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Maximum likelihood estimation of perceptual differences in sorting tasks

Author

Listed:
  • Yulong Liu
  • Huazhi Li
  • Yali Xiang
  • Mengni Zhou
  • Qingqing Li
  • Hongtao Yu
  • Yoshimichi Ejima
  • Satoshi Takahashi
  • Jiajia Yang
  • Bin Bai
  • Xinian Yi
  • Jinglong Wu

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.

Suggested Citation

  • Yulong Liu & Huazhi Li & Yali Xiang & Mengni Zhou & Qingqing Li & Hongtao Yu & Yoshimichi Ejima & Satoshi Takahashi & Jiajia Yang & Bin Bai & Xinian Yi & Jinglong Wu, 2026. "Maximum likelihood estimation of perceptual differences in sorting tasks," PLOS ONE, Public Library of Science, vol. 21(5), pages 1-23, May.
  • Handle: RePEc:plo:pone00:0349396
    DOI: 10.1371/journal.pone.0349396
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