8 citations · 11 across the 4 of their papers we have counts for
5 papers
Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model
Gemeng Zhang, Aiying Zhang, Biao Cai +3
Functional connectivity (FC) has been widely used to study brain network interactions underlying the emerging cognition and behavior of an individual. FC is usually defined as the…
Functional connectome fingerprinting: Identifying individuals and predicting cognitive function via deep learning
Biao Cai, Gemeng Zhang, Aiying Zhang +6
The dynamic characteristics of functional network connectivity have been widely acknowledged and studied. Both shared and unique information has been shown to be present in the con…
A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
Aiying Zhang, Gemeng Zhang, Biao Cai +4
Emotion perception is essential to affective and cognitive development which involves distributed brain circuits. The ability of emotion identification begins in infancy and contin…
Causal inference of brain connectivity from fMRI with -Learning Incorporated Linear non-Gaussian Acyclic Model (-LiNGAM)
Aiying Zhang, Gemeng Zhang, Biao Cai +6
Functional connectivity (FC) has become a primary means of understanding brain functions by identifying brain network interactions and, ultimately, how those interactions produce c…
Interpretable multimodal fusion networks reveal mechanisms of brain cognition
Wenxing Hu, Xianghe Meng, Yuntong Bai +7
Multimodal fusion benefits disease diagnosis by providing a more comprehensive perspective. Developing algorithms is challenging due to data heterogeneity and the complex within- a…