On the Dynamics of Information Accumulation in Recognition

On the Dynamics of Information Accumulation in Recognition Gregory E. Cox, Nicholas J. Lewis, Richard M. Shiffrin (grcox, njlewis, shiffrin)@indiana.edu Department of Psychological and Brain Sciences, Cognitive Science Program, Indiana University 1101 E. Tenth St., Bloomington, IN 47405 USA Abstract There is evidence that, even outside of experimental ma- nipulations to that effect, the nature of the evidence for recog- nition may vary over time. Information about the “oldness” of individual items is available quite early in processing, while associative information (e.g., whether a word pair was stud- ied in intact or rearranged order) requires approximately an additional 200 ms to become available (Gronlund & Rat- cliff, 1989). And Hintzman and Curran (1994, Experiment 3) found that, when tested with a foil that was a plural or singular form of a word that had been studied in the opposite plurality (e.g., “apple” was studied and “apples” was tested), subjects’ tendency to endorse the foil initially increased but then re- versed at longer response lags. These results are consistent with a recognition process that accumulates information over time, but at different rates for different kinds of information (e.g., Brockdorff & Lamberts, 2000). In an attempt to better understand the dynamics of the recognition process, we first present results from an experi- ment in which stimuli were constructed from a set of compo- nents which varied in diagnosticity as to whether the stimulus is old or new. In some conditions, components became visible at different times, allowing us to assess the effect of present- ing diagnostic information later or earlier. These results are explained in the context of a dynamic model of recognition (Cox & Shiffrin, 2012). The mechanisms employed can also be used to explain the “fluency” results of Jacoby and White- house (1989). Inspired by a dynamic approach to recognition memory (Cox & Shiffrin, 2012), we present results from a recognition mem- ory experiment in which the time at which diagnostic informa- tion arrives is unconsciously varied. Contrary to the predic- tions of most models, performance improves when diagnostic information is available later, rather than earlier. These results are accounted for by a dynamic model of recognition, where the time at which information starts to be accumulated for a recognition decision can vary independently of when features are available to be sampled from the test display. The same model is shown to be able to reproduce the priming results of Jacoby and Whitehouse (1989), originally attributed to a fluency heuristic. The ability to account for such seemingly disparate results with a single model illustrates the utility of a dynamic approach to recognition. Keywords: Episodic memory; recognition memory; memory models. Introduction Recognition continues to be a rich source of evidence re- garding the processes and mechanisms that underly episodic memory performance. Throughout its long history in psy- chology and cognitive science, recognition memory experi- ments have collected measures of reaction time. Despite this, most theories in recognition memory have been concerned only with accuracy. Most of the few models of recognition that also make predictions about response time (Hockley & Murdock, 1987; Mewhort & Johns, 2005; Malmberg, 2008; Nosofsky & Stanton, 2006) assume nonetheless that the ev- idence is stationary over time (an exception is Brockdorff & Lamberts, 2000). Thus, it would appear that much work re- mains to be done to better understand the fine-grained tempo- ral aspects of the recognition process. As a step in that direction, Cox and Shiffrin (2012) intro- duced a model of recognition that was based on the gradual accumulation of features over time. As features are sampled, they are added to a memory probe which is then compared to all the traces in memory (or at least those above a cer- tain threshold level of activation), resulting in a “familiarity” value. Familiarity will move up and down over time in a noisy fashion as features get sampled; positive changes in familiar- ity are evidence in favor of an “old” decision, while negative changes favor a “new” decision. However, because only a fi- nite number of features can be sampled, familiarity will even- tually reach a (noisy) asymptote. Thus, the evidence for the recognition process in this model is inherently nonstationary. Furthermore, its predictions will vary greatly with experimen- tal manipulations that affect the timing with which different information becomes available. Experiment 1: Dynamic Presentation In this experiment, the diagnosticity of information arriving at different times was varied unconsciously. Participants 55 undergraduate students from Indiana University partici- pated in the experiment for course credit. Stimuli All stimuli for a given list were generated from two pro- totypes consisting of random consonant triads, displayed in a triangular manner to minimize the effect of a left-to-right reading preference, e.g., X L K and Z D J . An old item was made from a prototype by replacing one of its letters with another consonant. This resulted in 6 old items for each prototype (2 replacements each for the three letters) and a total of 12 old items for study. The prototypes were not studied. New items were generated in a similar manner by replacing a single pro- totype consonant with a new randomly selected consonant that did not appear at study. This structure allows the sin-