Alpha asymmetry in infants at risk for autism spectrum disorders.

An emerging focus of research on autism spectrum disorder (ASD) targets the identification of early-developing ASD endophenotypes using infant siblings of affected children. One potential neural endophenotype is resting frontal electroencephalogram (EEG) alpha asymmetry, a metric of hemispheric organization. Here, we examined the development of frontal EEG alpha asymmetry in ASD high-risk and low-risk infant populations. Our findings demonstrate that low and high-risk infants show different patterns of alpha asymmetry at 6 months of age and opposite growth trajectories in asymmetry over the following 12 months. These results support the candidacy of alpha asymmetry as an early neural ASD endophenotype.

Functional connectivity in the first year of life in infants at risk for autism spectrum disorder: an EEG study.

In the field of autism research, recent work has been devoted to studying both behavioral and neural markers that may aide in early identification of autism spectrum disorder (ASD). These studies have often tested infants who have a significant family history of autism spectrum disorder, given the increased prevalence observed among such infants. In the present study we tested infants at high- and low-risk for ASD (based on having an older sibling diagnosed with the disorder or not) at 6- and 12-months-of-age. We computed intrahemispheric linear coherence between anterior and posterior sites as a measure of neural functional connectivity derived from electroencephalography while the infants were listening to speech sounds. We found that by 12-months-of-age infants at risk for ASD showed reduced functional connectivity compared to low risk infants. Moreover, by 12-months-of-age infants later diagnosed with ASD showed reduced functional connectivity, compared to both infants at low risk for the disorder and infants at high risk who were not later diagnosed with ASD. Significant differences in functional connectivity were also found between low-risk infants and high-risk infants who did not go onto develop ASD. These results demonstrate that reduced functional connectivity appears to be related to genetic vulnerability for ASD. Moreover, they provide further evidence that ASD is broadly characterized by differences in neural integration that emerge during the first year of life.

Developmental trajectories of resting EEG power: an endophenotype of autism spectrum disorder.

Current research suggests that autism spectrum disorder (ASD) is characterized by asynchronous neural oscillations. However, it is unclear whether changes in neural oscillations represent an index of the disorder or are shared more broadly among both affected and unaffected family members. Additionally, it remains unclear how early these differences emerge in development and whether they remain constant or change over time. In this study we examined developmental trajectories in spectral power in infants at high- or low-risk for ASD. Spectral power was extracted from resting EEG recorded over frontal regions of the scalp when infants were 6, 9, 12, 18 and 24 months of age. We used multilevel modeling to assess change over time between risk groups in the delta, theta, low alpha, high alpha, beta, and gamma frequency bands. The results indicated that across all bands, spectral power was lower in high-risk infants as compared to low-risk infants at 6-months of age. Furthermore high-risk infants showed different trajectories of change in spectral power in the subsequent developmental window indicating that not only are the patterns of change different, but that group differences are dynamic within the first two years of life. These findings remained the same after removing data from a subset of participants who displayed ASD related behaviors at 24 or 36 months. These differences in the nature of the trajectories of EEG power represent important endophenotypes of ASD.

EEG complexity as a biomarker for autism spectrum disorder risk.

BACKGROUND: Complex neurodevelopmental disorders may be characterized by subtle brain function signatures early in life before behavioral symptoms are apparent. Such endophenotypes may be measurable biomarkers for later cognitive impairments. The nonlinear complexity of electroencephalography (EEG) signals is believed to contain information about the architecture of the neural networks in the brain on many scales. Early detection of abnormalities in EEG signals may be an early biomarker for developmental cognitive disorders. The goal of this paper is to demonstrate that the modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and distinguish typically developing children from a group of infants at high risk for autism spectrum disorder (ASD), defined on the basis of an older sibling with ASD. METHODS: Using mMSE as a feature vector, a multiclass support vector machine algorithm was used to classify typically developing and high-risk groups. Classification was computed separately within each age group from 6 to 24 months. RESULTS: Multiscale entropy appears to go through a different developmental trajectory in infants at high risk for autism (HRA) than it does in typically developing controls. Differences appear to be greatest at ages 9 to 12 months. Using several machine learning algorithms with mMSE as a feature vector, infants were classified with over 80% accuracy into control and HRA groups at age 9 months. Classification accuracy for boys was close to 100% at age 9 months and remains high (70% to 90%) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter. CONCLUSIONS: This proof-of-principle study suggests that mMSE computed from resting state EEG signals may be a useful biomarker for early detection of risk for ASD and abnormalities in cognitive development in infants. To our knowledge, this is the first demonstration of an information theoretic analysis of EEG data for biomarkers in infants at risk for a complex neurodevelopmental disorder.

Brain Development and the Role of Experience in the Early Years.

Research over the past several decades has provided insight into the processes that govern early brain development and how those processes contribute to behavior. In the following article, we provide an overview of early brain development beginning with a summary of the prenatal period. We then turn to postnatal development and examine how brain functions are built and how experience mediates this process. Specifically, we discuss findings from research on speech and on face processing. The results of this research highlight how the first few years of life are a particularly important period of development of the brain.

Tachykinin regulation of cholinergic transmission in the limbic/prefrontal territory of the rat dorsal striatum: implication of new neurokinine 1-sensitive receptor binding site and interaction with enkephalin/mu opioid receptor transmission.

The tachykinin neurokinin 1 receptors (NK(1)Rs) regulation of acetylcholine release and its interaction with the enkephalin/mu opioid receptors (MORs) transmission was investigated in the limbic/prefrontal (PF) territory of the dorsal striatum. Using double immunohistochemistry, we first showed that in this territory, cholinergic interneurons contain tachykinin NK(1)Rs and co-express MORs in the last part of the light period (afternoon). In slices of the striatal limbic/PF territory, following suppression of the dopaminergic inhibitory control of acetylcholine release, application of the tachykinin NK(1)R antagonist, SSR240600, markedly reduced the NMDA-induced acetylcholine release in the morning but not in the afternoon when the enkephalin/MOR regulation is operational. In the afternoon, the NK(1)R antagonist response required the suppression of the enkephalin/MOR inhibitory control of acetylcholine release by betafunaltrexamine. The pharmacological profile of the tachykinin NK(1)R regulation tested by application of the receptor agonists [[Pro(9)]substance P, neurokinin A, neuropeptide K, and substance P(6-11)] and antagonists (SSR240600, GR205171, GR82334, and RP67580) indicated that the subtype of tachykinin NK(1)R implicated are the new NK(1)-sensitive receptor binding site. Therefore, in the limbic/PF territory of the dorsal striatum, endogenous tachykinin facilitates acetylcholine release via a tachykinin NK(1)R subtype. In the afternoon, the tachykinin/NK(1)R and the enkephalin/MOR transmissions interact to control cholinergic transmission.