Abstracts

Characterizing iEEG-fMRI Coupling in Epilepsy Patients Across Seizure States and Tissue Types

Abstract number : 2.216
Submission category : 5. Neuro Imaging / 5B. Functional Imaging
Year : 2023
Submission ID : 346
Source : www.aesnet.org
Presentation date : 12/3/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Marc Jaskir, BS – University of Pennsylvania

Alfredo Lucas, MD/PhD Student – University of Pennsylvania; Akash Pattnaik, Phd Student – University of Pennsylvania; Nishant Sinha, PhD – University of Pennsylvania; Joel Stein, MD, PhD – University of Pennsylvania; Sandhitsu Das, PhD – University of Pennsylvania; Kathryn Davis, MD, MSTR – University of Pennsylvania

Rationale:
Intracranial EEG (iEEG) is an essential tool for seizure localization in epilepsy patients. However, iEEG is a highly invasive diagnostic procedure and its incomplete spatial coverage imposes limitations for whole-brain functional mapping approaches, which may reveal global network properties that are relevant to seizure onset and propagation. Multimodal approaches combining iEEG with functional magnetic resonance imaging (fMRI) may afford complementary measures of functional organization that exploit each modality’s strengths in temporal resolution and spatial coverage, respectively. However, iEEG-fMRI coupling is poorly understood1 and their relationship is further complicated by modality-specific differences between grey and white matter signal properties2,3 which are understood to change over ictogenesis. Therefore, we thoroughly characterized iEEG-fMRI coupling in epilepsy patients during different stages of ictogenesis and across different tissue types.

Methods:
Using resting state fMRI and interictal, preictal, and ictal iEEG data from 32 epilepsy patients, we evaluated differences in average iEEG-fMRI correlations and the associations between their graph theoretic properties (global efficiency) across different tissue types, seizure states, and frequency bands. We also used dynamic functional connectivity to elucidate seizure state-specific changes in iEEG-fMRI coupling over time.

Results:
We found that ictal iEEG-fMRI coupling was higher on average in white matter subnetworks (r = 0.41) than grey matter subnetworks (r = 0.31, p < 0.05) and highest in the alpha (8-12 Hz) frequency band. Correspondence between interictal iEEG and fMRI global efficiency increased over ictogenesis only in white matter, particularly between the interictal (r=0.16) and ictal period (r = 0.19, p < 0.05). Average iEEG-fMRI coupling was considerably dynamic over the course of seizures, exhibiting lower coupling immediately after seizure onset relative to 50-60 seconds post-onset (p < 0.001).
Neuro Imaging