Abstract
Refractory epilepsy is a chronic brain network disorder characterized by unresponsiveness to multiple (>2) anti-epileptic drugs. Cannabidiol, a non-psychotropic neuroactive substance, is an emerging anti-epileptic treatment that was recently approved by the US Food and Drug Administration for the treatment of refractory epilepsy, especially Lennox Gastaut syndrome and Dravet syndrome. Here, we evaluated associations between global brain network dynamics and related changes and responsiveness to cannabidiol therapy using a combination of electroencephalography phase coherence and graph theoretical analyses. Refractory epilepsy patients with Lennox Gastaut syndrome or Dravet syndrome underwent serial electroencephalography testing prior to and during cannabidiol treatment. Patients showing greater than 70% seizure frequency reduction were classified as treatment responders for the purposes of this study. We calculated inter-electrode electroencephalography phase coherence in delta (1-3 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (13-30 Hz) frequency bands. Graph theoretical analysis of brain network dynamics was extracted from phase coherence to evaluate measures of network integration (i.e. characteristic path length, global efficiency and degree) and segregation (i.e. modularity and transitivity). We found that responders, relative to non-responders, showed increased network integration-as indexed by relatively higher global efficiency and lower degree-and increased network segregation-as indexed by relatively higher modularity-exclusively in the beta-frequency band. We also found that larger cannabidiol dosages were associated with increased network integration-as indexed by higher global efficiency with increasing dose-and increased network segregation-as indexed by lower transitivity with increasing dose-in the delta, theta and alpha frequency bands. In summary, we demonstrate novel effects of cannabidiol on brain network dynamics with important implications for the treatment of refractory epilepsy and, possibly, across broader research applications in the future.