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Daniel Baker, Bruno Richard; A dynamic double pass technique for characterizing internal noise during binocular rivalry. Journal of Vision 2016;16(12):1324. doi: 10.1167/16.12.1324.
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© ARVO (1962-2015); The Authors (2016-present)
The perceptual alternations characteristic of binocular rivalry have a stochastic component that is a consequence of internal noise in the visual system. Yet little is known about the properties of this noise, as we lack methods to probe it directly. We used a standard binocular rivalry monitoring paradigm, in which observers viewed a pair of dichoptic orthogonal gratings (2c/deg, 50% contrast) for trials of one minute duration, and reported their percepts continuously using a mouse. We then injected dynamic noise into the stimulus by adding independent sequences of temporally bandpass-filtered noise to the contrasts of the two gratings. The peak temporal frequency (0.0625 to 1Hz) and standard deviation (1 to 16%) of the noise were combined factorially giving 25 conditions. Dominance durations and autocorrelation functions calculated across five repetitions per observer showed effects of both noise variance and frequency, indicating that alternations were driven by high amplitude external noise at all temporal scales. We then repeated the experiment using the same samples of noise for each condition, and calculated the consistency of the observer's responses across the two passes, in a novel dynamic variant of the 'double pass' method (Burgess & Colborne, 1988, J Opt Soc Am A, 5: 617-627). Consistency increased from baseline (50%) at noise standard deviations of 4% and above, providing an approximate estimate of the amplitude of internal noise. Consistency scores showed bandpass tuning, with the highest consistency (around 70%) occurring at 0.125Hz, falling off at higher and lower frequencies. Using anticorrelated noise across the eyes (rather than uncorrelated noise) produced a slight increase in consistency to around 75%, providing an upper bound on the range of values. Cross-correlation between the noise streams and observer responses indicated a response latency of around 0.5-1s. We discuss our results in the context of computational models of the rivalry process.
Meeting abstract presented at VSS 2016
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