AMPLITUDE OF LOW FREQUENCY FLUCTUATION AT DIFFERENT FREQUENCY BANDS IN EARLY AMNESTIC MILD COGNITIVE IMPAIRMENT: RESULTS FROM ADNI

We used resting-state functional magnetic resonance imaging(fMRI)to determine whether there are any abnormalities in different frequency bands between amplitude of low-frequency fluctuations(ALFF)and fractional ALFF(fALFF)and between 10 early amnestic mild cognitive impairment(EMCI)patients and eight normal controls participating in the Alzheimer’s Disease Neuroimaging Initiative(ADNI).We showed widespread difference in ALFF/fALFF between two frequency bands(slow-4:0.027-0.073 Hz,slow-5:0.01-0.027 Hz)in many brain areas including posterior cingulate cortex(PCC),medial prefrontal cortex(MPFC),suprasellar cistern(SC)and ambient cistern(AC).Compared to the normal controls,the EMCI patients showed increased ALFF values in PCu,cerebellum,occipital lobe and cerebellum posterior lobe in frequency band slow-4.While in frequency band slow-5,the EMCI patients showed decreased ALFF values in temporal lobe,left cerebrum and middle temporal gyrus5.Moreover,the EMCI patients showed increased fALFF values in frontal lobe and inferior frontal gyrus in band slow-5.While in frequency band slow-4,the EMCI patients showed decreased fALFF values in limbic lobe,cingulate gyrus and corpus callosum.These results demonstrated that EMCI patients had widespread abnormalities of amplitude of LFF in different frequency bands.

An abnormal resting-state functional brain network indicates progression towards Alzheimer's disease

Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations （nor- mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer＇s disease） using the Alzheimer＇s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer＇s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest- ing-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addi- tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and AIz- heimer＇s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.