jsQuestPlus

jsQuestPlus implements the QUEST+ Bayesian adaptive procedure in JavaScript to estimate psychometric function parameters for online psychophysical experiments.

Key Features:

• Algorithm: Implements QUEST (Watson & Pelli, 1983) and QUEST+ (Watson, 2017) Bayesian adaptive methods to estimate psychometric function parameters such as sensory thresholds.
• Implementation: JavaScript implementation enabling execution of the QUEST+ algorithm within web environments.
• Platform compatibility: Integrates with jsPsych, PsychoPy/JS, and lab.js for deployment in online experimental paradigms.
• Benchmarking: Evaluated across 37 browser-computer configurations to assess performance and consistency.
• Performance metrics: Initialization mean time 461.08 ms (95% CI [328.29, 593.87]), per-trial stimulus-parameter computation <1 ms, and parameter update mean time 79.39 ms (95% CI [46.22, 112.55]).
• Accuracy: Preserves the estimation accuracy of the original QUEST+ method for psychometric parameters.

Scientific Applications:

• Online psychophysics: Estimation of sensory thresholds and psychometric function parameters in web-based experiments.
• Adaptive stimulus selection: Real-time selection of stimulus parameters using Bayesian adaptive procedures in experimental trials.
• Cross-platform validation: Assessment and comparison of adaptive procedure performance across different browser and hardware configurations.

Methodology:

Implements QUEST and QUEST+ Bayesian adaptive algorithms in JavaScript and was benchmarked across 37 browser–computer configurations measuring initialization time (mean 461.08 ms, 95% CI [328.29, 593.87]), per-trial computation (<1 ms), and parameter update time (mean 79.39 ms, 95% CI [46.22, 112.55]).