Sequential Sampling Models for Cognitive and Perceptual Decision Making

! Abstract ! In the Berlin Cognitive Science meetings there was a brief session titled 'Sequential Sampling Models' (session 42) that attracted enormous interest: The room was packed and overflowed by a considerable amount, and both speakers and audience members felt there was much more to be presented and discussed than the few speakers and talks could allow. Quite a few people present agreed that this topic needed a more thorough treatment in the next Cognitive Science Society meetings in Quebec City. The ensuing discussions led to an agreement that the currency, importance, and breadth of the topic required more time than a regular symposium would make possible. Thus we propose an all day workshop on this topic to be held at the Quebec City meetings. ! The topic is actually quite broad, involving models that attempt to handle a variety of rich data measures (accuracy, response time, motor trajectories, eyemovements, EEG, fMRI, and more) in tasks ranging from low level psychophysics through perception, memory, and high level decision making. A full day workshop will not be sufficient to cover this territory but certainly can present important current developments that are implicit or explicit in all these domains. Examples of such issues include fixed versus changing response boundaries for diffusion models, contrasts between counter models and random walk models, contrasts between models that separate retrieval from a subsequent decision process, and models that integrate the two. These are just a small sample of a large set of issues that are important for the field. The actual coverage will be determined by the speakers and participants selected for the workshop. The co-organizers listed below will be speakers and participants. If the workshop is approved, the organizers will begin the process of selection at once. ! At this point in time we wish to point out only the increasing research effort aimed at the dynamics of cognition, with rapidly changing advances in data collection and analysis, and in modeling, making the topic one of intense current interest. The list of proposers/co-organizers below consists mainly of those behavioral decision making modelers involved in last year's session, but the workshop would be expanded to include more neural and sensory contributions, and contributions on dynamic planning particularly from the machine learning community (among other topics).