The influence of attention on the detection of the list length effect in recognition memory

The Influence of Attention on the Detection of the List Length Effect in Recognition Memory Angela Kinnell (angela.kinnell@gmail.com) School of Psychology, Level 4, Hughes Building, North Terrace University of Adelaide, South Australia, 5005. Simon Dennis (simon.dennis@gmail.com) Department of Psychology, Ohio State University, 1835 Neil Avenue, Columbus, OH, 43210 USA Abstract The list length effect in recognition memory has been the subject of recent debate. Many studies have identified the effect, however Dennis and Humphreys (2001) argued that previous list length effect findings were the result of a failure to control for four potential confounds. The list length effect can be used to discriminate between item and context noise models of recognition memory. Item noise models predict the effect, while context noise models do not. In this paper, the role of attention on the detection of the list length effect is explored. The attention task at study was manipulated; participants either rated the pleasantness of study items or read the words only. In addition, the design was either retroactive or proactive. The results suggest that it is the proactive design in which the list length effect is evident. When the retroactive design is used in conjunction with the pleasantness rating task, there is the most even performance across list lengths and a nonsignificant effect of list length. This is consistent with context noise models of recognition. Keywords: recognition; list length; memory models. The source of interference in recognition memory has been the subject of recent debate. Some researchers have argued that interference to the memory trace for a particular item comes about as a consequence of the other items on the study list (e.g. Cary & Reder, 2003; Gillund & Shiffrin, 1984; Gronlund & Elam, 1994; Murdock, 1982). At the other end of the spectrum, Dennis and Humphreys (2001) have argued that interference comes from all of the previous contexts in which that particular item has been seen. Alternatively, interference could arise through a combination of the two (Criss & Shiffrin, 2004). Arising from these different approaches are a number of different mathematical models of recognition memory designed to fit several well-documented recognition findings. There has recently been some question as to whether one of these findings, the list length effect, is a real effect or is the result of one or more confounds (Dennis & Humphreys, 2001). The list length effect refers to the finding that recognition performance is superior for shorter rather than longer lists. The existence, or non-existence, of the list length effect can be used to help differentiate between these models of recognition memory. Item Noise Models The item noise approach is based upon the idea that it is the other items on the study list that interfere with one's ability to recognize a test probe. There are numerous mathematical models of recognition memory that define interference as arising from other list items. These include global matching models (GMMs) such as the Theory of Distributed Associative Memory (TODAM; Gronlund & Elam, 1994; Murdock, 1982), Minerva II (Hintzman, 1986), the Matrix model (Pike, 1984) and Search of Associative Memory (SAM; Gillund & Shiffrin, 1984) as well as the Retrieving Effectively from Memory model (REM; Shiffrin & Steyvers, 1997) and the Subjective Likelihood Model (SLiM; McClelland & Chappell, 1998). In these models a reconstruction of the study list context is used, often implicitly, to retrieve the items that appeared on the study list from memory. These are then compared to the test probe, with the level of activation integrated across all items. If this level of activation is above a certain threshold, the individual will respond “yes” indicating that they recognize the word from the study list. If this activation fails to reach the threshold, a “no” response will ensue. A longer study list means that more items must be matched to the cue resulting in greater interference as each new item introduces more variability. Thus, a list length effect is predicted by item noise models (Clark & Gronlund, 1996). Context Noise Models Alternatively, interference could arise from the other contexts in which a word has been encountered in the past and any interference from other items is negligible (Dennis & Humphreys, 2001). Context noise models are much fewer in number than item noise models and include the Bind Cue Decide Model of Episodic Memory (BCDMEM; Dennis & Humphreys, 2001) and the model of Anderson and Bower (1972). In BCDMEM, the test probe is used to cue retrieval of previous contexts in which that word has been encountered. These contexts are then compared to the reinstated study context. The stronger the global match between these, the higher the level of activation with the result being a “yes” response. Failure to reach the activation threshold will result in a “no” response. Other study list items do not affect