New EEG/MEG methods unlock millisecond-resolution brain network mapping

Electroencephalography (EEG) and magnetoencephalography (MEG) have long offered noninvasive windows into brain activity, but extracting reliable network-level insights has been challenging. In a new arXiv paper, researchers Richard Leahy and Takfarinas Medani provide a comprehensive methodological guide for using these techniques to map functional and effective brain networks. They emphasize the importance of subject-specific head modeling and accurate source reconstruction to overcome volume conduction and signal leakage—key obstacles that have historically muddied connectivity analyses.

The review covers a full toolkit of connectivity measures: coherence, phase synchronization, amplitude envelope correlation, Granger causality, dynamic causal modeling, and transfer entropy, each with its assumptions and best-use cases. The authors present end-to-end analysis pipelines using the open-source Brainstorm platform, which facilitates reproducible research. They also explore emerging approaches like time-varying connectivity and cross-frequency interactions, showing how these methods can reveal brain dynamics in both healthy and diseased states. This work serves as a practical roadmap for neuroscientists and advanced students looking to leverage millisecond-resolution electrophysiology for network neuroscience.