Temporal Dynamics Gap between Position Tracking and Attribute Tracking

Continuous tracking is a promising psychophysical paradigm to quickly estimate the temporal dynamics of the visuomotor system. It asks observers to mouse-track a randomly changing target spatial position (position tracking: PT) or attribute value (attribute tracking: AT). The impulse response can be computed from the cross-correlation in velocity between stimulus and response. To understand the visuomotor mechanisms underlying continuous tracking, we examined the effects of task (PT or AT) and stimulus. We used eleven stimuli: a Gaussian blob changing either in position (for PT) or in luminance (for AT); a color-modulated concentric Gabor (red-green or blue-yellow) changing in position or chromatic contrast; a luminance-modulated concentric Gabor (one of eight spatial frequencies) changing in position or luminance contrast. The results show that stimulus parameters affected the estimated impulse response. PT and AT responses were weakly correlated with regard to the effects of stimulus in either peak latency or impulse response width, which suggests a partial commonality of the underlying mechanism. However, the AT response was approximately 2.6 times slower in latency and 5.0 times broader in width than the PT response. Where does this difference come from? It cannot be ascribed to rapid automatic vision-hand mapping in PT since even when compared with an anti-PT condition where observers had to move the mouse in the opposite direction of the visual stimulus movement, the AT response was 1.7 times slower and 2.3 times broader. Another task difference is that PT does not need to evaluate the attribute value, but AT does. To test this factor, we measured the simple reaction time to the detection of a single stimulus change and found it agreed well with PT’s peak latency. The results suggest that slower responses for AT than for PT can be ascribed to the extra process to access the attribute content.

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Publication Details

Journal
Journal of Vision
Published
2024-09-15
DOI
https://doi.org/10.1167/jov.24.10.465
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

Temporal Dynamics Gap between Position Tracking and Attribute Tracking

Yen‐Ju Chen, Zitang Sun, Shin’ya Nishida
33 links
Journal of Vision
Multi-Criteria Decision Making
article

Temporal Dynamics Gap between Position Tracking and Attribute Tracking

Yen‐Ju Chen, Zitang Sun, Shin’ya Nishida
article en

Abstract

Continuous tracking is a promising psychophysical paradigm to quickly estimate the temporal dynamics of the visuomotor system. It asks observers to mouse-track a randomly changing target spatial position (position tracking: PT) or attribute value (attribute tracking: AT). The impulse response can be computed from the cross-correlation in velocity between stimulus and response. To understand the visuomotor mechanisms underlying continuous tracking, we examined the effects of task (PT or AT) and stimulus. We used eleven stimuli: a Gaussian blob changing either in position (for PT) or in luminance (for AT); a color-modulated concentric Gabor (red-green or blue-yellow) changing in position or chromatic contrast; a luminance-modulated concentric Gabor (one of eight spatial frequencies) changing in position or luminance contrast. The results show that stimulus parameters affected the estimated impulse response. PT and AT responses were weakly correlated with regard to the effects of stimulus in either peak latency or impulse response width, which suggests a partial commonality of the underlying mechanism. However, the AT response was approximately 2.6 times slower in latency and 5.0 times broader in width than the PT response. Where does this difference come from? It cannot be ascribed to rapid automatic vision-hand mapping in PT since even when compared with an anti-PT condition where observers had to move the mouse in the opposite direction of the visual stimulus movement, the AT response was 1.7 times slower and 2.3 times broader. Another task difference is that PT does not need to evaluate the attribute value, but AT does. To test this factor, we measured the simple reaction time to the detection of a single stimulus change and found it agreed well with PT’s peak latency. The results suggest that slower responses for AT than for PT can be ascribed to the extra process to access the attribute content.

Journal of VisionVol. 24(10)
Kyoto University (JP), NTT (Japan) (JP), Kyoto College of Graduate Studies for Informatics (JP)
Openalex Percentile: Top 80%
Multi-Criteria Decision Making
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