Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI

默认模式网络 重性抑郁障碍 静息状态功能磁共振成像 功能磁共振成像 心理学 显著性(神经科学) 神经科学 内科学 精神科 医学 扁桃形结构
作者
Yun Wang,Jia Li,Rui Liu,Zhifang Zhang,Jingjing Zhou,Feng Yuan,Peter Zeidman,Gang Wang,Yuan Zhou
出处
期刊:Journal of Psychiatry & Neuroscience [Joule Inc.]
卷期号:47 (6): E421-E434 被引量:6
标识
DOI:10.1503/jpn.220038
摘要

Background:

Understanding the neural basis for major depressive disorder (MDD) is essential for its diagnosis and treatment. Aberrant activation and functional connectivity of the default mode network (DMN), salience network (SN) and dorsal attention network (DAN) have been found consistently in patients with MDD. However, whether effective connectivity within and between these networks is altered in MDD remains unknown. The primary objective of this study was to investigate the effective connectivity of the 3 networks in patients with MDD at rest.

Methods:

We included 63 patients with MDD (35 first-episode and 28 recurrent) and 74 healthy controls, and collected resting-state functional MRI data for all participants. We defined 15 regions of interest from the 3 functional brain networks of interest using group independent component analysis. We estimated the coupling parameters that reflected the causal interactions among these regions using spectral dynamic causal modelling. We used parametric empirical Bayes to determine commonalities across groups, differences between patients with MDD and healthy controls, and differences between patients with recurrent and first-episode MDD.

Results:

We found positive (excitatory) connections within each network, negative (inhibitory) connections from the SN and DAN to the DMN, and positive connections from the DAN to the SN across groups. Compared to healthy controls, patients with MDD showed increased positive connections within the DMN, a decreased absolute value of negative connectivity from the SN to the DMN, and increased positive connections from the SN to the DAN. We also found that patients with recurrent MDD showed remarkably different effective connections compared to patients with first-episode MDD, especially related to the DAN.

Limitations:

Because of the relatively small sample size and the unclear medication history of the MDD sample, the present findings are in need of replication.

Conclusion:

These findings suggest that effective connectivity among high-order brain functional networks during rest was disrupted in patients with MDD. Moreover, patients with recurrent MDD exhibited different effective connections compared to patients with first-episode MDD. These differences in effective connectivity might provide new insights into the neural substrates of MDD.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
orixero应助科研通管家采纳,获得10
刚刚
小马甲应助科研通管家采纳,获得10
刚刚
李健应助科研通管家采纳,获得10
1秒前
上官若男应助科研通管家采纳,获得10
1秒前
思源应助科研通管家采纳,获得10
1秒前
1秒前
星辰大海应助科研通管家采纳,获得10
1秒前
搜集达人应助科研通管家采纳,获得10
1秒前
mo0应助科研通管家采纳,获得20
1秒前
汉堡包应助科研通管家采纳,获得10
1秒前
1秒前
赘婿应助科研通管家采纳,获得10
1秒前
顾矜应助科研通管家采纳,获得10
1秒前
赘婿应助科研通管家采纳,获得10
1秒前
1秒前
2秒前
3秒前
bkagyin应助Xiaoyuan采纳,获得30
3秒前
4秒前
monere应助骑羊采纳,获得10
4秒前
沐风发布了新的文献求助30
4秒前
6秒前
现实的小熊猫完成签到,获得积分10
6秒前
陈功完成签到,获得积分10
6秒前
科目三应助林也行采纳,获得20
7秒前
李健应助我要帅个够采纳,获得10
7秒前
小黄鱼完成签到 ,获得积分10
7秒前
搜集达人应助MicroCytoYL采纳,获得10
8秒前
9秒前
bbo发布了新的文献求助10
10秒前
11秒前
卢11关注了科研通微信公众号
11秒前
Arjun完成签到,获得积分20
12秒前
13秒前
穆清发布了新的文献求助10
13秒前
zhiyu完成签到 ,获得积分10
13秒前
14秒前
16秒前
16秒前
避橙发布了新的文献求助10
16秒前
高分求助中
The late Devonian Standard Conodont Zonation 2000
歯科矯正学 第7版(或第5版) 1004
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 1000
Semiconductor Process Reliability in Practice 1000
Smart but Scattered: The Revolutionary Executive Skills Approach to Helping Kids Reach Their Potential (第二版) 1000
Security Awareness: Applying Practical Cybersecurity in Your World 6th Edition 800
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 700
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3240186
求助须知:如何正确求助?哪些是违规求助? 2885221
关于积分的说明 8237360
捐赠科研通 2553498
什么是DOI,文献DOI怎么找? 1381664
科研通“疑难数据库(出版商)”最低求助积分说明 649317
邀请新用户注册赠送积分活动 625009