Regional homogeneity patterns reveal the genetic and neurobiological basis of State-Trait Anxiety

The ReHo patterns associated with anxiety may be driven by genetic and neurobiological traits. Our findings contribute to a deeper understanding of the pathogenesis of anxiety from a genetic and molecular perspective.

Authors

Institutions

Publication Details

Journal
BMC Psychiatry
Published
2024-11-20
DOI
https://doi.org/10.1186/s12888-024-06291-0
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Regional homogeneity patterns reveal the genetic and neurobiological basis of State-Trait Anxiety

N. C. Shen, Wenzhen Zhu, Yuanyuan Qin, Jia Li et al.
BMC Psychiatry
Functional Brain Connectivity Studies
article

Regional homogeneity patterns reveal the genetic and neurobiological basis of State-Trait Anxiety

N. C. Shen, Wenzhen Zhu, Yuanyuan Qin, Jia Li, Yan Su, Dong Liu, Yuanhao Li, Yan Xie, Li Li, Tian Tian, Jicheng Fang
article en

Abstract

The ReHo patterns associated with anxiety may be driven by genetic and neurobiological traits. Our findings contribute to a deeper understanding of the pathogenesis of anxiety from a genetic and molecular perspective.

BMC PsychiatryVol. 24(1)
Tongji Hospital (CN), Union Hospital (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 79%
Functional Brain Connectivity Studies
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.