Measuring saccade curvature: a curve-fitting approach.
Saccade curvature is becoming a popular measure for detecting the presence of competing saccadic motor programs. Several different methods of quantifying saccade curvature have been employed. In the present study, we compared these metrics with each other and with novel measures based on curve fitting. Initial deviation metrics were only moderately associated with the more widely used metric of maximum curvature. The latter was strongly related to a recently developed area-based measure and to the novel methods based on second- and third-order polynomial fits. The curve-fitting methods showed that although most saccades curved in only one direction, there was a population of trajectories with both a maximum and a minimum (i.e., double-curved saccades). We argue that a curvature metric based on a quadratic polynomial fit deals effectively with both types of trajectories and, because it is based on all the samples of a saccade, is less susceptible to sampling noise.
Ludwig
Casimir J H
CJ
Department of Experimental Psychology, University of Bristol, Bristol, England. c.ludwig@bristol.ac.uk
Gilchrist
Iain D
ID
D005403:Fixation, Ocular / Q000502:physiology; D006801:Humans; D010775:Photic Stimulation / Q000379:methods*; D012438:Saccades / Q000502:physiology*