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Canna~Fangled Abstracts

Functional Connectivity Derived From Electroencephalogram in Pharmacoresistant Epileptic Encephalopathy Using Cannabidiol as Adjunctive Antiepileptic Therapy

By February 23, 2021March 16th, 2021No Comments

doi: 10.3389/fnbeh.2021.604207. eCollection 2021.

Affiliations 

Abstract

To explore brain function using functional connectivity and network topology derived from electroencephalogram (EEG) in patients with pharmacoresistant epileptic encephalopathy with cannabidiol as adjunctive antiepileptic treatment. Sixteen epileptic patients participated in the study, six of whom had epileptic encephalopathy with a stable dose of cannabidiol Epidiolex (CBD) as adjunctive therapy. Functional connectivity derived from EEG was analyzed based on the synchronization likelihood (SL). The analysis also included reconstructing graph-theoretic measures from the synchronization matrix. Comparison of functional connectivity data between each pathological group with the control group was carried out using a nonparametric permutation test applied to SL values between pairs of electrodes for each frequency band. To compare the association patterns between graph-theoretical properties of each pathological group with the control group, Z Crawford was calculated as a measure of distance. There were differences between pairs of electrodes in all frequency bands evaluated in encephalopathy epileptic patients with CBD adjunctive therapy compared with the control (p < 0.05, permutation test). In the epileptic encephalopathy group without CBD therapy, the SL values were higher than in the control group for the beta, theta, and delta EEG frequency bands, and lower for the alpha frequency band. Interestingly, patients who had CBD as adjunctive therapy demonstrated greater synchronization for all frequency bands, showing less spatial distribution for alpha frequency compared with the control. When comparing both epileptic groups, those patients who had adjunctive CBD treatment also showed increased synchronization for all frequency bands. In epileptic encephalopathy with adjunctive CBD therapy, the pattern of differences for graph-theoretical measures according to Z Crawford indicated less segregation and greater integration suggesting a trend towards the random organization of the network principally for alpha and beta EEG bands. This exploratory study revealed a tendency to an overconnectivity with a random network topology mainly for fast EEG bands in epileptic encephalopathy patients using CBD adjunctive therapy. It can therefore be assumed that the CBD treatment could be related to inhibition of the transition of the interictal to ictal state and/or to the improvement of EEG organization and brain function.

 

Keywords: cannabidiol, electroencephalogram, epileptic encephalopathy, functional connectivity, graph theory

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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References

    1. Allendorfer J. B., Szaflarski J. P. (2017). Neuroimaging studies towards understanding the central effects of pharmacological cannabis products on patients with epilepsy. Epilepsy Behav. 70, 349–354. 10.1016/j.yebeh.2016.11.020 – DOI – PubMed
    1. Allendorfer J. B., Nenert R., Bebin E. M., Gaston T. E., Grayson L. E., Hernando K. A., et al. . (2019). fMRI study of cannabidiol-induced changes in attention control in treatment-resistant epilepsy. Epilepsy Behav. 96, 114–121. 10.1016/j.yebeh.2019.04.008 – DOI – PubMed
    1. Bartolomei F., Bettus G., Stam C. J., Guye M. (2013). Interictal network properties in mesial temporal lobe epilepsy: a graph theoretical study from intracerebral recordings. Clin. Neurophysiol. 124, 2345–2353. 10.1016/j.clinph.2013.06.003 – DOI – PubMed
    1. Bartolomei F., Bosma I., Klein M., Baayen J. C., Reijneveld J. C., Postma T. J., et al. . (2006). Disturbed functional connectivity in brain tumour patients: evaluation by graph analysis of synchronization matrices. Clin. Neurophysiol. 117, 2039–2049. 10.1016/j.clinph.2006.05.018 – DOI – PubMed
    1. Bartolomei F., Lagarde S., Wendling F., McGonigal A., Jirsa V., Guye M., et al. . (2017). Defining epileptogenic networks: contribution of SEEG and signal analysis. Epilepsia 58, 1131–1147. 10.1111/epi.13791 – DOI – PubMed

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