Addictive brain-network identification by spatial attention recurrent network with feature selection

Gong，Changwei1,2; Chen，Xinyi1,3; Mughal，Bushra4; Wang，Shuqiang1

2023-12-01

10.1186/s40708-022-00182-4

Brain Informatics   影响因子和分区

2198-4018

2198-4026

Addiction in the brain is associated with adaptive changes that reshape addiction-related brain regions and lead to functional abnormalities that cause a range of behavioral changes, and functional magnetic resonance imaging (fMRI) studies can reveal complex dynamic patterns of brain functional change. However, it is still a challenge to identify functional brain networks and discover region-level biomarkers between nicotine addiction (NA) and healthy control (HC) groups. To tackle it, we transform the fMRI of the rat brain into a network with biological attributes and propose a novel feature-selected framework to extract and select the features of addictive brain regions and identify these graph-level networks. In this framework, spatial attention recurrent network (SARN) is designed to capture the features with spatial and time-sequential information. And the Bayesian feature selection(BFS) strategy is adopted to optimize the model and improve classification tasks by restricting features. Our experiments on the addiction brain imaging dataset obtain superior identification performance and interpretable biomarkers associated with addiction-relevant brain regions.

Brain network Graph neural networks Neural imaging computing

EI

英语

其他

20230313383520

Biomarkers ; Brain mapping ; Feature Selection ; Magnetic resonance imaging ; Recurrent neural networks

Biomedical Engineering:461.1 ; Magnetism: Basic Concepts and Phenomena:701.2 ; Imaging Techniques:746

2-s2.0-85146118218

Scopus

1.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,518055,China
2.University of Chinese Academy of Sciences,Beijing,100049,China
3.Southern University of Science and Technology,Shenzhen,518055,China
4.Faculty of Engineering,University of Porto,Porto,0035122,Portugal

Gong，Changwei,Chen，Xinyi,Mughal，Bushra,et al. Addictive brain-network identification by spatial attention recurrent network with feature selection[J]. Brain Informatics,2023,10(1).

Gong，Changwei,Chen，Xinyi,Mughal，Bushra,&Wang，Shuqiang.(2023).Addictive brain-network identification by spatial attention recurrent network with feature selection.Brain Informatics,10(1).

Gong，Changwei,et al."Addictive brain-network identification by spatial attention recurrent network with feature selection".Brain Informatics 10.1(2023).