Dysregulated fear, or the persistence of high levels of fear in low-threat contexts, is an early risk factor for the development of anxiety symptoms. Previous work has suggested both propensities for over-control and under-control of fearfulness as risk factors for anxiety problems, each of which may be relevant to observations of dysregulated fear. Given difficulty disentangling over-control and under-control through traditional behavioral measures, we used delta-beta coupling to begin to understand the degree to which dysregulated fear may reflect propensities for over- or under-control. We found that toddlers who showed high levels of dysregulated fear evidenced greater delta-beta coupling at frontal and central electrode sites as preschoolers relative to children who were low in dysregulated fear. Importantly, these differences were not observed when comparisons were made based on fear levels in high threat contexts. Results suggest dysregulated fear may involve tendencies toward over-control at the neural level.

Although evidence suggests that delta-beta coupling may provide a useful index of trait level cortico-subcortical cross talk in baseline contexts, there has been little work done to clarify the role of delta-beta coupling across contexts and in association with other physiological markers of emotion processing. We examined whether individual differences in coupling were visible across both positive and negative emotion-eliciting episodes during infancy (age 6 months). We also tested the convergence between measures of delta-beta coupling and neuroendocrine reactivity, which is also believed to index emotion processing. Patterns of coupling across emotion-eliciting episodes differed based on infants’ levels of cortisol reactivity. Low cortisol-reactive infants largely did not show differences in coupling across emotion contexts while high cortisol-reactive infants showed greater coupling in non-fear contexts during baseline and fear episodes. Moreover, high cortisol-reactive infants showed greater coupling than low-reactive infants in non-positive episodes.

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Background: Autism Spectrum Disorder (ASD) is characterized by having deficits in social interactions. Screening measures for ASD are often used for children over five years of age, ultimately leading to diagnosis later in development. Identification of ASD in young children is critical for early intervention. Aims: The purpose of the present study was to examine whether prediction of ASD could be improved in young children by combining social interaction scores, as measured by the Ghuman-Folstein Screen for Social Interaction (GF-SSI), with the presence of selected demographic variables (sex, age, ethnicity, mother's educational level, and socioeconomic status). Methods and Procedures: One-hundred and seventy-one clinically referred children with previously diagnosed ASD or non-ASD developmental disorders and their caregivers were included in the study. Caregivers completed a sociodemographic survey and the GF-SSI. Outcomes and Results: Results demonstrated that the final model correctly identified 74% of the cases, and the GF-SSI was found to be the greatest predictor of children having ASD. The selected demographic variables were not found to be significant predictors of the diagnosis of ASD. Conclusions and Implications: These results are discussed in relation to the literature on predicting ASD in young children. Future directions for research are also discussed.