Estimation of the Cyclopean Eye From Binocular Smooth Pursuit Tests

• Published in: IEEE transactions on cognitive and developmental systems 2024-12, Vol.16 (6), p.2125-2137
• Main Authors: Luque-Buzo, Elisa, Bejani, Mehdi, Arias-London, Julian D., Gomez-Garcia, Jorge A., Grandas-Perez, Francisco, Godino-Llorente, Juan I.
• Format: Article
• Language: English
• Subjects: Binocular vision; Brain; cyclopean eye; Electrocardiography; Eye movements; Feature extraction; Functional magnetic resonance imaging; Independent component analysis; independent component analysis (ICA); Infrared analysis; Infrared tracking; Motors; Moving targets; Noise reduction; Ocular dominance; Sequences; smooth pursuit eye movements (SPEMs); Systematics; Tracking devices; videoculography; Visualization
• ISSN: 2379-8920; 2379-8939
• DOI: 10.1109/TCDS.2024.3410110

In binocular vision, the visual system combines images in the retina to generate a single perception, which triggers a sensorimotor process that forces the eyes to point to the same target. Thus, following a moving target, both eyes are expected to move synchronously following identical motor triggers but, in practise, significant differences between eyes are found due to the presence of certain artifacts and effects. Thus, a better indirect characterization of the underlying neurological behavior during eye motion would require new automatic preprocessing methods applied to the eye-tracking sequences for rendering the common and most significant movements of both eyes. To address this need, the present study proposes an automatic method for extracting the common components of the left- and right-eye motions from a set of Smooth Pursuit tests by applying an independent component analysis. To do so, both sequences are decomposed into two independent latent components: the first presumably correlates with the common motor triggering at the brain, while the second collects artifacts introduced during the recording process and small effects due to convergence deficits and eye dominance biases. The evaluations were carried out using data corresponding to 12 different smooth pursuit eye movements tests, which were collected using an infrared high-speed video-based eye-tracking device from 41 parkinsonian patients and 47 controls. The results show that the automatic method can separate the aforementioned components in 99.50% of cases, extracting a latent component correlated with the common motor triggering at the brain, which we hypothesize is characterizing the movements of the cyclopean eye. The estimated component could be used to simplify any other potential automatic analysis.