Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study

Abstract

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory impairment. Previous studies have largely focused on alterations of static brain activity occurring in patients with AD. Few studies to date have explored the characteristics of dynamic brain activity in cognitive impairment, and their predictive ability in AD patients.

Methods: One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (HC) were recruited. The dynamic amplitude of low-frequency fluctuation (dALFF) and the dynamic fraction amplitude of low-frequency fluctuation (dfALFF) were used to assess the temporal variability of local brain activity in patients with AD or mild cognitive impairment (MCI). Pearson's correlation coefficients were calculated between the metrics and subjects' behavioral scores.

Results: The results of analysis of variance indicated that the AD, MCI, and HC groups showed significant variability of dALFF in the cerebellar posterior and middle temporal lobes. In AD patients, these brain regions had high dALFF variability. Significant dfALFF variability was found between the three groups in the left calcarine cortex and white matter. The AD group showed lower dfALFF than the MCI group in the left calcarine cortex.

Conclusions: Compared to HC, AD patients were found to have increased dALFF variability in the cerebellar posterior and temporal lobes. This abnormal pattern may diminish the capacity of the cerebellum and temporal lobes to participate in the cerebrocerebellar circuits and default mode network (DMN), which regulate cognition and emotion in AD. The findings above indicate that the analysis of dALFF and dfALFF based on functional magnetic resonance imaging data may give a new insight into the neurophysiological mechanisms of AD.

Keywords: Alzheimer’s disease (AD); dynamic fraction amplitude of low-frequency fluctuation (dfALFF); mild cognitive impairment (MCI); resting-state functional magnetic resonance imaging (rs-fMRI); the dynamic amplitude of low-frequency fluctuation (dALFF).

Figure 1

Maps showing differences in dALFF in the AD, MCI, and HC groups. Differences between the groups were calculated using ANOVA with the threshold set at voxel P<0.05 and cluster P<0.005, and the cluster extent threshold set at k>25, with AlphaSim correction. dALFF, dynamic amplitude of low-frequency fluctuation; AD, Alzheimer’s disease; MCI, mild cognitive impairment; HC, healthy controls; ANOVA, analysis of variance.

Figure 2

Maps showing differences in dALFF between the AD and HC groups. Differences between the groups were calculated using post-hoc analysis based on a two-sample T-test with the threshold set at voxel P<0.05 and cluster P<0.005, and the cluster extent threshold set at k>25, with AlphaSim correction. dALFF, dynamic amplitude of low-frequency fluctuation; AD, Alzheimer’s disease; HC, healthy controls.

Figure 3

Maps showing difference in dfALFF in the AD, MCI and HC groups. Differences between the groups were calculated using ANOVA with the threshold set at voxel P<0.05 and cluster P<0.005, and the cluster extent threshold at k>25, with AlphaSim correction. dfALFF, dynamic fraction amplitude of low-frequency fluctuation; AD, Alzheimer’s disease; MCI, mild cognitive impairment; HC, healthy controls; ANOVA, analysis of variance.

Figure 4

Maps showing differences in dfALFF between the AD and MCI groups. Differences between groups were calculated using post-hoc analysis based on a two-sample T-test with the threshold set at voxel P<0.05 and cluster P<0.005, and the cluster extent threshold at k>25, with AlphaSim correction. dfALFF, dynamic fraction amplitude of low-frequency fluctuation; AD, Alzheimer’s Disease; MCI, mild cognitive impairment.