Signal Detection Theoretic Estimates of the Murine Absolute Visual Threshold Are Independent of Decision Bias.

Abstract

Decision bias influences estimates of the absolute visual threshold. However, most psychophysical estimates of the murine absolute visual threshold have not taken bias into account. Here we developed a one-alternative forced choice (1AFC) assay to assess the decision bias of mice at the absolute visual threshold via the theory of signal detection and compared our approach with the more conventional high-threshold theoretic approach. In the 1AFC assay, mice of both sexes were trained to signal whether they detected a flash stimulus. We directly measured both hit and false alarm rates, which were used to estimate d' Using the theory of signal detection, we obtained absolute thresholds by interpolating the intensity where d' = 1 from d'-psychometric functions. This gave bias-independent estimates of the absolute visual threshold which ranged over sixfold, averaging ∼1 R* in 1,000 rods (n = 7 mice). To obtain high-threshold theoretic estimates of the absolute visual threshold from the same mice, we estimated threshold intensities from the frequency of seeing curves, corrected for guessing. This gave us thresholds that were strongly correlated with decision bias, ranging over 13-fold and averaged ∼1 R* in 2,500 rods. We conclude that the theory of signal detection uses false alarms to overcome decision bias and narrow the range of threshold estimates in mice, providing a powerful tool for understanding detection behavior near absolute visual threshold.