Using your required reading, review the article “Aging Effects in Item and Associative Recognition Memory for Pictures and Words.” Your article review should include the following:
•·introduction of the topic,•·author’s main point(s),•·explanation of the connection between sensation and perception when recognizing pictures and words,•·description of how the signal detection theory helps with object recognition, and•·personal analysis.
You should not directly quote the article. Instead, paraphrase the article. Tip: When paraphrasing, read a paragraph a few times, then cover the article so you cannot see it; then, write down what you remember in your own words.
Your response must be a minimum length of two double-spaced pages. All sources used, including the textbook, must be referenced; paraphrased and quoted material must have accompanying citations and be cited per APA guidelines
BRIEF REPORT Aging Effects in Item and Associative Recognition Memory for Pictures and Words Roger Ratcliff and Gail McKoon The Ohio State University Item and associative recognition for pictures and words with college-age young adults and 60–75-year- old adults were examined in the experiment reported in this article. The diffusion model (Ratcliff & McKoon, 2008) was used to extract estimates of components of processing from the empirical values of accuracy and correct and error response time distributions. The model fit the empirical data well for both picture and word stimuli. Results showed that boundary separation was larger and nondecision time was longer for older relative to young adults. Drift rates were not lower for older adults for item recognition but they were for associative recognition, indicating that the richer structure of pictures did not provide an enhanced ability to form associations for the older adults. There were also significant correlations among the components of processing across the tasks of the experiment, suggesting common factors, but participants’ accuracy and response times did not significantly correlate within and across the tasks. Keywords: diffusion model, item recognition, associative recognition, pictures, aging Supplemental materials: http://dx.doi.org/10.1037/pag0000030.supp The experiment reported in this article examined the effects of age on memory for single words and single pictures (item infor- mation) and memory for pairs of words and pairs of pictures (associative information). Empirical differences between memory for item information and associative information have been ob- served at least from the 1970s (e.g., Murdock, 1974) and in more recent research (e.g., Hockley, 1991; Hockley & Cristi, 1996; Malmberg & Xu, 2007), the distinction has been brought to bear on the effects of age on cognition. Usually, only small effects of age on memory have been observed when single items are tested for recognition (Balota, Dolan, & Duchek, 2000; Craik, 1994; Kausler, 1994; Naveh-Benjamin, 2000; see the review in Neath, 1998, Chapter 16). But the differences have been significantly larger when pairs of words are tested (“Was this pair of items studied together in a list of pairs that was just studied?”; e.g., Buchler & Reder, 2007; Craik, 1983, 1986; Craik & McDowd, 1987; Healy, Light, & Chung, 2005; Naveh-Benjamin, 2000). In particular, Old and Naveh-Benjamin (2008) conducted a meta- analysis of data from 90 studies and found larger age-related deficits for associative recognition than item recognition under a wide variety of experimental manipulations. It has usually been concluded from studies like those just cited that item information is mostly preserved with age and associative information is not. However, almost all of the studies measured only accuracy, not response times (RTs), even though older adults are typically slower than young adults. Slowing for older adults has been interpreted as a deficit such that, for example, cognitive operations are not fully completed in the available time and so the products of earlier operations are not fully available to later oper- ations (e.g., Salthouse, 1996). When RTs are considered for item recognition, older adults do show significant deficits (Ratcliff, Thapar, & McKoon, 2004, 2010, 2011). The fact that RTs show significant deficits while accuracy does not means that a full explanation of item and associative recognition must accommo- date both measures. Tests of item and associative memory that compare older to younger adults have most often used words as the stimuli. In the experiment reported here, we also used pictures. Pictures show superior associative recognition relative to words for young adults (e.g., Hockley, 2008). If pictures allow better associative coding, then this might allow older adults to form better representations of pictures. Early studies that examined aging and item recognition with pictures (e.g., Park et al., 1986; Rybarczyk, Hart, & Harkins, 1987; Till, Bartlett, & Doyle, 1982) found only slight age-related decrements. However, Naveh-Benjamin, Hussain, Guez, and Bar-On (2003) did find an associative decrement. However, again, none of these studies measured reported instead of measured RTs. When accuracy and RTs are both considered, comparisons of item and associative memory between older and young adults face problems that require model-based analyses. Older adults’ perfor- mance relative to young adults’ is often obscured by the more conservative speed/accuracy decision criteria that they set, that is, This article was published Online First May 18, 2015. Roger Ratcliff and Gail McKoon, Department of Psychology, The Ohio State University. Preparation of this article was supported by Grant NIA R01-AG041176. Correspondence concerning this article should be addressed to Roger Ratcliff, Department of Psychology, The Ohio State University, Columbus, OH 43210. E-mail:
[email protected] T hi s do cu m en t is co py ri gh te d by th e A m er ic an Ps yc ho lo gi ca l A ss oc ia tio n or on e of its al lie d pu bl is he rs . T hi s ar tic le is in te nd ed so le ly fo r th e pe rs on al us e of th e in di vi du al us er an d is no t to be di ss em in at ed br oa dl y. Psychology and Aging © 2015 American Psychological Association 2015, Vol. 30, No. 3, 669–674 0882-7974/15/$12.00 http://dx.doi.org/10.1037/pag0000030 669 http://dx.doi.org/10.1037/pag0000030.supp mailto:
[email protected] http://dx.doi.org/10.1037/pag0000030 they are more concerned to avoid errors than young adults even if doing so slows performance (e.g., McKoon & Ratcliff, 2012, 2013; Ratcliff, Thapar, & McKoon, 2001, 2003, 2004, 2006a, 2006b, 2007, 2010, 2011; Spaniol, Madden, & Voss, 2006; Thapar, Rat- cliff & McKoon, 2003; the Ratcliff et al. papers are henceforth referenced as RTM). This results in different baseline levels of performance: Older adults’ overall RTs tend to be longer and, depending on the task, their overall accuracy may be higher than young adults’ or lower. The baseline difference can lead to a scaling problem such that a larger difference between conditions in RTs or accuracy for older adults might be due to better information or it might be that they have worse information but their larger difference is due to their more conservative criteria (for further discussion, see McKoon & Ratcliff, 2012). A direct comparison between the quality of information in memory for older and young adults requires a model that can solve the problems just described. The model must separate the quality of the information driving a decision from the effects of speed/ accuracy criteria and explain how accuracy and RTs arise from the same underlying cognitive processes. We used Ratcliff’s (1978; Ratcliff & McKoon, 2008) diffusion model, a member of the class of sequential sampling models. The insights the model can offer about older adults’ memory have been demonstrated by findings that in many (although not all) memory and perceptual tasks, the quality of the information on which performance is based is as good for older as young adults (e.g., RTM papers). The reason older adults are often slower than young is largely due to the more conservative speed/accuracy criteria that they set. The item and associative recognition tasks used for the experi- ment described here were two-choice tasks. Participants were given lists of pairs of items to remember. They were told whether the test would be item recognition or pair recognition only after the end of a to-be-remembered list. For item recognition, participants were asked to decide whether a test word or picture was “old” or “new” (i.e., whether it had or had not appeared in the list of pairs that was just studied). For associative recognition, participants were asked to decide whether a test pair of words or pictures was “intact” or “rearranged” (i.e., whether the two items of the test pair had or had not appeared together in the list of pairs that was just studied). In the diffusion model (Ratcliff & McKoon, 2008) for two- choice tasks, noisy information from a stimulus is accumulated over time from a starting point until a criterion (a boundary) is reached, one criterion for each choice, at which point a response is executed. The rate at which information is accumulated is labeled “drift rate” and it is determined by the quality of the information available from the stimulus. For example, in a memory task, the quality of the information would be worse for items studied once than items studied twice. Processes outside the decision process itself are combined into one parameter of the model, “nondecision” time. The total RT for a stimulus is the time taken by the decision process plus the nondecision time. Drift rates, boundaries, and nondecision times are the three main components of the model used in understanding differences among populations of individ- uals and differences among individuals. There have been four studies that have used the diffusion model to compare older to young adults’ performance on item recognition for words (Ratcliff, Thapar, & McKoon, 2004, 2010, 2011; Mc- Koon & Ratcliff, 2012) and two that have used the model to compare performance on associative recognition (McKoon & Rat- cliff, 2012; Ratcliff et al., 2011). In all cases, the older adults set their boundaries further apart and had longer nondecision times than the young adults. The important finding for understanding age differences in memory was that older adults’ drift rates for item recognition were near those of young adults, but their drift rates for associative recognition were significantly lower. Experiment There were four tasks in the experiment: item recognition with pictures and words and associative recognition with pictures and words. Our aim was to use a diffusion model analysis of the data from the four tasks to extract measures of the components of processing (i.e., parameter values) from accuracy and RT distri- butions for correct and error responses in order to make direct comparisons across tasks and age groups. Method Participants Twenty-four college-age participants were recruited from Ohio State University and Columbus, OH, area community centers. They were paid $12 per session for their participation. Twenty-five 60–74 year olds were recruited from local senior centers and were paid $15 per session (they were paid more than the young partic- ipants because they had to travel to the location at which they were tested). The participants participated in five 55-min sessions, the first three with words as the items and the last two with pictures. Materials There were two pools of words used to make up pairs, one of 503 high-frequency words (M Kucera & Francis frequency � 217.52, range � 66–999, SD � 233.47) and one of 693 low- frequency words (M � 4.4, range � 4–5, SD �0.5). For the picture experiments, there was a pool of 896 clip-art pictures