Interictal studies

In spite of the relevance and clinical importance of connectivity studies during seizure periods, the number of seizures in a given patient is usually limited. Therefore, functional connectivity analysis during interictal spikes could provide a more available insight into the organisation of epileptic networks. Indeed, the characterisation of the dynamics of interictal activity in the development of epileptic networks has been shown to be very relevant [186].

In [131], the authors applied PLV to interictal periods (not necessarily having interictal spikes) SEEG recordings, and found an excess of synchronization on the side of the epileptogenic zone in 82% of the patients, suggesting that the epileptogenic region distinguishes itself by an increased level of synchronisation and that the ability to localize the epileptogenic zone from interictal periods could be of high diagnostic value. In [187], transfer entropy was applied to the whole duration of intracranial EEG recordings in 4 patients with TLE and it was able to identify the epileptogenic focus without any subjective prior selection of the EEG segments or electrodes for analysis. In [188], using a synchronisation measure applied to intracranial recordings, the topological properties of the epileptogenic networks of 11 patients with drug-resistant TLE were studied and compared with a control group of 8 patients with neocortical epilepsy. They found that the network topology was more altered in the TLE group with respect to non-TLE patients and corresponded to a more random configuration, interpretable as an increase of local and a decrease of long distance connections. They suggested thus, the existence of an interictal organization alteration in TLE. It is worth noting that the authors selected periods of interictal recordings with no requirement about the occurrence or not of interictal spikes in those periods. Similarly, in [189], the authors applied PLI to interictal ECoG recordings of 27 TLE patients and further used graph measures to investigate the effects of disease duration on the topological properties of the network. They showed that functional connectivity was lower in patients with longer TLE history, and that longer TLE duration was correlated with more random

network configuration, suggesting that neural networks of TLE patients become more pathological over time, which could be due to temporal lobe changes associated with long-standing lesional epilepsy.

In [190], a time-varying method based on DTF (integrated adaptive DTF) was applied to interictal spikes of ECoG signals in one patient. It showed better performance than the conventional nontime-varying DTF in capturing the connectivity patterns, highlighting thus the importance of the use of time-varying Granger-causal modelling to retrieve the dynamic patterns of epileptic activity. In a follow-up study [21], the authors aimed to identify the drivers of interictal spike activity recorded with ECoG in 8 patients with drug-resistant epilepsy using the same time-varying approach. They correctly identified the irritative zone in all patients concordantly with the clinically-defined seizure onset zone, and as originating from the same cortical regions as the recorded ictal activity. This is a further evidence that the study of cortical networks obtained during interictal spikes provides information regarding the generators of the ictal activity, and might be thus a good surrogate marker of the epileptogenic zone. In [191], the same group used this DTF approach in combination with graph theory measures, namely the betweenness centrality, to identify crucial network nodes during ictal and interictal periods from ECoG recordings of 25 patients with drug resistant neocortical-onset epilepsy. They found that the betweenness centrality correlated with the location of the resected regions in patients who were seizure-free following epilepsy surgery and that the best outcome was associated with the resection of regions with highest betweenness centrality, suggesting that highly interconnected nodes play a crucial role in seizure onset and propagation. It is noteworthy that the authors observed patterns of altered network interactions not only during seizures, but also during interictal spikes and random non-ictal periods, which supports the evidence that functional brain networks in focal epilepsy are altered even during seizure-free periods.

In [23], the nonlinear correlation coefficient was applied to SEEG signals during interictal periods in 21 TLE and 14 non-TLE patients. Functional connectivity between medial temporal lobe regions was found to be higher in the TLE group. Of note, this study did not consider the presence or absence of IEDs in the analysed interictal periods and a healthy control group was not included.

As mentioned for the seizures studies, also few interictal studies have been performed at the level of scalp EEG-based signals (thus, scalp EEG or ESI signals).

In a preliminary study [192], coherence was applied to IEDs recorded with high-density EEG (256 electrodes) in 5 patients and they found characteristic coherence patterns in each patient before, during and after IEDs. In spite of the promising results, it is noteworthy that this study used a bivariate, nontime-varying and undirected functional connectivity measure in a small cohort of patients.

However, no study to date has yet investigated the dynamic patterns of directed functional connectivity during IEDs using source reconstructed signals. As we will detail in the next sections, this was the focus of our first study.

MEG studies have also shown promising results regarding the usefulness of functional connectivity analyses to localize the epileptogenic zone and to predict postoperative outcome. Magnetic source imaging (MSI) was performed in interictal spike periods of 5 patients with focal epilepsies, and DTF was then applied to these MSI signals. A good concordance between regions of strongest outflow and resection areas was

conventional DTF was used. In [193], MSI was also performed in 12 patients with focal epilepsies and functional connectivity during IEDs was carried out using PLV. They found a correlation between the duration of seizures and functional connectivity in the beta band between the epileptogenic zone and other brain regions. In [194], using also MSI signals and PLI, the authors investigated the correlations between changes in functional network organization, due to surgery and postoperative outcome in 20 patients with lesional epilepsy. They found that the outcome of epilepsy surgery was related to changes in resting-state functional network organization,. Moreover, they found a local decrease of betweenness centrality in regions close to the resection area in seizure-free patients, suggesting that it may reflect the surgical removal of local pathological hubs, resulting in seizure freedom. In a recent MEG study [195], the authors aimed to assess the relevance of MEG in detecting and characterizing non-invasively brain networks involved in IEDs. For that, they proposed a semiautomatic method based on independent component analysis and on co-occurrence of events across components in 7 patients and the results were compared with networks identified by SEEG.

MEG measurements could extract a significant proportion of the networks visible in SEEG, suggesting that MEG can help to noninvasively define interictal epileptic networks. MEG and SEEG were not acquired simultaneously though. It is also noteworthy that a further comparison with ESI results (from high-density scalp EEG) would have also been very interesting. In a very recent MEG study [196], the authors used generalized PDC applied to MSI signals in 5 patients with neocortical epilepsy. They were able to identify the epileptogenic focus in periods with and without IEDs, suggesting that even in the absence of spikes, abnormal electrophysiological activity is detectable. Another recent MSI-based study [197] used imaginary coherence to compare the resting-state functional connectivity of 30 patients with TLE and 31 patients with focal neocortical epilepsy with 31 healthy controls. They found that patients had a global decreased resting-state functional connectivity compared to controls, and an increased regional connectivity within the resection site that was related to postoperative seizure freedom. They also observed larger connectivity decreases in patients with a longer duration of epilepsy. While they show the potential of electro/magnetophysiological-based resting-state functional connectivity analysis to study the impact of focal epilepsies on brain networks, it is worth noting that they did not investigate the directionality of the connectivity changes and the resting-state periods were not specifically chosen to contain or not IEDs.

Overall, these studies show the importance and clinical relevance of functional connectivity analyses to better understand pathological brain networks related to focal epilepsy.