A meta-analytic brain map of age-related and individual differences in neurocognitive performance

Research in cognitive neuroscience of aging has provided clear evidence that normal aging process impacts individual’s cognitive function, brain activation, and behavioral performance. The compensation-related utilization of neural circuits hypothesis (CRUNCH) has been proposed to accommodate discrepant results to interpret age-related and individual differences in task-related neural activation and performance. The CRUNCH model posits that older adults would recruit more neuronal resources at lower level of task demand to maintain relatively intact performance than young adults, leaving fewer resources and declined performance for higher level of task demand. In the present study, we conducted a quantitative meta-analysis of task-related functional neuroimaging studies across a variety of cognitive domains to investigate the association between age-related neural activation and task performance. Healthy older participants were further divided into high-performing older groups (HPO; young and older participants had equivalent task performance in accuracy) and low-performing older group (LPO; older participants showed poorer accuracy than young participants) to specify the high and low levels of task demand. The meta-analytic results showed that HPO recruited greater and more distributed fronto-parietal regions compared to young group, suggesting a compensatory mechanism for optimizing task performance in older adults with lower level of task demand. In contract, LPO exhibited decreased neural activity compared to young participants with higher level of task demand, probably indicating an inefficient mechanism of the aging brain. Our findings provide supportive evidence for the CRUNCH model and suggest an adaptive view of the human brain that functionally reorganizes and responds to normal aging process.