Using Coherence to Study Changes in Pre-event Connectivity in a Novel Animal Model of Mesial Temporal Lobe Epilepsy
Abstract number :
3.073
Submission category :
1. Basic Mechanisms / 1E. Models
Year :
2022
Submission ID :
2205045
Source :
www.aesnet.org
Presentation date :
12/5/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:27 AM
Authors :
Zeyun Zhou, PharmD, MPH – Yale University; Mani Ratnesh Sandhu, MD, MHS – Yale University; Abhijeet Gummadavelli, MD – Yale University; Mark Bower, PhD – Yale University; Roni Dhaher, PhD – Yale University; Victoria Phoumthipphavong, BS – Yale University; Hitten Zaveri, PhD – Yale University; Dennis Spencer, MD – Yale University; Tore Eid, MD, PhD – Yale University; Jason Gerrard, MD, PhD, FAANS – Yale University
Rationale: Defining the networks of seizure initiation and propagation is paramount for our understanding of epileptogenesis, and the development of new treatment modalities. To understand and explore the “network theory” in epilepsy, we used novel animal model of mesial temporal lobe epilepsy (MSO model) implanted with multiple cortical and hippocampal tetrodes to define changes in network before an epileptic event.
Methods: Male Sprague-Dawley rats were surgically implanted with a microdialysis cannula and osmotic pump infusing methionine sulfoximine (MSO) targeting the ventral dentate gyrus and a chronic microdrive containing multiple, independently movable tetrodes/electrodes in a separate craniotomy targeting Cortex and hippocampal cell layers (CA1 and DG). Signals from each channel were acquired using a high-density Digital Lynx data acquisition system (Neuralynx, Bozeman, MT). Each animal then underwent recording sessions for several hours expanding over many days. We used changes in Teager energy operator to identify and detect epileptic discharges or seizures. These were visually inspected and classified by three independent observers as polyspike events, seizures, or noise. Changes in functional connectivity were measured at multiple time points prior to each event using a magnitude squared coherence estimate.
Results: We detected 208 events, of which 64.4% were polyspikes, 17.8% were brief ictal or interictal rhythmic discharges, 4.8% were seizures, 5.3% were noise and 7.7% events remained unclear. While there was no difference in global coherence between events, we observed increase in global coherence between tetrodes 1 second before the event (10 seconds: 0.29; 1 second: 0.51).
Conclusions: These preliminary results highlight a potentially robust pipeline that is capable of automatic detection of epileptic discharges and seizures and how we can implement it to study temporal relationships between regions before, during or after an event.
Funding: Yale Center for Clinical Investigation (YCCI) Scholar Award and the Swebilius Foundation
Basic Mechanisms