF volume, and global connectivity abnormalities on MRI, decreased sensitivity for familiar faces, atypical lateralization during facial and auditory processing, and different spectral powers across multiple band frequencies on EEG, and distinct developmental trajectories in functional connectivity and regional oxyhemoglobin concentrations in fNIRS. These findings in infants were found to be correlated with the core ASD symptoms and diagnosis at toddler age. Despite the lack of quantitative analysis of the research database, neuroimaging and electrophysiological biomarkers have promising value for the screening of ASD as early as infancy with high accuracy, which warrants further investigation.