Elsevier

Cortex

Volume 46, Issue 4, April 2010, Pages 462-473
Cortex

Special issue: Research report
Age differences in prefontal recruitment during verbal working memory maintenance depend on memory load

https://doi.org/10.1016/j.cortex.2009.11.009Get rights and content

Abstract

Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have revealed age-related under-activation, where older adults show less regional brain activation compared to younger adults, as well as age-related over-activation, where older adults show greater activation compared to younger adults. These differences have been found across multiple task domains, including verbal working memory (WM). Curiously, both under-activation and over-activation of dorsolateral prefrontal cortex (DLPFC) have been found for older adults in verbal WM tasks. Here, we use event-related fMRI to test the hypothesis that age-related differences in activation depend on memory load (the number of items that must be maintained). Our predictions about the recruitment of prefrontal executive processes are based on the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH; Reuter-Lorenz and Cappell, 2008). According to this hypothesis, more neural resources are engaged by older brains to accomplish computational goals completed with fewer resources by younger brains. Therefore, seniors are more likely than young adults to show over-activations at lower memory loads, and under-activations at higher memory loads. Consistent with these predictions, in right DLPFC, we observed age-related over-activation with lower memory loads despite equivalent performance accuracy across age groups. In contrast, with the highest memory load, older adults were significantly less accurate and showed less DLPFC activation compared to their younger counterparts. These results are considered in relation to previous reports of activation–performance relations using similar tasks, and are found to support the viability of CRUNCH as an account of age-related compensation and its potential costs.

Section snippets

Aging, WM, and DLPFC

While recruitment of DLPFC has figured prominently in neuroimaging work examining the effects of age on verbal WM, the results are seemingly inconsistent. On the one hand, several studies have reported age-related over-activation in DLPFC during the performance of simple verbal maintenance tasks (Reuter-Lorenz et al., 2000, Reuter-Lorenz et al., 2001, Cabeza et al., 2004).1

The current study

An important question for CRUNCH and for the cognitive neuroscience of aging more generally is whether additional regions recruited by older adults during the performance of specific tasks are the same regions recruited by young adults in response to increases in task demand (Stern, 2002). If so, this would strongly suggest that while older adults may be more challenged at lower objective levels of task demand than are younger adults, the basic neural and cognitive processes that contribute to

Participants

Twenty-one young (11 female) and 23 senior (13 female) adults were paid to participate in the study. See Table 1a, Table 1ba, b for detailed participant information. Young participants were recruited using advertisements posted on the University of Michigan campus. Older adults were recruited from Ann Arbor and surrounding communities through the University of Michigan Institute of Gerontology and newspaper and television advertisements. All participants were right-handed, native

Behavioral data analysis

Accuracy and RT data were analyzed in separate 2 (age group: young, senior) × 3 (memory load: 4, 5, 7 letters) analyses of variance (ANOVAs). Planned, pairwise t-tests were also performed between the age groups at each level of memory load; a Bonferroni correction was applied to control for the inflation of false positives which results from performing multiple comparisons and all reported p-values reflect this correction. For t-tests, only p-values less than .2 are reported.

fMRI data analysis

Functional images

Behavioral data

Young adults and seniors' mean accuracy and RT are depicted in Fig. 1, Fig. 2. Seniors performed less accurately than young adults [F(1, 42) = 5.6, p = .023]. Accuracy decreased with increasing memory load [F(2, 42) = 48.6, p < .001]. Age–group did not interact with memory load [F(2, 42) = 2.3, p = .11]. However, seniors were less accurate than young adults at a memory load of seven letters [t(42) = 2.61, p = .036]; whereas accuracy was age equivalent when remembering four [t(42) = 2.17, p = .11] or five letters [t

Discussion

We observed, within the same participants, both age-related over-activation and age-related under-activation of right prefrontal regions. Consistent with the predictions of CRUNCH, age-related over-activation was observed when participants maintained a relatively low WM load, and under-activation was observed during the maintenance of a relatively high memory load. This pattern was robust in right BA 46, but also evident in right BA 9 and BA 45. Also consistent with CRUNCH, over-activation

Resources and CRUNCH

Although CRUNCH is an hypothesis about how age-specific patterns of brain activation relate to task demands and performance, it has some commonalities with earlier ideas about age-related changes in the availability and distribution of resources that emerged from behavioral and neuropsychological studies of cognitive aging (see e.g., Kinsbourne, 1980; Craik and Byrd, 1982; Baltes, 1993; Reuter-Lorenz et al., 1999). Despite previous criticisms about its utility and falsifiability (e.g., Navon,

Conclusions

The present results are consistent both with studies that have found age-related over-activation of DLPFC and those that have observed age-related under-activation of DLPFC and provide a means of reconciling the seemingly inconsistent findings. At relatively low memory loads, seniors recruit more neural resources than do young adults in order to maintain good performance. At high memory loads, seniors have reached the limits of their neural resources, whereas young adults have resources to

Acknowledgments

We thank Megan Walsh and Laura Zahodne for their assistance with data collection and analysis. This work was supported by NIH AG18286 (PARL).

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