STNAGNN: Spatiotemporal Node Attention Graph Neural Network for Task-based fMRI Analysis
<|reference_start|>STNAGNN: Spatiotemporal Node Attention Graph Neural Network for Task-based fMRI Analysis: Task-based fMRI uses actions or stimuli to trigger task-specific brain responses and measures them using BOLD contrast. Despite the significant task-induced spatiotemporal brain activation fluctuations, most studies on task-based fMRI ignore the task context information aligned with fMRI and consider task-based fMRI a coherent sequence. In this paper, we show that using the task structures as data-driven guidance is effective for spatiotemporal analysis. We propose STNAGNN, a GNN-based spatiotemporal architecture, and validate its performance in an autism classification task. The trained model is also interpreted for identifying autism-related spatiotemporal brain biomarkers.<|reference_end|>
@article{wang2024stnagnn:,
    title={STNAGNN: Spatiotemporal Node Attention Graph Neural Network for
  Task-based fMRI Analysis},
    author={Jiyao Wang, Nicha C. Dvornek, Peiyu Duan, Lawrence H. Staib, Pamela
  Ventola, James S. Duncan},
    journal={arXiv preprint arXiv:2406.12065},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.12065},
    primaryClass={cs.LG q-bio.NC}
}