EEG and Pupillary Response in Children with Autism: Results from the ABC-CT Feasibility Study

Poster Presentation
Saturday, May 12, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
A. Naples1, F. Shic2, A. R. Levin3, R. Bernier4, G. Dawson5, M. Murias6, S. Jeste7, C. A. Nelson8, S. Faja8, K. Chawarska1, C. Sugar7, D. Senturk9, G. Hellemann9, J. Dziura10, C. Brandt10, S. J. Webb4 and J. McPartland1, (1)Child Study Center, Yale University School of Medicine, New Haven, CT, (2)Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, (3)Neurology, Boston Children's Hospital, Boston, MA, (4)Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, (5)Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Durham, NC, (6)Duke Center for Autism and Brain Development, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, (7)University of California, Los Angeles, Los Angeles, CA, (8)Boston Children's Hospital, Boston, MA, (9)UCLA, Los Angeles, CA, (10)Yale University, New Haven, CT
Background: Dysregulated attention and arousal are comorbid features of ASD. These symptoms are associated with differences in noradrenergic activity. Pupil diameter (PD) is a marker of locus coeruleus (LC) activity, the primary cortical source of norepinephrine. Prior work has established that individuals with ASD exhibit attenuated pupil response to light. Despite the broad neuromodulatory efferents from the LC to cortex, there have been no studies in humans linking the dynamics of the pupillary light reflex (PLR) to EEG features; this relationship may help to parse heterogeneity among individuals with ASD and between ASD and controls.

Objectives: We examine: (1) the relationship of the PLR and EEG; (2) The relationship between PLR and individual alpha frequency (IAF); (3) the relationship of the PLR and EEG to clinical characteristics.

Methods: Data were collected from 25 children with ASD and 26 typically developing controls (TD) across five sites. Ages ranged from 4-11 years and IQ ranged from 53-133. Analyses were conducted on subsets of participants contributing valid PLR (ASD=23, TD=26), EEG (ASD=23, TD=26), and IAF data (ASD=21, TD=24). EEG data were recorded at 1000hz and spectral power was calculated from one second epochs. IAF was calculated from occipital electrodes in the range from 6-12hz. The PLR was calculated in response to a 133ms white flash followed by a black screen. PLR dynamics included relative constriction, latency of constriction, and redilation and constriction velocities.

Results: PLR comparisons revealed marginal differences in constriction velocity (t=1.941, p=.058), such that constriction velocity, but not latency, was faster in individuals with ASD than in controls. EEG analyses revealed individuals with ASD exhibited an atypical power spectrum; a less steep slope (t = 2.184, p=.034), and higher power in theta (t=2.5, p=.017), beta (t=2.638, p=.011), and gamma (t=2.91, p=.005) bands compared to controls. PLR latency correlated with theta (r=.374, p=.009), beta (r=.473, p<.001), and gamma power (r=.312, p=.031), and IAF correlated with PLR constriction (r=.295, p=.051) and constriction velocity (r=.326, p=.031). Among children with ASD, the ADOS calibrated severity score correlated with theta (r=.473. p=.023) and PLR latency (r=.359, p=.093). PLR latency also correlated with the socialization domain of the Vineland (r=-.586, p =.005). The Social Responsiveness Scale Cognition Subscale correlated with PLR constriction (r=-.459, p=.003). For all correlations, attenuated PLR response predicted elevated symptomology.

Conclusions: These are the first data to examine relationships between EEG and PLR within individuals with ASD, revealing potential relationships between brainstem nuclei, cortical activity, and clinical symptomology. The directionality of effects suggests that increased LC activity, indicated by increased PLR latency and attenuated constriction, is related to an atypical EEG profile and increased symptomology. Further analyses will parse shared and unique variance between PLR and EEG contributions to ASD symptomology and measures of EEG coherence. These findings show promise for the potential of these biomarkers as indicators of treatment response and as potential targets for treatment development.