Abstract
A number of studies on texture and ensemble perception have shown that humans can immediately estimate the average of spatially distributed visual information. The present study characterized mechanisms involved in estimating averages for information distributed over both space and time. Observers viewed a rapid sequence of texture patterns in which elements’ orientation were determined by dynamic Gaussian noise with variable spatial and temporal standard deviations (SDs). We found that discrimination thresholds increased beyond a certain spatial SD if temporal SD was small, but if temporal SD was large, thresholds remained nearly constant regardless of spatial SD. These data are at odds with predictions that threshold is uniquely determined by spatiotemporal SD. Moreover, a reverse correlation analysis revealed that observers judged the spatiotemporal average orientation largely depending on the spatial average orientation over the last few frames of the texture sequence – a recency effect widely observed in studies of perceptual decision making. Results are consistent with the notion that the visual system rapidly computes spatial ensembles and adaptively accumulates information over time to make a decision on spatiotemporal average. A simple computational model based on this notion successfully replicated observed data.
Highlights
A number of studies on texture and ensemble perception have shown that humans can immediately estimate the average of spatially distributed visual information
We found that if temporal standard deviations (SDs) is small, discrimination thresholds increase as a function of spatial SD as has often been reported in previous studies: Threshold-vs-Noise (TvN) function[13,37]
Results suggest that discrimination of spatiotemporal statistics is greatly influenced by spatial irregularity for temporally coherent streams but not for streams that fluctuate over time
Summary
A number of studies on texture and ensemble perception have shown that humans can immediately estimate the average of spatially distributed visual information. A vast psychophysical literature has suggested that the visual system is capable of rapidly estimating the characteristics of an ensemble of complex elements (e.g., objects, faces)[5,6,7,8] as well as discriminating textures defined by simple visual features such as form, color and motion[9,10,11,12,13,14,15,16] These studies offer clear evidence that the visual system automatically extracts a statistical representation of the spatial properties of the image. Typical results obtained in these tasks (e.g., skewed distribution of reaction time, tradeoff between speed and accuracy) can be accounted for by a perceptual decision mechanism that accumulates sensory evidence over time toward a decision bound[36] It remains unclear how such temporal integration interacts with the computation of spatial statistics. Our results raise the possibility that the visual system estimates spatiotemporal statistics of uncertain stimuli by rapidly computing spatial statistics and integrating them over time
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