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Predicting surgical outcome in intractable epilepsy using a computational model of seizure initiation

A third of patients with epilepsy are refractory to anti-epileptic drug treatment. For some of these patients with focal epilepsy, better seizure control can be achieved by surgical treatment in which the seizure focus is localized and resected while avoiding crucial cortical tissues. However, approximately 30% of the patients continue to have seizures even after surgery. In other words, reliable criteria for patient's outcome prediction are absent. Computational models with appropriate parameter setting and patients specific connectivity allows an exciting opportunity to make predictions based on the model dynamics.

In this study, non-seizure (inter-ictal) epoch of electrographic recording has been used to calculate the functional synchrony between different cortical regions. This synchrony measure was then used as the connectivity parameter in a computational model of transitions to a seizure like state. Hypothesizing that the network synchrony plays an important role in determining the likelihood of surgical success, we retrospectively analyzed 19 patients having intractable epilepsy, who underwent surgical treatment to achieve seizure freedom. All data were collected confirming to ethical guidelines and under protocols monitored by the local Institutional Review Boards according to NIH guidelines.

Building upon the computational model in [1], the regions which were more likely to transit into a seizure like state were delineated. It was found that these regions are correlated with those identified by clinicians as the seizure onset zone. Moreover, it was found that the resection of these regions in the model reduces the overall likelihood of a seizure. The likelihood of a surgical success was calculated in silico by iteratively increasing the area of resection and the surgical outcomes were successfully predicted for 14 out of 19 patients.

The methods presented here may aid clinicians to delineate the seizure focus. Moreover, it may facilitate neurosurgeons in predicting the likelihood of a surgical success and to investigate alternative cortical tissues to operate on if the seizure focus is in the eloquent cortex.

Table 1 Prediction of surgical outcomes


  1. Nishant Sinha, Dauwels Justin, Wang Yujiang, Cash Sydney, Taylor Peter: An in silico approach for pre-surgical evaluation of an epileptic cortex. Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. 2014, 4884-4887.

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This work is funded in part by MOE Academic Research Funding Tier 1 grant M4010982.040.

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Correspondence to Nishant Sinha.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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Sinha, N., Dauwels, J., Wang, Y. et al. Predicting surgical outcome in intractable epilepsy using a computational model of seizure initiation. BMC Neurosci 16 (Suppl 1), P230 (2015).

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