DOI: 10.5176/ 2251-1865_CBP13.20
Authors: Johan Hellman, Sverker Sikström
Abstract:
Signal detection theory (SDT) and the Dual Process SDT (Yonelinas, 1994) are currently the most influential accounts of item variability in recognition memory. However, neither provides a sufficient account of differences in the familiarity distributions. Instead, this phenomenon is accounted for by the idea of encoding variability (Wixted, 2007) or an additional retrieval process (Yonelinas, 2001). We present the Generalized Signal Detection Theory (the GSDT), in which the familiarity distribution are a sum of signals described by a sigmoidal non-linear activation function. The GSDT accounts for a higher variability in the old item distribution by emphasizing the non-linarites, but also for equal variability in the new and old item distributions by attenuating the non-linearites. The GSDT also extends the interpretation of the new to old item variability, indexed by the slope of the z-ROC.
Keywords: Recognition memory; Item variability; Receiver-operating Characteristics
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