Search NASA⌕ Search

NASA NTRS · 20050075909

Eye-head coordination during optokinetic stimulation in squirrel monkeys

Abstract

Head and eye movements in the yaw plane were recorded during and after optokinetic stimulation in squirrel monkeys. 1) Phasic or tonic head deviations to the side of the ocular quick phase occurred in 94% of total recordings (n = 50) during the perstimulus period, and in 75% of recordings (n = 49) during the poststimulus period. Magnitude of mean head deviation was significantly different between perstimulus and poststimulus periods. 2) Head nystagmus associated with eye nystagmus was consistently observed in seven of nine squirrel monkeys during optokinetic stimulation. Squirrel monkeys are thereby less prone to display head nystagmus than either guinea pigs, pigeons or chickens. 3) Slow phase speeds of coupled head and eye nystagmus were subjected to statistical analysis. A highly significant negative correlation was found between slow phase head and eye speeds. The correlation coefficient was - 0.81 at 60 degrees / sec stimulus (n = 119) and -0.72 at 100 degrees / sec stimulus (n = 131). The gaze speed, calculated by summing the head and eye speeds, was 59.1 plus or minus 6.8 / sec at 60 degrees / sec and 92.2 plus or minus 11.4 at 100 degrees / sec stimulus. There was no significant difference between the gaze speed in a free head condition and the eye speed when the head was fixed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kubo, T., Igarashi, M., Jensen, D. W., Homick, J. L.. 1981-01-01. Eye-head coordination during optokinetic stimulation in squirrel monkeys. https://ntrs.nasa.gov/citations/20050075909

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗