Existing psychophysiological measures (fMRI, EEG) are impractical for a large-scale behavioral study due to their exor-bitant data acquisition cost. Psychological tests (Stroop task) are economical but are too coarse to inform dynamic interac-tions among perceptual, cognitive, and affective processes. By augmenting standard cognitive tests with choice-reachingmeasures, the complex interaction of motivation, action and cognition can be examined by analyzing the movement of thecomputer cursor pixel by pixel. Open source software and R library mousetrap help researchers to collect mouse-cursortrajectory data easily. With continued interest and innovation, the mouse-cursor trajectory method is likely to become astandard procedure for psychological tests, especially for the study investigating individual differences underlying cog-nitive, affective, and perceptual processing (Xiao & Yamauchi, 2014; Yamauchi et al., 2015; Yamauchi & Xiao 2017;Leontyev, Sun, Wolfe, & Yamauchi, 2018).

It is widely acknowledged that categories have many functions, but few studies have actually addressed the impact of these functions on the way categories are learned. For instance, many categorization experiments predominantly rely on classification-based incremental learning. The problem with this approach is that it implicitly assumes that the function of categorization is separable from the way that categories are learned. In this study, we examined the relation between learning and the subsequent use of categories by contrasting three types of category-learning methods — inference-based, classification-based, and a combination of these methods. The results of the experiment indicate that there is an intricate relationship between category-learning and subsequent use of the category. The results further suggest that different processing modes may have been adopted by subjects in the different learning conditions.