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Using reaction times and binary responses to estimate psychophysical performance: an information theoretic analysis.

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This study integrates reaction times (RTs) into psychophysical models, revealing that RTs offer valuable Shannon information. Integrating RTs with binary responses provides robust estimates of sensory information processing in humans.

Keywords:
Shannon informationchronometric functiondiffusion modelmutual informationpoint of subjective equalitypsychometric functionreaction timethreshold

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Area of Science:

  • Psychophysics
  • Cognitive Neuroscience
  • Information Theory

Background:

  • Psychometric functions describe accuracy, while chronometric functions describe reaction times (RTs) in response to stimuli.
  • Traditionally, RTs are overlooked in psychophysical parameter estimation, despite potentially containing significant Shannon information.
  • Existing diffusion models do not fully incorporate RT data or lapse rates.

Purpose of the Study:

  • To extend the proportional-rate diffusion model (PRD) to incorporate RTs and other parameters.
  • To estimate psychophysical parameters using both binary responses and RTs.
  • To quantify the Shannon information gained by observers about stimulus strength.

Main Methods:

  • Extended the PRD model (EPRD) to fit RTs to an inverse Gaussian distribution and include lapse rates and point-of-subjective-equality (PSE) parameters.
  • Utilized a two-alternative forced choice (2AFC) design.
  • Employed maximum likelihood estimation to fit binary responses and RT data separately and in combination to the EPRD model.

Main Results:

  • Parameter estimates from binary responses alone were comparable to those from RTs alone, supporting the diffusion model's validity.
  • The EPRD model successfully estimated mutual information between responses/RTs and stimulus strength.
  • Human observers gained an average of 2.68 to 3.55 bits/trial of Shannon information.

Conclusions:

  • RTs provide valuable information for psychophysical parameter estimation, complementing accuracy data.
  • The extended diffusion model offers a more comprehensive approach to understanding sensory information processing.
  • The study quantifies the information observers gain, introducing the 'Shannon increment' as a measure of detection capability.