Confidence as a continuous state of evidence with dynamic competition

For a long time, choice and response time (choice-RT) have been the central behavioral measures used to explore the mechanism of choice. In addition to choice-RT, confidence has also been considered as a measure of behavioral judgment. Recently, many researchers have attempted to integrate those behavioral measures (choice, response time, and confidence) into the unified modeling framework (Poisson Race Model: Merkle and Van Zandt, 2006; RTCON: Ratcliff and Starns, 2009; 2DSD: Pleskac and Busemeyer, 2010). Here, we propose a way of modeling confidence with the leaky, competing, accumulator (LCA; Usher and McClelland, 2001). To do so, we rely on a simple solution to mapping the continuous states of evidence in the LCA with the relative balance of evidence hypothesis (Vickers, 1979). The competitive nature of the accumulation process in the LCA framework can produce continuous decision states, as an asymptotic accumulation and have different effects on accuracy, RT, and of course, confidence. In this study, we will investigate how the LCA can be accompanied by confidence and how the dynamic competitions between the accumulators with information leakage and lateral inhibition can affect confidence as a continuous state of the evidence. Simulation results show that the LCA can successfully account for all the main benchmarks of confidence modeling (Pleskac and Busemeyer, 2010).