Dataset Information

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans.

ABSTRACT: Oculomotor selection exerts a fundamental impact on our experience of the environment. To better understand the underlying principles, researchers typically rely on behavioral data from humans, and electrophysiological recordings in macaque monkeys. This approach rests on the assumption that the same selection processes are at play in both species. To test this assumption, we compared the viewing behavior of 106 humans and 11 macaques in an unconstrained free-viewing task. Our data-driven clustering analyses revealed distinct human and macaque clusters, indicating species-specific selection strategies. Yet, cross-species predictions were found to be above chance, indicating some level of shared behavior. Analyses relying on computational models of visual saliency indicate that such cross-species commonalities in free viewing are largely due to similar low-level selection mechanisms, with only a small contribution by shared higher level selection mechanisms and with consistent viewing behavior of monkeys being a subset of the consistent viewing behavior of humans.

SUBMITTER: Wilming N

PROVIDER: S-EPMC5942390 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Publications

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans.

Wilming Niklas N Kietzmann Tim C TC Jutras Megan M Xue Cheng C Treue Stefan S Buffalo Elizabeth A EA König Peter P

Cerebral cortex (New York, N.Y. : 1991) 20170101 1

Oculomotor selection exerts a fundamental impact on our experience of the environment. To better understand the underlying principles, researchers typically rely on behavioral data from humans, and electrophysiological recordings in macaque monkeys. This approach rests on the assumption that the same selection processes are at play in both species. To test this assumption, we compared the viewing behavior of 106 humans and 11 macaques in an unconstrained free-viewing task. Our data-driven cluste ...[more]

PMID: 28077512

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Project description:Despite the enduring interest in motion integration, a direct measure of the space-time filter that the brain imposes on a visual scene has been elusive. This is perhaps because of the challenge of estimating a 3D function from perceptual reports in psychophysical tasks. We take a different approach. We exploit the close connection between visual motion estimates and smooth pursuit eye movements to measure stimulus-response correlations across space and time, computing the linear space-time filter for global motion direction in humans and monkeys. Although derived from eye movements, we find that the filter predicts perceptual motion estimates quite well. To distinguish visual from motor contributions to the temporal duration of the pursuit motion filter, we recorded single-unit responses in the monkey middle temporal cortical area (MT). We find that pursuit response delays are consistent with the distribution of cortical neuron latencies and that temporal motion integration for pursuit is consistent with a short integration MT subpopulation. Remarkably, the visual system appears to preferentially weight motion signals across a narrow range of foveal eccentricities rather than uniformly over the whole visual field, with a transiently enhanced contribution from locations along the direction of motion. We find that the visual system is most sensitive to motion falling at approximately one-third the radius of the stimulus aperture. Hypothesizing that the visual drive for pursuit is related to the filtered motion energy in a motion stimulus, we compare measured and predicted eye acceleration across several other target forms.SIGNIFICANCE STATEMENT A compact model of the spatial and temporal processing underlying global motion perception has been elusive. We used visually driven smooth eye movements to find the 3D space-time function that best predicts both eye movements and perception of translating dot patterns. We found that the visual system does not appear to use all available motion signals uniformly, but rather weights motion preferentially in a narrow band at approximately one-third the radius of the stimulus. Although not universal, the filter predicts responses to other types of stimuli, demonstrating a remarkable degree of generalization that may lead to a deeper understanding of visual motion processing.

Dataset Information

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans.

Publications

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans.

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