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Related Experiment Video

Updated: Jan 27, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

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Published on: May 7, 2014

Altered brain network dynamics and functional connectivity in subjective cognitive decline: an edge-centric network

Xiaofan Wei^1,2, Baiwan Zhou¹, Juanling Li¹

¹Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Frontiers in Aging Neuroscience

|January 26, 2026

Summary

Subjective cognitive decline (SCD) shows altered brain network dynamics, particularly in high-amplitude states. These neurodynamic changes may serve as novel biomarkers for early detection of cognitive decline.

Keywords:

dynamic functional connectivity edge-centric network high- and low-amplitude frame network resting-state functional magnetic resonance imaging subjective cognitive decline

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Last Updated: Jan 27, 2026

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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Area of Science:

Neuroscience
Cognitive Science
Medical Imaging

Background:

Subjective cognitive decline (SCD) represents early-stage cognitive impairment.
Understanding the neurodynamic underpinnings of SCD is crucial for early diagnosis and intervention.

Purpose of the Study:

To investigate the neurodynamic bases of SCD using an edge-centric functional network framework.
To identify potential imaging biomarkers for SCD.

Main Methods:

Utilized resting-state functional magnetic resonance imaging (fMRI) data from 211 SCD patients and 210 healthy controls (HC).
Constructed high- and low-amplitude frame networks based on edge time series (ETS) co-fluctuation signals.
Applied graph theory and network-based statistics (NBS) for network analysis and correlated findings with cognitive scores and APOE ε4 genotype.

Main Results:

SCD patients exhibited reduced peak amplitude and prolonged trough-to-trough duration (TTD) compared to HC.
Significant reductions in normalized clustering coefficient, characteristic path length, small-worldness, and global efficiency were observed in SCD.
The high-amplitude frame network revealed more extensive brain alterations and identified a specific SCD-related subnetwork.

Conclusions:

The edge-centric network framework provides novel insights into brain network alterations in SCD.
Identified neurodynamic changes and subnetworks in SCD hold potential as reliable biomarkers for early detection and characterization of cognitive decline.