Dataset Information

Spatiotemporal Filter for Visual Motion Integration from Pursuit Eye Movements in Humans and Monkeys.

ABSTRACT: 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.

SUBMITTER: Mukherjee T

PROVIDER: S-EPMC5299399 | biostudies-other | 2017 Feb

REPOSITORIES: biostudies-other

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Project description:Smooth pursuit eye movements (pursuit) are used to minimize the retinal motion of moving objects. During pursuit, the pattern of motion on the retina carries not only information about the object movement but also reafferent information about the eye movement itself. The latter arises from the retinal flow of the stationary world in the direction opposite to the eye movement. To extract the global direction of motion of the tracked object and stationary world, the visual system needs to integrate ambiguous local motion measurements (i.e., the aperture problem). Unlike the tracked object, the stationary world's global motion is entirely determined by the eye movement and thus can be approximately derived from motor commands sent to the eye (i.e., from an efference copy). Because retinal motion opposite to the eye movement is dominant during pursuit, different motion integration mechanisms might be used for retinal motion in the same direction and opposite to pursuit. To investigate motion integration during pursuit, we tested direction discrimination of a brief change in global object motion. The global motion stimulus was a circular array of small static apertures within which one-dimensional gratings moved. We found increased coherence thresholds and a qualitatively different reflexive ocular tracking for global motion opposite to pursuit. Both effects suggest reduced sampling of motion opposite to pursuit, which results in an impaired ability to extract coherence in motion signals in the reafferent direction. We suggest that anisotropic motion integration is an adaptation to asymmetric retinal motion patterns experienced during pursuit eye movements. NEW & NOTEWORTHY This study provides a new understanding of how the visual system achieves coherent perception of an object's motion while the eyes themselves are moving. The visual system integrates local motion measurements to create a coherent percept of object motion. An analysis of perceptual judgments and reflexive eye movements to a brief change in an object's global motion confirms that the visual and oculomotor systems pick fewer samples to extract global motion opposite to the eye movement.

Project description:Smooth pursuit and motion perception have mainly been investigated with stimuli moving along linear trajectories. Here we studied the quality of pursuit movements to curved motion trajectories in human observers and examined whether the pursuit responses would be sensitive enough to discriminate various degrees of curvature. In a two-interval forced-choice task subjects pursued a Gaussian blob moving along a curved trajectory and then indicated in which interval the curve was flatter. We also measured discrimination thresholds for the same curvatures during fixation. Motion curvature had some specific effects on smooth pursuit properties: trajectories with larger amounts of curvature elicited lower open-loop acceleration, lower pursuit gain, and larger catch-up saccades compared with less curved trajectories. Initially, target motion curvatures were underestimated; however, ∼300 ms after pursuit onset pursuit responses closely matched the actual curved trajectory. We calculated perceptual thresholds for curvature discrimination, which were on the order of 1.5 degrees of visual angle (°) for a 7.9° curvature standard. Oculometric sensitivity to curvature discrimination based on the whole pursuit trajectory was quite similar to perceptual performance. Oculometric thresholds based on smaller time windows were higher. Thus smooth pursuit can quite accurately follow moving targets with curved trajectories, but temporal integration over longer periods is necessary to reach perceptual thresholds for curvature discrimination.NEW & NOTEWORTHY Even though motion trajectories in the real world are frequently curved, most studies of smooth pursuit and motion perception have investigated linear motion. We show that pursuit initially underestimates the curvature of target motion and is able to reproduce the target curvature ∼300 ms after pursuit onset. Temporal integration of target motion over longer periods is necessary for pursuit to reach the level of precision found in perceptual discrimination of curvature.

Dataset Information

Spatiotemporal Filter for Visual Motion Integration from Pursuit Eye Movements in Humans and Monkeys.

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