Research Interests Prof. W. Schwarz

Part of my modeling efforts are in the area of diffusion models which offer useful and flexible formal representations to account for accuracy and latency in choice tasks. For example, I derived exact results, beyond Wald's standard approximation, on mean conditional first passage times [Schwarz (1990b)] and conditional first passage time variances [Schwarz (1991c)] for a class of continuous-step discrete-time random walk models. I also used diffusion models to account for the temporal dynamics of redundant signals [Schwarz (1989b), Schwarz (1994a), Schwarz (2006)], or numerical distance effects [Schwarz & Stein (1998), Schwarz & Ischebeck (2003)].

Another concept that I find useful and explored and applied in a number of papers is that of stochastic neural counting processes [Schwarz (1989d)], and especially that of temporal coincidences in such processes [Schwarz (1989c), Schwarz (1993c), Schwarz (2010)]. I also presented a model based on the concept that information is passed on by the various stages of the central nervous system in the manner of a stochastic cascade process [Schwarz (2003)]. The `"Ex-Wald'" model that I proposed assumes that reaction time can be represented as a convolution of a first passage time in a diffusion process and an independent exponential motor time [Schwarz (2001, 2002)]. Modeling work done jointly with Dirk Vorberg looked at information-processin interpretations of the psychometric concept of so-called Rasch-representable RT distributions [Vorberg & Schwarz (1990)], and also at criteria to identify oscillatory components (and to avoid artefacts) in human reaction times [Vorberg & Schwarz (1987, 1988)].