dc.contributor.author | Lopes, M | |
dc.contributor.author | Richardson, MP | |
dc.contributor.author | Abela, E | |
dc.contributor.author | Rummel, C | |
dc.contributor.author | Schindler, K | |
dc.contributor.author | Goodfellow, M | |
dc.contributor.author | Terry, J | |
dc.date.accessioned | 2018-03-07T15:34:15Z | |
dc.date.issued | 2018-03-01 | |
dc.description.abstract | Recent studies have shown that mathematical models can be used to analyze brain
networks by quantifying how likely they are to generate seizures. In particular, we have
introduced the quantity termed brain network ictogenicity (BNI), which was demonstrated
to have the capability of differentiating between functional connectivity (FC) of healthy
individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and
predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal
intracranial electroencephalography (iEEG). This modeling framework is based on the
assumption that the inferred FC provides an appropriate representation of an ictogenic
network, i.e., a brain network responsible for the generation of seizures. However, FC
networks have been shown to change their topology depending on the state of the brain.
For example, topologies during seizure are different to those pre- and post-seizure. We
therefore sought to understand how these changes affect BNI. We studied peri-ictal
iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found
that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However,
elevated ictal BNI was not observed in every individual, rather it was typically observed
in those who had good post-operative seizure control. We therefore hypothesize that
elevated ictal BNI is indicative of an ictogenic network being appropriately represented in
the FC. We evidence this by demonstrating superior model predictions for post-operative
seizure control in patients with elevated ictal BNI. | en_GB |
dc.description.sponsorship | ML, MG, MR, and JT gratefully acknowledge funding from
the Medical Research Council via grant MR/K013998/1. MG,
MR, and JT further acknowledge the financial support of the
EPSRC via grant EP/N014391/1. The contribution of MG and
JT was further generously supported by a Wellcome Trust
Institutional Strategic Support Award (WT105618MA). MR
and EA are supported by the National Institute for Health
Research (NIHR) Biomedical Research Centre at the South
London and Maudsley NHS Foundation Trust. KS gratefully
acknowledges support by the Swiss National Science Foundation
(SNF 32003B_155950). | en_GB |
dc.identifier.citation | Vol. 9: 98 | en_GB |
dc.identifier.doi | 10.3389/fneur.2018.00098 | |
dc.identifier.uri | http://hdl.handle.net/10871/31945 | |
dc.language.iso | en | en_GB |
dc.publisher | Frontiers Media | en_GB |
dc.rights | © 2018 Lopes, Richardson, Abela, Rummel, Schindler, Goodfellow and Terry. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | en_GB |
dc.title | Elevated ictal brain network ictogenicity enables prediction of optimal seizure control | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2018-03-07T15:34:15Z | |
dc.identifier.issn | 1664-2295 | |
dc.description | This is the final version of the article. Available from Frontiers Media via the DOI in this record. | en_GB |
dc.identifier.journal | Frontiers in Neurology | en_GB |