Recognition memory and the medial temporal lobe: a new perspective

Abstract

Recognition memory is widely viewed as consisting of two components, recollection and familiarity, which have been proposed to be dependent on the hippocampus and the adjacent perirhinal cortex, respectively. Here, we propose an alternative perspective: we suggest that the methods traditionally used to separate recollection from familiarity instead separate strong memories from weak memories. A review of work with humans, monkeys and rodents finds evidence for familiarity signals (as well as recollection signals) in the hippocampus and recollection signals (as well as familiarity signals) in the perirhinal cortex. We also indicate ways in which the functions of the medial temporal lobe structures are different, and suggest that these structures work together in a cooperative and complementary way.

Figure 1. Signal-detection theory and the receiver operating characteristic

aThe signal-detection representation of a strong memory condition. The targets (old items) and foils (new items) in a recognition memory test are presumed to have varying degrees of memory strength (the subjective certainty that an item was or was not previously presented), and the mean and variance of the target distribution are greater than those of the foil distribution. A test item that generates a memory strength that exceeds a criterion value (indicated by the vertical line labelled c) is declared to be ‘old’. Otherwise, the test item is declared to be ‘new’. Confidence ratings (indicated by vertical dashed lines) of one to six range from ‘sure new’ to ‘sure old’. Items with memory strength to the left of the left-most vertical line are given ‘high confidence new’ responses. Items with memory strength to the right of the right-most vertical line are given ‘high confidence old’ responses. The right-hand panel shows a receiver operating characteristic (ROC) curve constructed from a subject’s confidence ratings. Five pairs of hit and false-alarm rates are computed from the six-point confidence rating scale. The left-most point represents the hit and false-alarm rates for targets and foils that receive a rating of 6. The second point represents the proportion of targets and foils that receive a rating of either 5 or 6, and so on. As is almost always the case in strong memory conditions, the resulting ROC curve in this example is asymmetrical. b. The signal-detection representation of a weak memory condition, in which the means and variances of the target and foil distributions are more similar and the ROC curve is more symmetrical.

Figure 2. High threshold/signal-detection theory and the receiver operating characteristic

aThe high threshold/signal-detection representation of a strong memory condition that involves both recollection and familiarity. Recollection occurs with some discrete probability (R; in this example, R = 0.5). When a test item generates recollection, a ‘high confidence old’ decision (which is equivalent to a confidence rating of six on a six-point scale) is made. When a test item fails to generate recollection (a situation that occurs with probability equal to 1 − R), the decision is based on familiarity. Decisions based on familiarity are characterized by a signal-detection model in which the targets (the old items) and foils (the new items) are presumed to have different average levels of familiarity but equivalent variances. A test item that generates a familiarity value exceeding a criterion value (indicated by the solid vertical line labelled c) is declared to be ‘old’. Otherwise, the test item is declared to be ‘new’. Thus, whereas most confidence ratings of six are based on recollection in this example (the 50% of the targets that are recollected receive this rating), a few additional ratings of six are based on familiarity. The right-hand panel shows the predicted asymmetrical ROC curve, which is similar to the asymmetrical ROC curve predicted by the traditional signal-detection model when memory is strong (FIG. 1a). b. The high threshold/signal-detection representation of a condition in which recollection is not involved (that is, in which R = 0) but familiarity can be used to discriminate targets and foils. The right-hand panel shows the predicted symmetrical ROC curve, which is similar to the symmetrical ROC curve predicted by the traditional signal-detection model when memory is weak (FIG. 1b). Although the high-threshold/signal-detection model fits ROC data reasonably well, recent findings favour the traditional signal-detection model–.

Figure 3. Roc data as a function of memory strength

In the study depicted, young adults (in groups of 19–24) studied 50-item word lists and then took a recognition-memory test involving the 50 old words and 50 new words after one of five retention intervals. The ROC curve was asymmetrical after the shortest retention interval (1 hour) and became more symmetrical as the interval grew and performance decreased (from 83% correct at 1 hour to 53% correct at 8 weeks). Performance was significantly above chance after all retention intervals. These findings differ from a previous study in rats which suggested that the ROC curve might be linear after a relatively long retention interval (75 minutes). The ROC data illustrated here are better fit by a curvilinear function based on signal-detection theory. Figure reproduced, with permission, from REF. © (2006) Elsevier Science.

Figure 4. The signal-detection interpretation of remember–know judgments

aA strong memory condition. ‘Remember’ judgments are made for items that exceed a high memory-strength criterion (labelled R), whereas ‘know’ judgments are made for items that exceed a lower criterion (labelled K) but not the high criterion. Items that fall below the K criterion are judged new. The ‘remember’ hit rate is the proportion of the target distribution that exceeds the R criterion (representing strong memories), and the ‘know’ hit rate is the proportion of the target distribution that falls between the K and R criteria (representing weak memories). b. In a weaker memory condition (as might occur, for example, after less extensive training), both criteria shift to the left, with the K criterion remaining approximately midway between the means of the target and foil distributions (its typical location for an unbiased subject). As a result, the ‘remember’ hit rate decreases, and the ‘remember’ false-alarm rate increases. This illustration explains why memory-impaired patients with hippocampal lesions often have a high ‘remember’ false-alarm rate compared with controls. In contrast to the ‘remember’ hit rate, the ‘know’ hit rate can actually increase in a weak memory condition, as illustrated in this example. If estimates of recollection and familiarity were derived from data like these (as they often are), such estimates would suggest that recollection is greatly reduced in the weak memory condition whereas familiarity is relatively unaffected. However, a simpler explanation of data like these is that memory is weaker overall.

Figure 5. Characteristic nonlinear relationships between fMri activity and memory strength

aIn the hippocampus, the relationship between functional MRI (fMRI) activity and memory strength at encoding is such that there is often a relatively steep increase in activity at the high end of the memory-strength scale (with high strength indicated by ‘remember’ responses or by hits with correct source information),,. Thus, the slope of the fMRI response is steeper when memory is strong than when it is weak. We suggest that this relationship reflects nonlinear properties of the measurement scale that arise for reasons unrelated to the distinction between recollection and familiarity. The same relationship has been observed even for purely recollection-based tasks. b. In the perirhinal cortex, the relationship between fMRI activity and memory strength at encoding is such that there is often a relatively steep increase in activity when memories are weak, but a more shallow increase when memories are stronger–. This nonlinear pattern has also been observed for purely recollection-based tasks. c. In the hippocampus, the relationship between fMRI activity and memory strength at retrieval is generally the same as is observed at encoding,,. d. In the perirhinal cortex, the relationship between fMRI activity and memory strength at retrieval is such that there is often a decrease in activity as memory strength increases,,. This pattern holds true for item-based memory tasks and may be indicative of novelty detection. The same pattern has also been observed in the anterior hippocampus (not shown). Lastly, unlike item-based memory tasks, the relationship between fMRI activity and memory strength in perirhinal cortex tends to be positively sloped for recollection-based associative memory tasks (not shown),.