Most decisions require information gathering from a stimulus presented with different gaps. However, the neural mechanism underlying this integration is ambiguous. Recently, it has been claimed that humans can optimally integrate the information of two discrete pulses independent of the temporal gap between them. Interestingly, subjects' performance on such a task, with two discrete pulses, is superior to what a perfect accumulator can predict. Although numerous neuronal and descriptive models have been proposed to explain the mechanism of perceptual decision-making, none can explain human behavior on this two-pulse task. In order to investigate the mechanism of decision-making on the noted tasks, a set of modified drift-diffusion models based on different hypotheses were used. Model comparisons clarified that, in a sequence of information arriving at different times, the accumulated information of earlier evidence affects the process of information accumulation of later evidence. It was shown that the rate of information extraction depends on whether the pulse is the first or the second one. Moreover, our findings suggest that a drift diffusion model with a dynamic drift rate can also explain the stronger effect of the second pulse on decisions as shown by Kiani et al. (Journal of Neuroscience, 33 (42), 16483-16489, 2013).
Keywords: Accumulation to bound model; Accuracy; Discrete pulses; Perceptual decision-making; Random-dot motion.