B
Baojuan Li
Researcher at National University of Defense Technology
Publications - 31
Citations - 1957
Baojuan Li is an academic researcher from National University of Defense Technology. The author has contributed to research in topics: Medicine & Functional magnetic resonance imaging. The author has an hindex of 11, co-authored 21 publications receiving 1654 citations. Previous affiliations of Baojuan Li include Fourth Military Medical University & Harvard University.
Papers
More filters
Journal ArticleDOI
Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis
Ling-Li Zeng,Hui Shen,Li Liu,Lubin Wang,Baojuan Li,Peng Fang,Zongtan Zhou,Yaming Li,Dewen Hu +8 more
TL;DR: The majority of the most discriminating functional connections were located within or across the default mode network, affective network, visual cortical areas and cerebellum, thereby indicating that the disease-related resting-state network alterations may give rise to a portion of the complex of emotional and cognitive disturbances in major depression.
Journal ArticleDOI
A Treatment-Resistant Default Mode Subnetwork in Major Depression
TL;DR: A dissociation of the DMN into subnetworks is suggested, where persistent abnormal functional connectivity within the anterior subnetwork in recovered MDD subjects may constitute a biomarker of asymptomatic depression and potential for relapse.
Journal ArticleDOI
Network discovery with DCM
Karl J. Friston,Baojuan Li,Baojuan Li,Jean Daunizeau,Jean Daunizeau,Klaas E. Stephan,Klaas E. Stephan +6 more
TL;DR: A scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity is described that furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks.
Journal ArticleDOI
Generalised filtering and stochastic DCM for fMRI
Baojuan Li,Jean Daunizeau,Jean Daunizeau,Klaas E. Stephan,Klaas E. Stephan,William D. Penny,Dewen Hu,Karl J. Friston +7 more
TL;DR: The ability to model endogenous or random fluctuations on hidden neuronal (and physiological) states provides a new and possibly more plausible perspective on how regionally specific signals in fMRI are generated.
Journal ArticleDOI
A brain network model for depression: From symptom understanding to disease intervention.
TL;DR: Recent studies of functional and effective connectivity in depression, in terms of functional integration in the brain, point to the involvement of at least four networks, which serve as evidence for the crucial role of these networks in the pathophysiology of depression.