The Timescale of Perceptual Evidence Integration Can Be Adapted to the Environment

Abstract

A key computation underlying perceptual decisions is the temporal integration of "evidence" in favor of different states of the world. Studies from psychology and neuroscience have shown that observers integrate multiple samples of noisy perceptual evidence over time toward a decision. An influential model posits perfect evidence integration (i.e., without forgetting), enabling optimal decisions based on stationary evidence. However, in real-life environments, the perceptual evidence typically changes continuously. We used a computational model to show that, under such conditions, performance can be improved by means of leaky (forgetful) integration, if the integration timescale is adapted toward the predominant signal duration. We then tested whether human observers employ such an adaptive integration process. Observers had to detect visual luminance "signals" of variable strength, duration, and onset latency, embedded within longer streams of noise. Different sessions entailed predominantly short or long signals. The rate of performance improvement as a function of signal duration indicated that observers indeed changed their integration timescale with the predominant signal duration, in accordance with the adaptive integration account. Our findings establish that leaky integration of perceptual evidence is flexible and that cognitive control mechanisms can exploit this flexibility for optimizing the decision process.

The urgency-gating model can explain the effects of early evidence

“…One possibility is that the filter time-constant is contextdependent (Ghose, 2006;Ossmy et al, 2013). While that is a viable possibility, we believe a simpler answer is that what changes depending on task-context is the mean rate at which the urgency signal grows over time (i.e., the steepness of its slope).…”

“…The specific setting of the time constant is difficult to estimate in behavioral experiments, although prior studies and our recent neural data suggest that in some conditions it can be as short as 100 ms (Ludwig et al, 2005;Ghose, 2006;. It could also be task dependent and adjustable (Ossmy et al, 2013).…”

Absolutely relative or relatively absolute: violations of value invariance in human decision making

“…Ample evidence from psychology and biology indicates that choices and their latencies are the result of a process that sequentially accumulates samples of noisy, momentary, evidence values towards an internal decision criterion (Marshall et al 2009;Meyer et al 1988;Ossmy et al 2013;Ratcliff and Rouder 1998;Ratcliff 1978;Teodorescu and Usher 2013;Usher and McClelland 2004). In this sequential sampling framework, a relative model is one that either accumulates relative momentary values (e.g., momentary evidence value differences) or, alternatively, accumulates absolute values but implements a relative stopping rule (e.g.…”

Decision-related pupil dilation reflects upcoming choice and individual bias

“…Many perceptual decisions are not transient events but evolve gradually over several hundreds of milliseconds, due to the slow accumulation of noisy sensory information (27)(28)(29)(30)(31)(32)(33). Further, perceptual decisions are, like economic decisions (34), prone to strong biases that are not due to external asymmetries in the magnitude or probability of payoffs for certain choices.…”