= 91.5%, and for different = 94.5%), but was only 70% correct overall in the high-interference condition (mean of the three serial positions for same = 60.8%, and different = 79.3%) as shown in Figure 21. Thus, repeating a small set of six items lowers three-item list-memory performance by a considerable 23 percent and explains why other investigators likely had trouble obtaining accurate list-memory performance from their monkeys (Devine & Jones, 1975; Eddy, 1973; Gaffan, 1977).
| Fig 21Repeated-item interference on a rhesus monkey's three-item list memory results with memory items selected from a six-item set (High PI) compared to a low interference condition with items selected from a 211-item set (Low PI). Serial position 1 was the (more ...) |
Discovering the locus of this repeated-item interference effect was of particular interest to us. Consider a monkey performing the three-item list-memory task of Figure 21. After just a few trials, all six items will have been seen, and by the middle of the session all items will have been seen many times. When this subject is then presented with a test on a different trial (where the test does not match any item from the current trial), the subject will be confused as to whether this item was in the current list or some previous list. Confusion and conflict will be greater the more recently the interfering item was seen (e.g., the preceding trial).
We conducted a test of this locus of the proactive interference effect by embedding potentially interfering items within previous lists and testing them later on different trials (Wright, Urcuioli, & Sands, 1986). Figure 22 shows that when an interfering item was in the immediately preceding list, performance was comparatively poor—64% correct. This is nearly a 30% drop in accuracy from baseline (NO-PI) performance. As the trial separation increased, performance improved showing the graded effect of this interference. At the largest separation that was tested (six lists or as many as 60 items), performance had improved to 83% correct, but was still 10% less than the 93% correct baseline (i.e., trial-unique) performance. This last result shows the far-reaching effects of this repeated-item interference. The role that repeated-item interference might play in determining how memory works will be discussed in the next section.
| Fig 22Interference tests of a rhesus monkey's 10-item list memory performance as a function of the number of items occurring between a test item on a different trial and its previous presentation. The NO-PI condition is a no-interference condition. The dotted (more ...) |
Familiarity, Identity, and Episodic Memory
Related to the far-reaching effects of proactive interference shown in Figure 22 is the issue of whether this monkey was making “true” identity judgments or simply responding on the basis of familiarity. The issue of familiarity was brought into sharpest focus for researchers working in animal learning and cognition by David Premack more than 25 years ago when he questioned whether or not pigeons had the cognitive capability to learn abstract concepts (Premack, 1978, 1983). This same issue of familiarity is now at the forefront of memory research with animals and humans. Regarding single-item memory performance (i.e., delayed same/different performance) Premack (1983) said: “The animal simply reacts to whether or not it has experienced the item before. Old/new or familiar/unfamiliar would be better tags for this case than same/different” (p. 354). Implicit in Premack's claim was that familiarity—recognition of an item without regard to whether it was on the current trial—might differ from other processes that would explicitly limit such judgments to items of the current trial. This issue of familiarity comes up in virtually all abstract-concept learning and memory experiments, particularly with animals. One cannot avoid the issue of familiarity by using delayed nonmatching to sample (DNMS) instead of DMTS as some researchers have contended (e.g., Gaffan & Weiskrantz, 1980; Mishkin & Delacour, 1975). In DNMS, the subject could use familiarity to identify the matching stimulus (the incorrect choice) and then switch and choose the other (unfamiliar) stimulus. Likewise, using simultaneous instead of delayed same/different (S/D) does not rule out the use of familiarity as Premack (1983) would have us believe. In simultaneous S/D, subjects could first look at one stimulus (as they often do) and then look at the other stimulus, thus transforming the simultaneous S/D task into a delayed S/D task.Familiarity has been a hot topic of research in human memory for at least as long as it has been in animal memory (e.g., Atkinson & Juola, 1974; Mandler, 1980). Indeed, human memory researchers have led the way by specifying the alternatives to familiarity (e.g., explicit memory, recollection, controlled memory, and episodic memory), unlike counterparts in animal memory. It is one thing to say that animals of some study may be just responding on the basis of familiarity (e.g., Mackintosh, 2000; Premack, 1983), but it is quite a different matter to specify what they should be doing and how to test those possibilities. Before considering alternatives to familiarity that animals might employ, it may be worthwhile considering how human-memory researchers dissociate familiarity from other types of memory. In one procedure, participants are either instructed to identify items experienced in a particular context (e.g., seen as an anagram) or in any context (i.e., items read, heard, or seen as an anagram). Measures of recollection and familiarity are computed from algebraic equations representing these different memory tests (e.g., Jacoby, 1991, 1998; Yonelinas, 2002). In another procedure, participants are asked if they actually did remember (episodic memory) an item, or just know (familiarity) that some item had been experienced (e.g., Gardiner & Richardson-Klavehn, 2000; Tulving, 1972, 1985, 2002). It is unclear (at least to me) how either of these procedures might be adapted to testing animal memory.
Nevertheless, recent experiments demonstrate that some animals have memory considerably more precise than simple familiarity memory. The most well known are the scrub-jay caching experiments by Clayton and her colleagues (e.g., Clayton, Bussey, & Dickinson, 2003; Clayton & Dickinson, 1998). Scrub jays are trained to cache perishable wax worms and non-perishable peanuts in separate and distinctive halves of two distinctive sand-filled ice-cube trays (2 X 7 arrays). When the jays recovered their caches after a short delay of only 4 hr, they recovered the more desirable wax worms first. After much longer delays of 124 hr, jays first recovered peanuts if they had previously learned that wax worms deteriorated in this amount of time. Reversal of their earlier preference for wax worms means that they remembered “what” (peanuts vs. wax worms), “when” (4 vs. 124 hr), and “where” (which tray side) the foods were stored. Other experiments by Clayton and colleagues showed that manipulating experience for the time of worm deterioration or degrading worm preference (satiation and taste aversion) between caching and recovery altered recovery preferences. These latter experiments demonstrated that the birds' recollective/declarative memory was flexible and not in Tulving's words “…a hard-wired connection between fixed behaviour prompted by fixed knowledge…” (2002, p. 283).
Other experiments with rats have shown that this mammal species, like scrub jays, can remember things that cannot be explained by familiarity alone. Rats were trained in a radial-arm maze task where they obtained a preferred chocolate reinforcement in one location and nonpreferred pellets in some of the other locations (Babb & Crystal, 2006). The chocolate reinforcer was replenished at its original location only on long-delay tests, not on short-delay tests. Pellets were never replenished at their original locations during training but were found during both short- and long-delay tests at the original unbaited locations. At long-delay tests, but not short-delay tests, the rats first visited the location of the preferred chocolate, demonstrating that this memory was unique for the particular reinforcer, chocolate, at a particular place, and at a particular time. Other tests by these researchers showed that the rat's memory was flexible by depreciating chocolate, and that time of day was not instrumental in revisiting the chocolate location. In yet other experiments, rats were trained to discriminate sand-filled cups containing distinctive odors (Fortin, Wright, & Eichenbaum, 2004). The receiver-operating-characteristic curves (ROCs) had asymmetrical and curvilinear components like those of humans (Yonelinas, 1997), suggesting the existence of both recollection and familiarity. Following selective damage to the hippocampus, the rats' ROC curves became symmetrically curvilinear suggesting that the hippocampus specifically mediates recollection (for a review, see Eichenbaum & Fortin, 2005).
Despite these clever advances in animal memory research, there is little danger that these animals will anytime soon be anointed as having episodic memory. Critics can always claim (as some do) that such behavior might be mediated by simple S–R associative conditioning, “They may just ‘know’ what kind of food is where, and what state it is in—fresh or rotten—without knowing how or why they know it” (Tulving, 2001, p.1512).
A New Approach to Testing Familiarity and Recollection—Interference
Notwithstanding the clever experiments previously mentioned, there is little evidence as to the particular memory processes that animals use in most laboratory memory tasks. One could point to pigeons learning a continuous-matching task (e.g., respond if it's old, not if it's new) which has aspects akin to familiarity (Macphail & Reilly, 1989; Todd & Mackintosh, 1990). But this demonstration does not prove that familiarity was the basis of this performance or what subjects might be doing in S/D and list-memory tasks. What are needed are experiments that manipulate the effectiveness of familiarity in performing a particular task and an objective assessment of how subjects use familiarity.We have begun exploring the possibility of using repeated-item interference and the interference function (e.g., Figure 22) to determine the degree to which subjects rely on familiarity and under what conditions they might employ other memory processes. (See also Cowan, Johnson, & Saults, 2005, for the use of repeated-item interference to determine human working-memory capacity.) Consider an interference function like the one shown in Figure 22 where a subject was trained with trial-unique items. If such a subject was completely indiscriminate with regard to how far back in time he would accept a stimulus as a match (i.e., any degree of familiarity would suffice), then the PI function should be relatively flat (e.g., 64% correct, like the interference on the immediately preceding trial in Figure 22) extending back across many previous trials, possibly even the whole session. Such a case could conceivably occur, because the rule “have I seen this item before in this session” would work just as well as “was this test item in the list of the current trial.” One can think of such a situation as a case of a very lax familiarity criterion. Of course, a history of having to make memory judgments under repeated-item interference (e.g. Figure 21) would likely moderate any lax familiarity criterion and produce a more graded performance, perhaps not unlike that seen in Figure 22 (see Wright, 2006, Figure 9.5, for predicted effects on the PI function with familiarity-criterion changes.) If the interference function shown in Figure 22 was due to a moderate familiarity criterion, then consider what effect making the task more difficult would likely have on the interference function. In the case of longer retention intervals, overall accuracy might suffer because when a test item matched a list item, the list item would be less familiar because it would be further in the past. Subjects could, in theory, reduce their familiarity criterion. But this would only be effective if repetitions (and interference) were minimal. Figure 23 shows the effect of varying the delay on a monkey's PI function. Tests with interfering items placed in prior trials—one to four trials prior—interfered more at the 20-s delay than at the 1-s delay. This performance difference disappears at greater separations (8 and 16 trial separations) showing that memory is not just universally affected or that any interference disrupts memory performance.
| Fig 23Interference tests of a rhesus monkey's single-item memory performance under separate tests with 1-s or 20-s retention delays as a function of the number of items occurring between a test item on a different trial and its previous presentation. The NO-PI (more ...) |
Another way to make the task more difficult would be to increase item repetitions and interference in the memory task generally. In this case, subjects would tend to respond same more often because all the items would be more familiar. But unlike the delay case with unique items, no adjustment of a familiarity criterion would be able to restore former accuracy levels (in signal detection theory terms there would be a change in discriminability, e.g., d', and raising the familiarity criterion would help performance on different trials but would be offset by more errors on same trials).
But there is a way these subjects might be able to restore their former accuracy in this memory task: They could change their memory strategy from a familiarity memory process to a more recollective memory process, or some combination of the two (cf. Wixted, 2007; Wixted & Stretch, 2004). Such a change in how they performed the memory task would mean that they might be able to recollect what memory items were in the current trial as opposed to memory items of past trials. Said otherwise, this is a context conditioning issue, where the context in question is the current trial. In the parlance of episodic memory, there would be a premium on the “when” component.
This discussion of how repeated-item interference and delay should affect bias and discriminability provides us with a framework for testing these possible changes using the function for repeated-item PI (e.g., the functions of Figures 22 and 23). In some of our memory studies we have found that monkeys slowly improve their performance under high repeated-item interference. Such changes would be expected to occur slowly if subjects were learning a different and more recollective memory process. In one case, a highly trained monkey was switched from a low-interference condition (432-stimulus set) to a high-interference condition (eight-stimulus set). This monkey's long-delay (20 s and 30 s) performance gradually improved over 2000 training trials. In addition to these indications from our work, one can see similar indications in others' single-item memory research. In a study with one monkey, there was a gradual rise and improvement in the delay function over 30,000 DMTS training trials under high-interference (small stimulus set) conditions (D'Amato, 1973). In another study, pigeons' memory performance improved over 15,000 DMTS training trials under high-interference (small stimulus set) conditions (Grant, 1975, 1976; Roberts, 1998). Although somewhat indirect, this evidence indicates that animals probably have the ability to adopt strategies that combat the effects of repeated-item interference. If the type of memory processing that is employed can change according to the changing circumstances, then such changes should have some direct similarities to the controlled and recollection processes of the human dissociation procedures.
Conclusions and Directions The four species tested in a four-item visual list-memory task showed similar dynamic changes in their primacy and recency effects as the retention delay was increased. This finding showed qualitative similarity in visual-memory processing across species with differing evolutionary histories and neural architectures. There were, however, quantitative differences across species in the time courses by which the primacy and recency effects changed with retention delay. These similarities and differences in memory were made apparent by using short memory lists and investigating list memory over a substantial range of the effective retention delay. If longer lists (e.g., 10 items) had been used, then the changes at short-retention delays (increasing primacy effect with delay) would have already occurred while the longer lists were still being presented, and the short-delay changes would have been missed. If only one retention delay had been tested, then the particular stage of the dynamic-evolving SPF would likely have been different for different species. In that case, the conclusion might have been that these different species had qualitatively different visual memory. One future direction of our work is to explore the possibility that the effects of proactive interference from previously seen items (on later different-trial test performance) might reveal the type of memory processing (familiarity, recollection) used by our animal subjects. Evidence for a change from familiarity to recollection would depend upon showing that these subjects can improve their memory performance in the face of high repeated-item interference. Experiments on the rhesus monkey's auditory memory showed that inhibition among to-be-remembered items of individual lists was instrumental in determining the shape of the SPF, and changes in inhibition with retention delay (e.g., from proactive to retroactive inhibition) changed the shape of the auditory SPF. Five experiments showed that at short retention delays, proactive inhibition among the items of auditory memory lists caused retrieval failure of the last list items. Release from this proactive inhibition caused an absolute increase in recency memory and the resulting retroactive inhibition caused retrieval failure of the first items of the list. No other explanation seems to fare as well for these auditory SPF changes. Another future direction of our work is to explore the possibility that inhibition among visual list items determines the shape of the visual SPF. If so, then we would expect to find that retroactive inhibition would dominate at short delays and give way to proactive inhibition as the retention delay increased. Our hope is that these patterns of SPF changes across retention delay for animal visual and auditory memory will provide a promising target for human as well as animal memory theories dealing with serial order and serial position effects. |
Acknowledgments This research was supported by NIH grants RO1MH-072616, RO1MH-061798, and RO1DA-10715. I thank Jeff Katz, Len Green, Howard Eichenbaum, John Wixted, Margaret A. McDevitt, and Michael E. Young for their thoughtful comments on earlier drafts of this manuscript. Reprints may be obtained from the author, Department of Neurobiology and Anatomy, University of Texas Medical School at Houston, P.O. Box 20708, Houston, Texas, 77225 or by email: anthony.a.wrightuth.tmc.edu. |
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