Figure 6

Diffusion model simulations with the relative starting point (\(\frac{{s_{z} }}{a}\)) fixed across conditions. We simulated the predictions of the diffusion model by keeping \(\frac{{s_{z} }}{a}\) constant across conditions. The boundary \(a\) varied from 0 to 0.2 in steps of 0.01, the drift rate \(v\) was set to 0.15, the starting point of the accumulation \(z\) was fixed to halfway between the two boundaries, the non-decision time \(T_{er}\) was fixed to 0.27, and the non-decision time variability \(s_{t}\) was fixed to 0.1. The simulations produced inverted-U d′-RT curves (upper left panel) even though the empirical curves were linear. For each set of parameters \(\left( {\eta ,\frac{{s_{z} }}{a}} \right)\), the points with higher RT correspond to higher values of the boundary \(a\). The simulations also produced either monotonically increasing or monotonically decreasing curves for the RT difference between error and correct trials (upper right panel), S-shaped \(\frac{{SD\left( {RT} \right)}}{{mean\left( {RT} \right)}}\) curves (lower left panel), and inverted-U shapes for the skewness of the RT distributions (lower right panel). In all of these cases, the qualitative shapes differed from what was observed in the empirical data (Fig. 3).