Abstract
There are six neuronal control systems which are
widely accepted as basic eye-movement patterns: Fixation system/ Saccadic eye
movements/ Smooth-pursuit/ Vergence movements/ Vestibulo-ocular reflexes/
Optokinetic movements. Different subjects have different eye-movement
performance in same or different tasks, so we try to analyze the daily
performance through behavioral data of several macaques using machine learning
algorithm, including parameters such as reaction time, duration, accuracy,
amplitude, velocity, acceleration, pre-saccadic oscillations, post-saccadic
oscillations. The results indicate that behavioral tendency of same macaque in
different experimental tasks may represents one stable type of personality from
the raw data to feature extraction and the final classification. In the same
experimental task, macaques with different characteristics may have different
response tendencies. In different experimental tasks, macaques with the same
personality may have the same response tendency. Error trials will also be
analyzed. This study attempts to obtain the quantitative estimation of
personality through the Combination of the eyemovement data and the personality
scale, providing a quantitative indicator for the psychological personality
test. Meanwhile, the result may be used to assist in the diagnosis of ADHD,
Autism, Parkinson’s disease and other diseases in human.