Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: A multiscale entropy analysis

The nonlinear properties of spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals remain unexplored. We test the hypothesis that complexity of BOLD activity is reduced with aging and is correlated with cognitive performance in the elderly. A total of 99 normal older and 56 younger male subjects were included. Cognitive function was assessed using Cognitive Abilities Screening Instrument and Wechsler Digit Span Task. We employed a complexity measure, multiscale entropy (MSE) analysis, and investigated appropriate parameters for MSE calculation from relatively short BOLD signals. We then compared the complexity of BOLD signals between the younger and older groups, and examined the correlation between cognitive test scores and complexity of BOLD signals in various brain regions. Compared with the younger group, older subjects had the most significant reductions in MSE of BOLD signals in posterior cingulate gyrus and hippocampal cortex. For older subjects, MSE of BOLD signals from default mode network areas, including hippocampal cortex, cingulate cortex, superior and middle frontal gyrus, and middle temporal gyrus, were found to be positively correlated with major cognitive functions, such as attention, orientation, short-term memory, mental manipulation, and language. MSE from subcortical regions, such as amygdala and putamen, were found to be positively correlated with abstract thinking and list-generating fluency, respectively. Our findings confirmed the hypothesis that complexity of BOLD activity was correlated with aging and cognitive performance based on MSE analysis, and may provide insights on how dynamics of spontaneous brain activity relates to aging and cognitive function in specific brain regions.