Abstracts

Rationale: Electrical status epilepticus of sleep (ESES) is an electrographic pattern that can variably be associated with neurocognitive and behavioral decline. The neurobiological basis of these functional declines, however, has not been elucidated. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate the topological network effects of ESES on a cohort of children with ESES without any structural MRI abnormalities.

Methods: Eight minutes of resting state fMRI data were collected from nine children with imaging-negative ESES and 22 healthy controls (HC). The functional imaging was co-registered to the MNI template, and the cortex was parcellated into 360 regions of interest. Whole brain networks were calculated using the mean connectivity values between all cortical parcels. Individual network graphs for three intrinsic cognitive networks (ICNs)—the default mode (DMN), dorsal attention (DAN), and frontoparietal (FPN) networks—were extracted. Differences in mean connectivity strength and graph features were measured globally and within each of the ICNs. Permutation testing was used to test for group differences across density-based network thresholds.

Results: Mean functional connectivity is reduced in children with ESES compared to HC globally (HC 0.22, ESES 0.20, p = 0.005) and within the intrinsic cognitive networks (DMN: HC 0.25, ESES 0.21, p = 0.004; DAN: HC 0.27, ESES 0.22, p = 0.001; FPN: HC 0.24, ESES 0.22, p = 0.04; Figure 1A–D). After normalizing for the whole brain differences, however, network-specific differences in mean connectivity are attenuated (DMN: HC 1.12, ESES 1.07, p = 0.11; DAN: HC 1.20, ESES 1.10, p = 0.03; FPN: HC 1.09, ESES 1.10, p = 0.58; Figure1E–G). Global topology showed more random features in ESES compared to HC (Figure 2A–C) with lower local efficiency (AUC difference: 0.006; p = 0.048), a lower clustering coefficient (AUC difference: 0.011; p = 0.05) and a more fragmented modular structure (AUC for ESES – HC: 8.713; p = 0.004). While there was a trend toward a shorter average path length this did not reach statistical significance (AUC difference: 0.009; p = 0.11). Within the individual ICNs, however, there was a significantly lower clustering coefficient in both the default mode (AUC difference: 0.019; p = 0.01) and dorsal attention (AUC difference: 0.041; p = 0.003) networks but not in the frontoparietal network (AUC difference: 0.015; p = 0.06; Figure 2D–F).

Conclusions: In children with ESES, global connectivity shows decreased strength and a more random topology. These findings are also reflected in the individual ICNs, although these differences were diminished when accounting for global differences. Investigation into the clinical and cognitive correlates of these topological changes in the cortical networks of children with ESES is needed.

Funding: Please list any funding that was received in support of this abstract.: This work was supported in part by a grant from the National Institutes of Health, National Institute of Neurological Disorders and Stroke (NIH K12 NS089417).