Slowing Down: Age-Related Neurobiological Predictors of Processing Speed

Abstract

Processing speed, or the rate at which tasks can be performed, is a robust predictor of age-related cognitive decline and an indicator of independence among older adults. This review examines evidence for neurobiological predictors of age-related changes in processing speed, which is guided in part by our source based morphometry findings that unique patterns of frontal and cerebellar gray matter predict age-related variation in processing speed. These results, together with the extant literature on morphological predictors of age-related changes in processing speed, suggest that specific neural systems undergo declines and as a result slow processing speed. Future studies of processing speed – dependent neural systems will be important for identifying the etiologies for processing speed change and the development of interventions that mitigate gradual age-related declines in cognitive functioning and enhance healthy cognitive aging.

Age and gender differences in spatial perspective taking

“…Error bars represent one standard error Aging Clin Exp Res high complexity of the task could have been the most important factor modulating the performance of the groups, making the number of items unanswered similar across groups. Although older people usually require more time to complete the tasks, due in part to a reduction in processing speed, in our study this variable seemed not to be significant [28,[43][44][45].…”

Fatigability Disrupts Cognitive Processes' Regulation of Inflammatory Reactivity in Old Age

“…Of note, SOP is not a simple psychomotor ability, but a fundamental brain process related to temporary information manipulation (43, 44). According to a recent review, SOP reflects the integrity of multiple neural networks involved in other levels or domains of cognitive processes (e.g., attention, EF) and most higher-order cognitive functions (e.g., memory, reasoning, and language) (11). Previous studies found that, increased fatigability can specifically affect medial and lateral frontal cortex independent of basal ganglia inputs (23), while atrophy of these frontal regions often occurs early in individuals with decreased SOP, making these regions particularly vulnerable to adverse impact of fatigability (11).…”

“…According to a recent review, SOP reflects the integrity of multiple neural networks involved in other levels or domains of cognitive processes (e.g., attention, EF) and most higher-order cognitive functions (e.g., memory, reasoning, and language) (11). Previous studies found that, increased fatigability can specifically affect medial and lateral frontal cortex independent of basal ganglia inputs (23), while atrophy of these frontal regions often occurs early in individuals with decreased SOP, making these regions particularly vulnerable to adverse impact of fatigability (11). It is possible that fatigability will first and primarily influence this most fundamental and vulnerable cognitive process by disrupting the control of SOP on different formats of stress responses.…”

“…Alterations in the function of these cortical regions, especially the prefrontal cortex, (e.g., applying mindfulness training) have been shown to decrease the peripheral pro-inflammatory cytokines gene expression in old age (9, 10). These cortical regions also mediate executive function (EF), speed of processing (SOP), and attention (11, 12). Williams et al propose that these frontally-oriented cognitive processes are involved in the top-down regulation of individuals' stress responses, including peripheral inflammatory responses (13).…”

A theoretical framework for cognitive and non-cognitive interventions for older adults: stimulation versus compensation

“…The model of speed of processing posits that there is a weak relation between age and memory performance and that age is indirectly related to memory function, mediated by the speed of processing (Salthouse, 1996). A recent neuroimaging study reports deficits in a dorsal attention system and impairments in regional cerebellar gray matter volume in the processing speed declines of older adults, confirming the role of processing speed as a predictor of cognitive aging (Eckert, 2011). The hypothesis about cognitive aging extends to the model of working memory deficits (Mitchell, Johnson, Raye, Mather, & D'Esposito, 2000;Salthouse, 1992), which points out dysfunctions in neural networks of frontal, parietal, and subcortical brain areas (Dahlin, Backman, Neely, & Nyberg, 2009).…”