The timed racing diffusion model of decision making
Many theories of decision making assume accumulation-to-threshold mechanisms. These thresholds almost always represent a criterion quantity on the 'evidence' or 'information' required to support a decision. We present a quantitative model that involves an additional accumulation-to-threshold mechanism where decisions can be triggered when a sufficient amount of time has been committed to the decision process. We show that a decision architecture composed of a competitive race with evidence-based and time-based thresholds provides a cohesive account of decision-making phenomena, including the speed-accuracy tradeoff. We show that it can also explain phenomena outside the domain of conventional evidence accumulation models, including simultaneously accounting for performance in decision and timing tasks. As a byproduct, the evidence-based vs time-based decision architecture eliminates the need for decision-to-decision variability parameters that are key elements of many accumulation-based theories of decision making.
I think this work is very interesting and the presentation was really well put together! In particular, it's very cool that the TRDM is able to produce fast and slow error patterns without trial-to-trial variability. I'm finding it a little hard to distinguish race against the timing diffusion process from collapsing bounds. It is mentioned...