BACE: Behavior-Adaptive Connectivity Estimation for Interpretable Graphs of Neural Dynamics
This work addresses the need for predictive and interpretable models of neural dynamics in neuroscience, offering a tool for generating hypotheses about subcortical coordination during behavior, though it is incremental as it builds on existing connectivity estimation methods.
The paper tackled the problem of modeling interpretable brain connectivity from neural data by introducing BACE, a framework that learns phase-specific directed connectivity from local field potentials, achieving accurate graph recovery on synthetic data and providing explicit connectivity matrices for human data during a reaching task.
Understanding how distributed brain regions coordinate to produce behavior requires models that are both predictive and interpretable. We introduce Behavior-Adaptive Connectivity Estimation (BACE), an end-to-end framework that learns phase-specific, directed inter-regional connectivity directly from multi-region intracranial local field potentials (LFP). BACE aggregates many micro-contacts within each anatomical region via per-region temporal encoders, applies a learnable adjacency specific to each behavioral phase, and is trained on a forecasting objective. On synthetic multivariate time series with known graphs, BACE accurately recovers ground-truth directed interactions while achieving forecasting performance comparable to state-of-the-art baselines. Applied to human subcortical LFP recorded simultaneously from eight regions during a cued reaching task, BACE yields an explicit connectivity matrix for each within-trial behavioral phase. The resulting behavioral phase-specific graphs reveal behavior-aligned reconfiguration of inter-regional influence and provide compact, interpretable adjacency matrices for comparing network organization across behavioral phases. By linking predictive success to explicit connectivity estimates, BACE offers a practical tool for generating data-driven hypotheses about the dynamic coordination of subcortical regions during behavior.