Cargando…

Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Anderson, David E, Madhavan, Deepak, Swaminathan, Arun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751013/
https://www.ncbi.nlm.nih.gov/pubmed/33376981
http://dx.doi.org/10.1093/braincomms/fcaa140
_version_ 1783625588407271424
author Anderson, David E
Madhavan, Deepak
Swaminathan, Arun
author_facet Anderson, David E
Madhavan, Deepak
Swaminathan, Arun
author_sort Anderson, David E
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7751013
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-77510132020-12-28 Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy Anderson, David E Madhavan, Deepak Swaminathan, Arun Brain Commun Original Article 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. Oxford University Press 2020-08-31 /pmc/articles/PMC7751013/ /pubmed/33376981 http://dx.doi.org/10.1093/braincomms/fcaa140 Text en © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Anderson, David E
Madhavan, Deepak
Swaminathan, Arun
Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title_full Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title_fullStr Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title_full_unstemmed Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title_short Global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
title_sort global brain network dynamics predict therapeutic responsiveness to cannabidiol treatment for refractory epilepsy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751013/
https://www.ncbi.nlm.nih.gov/pubmed/33376981
http://dx.doi.org/10.1093/braincomms/fcaa140
work_keys_str_mv AT andersondavide globalbrainnetworkdynamicspredicttherapeuticresponsivenesstocannabidioltreatmentforrefractoryepilepsy
AT madhavandeepak globalbrainnetworkdynamicspredicttherapeuticresponsivenesstocannabidioltreatmentforrefractoryepilepsy
AT swaminathanarun globalbrainnetworkdynamicspredicttherapeuticresponsivenesstocannabidioltreatmentforrefractoryepilepsy