Fast and slow decisions exhibit distinct behavioral properties, such as the presence of decision bias in faster but not slower responses. This dichotomy is currently explained by assuming that distinct cognitive processes map to separate brain mechanisms. Here, we suggest an alternative single-process account based on the stochastic properties of decision processes. Our experimental results show perceptual biases in a variety of tasks (specifically: learned priors, tilt aftereffect, and tilt illusion) that are much reduced with increasing reaction time. To account for this, we consider a simple yet general explanation: prior and noisy decision-related evidence are integrated serially, with evidence and noise accumulating over time (as in the standard drift diffusion model). With time, owing to noise accumulation, the prior effect is predicted to diminish. This illustrates that a clear behavioral separationpresence vs. absence of bias-may reflect a simple stochastic mechanism.

The human visual system continuously adjusts to the current environment. To investigate these adjustments, biases in observers' perceptions owing to changes in the visual environment are measured (visual aftereffects). Typically, the stimuli used are synthetic and are composed of oriented patterns such as lines or gratings. These patterns are known to activate individual neurons in the visual cortex, but cover only a small subset of actual visual stimulations. To overcome this drawback, recent research has focused on synthetic patterns that mimic several aspects of natural stimulation. However, the aftereffects of natural stimulation per-se remain largely unexplored. Here, we interleaved presentations of unmodified natural image adaptors, selected according to criteria favoring content at a particular orientation, with presentations of targets that test a perceived orientation. This allowed us to measure the change in the perceived orientation, namely the tilt aftereffect (TAE), which resulted from repeated image presentations. Results show a close to standard TAE with adaptor durations around 500ms, which is reduced with longer presentations. Importantly, our method can be generalized to investigate other aftereffects by selecting images differently.

Fast and slow decisions exhibit distinct behavioral properties, such as the presence of decision bias in faster but not slower responses. This dichotomy is currently explained by assuming that distinct cognitive processes map to separate brain mechanisms. Here, we suggest an alternative, single-process account based on the stochastic properties of decision processes. Our experimental results show perceptual biases in a variety of tasks (specifically: learned priors, tilt illusion, and tilt aftereffect) that were much reduced with increasing reaction time. To account for this, we consider a simple yet general explanation: prior and noisy decision-related evidence are integrated serially, with evidence and noise accumulating over time (as in the standard drift diffusion model). With time, owing to noise accumulation, the prior effect is predicted to diminish. This illustrates that a clear behavioral separationpresence vs. absence of biasmay reflect a simple stochastic mechanism.Highlights  Perceptual and decisional biases are reduced in slower decisions. Simple mechanistic single-process account for slow bias-free decisions. Signal detection theory criterion is ~zero in decision times>median.

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Following exposure to an oriented stimulus, the perceived orientation is slightly shifted, a phenomenon termed the tilt aftereffect (TAE). This estimation bias, as well as other context-dependent biases, is speculated to reflect statistical mechanisms of inference that optimize visual processing. Importantly, although measured biases are extremely robust in the population, the magnitude of individual bias can be extremely variable. For example, measuring different individuals may result in TAE magnitudes that differ by a factor of 5. Such findings appear to challenge the accounts of bias in terms of learned statistics: is inference so different across individuals? Here, we found that a strong correlation exists between reaction time and TAE, with slower individuals having much less TAE. In the tilt illusion, the spatial analogue of the TAE, we found a similar, though weaker, correlation. These findings can be explained by a theory predicting that bias, caused by a change in the initial conditions of evidence accumulation (e.g., prior), decreases with decision time (Dekel & Sagi, 2019b). We contend that the context-dependence of visual processing is more homogeneous in the population than was previously thought, with the measured variability of perceptual bias explained, at least in part, by the flexibility of decision-making. Homogeneity in processing might reflect the similarity of the learned statistics. Highlights The tilt aftereffect (TAE) exhibits large individual differences. Reduced TAE magnitudes are found in slower individuals.  Reduced TAE in slower decisions can be explained by the reduced influence of prior. Therefore, individual variability can reflect decision making flexibility..