mlsanityData to 7 Oct 2026

Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis

arXiv 2003.10613 ↗First posted 24 Mar 2020cs.LG stat.MLcited by 57

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Abstract (arXiv)

The Blood-Oxygen-Level-Dependent (BOLD) signal of resting-state fMRI (rs-fMRI) records the temporal dynamics of intrinsic functional networks in the brain. However, existing deep learning methods applied to rs-fMRI either neglect the functional dependency between different brain regions in a network or discard the information in the temporal dynamics of brain activity. To overcome those shortcomings, we propose to formulate functional connectivity networks within the context of spatio-temporal graphs. We train a spatio-temporal graph convolutional network (ST-GCN) on short sub-sequences of the BOLD time series to model the non-stationary nature of functional connectivity. Simultaneously, the model learns the importance of graph edges within ST-GCN to gain insight into the functional connectivities contributing to the prediction. In analyzing the rs-fMRI of the Human Connectome Project (HCP, N=1,091) and the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA, N=773), ST-GCN is significantly more accurate than common approaches in predicting gender and age based on BOLD signals. Furthermore, the brain regions and functional connections significantly contributing to the predictions of our model are important markers according to the neuroscience literature.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 13; 2023: 8; 2024: 8; 2025: 11; 2026: 9.

57 papers.

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  1. 2021Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attentioncited by 86
  2. 2021Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Futurecited by 67
  3. 2022A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspectivecited by 56
  4. 2023SwiFT: Swin 4D fMRI Transformercited by 36
  5. 2023NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomicscited by 33
  6. 2022BolT: Fused Window Transformers for fMRI Time Series Analysiscited by 23
  7. 2021Self-Supervised Transformers for fMRI representationcited by 17
  8. 2024Graph Neural Networks for Brain Graph Learning: A Surveycited by 13
  9. 2021Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivitycited by 9
  10. 2022Joint Graph Convolution for Analyzing Brain Structural and Functional Connectomecited by 9
  11. 2021A deep learning model for data-driven discovery of functional connectivitycited by 8
  12. 2021Dynamic Adaptive Spatio-temporal Graph Convolution for fMRI Modellingcited by 7
38 more
  1. 2022Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applicationscited by 7
  2. 2023Dynamic Brain Transformer with Multi-level Attention for Functional Brain Network Analysiscited by 7
  3. 2025Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Datacited by 6
  4. 2021Heterogeneous Graph-Based Multimodal Brain Network Learningcited by 5
  5. 2021Learning to Model the Relationship Between Brain Structural and Functional Connectomescited by 5
  6. 2023Meta Transfer of Self-Supervised Knowledge: Foundation Model in Action for Post-Traumatic Epilepsy Predictioncited by 5
  7. 2022Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applicationscited by 4
  8. 2022DynDepNet: Learning Time-Varying Dependency Structures from fMRI Data via Dynamic Graph Structure Learningcited by 4
  9. 2022Benchmarking Graph Neural Networks for FMRI analysiscited by 4
  10. 2023Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRIcited by 4
  11. 2023Preserving Specificity in Federated Graph Learning for fMRI-based Neurological Disorder Identificationcited by 4
  12. 2022Improving the Diagnosis of Psychiatric Disorders with Self-Supervised Graph State Space Modelscited by 3
  13. 2024Joint-Embedding Masked Autoencoder for Self-supervised Learning of Dynamic Functional Connectivity from the Human Braincited by 3
  14. 2024Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equationcited by 3
  15. 2026ODEBrain: Continuous-Time EEG Graph for Modeling Dynamic Brain Networkscited by 3
  16. 2022Deep Dynamic Effective Connectivity Estimation from Multivariate Time Seriescited by 2
  17. 2022Spatial Temporal Graph Convolution with Graph Structure Self-learning for Early MCI Detectioncited by 2
  18. 2024Spatial Craving Patterns in Marijuana Users: Insights from fMRI Brain Connectivity Analysis with High-Order Graph Attention Neural Networkscited by 2
  19. 2024ACTION: Augmentation and Computation Toolbox for Brain Network Analysis with Functional MRIcited by 2
  20. 2024STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FCcited by 2
  21. 2025BrainNetMLP: An Efficient and Effective Baseline for Functional Brain Network Classificationcited by 2
  22. 2025Hierarchical Characterization of Brain Dynamics via State Space-based Vector Quantizationcited by 2
  23. 2026Moving Beyond Functional Connectivity: Time-Series Modeling for fMRI-Based Brain Disorder Classificationcited by 2
  24. 2026NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoningcited by 2
  25. 2022fMRI-S4: learning short- and long-range dynamic fMRI dependencies using 1D Convolutions and State Space Modelscited by 1
  26. 2024Generalizable Representation Learning for fMRI-based Neurological Disorder Identificationcited by 1
  27. 2025BrainATCL: Adaptive Temporal Brain Connectivity Learning for Functional Link Prediction and Age Estimationcited by 1
  28. 2022Inferring Brain Dynamics via Multimodal Joint Graph Representation EEG-fMRIcited by 0
  29. 2022Toward Improved Generalization: Meta Transfer of Self-supervised Knowledge on Graphscited by 0
  30. 2023Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRIcited by 0
  31. 2023Spatial-Temporal DAG Convolutional Networks for End-to-End Joint Effective Connectivity Learning and Resting-State fMRI Classificationcited by 0
  32. 2024SpaRG: Sparsely Reconstructed Graphs for Generalizable fMRI Analysiscited by 0
  33. 2025Towards Zero-Shot Task-Generalizable Learning on fMRIcited by 0
  34. 2025ASD Classification on Dynamic Brain Connectome using Temporal Random Walk with Transformer-based Dynamic Network Embeddingcited by 0
  35. 2025Brain Network Classification Based on Graph Contrastive Learning and Graph Transformercited by 0
  36. 2025Comorbidity-Informed Transfer Learning for Neuro-developmental Disorder Diagnosiscited by 0
  37. 2025SlepNet: Spectral Subgraph Representation Learning for Neural Dynamicscited by 0
  38. 2025Defining and Benchmarking a Data-Centric Design Space for Brain Graph Constructioncited by 0

50 most cited of 57 All 57 (JSON)