Effects of Anosognosia on Static and Dynamic Amplitudes of Low-Frequency Fluctuation in Mild Cognitive Impairment

Abstract

Background: Anosognosia is a significant symptom in patients with mild cognitive impairment (MCI) while the underlying neurological mechanism behind it is still unclear.Methods: A total of 121 subjects were included and classified into three groups, including 39 normal controls (NCs), 42 individuals with MCI without anosognosia (MCI-NA), and 40 individuals with MCI with anosognosia (MCI-A), based on their everyday cognition (ECog) questionnaire (discrepancy score). Resting-state functional MRIs were acquired from all the subjects, and the static amplitudes of low-frequency fluctuation (sALFF) and dynamic ALFF (dALFF) variance were investigated to evaluate the intrinsic functional network strength and stability, respectively, and both were corrected by age, sex, education, and gray matter volume. Eventually, correlation analyses were conducted to explore the relationship between brain activity changes and cognitive status in all the subjects.Results: No significant difference was found between MCI-A and MCI-NA (P > 0.05) in cognitive ability. Regarding intrinsic brain activity, MCI-A had increased sALFF and dALFF variance in the anterior cingulate cortex (ACC) relative to MCI-NA, as well as decreased sALFF and dALFF variance in the precuneus relative to MCI-NA and controls. Moreover, MCI-A had decreased sALFF in the inferior temporal gyrus (ITG) and paracentral lobule (PCL) compared to MCI-NA. Among all the subjects, correlation analyses showed that the sALFF and dALFF variance in the precuneus was related to the Ecog discrepancy score (r = 0.232 and 0.235, respectively), immediate story recall (r = 0.200 and 0.277, respectively), and delayed story recall (r = 0.255 and 0.298, respectively).Conclusion: Alterations of intrinsic brain activation in the ACC and precuneus seem to be associated with the anosognosia symptom in patients with MCI.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease

“…Previous evidence of hippocampal atrophy combined with our results of decreased parahippocampal gyrus activity might account for and predict the cognitive impairment in PD patients. Similarly, in the study of vascular dementia and Alzheimer's disease, it was found that abnormal brain activities in different parts of brain were related to pathological processes, which provided theoretical support for explaining the mechanism of cognitive impairment in imaging perspective 52,53 . The study found that sharp ripples are a manifestation of interactions between the hippocampus and cortical loops, which are closely linked to cognition and memory 54 .…”

“…Similarly, in the study of vascular dementia and Alzheimer's disease, it was found that abnormal brain activities in different parts of brain were related to pathological processes, which provided theoretical support for explaining the mechanism of cognitive impairment in imaging perspective. 52 , 53 The study found that sharp ripples are a manifestation of interactions between the hippocampus and cortical loops, which are closely linked to cognition and memory. 54 However, whether similar cognitive loop abnormalities exist in the PD co‐morbid cognitively impaired population warrants elucidation in terms of functional versus causal connectivity.…”

Alteration of brain network centrality in CTN patients after a single triggering pain

“…A short window length may increase the risk of introducing spurious fluctuations in the observed dDC, and a long window length may hinder the characterization of the temporal variability dynamics of the dDC ( Zang et al, 2004 ). In line with our previous study ( Ge et al, 2022b ), we used a 50 TR (100 s) sliding window length and a 2 TR (4 s) step size ( Fu et al, 2021 ; Ge et al, 2022b ; Li et al, 2022 ; Sun et al, 2022 ). Based on the method similar to sDC, after calculating the DC of all voxels in the time window, each participant will obtain multiple window-based DC graphs.…”

Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease

“…The coefficient of variation (CV) map was computed across time windows. In order to be consistent with the previous dynamic rs-fMRI studies (35)(36)(37)(38), we used a 50 TR sliding window length and a 2 TR step length. We have further verified our results using 60 TR sliding window length and a 2 TR step size and added the figures for validation in the Supplementary Figures 1, 2.…”