On the Automaticity of Familiarity in Short-term Recognition: A Test of the Dual-Process Assumption with the PRP Paradigm

Dual-process models of recognition often assume that one retrieval process, generating a familiarity signal, is automatic, whereas the other, recollection, is controlled. Four experiments are presented to test for automaticity of familiarity in a short-term recognition task. The experiments use the Psychological Refractory Period (PRP) paradigm to assess whether familiarity requires central processing capacity. Task 1 was an oral tone-classification task. Task 2 was a local-recognition task, in which participants decided whether a probe matched a particular item in the memory set, identified by its screen location. Intrusion probes, matching an item of the memory set in a different location, were slower and more difficult to reject than new probes. The size of this intrusion cost reflects the influence of familiarity on recognition. In all four experiments the size of the intrusion cost was additive with the stimulus-onset-asynchrony (SOA) of Task 1 and Task 2, demonstrating that extraction of familiarity requires central capacity. In addition, Experiment 2 showed additive effects of memory set size and serial position with SOA, confirming that recollection, too, requires central capacity. Experiments 3A and 3B compared a condition including new probes to one including only positive and intrusion probes; in the latter condition the familiarity signal was completely uninformative. Participants showed some ability to reduce the influence of familiarity when it was completely uninformative, but only when they were explicitly told to do so (Experiment 3B). To conclude, by one criterion familiarity is a controlled process: It demands central processing capacity. It might also be controlled by another criterion: People can intentionally reduce the influence of familiarity on recognition decision, but they fail to do so spontaneously even when it would be advantageous. All raw data are available on the Open Science Framework: osf.io/7pr72.