Abstract
Alzheimer’s disease (AD) is characterized by progressive deterioration of brain function among elderly people. Studies revealed aberrant correlations in spontaneous blood oxygen level-dependent (BOLD) signals in resting-state functional magnetic resonance imaging (rs-fMRI) over a wide range of temporal scales. However, the study of the temporal dynamics of BOLD signals in subjects with AD and mild cognitive impairment (MCI) remains largely unexplored. Multiscale entropy (MSE) analysis is a method for estimating the complexity of finite time series over multiple time scales. In this research, we applied MSE analysis to investigate the abnormal complexity of BOLD signals using the rs-fMRI data from the Alzheimer’s disease neuroimaging initiative (ADNI) database. There were 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients. Following preprocessing of the BOLD signals, whole-brain MSE maps across six time scales were generated using the Complexity Toolbox. One-way analysis of variance (ANOVA) analysis on the MSE maps of four groups revealed significant differences in the thalamus, insula, lingual gyrus and inferior occipital gyrus, superior frontal gyrus and olfactory cortex, supramarginal gyrus, superior temporal gyrus, and middle temporal gyrus on multiple time scales. Compared with the NC group, MCI and AD patients had significant reductions in the complexity of BOLD signals and AD patients demonstrated lower complexity than that of the MCI subjects. Additionally, the complexity of BOLD signals from the regions of interest (ROIs) was found to be significantly associated with cognitive decline in patient groups on multiple time scales. Consequently, the complexity or MSE of BOLD signals may provide an imaging biomarker of cognitive impairments in MCI and AD.
Highlights
Functional connectivity (FC) of spontaneous blood oxygen leveldependent (BOLD) signals in functional magnetic resonance imaging has become an important tool for probing brain function changes in normal aging and neurodegenerative diseases
These results suggest that the complexity analyses using Multiscale entropy (MSE) of blood oxygen level-dependent (BOLD) signals can provide information on the temporal dynamics of neural signals across multiple scales that are relevant to the cognitive impairments in mild cognitive impairment (MCI) and Alzheimer’s disease (AD)
Wang et al (2018) investigated the neurophysiological underpinnings of complexity (MSE) of functional magnetic resonance imaging (fMRI) signals and their relations to FC and the results showed that the associations between MSE and FC were dependent on the temporal scales or frequencies It has been proposed that each frequency band is generated by different mechanisms and relates to different physiological functions, higher frequency oscillations are confined to a small neuronal space, whereas lower frequencies may reflect longrange interactions (Buzsáki and Draguhn, 2004; Zuo et al, 2010)
Summary
Functional connectivity (FC) of spontaneous blood oxygen leveldependent (BOLD) signals in functional magnetic resonance imaging (fMRI) has become an important tool for probing brain function changes in normal aging and neurodegenerative diseases. Relatively few studies have investigated the temporal dynamics of BOLD signals and its relations with pathologic changes in neurophysiology (Sporns et al, 2000; Friston et al, 2003; Wu et al, 2012). The BOLD signals possess complex temporal fluctuations, which could be imitated by nonlinear dynamical processes (Soltysik et al, 2004; Stephan et al, 2008; Yan et al, 2017). A widely used non-linear statistical method is sample entropy (SE) proposed by Richman and Moorman (2000). Recent studies found that neural signals in the brain possess correlations over a wide range of temporal and spatial scales, stemming from long-range interactions (Costa et al, 2005; Peng et al, 2009; Morabito et al, 2012). SE may not be adequate to fully capture the complexity of neural signals by only calculating signal entropy on a single scale
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
