The Inverse List Length Effect: Implications for Exemplar Models of Recognition Memory

The Inverse List Length Effect: Implications for Exemplar Models of Recognition Memory Simon Dennis (simon.dennis@gmail.com) 225 Psychology Building, 1835 Neil Avenue Columbus, OH 43210 USA Allison Chapman (achapman.274@gmail.com) 225 Psychology Building, 1835 Neil Avenue Columbus, OH 43210 USA Abstract A. H. Criss and R. M. Shiffrin (2004) argued against the composite context noise explanation of recognition memory introduced by Dennis and Humphreys (2001) by showing that with novel face stimuli, related distractors that are drawn from study categories show elevated false alarm rates. Dennis and Humphreys (2001) proposed two mechanisms by which related false alarm rates might arise. The first mechanism posited that such items might be produced as implicit associative responses. Such a mechanism is unlikely to apply to face stimuli. The second mechanism posited a category wide criterion shift, which Criss and Shiffrin (2004) argued was implausible because it requires criterion to be adjusted on an item by item basis during test. Rather they contended that direct interference between study items was more likely to account for the data and fit the Retrieving Effectively from Memory model (REM, Shiffrin & Steyvers, 1997) to their data. We suggest that the mechanism by which false alarms are generated for word and novel face stimuli may differ. Instead of focusing on related distractors, we focus on unrelated distractors. Using words, we show that if list length is manipulated by keeping the number of categories constant but increasing the number of exemplars in each category, then the unrelated false alarm rate decreases - thus inducing an inverse list length effect in which performance on short lists is worse than on long lists. Simulations demonstrate that exemplar models such as REM are not capable of accounting for the results without modification. Rather a composite representation of the studied categories that subjects can use to reject unrelated lures must be formed. Keywords: recognition memory, category effects, list length effect Introduction Criss and Shiffrin (2004) in a comment on Dennis and Humphreys (2001) argue that episodic recognition memory involves both item noise generated by the other items that ap- peared during the study episode and context noise generated by other contexts in which a test item has been seen. They present the results of two experiments. The second is a multi- list design which demonstrates that at least under some con- ditions context noise seems to play a substantial role. This re- sult supports the main point of Dennis and Humphreys (2001) and we will not discuss it further. The first experiment involved the presentation of word/face pairs at study. The words were drawn from both semantic and orthographic/phonological categories and face stimuli from face categories defined by gender, race and age. The length of these categories was manipulated independently at study (2, 6 or 9 items). At test, words and faces were presented in sepa- rate blocks and participants were required to make two judge- ments. Firstly, they were required to rate how confident they were that the item appeared on the study list. Secondly, they had to indicate how many similar items appeared at study. The probability of correctly identifying studied items as stud- ied increased with category length as did the probability of incorrectly identifying related distractors. Furthermore, par- ticipants’ estimates of the number of related items at test in- creased with the actual category length. Criss and Shiffrin (2004) proposed a version of the Re- trieving Effectively from Memory model (REM, Shiffrin & Steyvers, 1997) that incorporated both item and context noise. Their account of the category length effects drew on previ- ous work on the global matching models (Clark & Gron- lund, 1996; Humphreys, Pike, Bain, & Tehan, 1989) which attributes category effects to the overlap in item representa- tions. Related lures are assumed to overlap with many stud- ied items and as a consequence have higher match values. The more category exemplars on the list the higher the match value is likely to be and the more likely it is that a false alarm will be generated. By contrast, Dennis and Humphreys (2001) argued that similarity effects like those found by (Criss & Shiffrin, 2004) could be captured in a context noise model in at least two ways. The first proposed that when exposed to categorically organized lists of this kind, subjects might generate implicit associative responses (IARs, c.f. Underwood, 1978). IARs are self generated items that are bound to the study context not because they actually appeared, but because they were in- ternally generated by the subject. For instance, if the subject received a list containing the words, “bed”, “night”, “dark”, . , then they might think of the word “sleep” and in so doing establish an association to the list context. Subsequently, the existence of this association might increase the likelihood of incorrectly recognizing “sleep”. Criss and Shiffrin (2004) ar- gued that such a mechanism was implausible with face stim- uli because it would not be clear what could be generated as the IAR. The second mechanism proposed by Dennis and Humphreys (2001) was a category wide criterion shift. If participants were conscious of the categories in the list they might be inclined to use a low criterion for studied