Structural-functional connectivity decoupling in multiscale brain networks in Parkinson’s disease

These findings suggest that PD is characterized by SC-FC decoupling in topological organization of multiscale brain networks, providing insights into the brain network mechanisms in PD.

Authors

Institutions

Publication Details

Journal
BMC Neuroscience
Published
2024-12-26
DOI
https://doi.org/10.1186/s12868-024-00918-4
Citations
3
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
1.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Structural-functional connectivity decoupling in multiscale brain networks in Parkinson’s disease

Qing Chun Gao, Wei Liao, Chong Wang, Xuyang Wang et al.
3 citations
BMC Neuroscience
Functional Brain Connectivity Studies
1.03
article

Structural-functional connectivity decoupling in multiscale brain networks in Parkinson’s disease

Qing Chun Gao, Wei Liao, Chong Wang, Xuyang Wang, Lin Gan, Chunyan Zhang, Jingliang Cheng, Ting Zou, Chen Chen, Rong Li, Huafu Chen
article en
3 citations

Abstract

These findings suggest that PD is characterized by SC-FC decoupling in topological organization of multiscale brain networks, providing insights into the brain network mechanisms in PD.

BMC NeuroscienceVol. 25(1)
University of Electronic Science and Technology of China (CN), First Affiliated Hospital of Zhengzhou University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 23%
Functional Brain Connectivity Studies
1.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.