Interestingly, this view of WM decline in aging does not necessarily imply that older adults should show down-regulation of their brain activity during WM tasks compared with younger adults. An inappropriate focus on irrelevant/distracting information, stemming from age-related difficulties in attention control, may effectively reduce the WM capacity that is available for the task at hand and lead to decreased performance. In our own research, we have also found evidence supporting the claim that older adults may have problems inhibiting the processing of irrelevant information present within the experimental context ( Fabiani, Low, Wee, Sable, & Gratton, 2006 Fabiani, Friedman, & Cheng, 1998 Fabiani & Friedman, 1995). In fact, there is substantial evidence of reduced inhibition of the processing of distracting or irrelevant information in older adults, which may support such a scenario ( Hasher, Lustig, & Zacks, 2008 Hasher & Zacks, 1988). However, it is also possible to link age-related WM decline to a reduced ability to maintain an appropriate/stable attention focus. For example, Salthouse (1996) proposed that aging leads to reduced speed of processing, rendering it more difficult to maintain many items in memory at a time. Several theories have been developed to explain this decline. Several studies have shown that, similarly to other cognitive functions, WM performance declines with increasing age (e.g., Bopp & Verhaeghen, 2005 Park et al., 2002 Verhaeghen & Salthouse, 1997). To address this question, this study aims at examining in detail the changes in brain activity that are observed when WM capacity limits are reached.Īlthough the majority of studies of WM capacity have been carried out in young adults, in the last several decades researchers have also investigated how WM changes with age (e.g., Craik & Byrd, 1982 Craik, 1968). A related question is how WM capacity is linked to brain activations during WM tasks. A similar view has been proposed by Engle and Kane (2004), Kane, Bleckley, Conway, and Engle (2001), and Kane and Engle (2000). Thus, this “activation capacity” is assumed to be dependent on attention deployment, and WM is assumed to be limited by attention span. The limitation, therefore, is not really in memory capacity per se but in how many items can be kept into the focus of attention at any point in time. An important aspect of Cowan’s model is that WM is seen as a part of a more extended memory system, in which a small number of items are activated out of a much larger pool, so as to be readily available for the performance of a particular task. However, in a more recent review of a large number of studies, Cowan (2001) proposed that the core of the WM system can only hold 4 ± 1 items and that additional processes such as “chunking” are required for more items. Miller (1956), in a classic article, proposed that the capacity of WM is 7 ± 2 items. One of the most intriguing findings in cognitive psychology is that the capacity of WM is in fact very limited, although there is some debate as to exactly how many items can be maintained and manipulated. Working memory (WM) is a system that allows us to store and manipulate small amounts of information for a short time ( Baddeley, 1986 Baddeley & Hitch, 1974). Results are discussed in terms of Cowan’s model of working memory and theories of impaired inhibitory processes in aging. Interestingly, the brain activation data show a sigmoid relationship with load. The results suggest that age differences in brain activation can be largely attributed to individual variations in working memory span. Specifically, we hypothesized a nonlinear relationship between load and both performance and brain activity and predicted that asymptotes in the brain activation function should correlate with performance asymptotes (corresponding to working memory span). In a Sternberg memory search task, this can be achieved by assessing brain activity as a function of load relative to the individual’s memory span, which declines with age. The Compensation-Related Utilization of Neural Circuits Hypothesis leads to the prediction that activation differences between younger and older adults should disappear when task difficulty is made subjectively comparable. A possible interpretation of this finding is that older adults need to recruit neuronal resources at lower loads than younger adults, leaving no resources for higher loads, and thus leading to performance decrements. Neuroimaging data emphasize that older adults often show greater extent of brain activation than younger adults for similar objective levels of difficulty.
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