Implications for memory models

Strength and length effects have been investigated in memory research partly because they can be used to test assumptions of computational models (for reviews, see Clark & Gronlund, 1996; Diana et al., 2006). The first theoretical question we addressed in Experiments 1 to 4 was whether LLE and LSE are more dependent on recollection than familiarity. The results of Experiments 3 and 4 clearly show that both LSE and (to a lesser extent) LLE are modulated by the engagement of recollection at test in the form of recall-to-reject.

These results support dual-process models, such as CLS and SAC, because they incorporate mechanisms that can account for the observed dissociations. In CLS,

when studied items are unrelated, strengthening some traces in memory (or adding new traces to memory) has the effect of reducing the weights and thus the

activation of the other stored traces; the interference effect is more pronounced in the hippocampal model (recollection) than in the cortical model (familiarity) because in the former activation of lures is at floor whereas in the latter it is not and may consequently decrease with interference. In SAC, strengthening some items (or adding new items to memory) has the effect of reducing the activation of other items because there is less activation available to spread from context nodes, which are reactivated at test, to the episode nodes of the other studied items; the effect is more pronounced in episode nodes (recollection) because concept nodes (familiarity) have another source of activation, as they are also reinstated at test.8

The results of Experiments 3 and 4 do no support REM in that the model does not

a prioripredict an LSE (recall that REM was developed to account for null LSEs). The results presented here, however, are not strongly constraining on REM, since the model is flexible enough to fit positive, negative and null LSE results. The results, however, are constraining on BCDMEM: the model should be able to predict not only the presence of LLEs and LSEs but also their differential susceptibility to tests involving unrelated and highly similar lures. The effects observed here could not be easily attributed to confounds, such as contextual inertia, because the effects were also found in Experiment 4, where contextual inertia was presumably minimised in the long retention interval condition.

According to BCDMEM, only context noise (the number of contexts in which a word has been seen before) causes interference in recognition memory tasks, whereas item noise (the number and strength of words seen in the same context) should not matter. Because the present task is an item noise task, null LLE and LSE are predicted. The fact that we found positive effects challenges the context- noise assumption. However, that is not to say that context noise is irrelevant. Criss and Shiffrin (2004a, Exp. 2) showed that both the number of lists in which a target word appeared (context noise) and the number of words on the list that were similar to that target word (item noise) contributed to recognition. Thus, both item

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and context noises seem to underlie forgetting in recognition. Yet, the model, as presented in Dennis and Humphreys (2001), lacks an item-noise mechanism. Furthermore, it is unclear how BCDMEM could distinguish between targets (e.g.,

banana) and SP lures (e.g.,bananas) and therefore account for the present results, since it represents words as individual nodes regardless of plurality.

Experiments 2, 3 and 4 also addressed the question of whether or not retention interval affects interference. Although most models would predict that stronger items in memory would entail stronger interference effects (i.e., that interference should be higher with short retention intervals), to our knowledge no direct test of this prediction has been carried out for both length and strength manipulations. Results confirming this prediction would support most models and fill an empirical gap; results disconfirming this prediction would present a problem for most models. Although Experiments 2 and 3 together suggest that retention interval may in fact modulate the size of LLE and LSE, Experiment 4 failed to replicate the same pattern. At this point we refrain from making strong claims about the retention interval results because they were observed in a comparison between experiments. We address this shortcoming in Chapter 4.

Another theoretical issue investigated here involves the impact of manipulation strength on the sizes of the interference effects. Although, from an empirical point of view, it may seem obvious that stronger manipulations should produce larger interference effects, from a theoretical perspective, that may not be the case. Both CLS and SAC predict a monotonic increase in LSE with interference strength, as repeatedly studying one item degrades the traces of other items (CLS) or reduces the activation spread to episode nodes (SAC). The fact that the LSE did not increase with extra strength, however, does not support the models’ predictions. By contrast, REM predicts that LSE could disappear with more and more repetitions, since strong items would become so differentiated that they would contribute a negligible amount of activation at test, keeping sensitivity

unchanged.9The fact that LSEs were found in Experiments 3 and 4, regardless of manipulation strength, argues against REM’s prediction of total differentiation.

The results also showed an increase in LLE in the SSP discrimination when the list-length ratio rose from 2:1 to 3.5:1, supporting CLS and SAC’s predictions. Both CLS and SAC predict increases in LLE with longer lists, as adding new items degrades the traces of other items (CLS) or reduces the activation spread to the remaining episode nodes (SAC). REM, on the other hand, predicts little or no LLE whenluresare too similar totargets, regardless of manipulation strength, sinceSP lures generate matches so strong that in effect they behave liketargets; becausetargetodds decrease with list length, so doesSP lureodds, resulting in no difference, and no LLE in SSP discrimination (Criss & McClelland, 2006, Fig. 3).

Finally, comparison of Experiments 2 and 3 suggests that strength manipulations can cause more interference than length manipulations, at least at lower strengths (e.g., 3 presentations). If confirmed, the result may be problematic for SAC, which predicts larger length effects than strength effects, and for CLS, which predicts either equal-sized effects or larger effects of length. The results would also pose problems to BCDMEM to the extent that the model treats length and strength manipulations as equally irrelevant to interference in recognition.