Enhancing cognition across the lifespan : transfer effects of task-switching training in young and old adults

Abstract

knowledge base that the individual is endowed with, and which can grow by the influence of culture. This component does not show decline until very old age. The ‘mechanics’ component is the means to gain knowledge, while ‘pragmatics’ component is the abstract knowledge gained, or that is being 'crystallized'. Evidence for this two-component model comes from multiple sources (see Baltes et al., 2006; p. 598600.), including longitudinal studies (e.g. Seattle Longitudinal Study) indicating that cognitive abilities related with the ‘mechanic’ component (i.e. reasoning, memory, perceptual speed, spatial orientation) follow a nearly linear decline throughout adulthood, while cognitive abilities related with the ‘pragmatics’ component (i.e. verbal ability, numeric ability) does not show decline until very old age (see Figure 1). Figure 1 Cross-sectional data from the Seattle Longitudinal Study (image from Hedden & Gabrieli, 2004) Causes of Age-Related Changes in Cognition In this section different approaches to explain age-related changes in cognition will be outlined, along with empirical findings. The first of these is the 'general slowing' hypothesis, which mainly explains age-related changes in intellectual fluid abilities as a 9 function of a general slowing of processes (T. Salthouse, 1996). According to this theory, the slowing down of executing processes leads to impaired cognitive performance in most cognitive tasks. While the general slowing hypothesis is still an integral theory for explaining age-related decline in many areas, it is not adequate to explain age-differences in conditions with high cognitive control demands (Mayr & Kliegl, 1993; Verhaeghen, Steitz, Sliwinski, & Cerella, 2003). Age-related changes in intellectual abilities can also be explained as a function of changes in inhibitory processes. An early study (Kramer, Humphrey, Larish, & Logan, 1994) for instance, found little evidence for age-related deficits in inhibitory processes, however older adults had more difficulty than younger adults to abort an action (in a stop signal paradigm where participants are asked to respond to a visual stimuli unless they hear an auditory signal), and it also proved more difficult for older adults to learn new rules in a categorization task. Also, comparing younger and older adults, inhibition related processes were found to be delayed in the elderly as evidenced by delayed inhibition-related ERPs (event related potentials, recorded with electroencephalogram) (Falkenstein, Hoormann, & Hohnsbein, 2002). It is also possible to attribute age-related differences in intellectual abilities to changes in working-memory performance. Recent studies have demonstrated that older adults show deficits in suppressing task-irrelevant information during working-memory performance whereas their ability to enhance task-relevant information is intact (Gazzaley, Cooney, Rissman, & D’Esposito, 2005). Furthermore, it has been shown that an interruption during task maintenance distracts both younger and older adults, however while younger adults quickly disengage from the task-irrelevant disruptor and reestablish task-relevant functional networks, older adults are impaired in dynamic shifting between competing representations (Clapp, Rubens, Sabharwal, & Gazzaley, 2011). Similar 10 findings came also from a study employing an inhibition of return paradigm (Wascher, Falkenstein, & Wild-Wall, 2011) and another study using a dual task paradigm (Hahn, Wild-Wall, & Falkenstein, 2011) suggesting that older adults process irrelevant information similarly as relevant information, and this leads to impairments in workingmemory performance. We can also approach to explain age-related differences in intellectual abilities in terms of biological changes in the nervous system. Some decades ago large scale general neuron loss was suggested to be the main reason for age-related cognitive decline (Ball, 1977; Coleman & Flood, 1987). However, recently it became evident that general neuron loss in most areas does not contribute significantly to age-related cognitive decline (Burke & Barnes, 2006) but rather there are specific areas such as the prefrontal cortex (PFC) in which neuron loss is related to cognitive decline. A study, for example, with aged monkeys have found an approximately 30 percent reduction of neurons compared to younger animals in the dorsolateral PFC area 8A, and this reduction correlated with impaired performance in a working-memory task, but at the same time other areas related to working-memory (such as area 46) were well preserved (Smith, Rapp, McKay, Roberts, & Tuszynski, 2004). Less age-related change has been reported for many electrophysiological properties of neurons in the hippocampus and the PFC, such as resting membrane potential, membrane time constant, threshold to elicit an action potential, and rise time and duration of an action potential (Burke & Barnes, 2006). However, reduced synapse number in older animals might be related with cognitive decline. It has been found in rats, that synapse number per neuron diminishes during aging in the dentate gyrus, which is a hippocampal sub-region that is important in spatial memory (Geinisman, Toledo-Morrell, & Morrell, 1986).