| Literature DB >> 32570392 |
Meenakshi Chatterjee1, Nikolay V Manyakov2, Abigail Bangerter1, Dzmitry A Kaliukhovich2, Shyla Jagannatha1, Seth Ness1, Gahan Pandina1.
Abstract
Eye tracking studies have demonstrated deficits in attention in individuals with Autism Spectrum Disorder (ASD) for a range of different social attention-based tasks. Here we examined social attention skills in a large sample of ASD participants (n = 120), using eye tracking data from a social information processing task, and compared them with a typically developing (TD) group (n = 35). Assuming eye movement parameters are random variables generated by an underlying stochastic process, we modeled the fixation sequences of participants in ASD and TD groups with a Hidden Markov Model. The Regions of Interests (ROIs), modeled as hidden states, corresponded to the true ROIs with a prediction accuracy of >90% for each group. The transition between ROIs revealed bias towards a specific area in the scene in ASD group, which deviated from the TD group. Objective time-dynamic measures of gaze patterns can potentially serve as useful endpoints in ASD diagnosis. Clinical Trial Registration: NCT02299700.Entities:
Keywords: Autism Spectrum Disorder; Hidden Markov Model; eye tracking
Mesh:
Year: 2020 PMID: 32570392 DOI: 10.3233/SHTI200168
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630