Bethany C. Routley

The paper predicts resting-state functional connectivity using microstructural metrics and finds that streamline count and myelin measures yield the most accurate predictions.

This study investigates electrophysiological network changes in adults with neurodevelopmental risk copy number variants using MEG, finding decreased connectivity and network segregation differences.

This study uses MEG energy landscape analysis to show JME patients have altered network dynamics in the frontoparietal network, with fewer local energy minima and reduced time in characteristic energy basins.

This study evaluates the reliability of static and dynamic functional connectivity metrics from resting-state MEG data, finding that dynamic metrics and chronnectomic parameters are more reliable than static node-wise metrics.