Chapter 3 - Discussion
5. Future Perspectives
Future studies should also include other types of focal epilepsy as well as patients with a poor seizure outcome. This will yield further confirmation for the clinical reliability of the used method, namely by indentifying strong drivers of activity outside the resection area in poor outcome patients.
In order to validate the clinical reliability of this functional connectivity method for presurgical evaluation, and also, how better it can perform as compared with other methods (for example, using only ESI), a study including a large cohort of patients (n>100) with several types of lesion should be considered.
Another important study with huge potential implication for the clinical practice will be to perform resting-state directed functional connectivity (without IEDs) in several types of epilepsy and healthy controls and build a classification system that, given a patient with an uncertain diagnose, is able to correctly classify it as having epilepsy or not and of which type.
Regarding the validation of ESI directed functional connectivity, simultaneous recordings of intracranial and scalp EEG provide a very important contribute. We have started by studying spikes that are seen at both
scalp and intracranial EEG, but it will also be important to study spikes that are only seen in the intracranial in order to find out whether functional connectivity analyses could find the important drivers even when scalp spikes are not be visible. This would be an important biomarker of epileptic activity.
Here, we studied only the outflows because we were interested in studying the main drivers of the network. However, it would be interesting in further studies to also investigate the inflows.
There are several factors that affect directed functional connectivity based on ESI signals. First of all, we should investigate which methods for restricting the dipole direction (average direction, decomposition techniques, anatomical orientation constraints) would yield the most reliable connectivity results. Secondly, there are currently some debated on whether the input data of the connectivity algorithm should be normalized or not. This is an important point and has to be investigated not only for simulation data, but most importantly, for real seizure or interictal spike data.
Another important point would be to perform a comparison in simulation and real data of the performance of be multivariate linear measures based on Granger-causality, such as DTF and PDC, with nonlinear measures such as the nonlinear correlation coefficient.
Conclusions
Epilepsy has been accepted as a network disorder [7], involving widespread brain networks rather than isolated single sources. In this project, we developed a methodological pipeline to investigate whole-brain directed functional connectivity from scalp EEG signals, and then applied it to assess the connectivity pattern changes in patients with LTLE and RTLE during interictal spikes and resting-state. We also showed that the same approach is suitable to study the main drivers of the resting brain and the directionality of their connections in healthy subjects. Our studies show that whole-brain electrophysiological-based directed functional connectivity analysis is a very promising tool to investigate connectivity patterns and how brain regions driver others during epileptic and non-epileptic activity. This could, therefore, constitute an important contribution for epilepsy presurgical planning, especially in patients in which the focus is not clear by other already available neuroimaging tools. It also holds promise for the use of EEG-based functional connectivity as a neuroimaging tool to investigate whole-brain cognitive processes.
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