Abstracts

Network mechanisms of working memory dysfunction across the epilepsy spectrum: A task-based dynamic fMRI analysis

Abstract number : 545
Submission category : 5. Neuro Imaging / 5B. Functional Imaging
Year : 2020
Submission ID : 2422886
Source : www.aesnet.org
Presentation date : 12/6/2020 5:16:48 PM
Published date : Nov 21, 2020, 02:24 AM

Authors :
Lorenzo Caciagli, University College London Queen Square Institute of Neurology; Xiaosong He - University of Pennsylvania; Urs Braun - University of Pennsylvania; Bianca De Blasi - UCL; Britta Wandschneider - UCL Queen Square Institute of Neurology; Salli


Rationale:
Working memory (WM) is a building block for all cognitive tasks, and is impaired in focal epilepsies, including temporal and frontal lobe epilepsy (TLE, FLE), as well as in genetic generalized syndromes, such as juvenile myoclonic epilepsy (JME). Prior functional MRI (fMRI) work used conventional, static metrics of activity and connectivity, that cannot capture the time-varying, dynamic reconfigurations of brain networks elicited by task demands. Thus, network mechanisms accounting for epilepsy-related WM dysfunction remain poorly characterized, and knowledge of whether different syndromes present with unique neural signatures, which can inform targeted treatment approaches, is also lacking. Here, we apply the emerging framework of dynamic network analysis to a large (n=274) fMRI sample, decode network mechanisms of WM dysfunction in epilepsy, and identify syndrome-specific and shared patterns in three common syndromes, capturing trait distributions across the disease spectrum.
Method:
We analyzed 120 TLE patients (59 left), 62 FLE patients (36 left), 37 JME patients, and 55 controls comparable in age, sex, and handedness, who completed IQ, WM and mental flexibility tests, and a 3T-fMRI visuo-spatial WM task. After preprocessing and regional parcellation, we applied open source MATLAB code to obtain sliding windows of functional connectivity matrices, coupled these into a multi-layer network, derived network modules, and tracked their evolution during the task (Fig.1). To quantify dynamic reconfigurations on the backbone of canonical subcortical and cortical (Yeo) networks, we estimated (a) recruitment, the stability of a given cognitive network, and (b) integration, the frequency of transient interactions among different networks. We compared groups via multivariate analysis of variance, after adjusting for age and sex (pFDR< 0.05).
Results:
TLE and FLE had lower scores than controls in all tests; only mental flexibility was impaired in JME. Compared to controls (Fig.2), all patient groups had reduced stability of salience (SAL) and default-mode networks (DMN). Enhanced subcortical and reduced frontoparietal stability were common to JME and FLE, while impaired stability of the dorsal attention network (DAN) was specific to TLE. The DMN had abnormally high integration to “task-positive” networks (DAN, SAL) in both focal epilepsies. In JME, DMN changes were less marked, whereas we found enhanced integration of the somatomotor with both DAN and frontoparietal control network, that discriminated patients from controls (AUC= 0.73/0.69, p< 0.001/0.004). Increased integration between somatomotor and frontoparietal control networks, however, was also detected in FLE and TLE. Task performance significantly correlated with dynamic metrics (partial Spearman rho= 0.17/-0.19, p< 0.008 for SAL stability and integration with DMN).
Neuro Imaging