Clinical trial NCT01738516: Contribution of High Resolution EEG Functional Connectivity Measures to Presurgical Evaluation of Patients With Intractable Epilepsy
Official title: Contribution of High Resolution EEG Functional Connectivity Measures to Presurgical Evaluation of Patients With Intractable Epilepsy
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Epilepsy
Lead sponsor: Rennes University Hospital
Sponsor class: OTHER
First posted: 2012-11-30
Enrollment: 44
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: SINGLE_GROUP
Primary purpose: OTHER

Brief summary: Electroencephalography (EEG) with very high spatial resolution (HR-EEG, 256 electrodes) allow for better analysis of local and global activity of the cerebral cortex, as compared with conventional EEG. Since January 2012, the Neurology Department of CHU Rennes is the first clinical service in France equipped with such a system.

Applied to HR-EEG recordings, brain connectivity methods are likely to provide essential information (in the form of "connectivity graphs") on cortical networks, either dysfunctional or not, involved in the generation of interictal paroxysms (like spikes or spike-waves) and during seizures.

So far, many methods have been proposed (see for a review: Wendling et al., 2009; Wendling et al., 2010). However, since each method is highly sensitive to the type of model that is assumed for the underlying relationship between distinct brain regions (Ansari-Asl et al., 2006), none of them has yet demonstrated its effectiveness.


Eligibility criteria: Inclusion Criteria Patients:

* Being more than 18 years old,
* Having a chronic partial epilepsy resistant to medical treatments well administered and well followed in the course of pre-surgical assessment.

Inclusion Criteria Healthy Volunteers:

* Being French native speaker,
* Being more than 18 years old,
* Being right-handed.

Exclusion Criteria Patients:

* All patients for whom a preoperative surgical exam is not suitable,
* Any patient with psychiatric disease or intellectual disorder such that informed consent could not be obtained,
* Any patient with no abnormal EEG during intercritical phases,
* All patients presenting psychiatric, neuropsychological or developmental difficulties in addition to epilepsy,
* Adult persons subject to legal protection (judicial protection, temporary guardianship/guardianship, administrative supervision), persons deprived of their liberty and pregnant or lactating women.

Exclusion Criteria Healthy Volunteers:

* The presence of any psychiatric, neuropsychological, and developmental disorder,
* Any uncorrected visual impairment,
* Any trouble or delay in learning to read / speak or write French,
* Being fully bilingual or multilingual
* Medication, treatment and / or substances that may alter or modify brain functions,
* Adult persons subject to legal protection (judicial protection, temporary guardianship/guardianship, administrative supervision), persons deprived of their liberty and pregnant or lactating women.

Primary outcomes:
measure: The quality of matching between i) the graphs produced by the evaluated connectivity method(s) applied to the HR-EEG and ii) the results of the visual analysis typically performed by an expert on the standard EEG recorded during intercritical phase.
timeFrame: 2 years
Secondary outcomes:
measure: The quality of matching between i) the connectivity graphs obtained from control subjects performing a well defined cognitive task to ii) data from the literature on networks activated and sustaining these cognitive processes.
timeFrame: 2 years
Other outcomes:
Locations:
city: Rennes
country: France
facility: Rennes University Hospital
state: Brittany
Study officials:
affiliation: Rennes University Hospital
name: Arnaud Biraben
role: PRINCIPAL_INVESTIGATOR
References:
citation: Mheich A, Hassan M, Khalil M, Gripon V, Dufor O, Wendling F. SimiNet: A Novel Method for Quantifying Brain Network Similarity. IEEE Trans Pattern Anal Mach Intell. 2018 Sep;40(9):2238-2249. doi: 10.1109/TPAMI.2017.2750160. Epub 2017 Sep 8.
citation: Kabbara A, El Falou W, Khalil M, Wendling F, Hassan M. The dynamic functional core network of the human brain at rest. Sci Rep. 2017 Jun 7;7(1):2936. doi: 10.1038/s41598-017-03420-6.
citation: Mheich A, Hassan M, Khalil M, Berrou C, Wendling F. A new algorithm for spatiotemporal analysis of brain functional connectivity. J Neurosci Methods. 2015 Mar 15;242:77-81. doi: 10.1016/j.jneumeth.2015.01.002. Epub 2015 Jan 10.
citation: Hassan M, Merlet I, Mheich A, Kabbara A, Biraben A, Nica A, Wendling F. Identification of Interictal Epileptic Networks from Dense-EEG. Brain Topogr. 2017 Jan;30(1):60-76. doi: 10.1007/s10548-016-0517-z. Epub 2016 Aug 22.
citation: Rizkallah J, Benquet P, Kabbara A, Dufor O, Wendling F, Hassan M. Dynamic reshaping of functional brain networks during visual object recognition. J Neural Eng. 2018 Oct;15(5):056022. doi: 10.1088/1741-2552/aad7b1. Epub 2018 Aug 2.
citation: Hassan M, Shamas M, Khalil M, El Falou W, Wendling F. EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome. PLoS One. 2015 Sep 17;10(9):e0138297. doi: 10.1371/journal.pone.0138297. eCollection 2015.
citation: Hassan M, Dufor O, Merlet I, Berrou C, Wendling F. EEG source connectivity analysis: from dense array recordings to brain networks. PLoS One. 2014 Aug 12;9(8):e105041. doi: 10.1371/journal.pone.0105041. eCollection 2014.
citation: Hassan M, Benquet P, Biraben A, Berrou C, Dufor O, Wendling F. Dynamic reorganization of functional brain networks during picture naming. Cortex. 2015 Dec;73:276-88. doi: 10.1016/j.cortex.2015.08.019. Epub 2015 Sep 28.