Fig. 3.

Signal detection methods. A: response classification table for a classic signal detection experiment. Each trial is either signal present or signal absent (rows of the table) and the subject can respond signal present or absent (columns of the table). Detectability is calculated using the hit and false alarm rates from this table (see Eq. 1). B: signal detection model. The 2 distributions represent the probability associated with different stimulus values given that signal is present (signal distribution) or absent (noise distribution). The model assumes that observers respond signal present when they observe a stimulus value greater than the criterion and signal absent otherwise. Note that the location of the criterion along the x-axis varies from observer to observer and even from condition to condition for the same observer.