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arXiv Machine Learning By Yiran Huang, Amirhossein Nouranizadeh, Christine Ahrends, Mengjia Xu

BrainATCL: Adaptive Temporal Brain Connectivity Learning for Functional Link Prediction and Age Estimation

Read the original on arXiv Machine Learning →

BrainATCL is an unsupervised, nonparametric framework that learns adaptive temporal brain connectivity from resting‑state fMRI data. It dynamically adjusts the lookback window for each snapshot based on newly added edges and encodes graph sequences with a GINE‑Mamba2 backbone, incorporating brain‑structure and function‑informed edge attributes. The method is evaluated on functional link prediction and age estimation, showing superior performance and strong generalization, even across sessions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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