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Jingyang Zhou, Silvia Choi, Jonathan Winawer; Temporal windows in psychophysical discrimination and in neural responses in human visual cortex. Journal of Vision 2017;17(10):191. doi: 10.1167/17.10.191.
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© ARVO (1962-2015); The Authors (2016-present)
Previously at VSS (Zhou et al., 2016, 56.4040), we presented a model of temporal responses to briefly viewed stimuli measured with fMRI and intracranial electrodes. We showed that the duration over which responses to visual stimuli interact, a temporal window, increases along the visual hierarchy. Here, we tested a behavioral correlate of the different temporal window lengths with several psychophysical tasks designed such that performance was expected to be limited by different stages of cortical processing. We adopted a psychophysics paradigm similar to Burr and Santoro 2001, (doi:10.1016/S0042-6989(01)00072-4), in which we measured discrimination sensitivity as a function of exposure duration, defining the temporal window for a given task as the duration at which sensitivity saturated (the inflection point in the sensitivity versus duration plots). The first two tasks were adapted from Burr and Santoro, and the third was novel: (1) contrast thresholds for dot motion direction judgments (left or right; 100% coherence); (2) coherence thresholds for dot motion direction judgments (left or right; high contrast); (3) contrast thresholds for judgments of facial emotional expression (happy or sad). Task 1 was expected to isolate a first stage motion mechanism that is spatially local, represented in early visual areas (V1), with short temporal windows. Task 2 was expected to be limited by a second stage motion mechanism which integrates motion direction over large regions (MT or MST), with longer temporal windows. Task 3 was expected to be limited by a late stage object recognition mechanism, with long temporal windows. The results were in accord with these predictions, with short temporal windows for Task 1 (~300 ms) and long windows for Tasks 2 and 3 (~1000 ms; ~1700 ms). Future work will test explicit linking models that predict the psychophysical window length from the neural models.
Meeting abstract presented at VSS 2017
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