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Large-scale effective connectivity analysis reveals the existence of two mutual inhibitory systems in patients with major depression

Authors :
Jia Wang
Baojuan Li
Jian Liu
Jiaming Li
Adeel Razi
Kaizhong Zheng
Baoyu Yan
Huaning Wang
Hongbing Lu
Karl Friston
Source :
NeuroImage: Clinical, Vol 41, Iss , Pp 103556- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

It is posited that cognitive and affective dysfunction in patients with major depression disorder (MDD) may be caused by dysfunctional signal propagation in the brain. By leveraging dynamic causal modeling, we investigated large-scale directed signal propagation (effective connectivity) among distributed large-scale brain networks with 43 MDD patients and 56 healthy controls. The results revealed the existence of two mutual inhibitory systems: the anterior default mode network, auditory network, sensorimotor network, salience network and visual networks formed an “emotional” brain, while the posterior default mode network, central executive networks, cerebellum and dorsal attention network formed a “rational brain”. These two networks exhibited excitatory intra-system connectivity and inhibitory inter-system connectivity. Patients were characterized by potentiated intra-system connections within the “emotional/sensory brain”, as well as over-inhibition of the “rational brain” by the “emotional/sensory brain”. The hierarchical architecture of the large-scale effective connectivity networks was then analyzed using a PageRank algorithm which revealed a shift of the controlling role of the “rational brain” to the “emotional/sensory brain” in the patients. These findings inform basic organization of distributed large-scale brain networks and furnish a better characterization of the neural mechanisms of depression, which may facilitate effective treatment.

Details

Language :
English
ISSN :
22131582
Volume :
41
Issue :
103556-
Database :
Directory of Open Access Journals
Journal :
NeuroImage: Clinical
Publication Type :
Academic Journal
Accession number :
edsdoj.5d51c3b867f1425b8536b9e433009668
Document Type :
article
Full Text :
https://doi.org/10.1016/j.nicl.2023.103556