Maximum likelihood estimation of perceptual differences in sorting tasks

Abstract

Psychophysical paradigms are foundational for quantifying perceptual discrimination. Yet, a persistent trade-off between assessment efficiency and accuracy limits their broad applicability. To address this, we introduce a novel evaluation model grounded in maximum likelihood estimation (MLE) for perceptual sorting tasks. This work details the model's formulation, validates its performance through simulation, and demonstrates its efficacy in a tactile angle-sorting experiment. Our findings reveal that the sorting paradigm, particularly with five stimuli across three trials, achieves an optimal balance of efficiency and robustness. This method provides a potentially useful and relatively efficient approach for assessing perceptual discriminability within the tactile experimental context, with preliminary indications of its applicability in both research and practical screening.