Recurrent and concurrent patterns of regional BOLD dynamics and functional connectivity dynamics in cognitive decline
Lingyan Liang1, Yueming Yuan2,3, Yichen Wei1
1Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China.
Alzheimer'S Research & Therapy
|January 17, 2021
Summary
This study reveals how dynamic brain activity patterns, including dynamic functional connectivity (dFC) and dynamic fractional amplitude of low-frequency fluctuations (dfALFF), change in subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Findings suggest these dynamic neural signatures can help differentiate cognitive decline stages and may aid early Alzheimer's disease diagnosis.
Area of Science:
- Neuroscience
- Cognitive Science
- Medical Imaging
Background:
- Cognitive decline, including subjective cognitive decline (SCD) and mild cognitive impairment (MCI), is associated with alterations in brain dynamics.
- Understanding the interplay between dynamic spontaneous neural activity and dynamic functional connectivity (dFC) is crucial for characterizing these changes.
- Current knowledge on how these dynamic brain states co-evolve in cognitive decline is limited.
Purpose of the Study:
- To investigate recurrent and concurrent patterns of dynamic brain states in relation to cognitive decline.
- To explore the relationship between dynamic functional connectivity (dFC) and dynamic fractional amplitude of low-frequency fluctuations (dfALFF) in individuals with SCD and MCI.
- To identify potential neuroimaging biomarkers for early detection of cognitive decline.
Main Methods:
- Analysis of resting-state functional magnetic resonance imaging (fMRI) data from healthy controls (HCs), SCD patients, and MCI patients.
- Utilized sliding-window and clustering techniques to identify recurrent brain states in dFC and dfALFF.
- Extracted occurrence and co-occurrence frequencies of identified dFC and dfALFF states for each participant.
Main Results:
- Identified distinct recurrent states for dfALFF and dFC, along with their co-occurring patterns.
- Observed significant differences in the frequency of default-mode network (DMN)-dominated dFC states between HCs and SCD patients.
- Found significant differences in co-occurrence frequencies of DMN-dominated dFC and dfALFF states between SCD and MCI patients, both correlating positively with cognitive scores.
Conclusions:
- Novel fMRI-based neural signatures of cognitive decline were identified through dynamic dfALFF and dFC patterns.
- Findings support SCD as a transitional phase between normal aging and MCI.
- These dynamic brain features show potential as objective neuroimaging biomarkers for early diagnosis and intervention in Alzheimer's disease.
Keywords:
Default mode networkDynamic functional connectivityFractional amplitude of low-frequency fluctuationsMild cognitive impairmentSubjective cognitive declineMore Related Videos
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