Title: Interval Timing and Decision Making with an Opponent Poisson Diffusion Model
Speaker: Patrick Simen (Assistant Professor, Oberlin College)
Abstract: Diffusion models explain patterns of choice probabilities and response times in perceptual decision tasks. In these models, a random quantity representing “evidence” builds up over time until a boundary is reached, yielding a decision. Recently, my colleagues and I have applied diffusion models to a different task: interval timing. Despite major differences between these task types, response time distributions in both typically exhibit constant coefficients of variation (CVs) across conditions. To understand how diffusion could explain CV invariance, we analyzed diffusion processes that emerge from accumulating excitatory and inhibitory Poisson spikes. Assuming spike rates are proportional to evidence strength (in decision making) or clock speed (in timing) leads to CV invariance and conformance to Weber’s law under certain changes of task conditions, but not others. We tested these predictions in three sensory modalities. Most held up, suggesting that decision making and timing may derive from a common process of diffusion.