Eye Movement Measures in Schizophrenia

Abstract

Among the contemporary techniques used to study the human brain, eye tracking is one of the most effective tools to study attention and decision making. By providing information about the gaze position, gaze direction, eye movements (saccades, fixations, etc) and pupil size, eye tracking has several applications not only in psychology but also in psychiatry, gaming, advertising, etc. Since eye movement abnormalities had been identified in various psychiatric disorders, studying eye movements using eye tracking provides one an economical, accessible and accurate tool to detect and diagnose these disorders. In this project, we focussed mainly on developing a novel methodology to analyse EyeLink eye tracking data using PyGaze, an open-source Python toolbox. The methodology was then used to analyse the eye movement data from healthy controls and patients with Schizophrenia. Measures for the eye movement paradigms were extracted using the developed methodology. A very high degree of reliability was found between the results from the EyeLink data viewer and the developed methodology for the antisaccade paradigm measures. Most of the fixation stability test measures were found to be statistically significant when compared across healthy controls and schizophrenic patients, and the results obtained were consistent with other studies. The measures, extracted using the developed methodology, could be developed into potential behavioral biomarkers to aid in the research on psychiatric disorders like Schizophrenia.