Recognition errors suggest fast familiarity and slow recollection in rhesus monkeys

Abstract

One influential model of recognition posits two underlying memory processes: recollection, which is detailed but relatively slow, and familiarity, which is quick but lacks detail. Most of the evidence for this dual-process model in nonhumans has come from analyses of receiver operating characteristic (ROC) curves in rats, but whether ROC analyses can demonstrate dual processes has been repeatedly challenged. Here, we present independent converging evidence for the dual-process model from analyses of recognition errors made by rhesus monkeys. Recognition choices were made in three different ways depending on processing duration. Short-latency errors were disproportionately false alarms to familiar lures, suggesting control by familiarity. Medium-latency responses were less likely to be false alarms and were more accurate, suggesting onset of a recollective process that could correctly reject familiar lures. Long-latency responses were guesses. A response deadline increased false alarms, suggesting that limiting processing time weakened the contribution of recollection and strengthened the contribution of familiarity. Together, these findings suggest fast familiarity and slow recollection in monkeys, that monkeys use a "recollect to reject" strategy to countermand false familiarity, and that primate recognition performance is well-characterized by a dual-process model consisting of recollection and familiarity.

Figure 1.

False alarms and misses plotted as a function of response latency. Quick errors were disproportionately false alarms, whereas slow errors were more likely to be guesses. Errors are depicted for Experiment 1a (top row) and Experiment 1b (bottom row). The left two panels depict absolute false alarm rates (number of false alarms/number of nonmatch trials) as a function of response time in 100-msec bins. The middle two panels depict miss rates (number of misses/number of match trials) in the same way. Each dot represents all trials that fell into that bin from a single monkey; however, because not all monkeys made responses at all times, not all bins contain the same number of subjects. The right two panels depict errors and accuracies binned such that each bin contains 10% of each monkey’s trials. (Solid line with solid dots) False alarms; (dashed line with open dots) misses; (dotted line with open triangles) accuracy (d′). Error bars are ±1 SEM.

Figure 2.

Diagram of a match/nonmatch recognition test used in Experiment 2. Monkeys initiated trials by touching a green square in the bottom center of the screen, saw and touched a sample image presented in the center of the screen, waited during a memory delay, and then received either a match or a nonmatch test. Monkeys earned food by touching the test image if it matched the sample or by touching the nonmatch symbol if the test image did not match the sample. The test image and the nonmatch symbol appeared equally often in all four screen corners. Trials were separated by a 10-sec interval during which the screen was black.

Figure 3.

False alarms and misses as a function of response time. Quick errors were disproportionately false alarms, whereas slow errors were guesses. (Solid line with solid dots) False alarms; (dashed line with open dots) misses; (dotted line with open triangles) accuracy (d′). Error bars are ±1 SEM. Each bin contains 10% of each monkey’s trials.

Figure 4.

Error rates under normal and speeded responding. Speeding responding selectively increased false alarms. Mean miss and false alarm rates (±SEM) are depicted for both normal sessions and sessions in which responses were sped using a response deadline. (*) Statistically significant differences.