Brain connectivity analysis in fathers of children with autism
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RESEARCH ARTICLE
Brain connectivity analysis in fathers of children with autism Vida Mehdizadehfar1 • Farnaz Ghassemi1 • Ali Fallah1 • Iman Mohammad-Rezazadeh2 • Hamidreza Pouretemad3 Received: 29 January 2020 / Revised: 28 July 2020 / Accepted: 16 August 2020 Ó Springer Nature B.V. 2020
Abstract Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder in which changes in brain connectivity, associated with autistic-like traits in some individuals. First-degree relatives of children with autism may show mild deficits in social interaction. The present study investigates electroencephalography (EEG) brain connectivity patterns of the fathers who have children with autism while performing facial emotion labeling task. Fifteen biological fathers of children with the diagnosis of autism (Test Group) and fifteen fathers of neurotypical children with no personal or family history of autism (Control Group) participated in this study. Facial emotion labeling task was evaluated using a set of photos consisting of six categories (mild and extreme: anger, happiness, and sadness). Group Independent Component Analysis method was applied to EEG data to extract neural sources. Dynamic causal connectivity of neural sources signals was estimated using the multivariate autoregressive model and quantified by using the Granger causality-based methods. Statistical analysis showed significant differences (p value \ 0.01) in the connectivity of neural sources in recognition of some emotions in two groups, which the most differences observed in the mild anger and mild sadness emotions. Short-range connectivity appeared in Test Group and conversely, long-range and interhemispheric connections are observed in Control Group. Finally, it can be concluded that the Test Group showed abnormal activity and connectivity in the brain network for the processing of emotional faces compared to the Control Group. We conclude that neural source connectivity analysis in fathers may be considered as a potential and promising biomarker of ASD. Keywords Broader autism phenotype (BAP) Facial emotion recognition Group independent component analysis (gICA) Connectivity analysis Granger causality
Introduction Nonverbal communications in human interactions convey signals to others about an individuals’ thinking, intentions, and feelings have been a crucial part of human communications (Black et al. 2017). Facial gesture plays an important role in social interactions and helps to find out internal emotional and mental moods. Problems in
& Farnaz Ghassemi [email protected] 1
Faculty of Biomedical Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran
2
Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
3
Department of Psychology, Shahid Beheshti University, Tehran, Iran
recognizing other’s facial expressions have been observed in children and adults diagnosed with ASD (American Psychiatric Association 2
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