Abstract Perceptual threshold estimation stands as a fundamental variable manipulation in psychology and neuroscience, fine-tuning sensory input intensity to align perceptual precision across individuals. Current methods, such as constant stimuli and staircase procedures, inaccurately assume that perceptual thresholds are influenced solely by sensitivity, overlooking the role of response biases and consequently leading to unreliable estimates. The underlying reason is that classical methods traditionally focus on hit rates—the correct detection of stimuli—while neglecting false alarms, where participants incorrectly report a stimulus when none is present. According to signal detection theory, hit rates can arise from genuine sensitivity or a liberal response criterion, making it crucial to account for both measures. To overcome this confound, we developed bias-free versions of these methods by including target-absent trials to factor in decisional bias during threshold evaluation. Across 74 participants, we robustly demonstrated that widely used classical procedures overestimate perceptual thresholds due to uncontrolled interindividual variability in participant criterion. Conversely, the bias-free staircase procedure achieved reliable sensitivity thresholds, effectively mitigating the influence of decisional bias. We strongly advocate for the adoption of this straightforward, bias-free approach. Its effectiveness, simplicity, and quick execution make it highly feasible for widespread use in enhancing the reliability of threshold estimation and reducing variability in future scientific investigations across various fields.
Tarasi et al. (Tue,) studied this question.