Connectivity Analysis in the Stormy Phase of EMAtS Reveals a Distinct Pattern from LGS
Abstract number :
2.105
Submission category :
3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG
Year :
2023
Submission ID :
546
Source :
www.aesnet.org
Presentation date :
12/3/2023 12:00:00 AM
Published date :
Authors :
First Author: Lin Li, PhD – University of North Texas
Presenting Author: Purva Choudhari, MD – UT Southwestern
Charuta Joshi, MBBS, FAES, CSCN(EEG) – Professor, Pediatric Neurology, UTSW, Childrens Health Dallas; Anatol Bragin, PhD – Professor, UCLA
Rationale:
Patients with Epilepsy with Myoclonic Atonic Seizures (EMAtS) that enter the Stormy Phase (SP) not only have seizures but their EEG changes from previously normal to one that shows background slowing and multifocal spike wave activity. These EEG findings are also present in patients with Lennox Gastaut syndrome which is a differential diagnosis for EMAtS and another Developmental and Epileptic Encephalopathy (DEE). We hypothesize that patients in the Stormy phase have distinct EEG from those with LGS. We sought to identify the connectivity patterns of patients who are normal those in SP and those with LGS. We examined the effects of grouping on functional brain connectivity using scalp EEG data recorded from 14 patients.
Methods:
Data were recorded from 14 patients (Group 1, n=5; Group 2, n=4; Group 3, n=5) using a 256Hz sampling frequency in the multichannel scalp EEG system. The data were preprocessed using the pipeline, which included a high-pass filter of 1Hz, automatic motion artifact rejection [1], and scalp current density regression [2]. The cleaned data, totaling 492 hours, were then analyzed for functional brain connectivity using broadband coherence coupling from 3-70Hz, as suggested by [3]. Fourteen brain regions, defined as regions of interest (ROIs), were selected as nodes for the functional connectivity matrix. The total connectivity strength was computed using Fisher-Z transformation.
Results:
Group Three showed a significant increase (P < 0.001) in total connectivity strength compared to Group Two and Group One. Group Three also exhibited significant changes in between-region connectivity, including prefrontal to frontal cortex (P < 0.001), prefrontal to central line (P < 0.001), prefrontal to parietal (P < 0.001), and frontal cortex to parietal cortex (P=0.013), as determined by one-way ANOVA. No significant differences in total connectivity or between-region connectivity were found between Group One and Group Two. However, increased within-region connectivity was observed in the prefrontal cortex in Group 2 (P < 0.001).
Neurophysiology