Haemodynamic correlates of interictal and ictal epileptic discharges and ictal semiology using simultaneous scalp video-EEG-fMRI and intracranial EEG-fMRI

Interictal and ictal epileptic discharges are produced by focal and widespread dysfunctional neuronal networks. Identification and characterization of epileptic discharges underlie the diagnosis and the choice of treatment for epilepsy patients. A better knowledge of the generation, propagation and localisation of epileptic discharges, and their interaction with the physiological and pathological brain networks can be very helpful in planning epilepsy surgery and minimizing the risk of damaging the physiological brain networks. This work describes a number of methodological developments and novel applications investigating the epileptic networks in humans using EEG-fMRI. First, I implemented synchronized video recording inside the MRI-scanner during simultaneous EEG-fMRI studies, which did not deteriorate the imaging and EEG data quality. Secondly, I used video recordings to identify physiological activities to be modelled as confounds in the functional imaging data analysis for interictal activity, thus increasing the sensitivity of video-EEG-fMRI. Thirdly, I applied this modelling approach to investigate seizure related functional networks in patients with focal epilepsy. Video recordings allowed partitioning seizures into phases separating the ictal onset related functional networks from propagation related networks. Localisation of the ictal onset related networks may be useful in the planning for epilepsy surgery in a selected group of patients, as demonstrated by their comparison with intracranial-EEG recordings. Further, I investigated haemodynamic changes during preictal period which suggested recruitment of an inhibitory followed by an excitatory network prior to the ictal onset on scalp EEG. In the next step, I used simultaneous intracranial-EEG-fMRI in patients undergoing invasive evaluation, demonstrating that local and remote networks associated with very focal interictal discharges recorded on intracranial-EEG may predict the surgical outcome. Finally, I investigated the interaction of epileptic discharges with the working memory, using scalp video-EEG-fMRI, showing that the presence of epileptic activity may alter the working memory related networks. Methodological constraints, clinical applications and future perspectives are discussed

Localisation of epileptic foci using novel imaging modalities.

This review examines recent reports on the use of advanced techniques to map the regions and networks involved during focal epileptic seizure generation in humans

Temporal Lobe Spikes Affect Distant Intrinsic Connectivity Networks

Objective: To evaluate local and distant blood oxygen level dependent (BOLD) signal changes related to interictal epileptiform discharges (IED) in drug-resistant temporal lobe epilepsy (TLE). Methods: Thirty-three TLE patients undergoing EEG–functional Magnetic Resonance Imaging (fMRI) as part of the presurgical workup were consecutively enrolled. First, a single-subject spike-related analysis was performed: (a) to verify the BOLD concordance with the presumed Epileptogenic Zone (EZ); and (b) to investigate the Intrinsic Connectivity Networks (ICN) involvement. Then, a group analysis was performed to search for common BOLD changes in TLE. Results: Interictal epileptiform discharges were recorded in 25 patients and in 19 (58%), a BOLD response was obtained at the single-subject level. In 42% of the cases, BOLD changes were observed in the temporal lobe, although only one patient had a pure concordant finding, with a single fMRI cluster overlapping (and limited to) the EZ identified by anatomo-electro-clinical correlations. In the remaining 58% of the cases, BOLD responses were localized outside the temporal lobe and the presumed EZ. In every patient, with a spike-related fMRI map, at least one ICN appeared to be involved. Four main ICNs were preferentially involved, namely, motor, visual, auditory/motor speech, and the default mode network. At the single-subject level, EEG–fMRI proved to have high specificity (above 65%) in detecting engagement of an ICN and the corresponding ictal/postictal symptom, and good positive predictive value (above 67%) in all networks except the visual one. Finally, in the group analysis of BOLD changes related to IED revealed common activations at the right precentral gyrus, supplementary motor area, and middle cingulate gyrus. Significance: Interictal temporal spikes affect several distant extra-temporal areas, and specifically the motor/premotor cortex. EEG–fMRI in patients with TLE eligible for surgery is recommended not for strictly localizing purposes rather it might be useful to investigate ICNs alterations at the single-subject level

EEG-fMRI in the presurgical evaluation of temporal lobe epilepsy.

Drug-resistant temporal lobe epilepsy (TLE) often requires thorough investigation to define the epileptogenic zone for surgical treatment. We used simultaneous interictal scalp EEG-fMRI to evaluate its value for predicting long-term postsurgical outcome

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially. Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes. Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps. Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play

Imaging brain networks in focal epilepsy: a prospective study of the clinical application of simultaneous EEG-fMRI in pre-surgical evaluation

Epilepsy is a common disorder with significant associated morbidity and mortality. Despite advances in treatment, there remain a minority of people with pharmacoresistant focal epilepsy for whom surgery may be beneficial. It has been suggested that not enough people are offered surgical treatment, partly owing to the fact that current non-invasive techniques do not always adequately identify the seizure onset zone so that invasive EEG is required. EEG-fMRI is an imaging technique, developed in the 1990s (Ives, Warach et al. 1993) which identifies regions of interictal epileptiform discharge associated haemodynamic changes, that are concordant with the seizure onset zone in some patients (Salek-Haddadi, Diehl et al. 2006). To date there has been no large scale prospective comparison with icEEG and postoperative outcome. This thesis presents a series of experiments, carried out in a cohort of patients scanned using EEG-fMRI as part of a multi-centre programme, designed to investigate the relationship between EEG-fMRI and intracranial EEG and to assess its potential role in pre-surgical evaluation of patients with focal epilepsy. The results suggested that positive, localised IED-related BOLD signal changes were sensitive for the seizure onset zone, as determined on icEEG, both in patients neocortical epilepsies, but were not predictive of outcome. Widespread regions of positive IEDrelated BOLD signal change were associated with widespread or multifocal abnormalities on icEEG and poor outcome. Patterns of haemodynamic change, identified using both data driven and EEG derived modeling approaches, correspond to regions of seizure onset on icEEG, but improvements for modeling seizures are required. A study of a single seizure in a patient who underwent simultaneous icEEGfMRI, showed similar findings.. An exploratory investigation of fMRI-DCM in EEG-fMRI, suggested it can provide information about seizure propagation and this opens new avenues for the non-invasive study of the epileptic network and interactions with function

Automated classification of human epileptic spikes for the purpose of modelling bold changes using simultaneous intracranial EEG-fMRI

Mapping the BOLD correlates of interictal epileptiform discharges (IEDs) using EEG-fMRI can provide a unique insight into the region(s) responsible for their generation. Scalp EEG-fMRI studies have shown to provide added clinical value in the localisation of the epileptogenic zone in patients with pharmacoresistant epilepsy undergoing presurgical evaluation. However, scalp EEG has limited sensitivity in detecting IEDs as only a small percentage of the underlying electrical activity is recorded. Intracranial EEG (icEEG) provides a higher sensitivity of detecting underlying IEDs compared to scalp EEG due to the electrodes being closer to their generators. Recent safety and feasibility studies have allowed the acquisition of simultaneous icEEG-fMRI circumventing the lack of whole brain coverage of icEEG. Therefore, icEEG-fMRI has the potential to provide unprecedented insight in the relationship between the region(s) generating IEDs and the epileptogenic zone. However, one of the main challenges associated with icEEG-fMRI data is the difficulty of forming a parsimonious model of potential BOLD changes from the complex spatio-temporal dynamics of icEEG IEDs. The aim of this thesis is to provide a solution for a more consistent and less biased marking of icEEG IEDs using an automated neuronal spike classification algorithm, Wave_clus (WC), for the purpose of producing more biological meaningful IED-related BOLD maps. Adapting the icEEG IED dataset to Wave_clus was the first problem tackled which involved developing a new algorithm that identified the peak of the spiky component of an IED and defining an optimal IED classification epoch time-window. The two chapters that followed involved assessing the performance of WC as an icEEG IED classifier. First, I assessed the performance by comparing WC IED classification to the classification of multiple EEG reviewers using a novel validation scheme. This was determined by analysing whether WC-human agreement variability falls within inter-reviewer agreement variability and comparing the individual IED class labels visually and quantitatively. In this regard WC performance was found to be indistinguishable to that of EEG reviewers. Second I assessed the performance of WC by comparing the IED-related BOLD maps obtained using WC to those obtained using the visual/conventional approach. I found that WC was able to produce more biologically meaningful IED-related BOLD maps indicating that this approach can be used to further explore the region(s) responsible for generating IEDs in patients that have undergone icEEG-fMRI

Study of the relationship between the EEG and BOLD signals using intracranial EEG - fMRI data simultaneously acquired in humans

The principal aim of this work was to further characterise the relationship between the electrophysiological and BOLD fMRI signals at the local level, exploiting the unique opportunity to analyse intracranial EEG (icEEG) and fMRI data recorded simultaneously in humans, during a finger tapping task and at rest. The MR-environment (gradient switch and mechanical vibration) related artefacts corrupting the icEEG data were the first problem tackled; they were characterised and removed using techniques developed by me. The two parts that followed aimed to shed further light on the neurophysiological basis of the BOLD effect. Firstly, the influence of the phase of the low frequency EEG activities (70 Hz) (phase-amplitude coupling: PAC) was found to explain variance in addition to a combination of , , and band powers, suggesting that PAC strength and power fluctuations result from complementary neuronal processes. Secondly, five interictal epileptiform discharge (IED) morphology and field extent related features were tested in their individual capability to predict the amplitude of the co-localised BOLD signal; these were the amplitude and rising phase slope, thought to reflect the degree of neuronal activity synchrony; width and energy, thought to reflect the duration of the excitatory post-synaptic potentials; and spatial field extent, thought to reflect the spatial extent of the surrounding, synchronised sources of neuronal activity. Among these features, the IED width was the only one found to explain BOLD signal variance in addition to the IED onsets, suggesting that the amplitude of the BOLD signal is comparatively better predicted by the duration of the underlying field potential, than by the degree of neuronal activity synchrony

Functional network correlates of language and semiology in epilepsy

Epilepsy surgery is appropriate for 2-3% of all epilepsy diagnoses. The goal of the presurgical workup is to delineate the seizure network and to identify the risks associated with surgery. While interpretation of functional MRI and results in EEG-fMRI studies have largely focused on anatomical parameters, the focus of this thesis was to investigate canonical intrinsic connectivity networks in language function and seizure semiology. Epilepsy surgery aims to remove brain areas that generate seizures. Language dysfunction is frequently observed after anterior temporal lobe resection (ATLR), and the presurgical workup seeks to identify the risks associated with surgical outcome. The principal aim of experimental studies was to elaborate understanding of language function as expressed in the recruitment of relevant connectivity networks and to evaluate whether it has value in the prediction of language decline after anterior temporal lobe resection. Using cognitive fMRI, we assessed brain areas defined by parameters of anatomy and canonical intrinsic connectivity networks (ICN) that are involved in language function, specifically word retrieval as expressed in naming and fluency. fMRI data was quantified by lateralisation indices and by ICN_atlas metrics in a priori defined ICN and anatomical regions of interest. Reliability of language ICN recruitment was studied in 59 patients and 30 healthy controls who were included in our language experiments. New and established language fMRI paradigms were employed on a three Tesla scanner, while intellectual ability, language performance and emotional status were established for all subjects with standard psychometric assessment. Patients who had surgery were reinvestigated at an early postoperative stage of four months after anterior temporal lobe resection. A major part of the work sought to elucidate the association between fMRI patterns and disease characteristics including features of anxiety and depression, and prediction of postoperative language outcome. We studied the efficiency of reorganisation of language function associated with disease features prior to and following surgery. A further aim of experimental work was to use EEG-fMRI data to investigate the relationship between canonical intrinsic connectivity networks and seizure semiology, potentially providing an avenue for characterising the seizure network in the presurgical workup. The association of clinical signs with the EEG-fMRI informed activation patterns were studied using the data from eighteen patients’ whose seizures and simultaneous EEG-fMRI activations were reported in a previous study. The accuracy of ICN_atlas was validated and the ICN construct upheld in the language maps of TLE patients. The ICN construct was not evident in ictal fMRI maps and simulated ICN_atlas data. Intrinsic connectivity network recruitment was stable between sessions in controls. Amodal linguistic processing and the relevance of temporal intrinsic connectivity networks for naming and that of frontal intrinsic connectivity networks for word retrieval in the context of fluency was evident in intrinsic connectivity networks regions. The relevance of intrinsic connectivity networks in the study of language was further reiterated by significant association between some disease features and language performance, and disease features and activation in intrinsic connectivity networks. However, the anterior temporal lobe (ATL) showed significantly greater activation compared to intrinsic connectivity networks – a result which indicated that ATL functional language networks are better studied in the context of the anatomically demarked ATL, rather than its functionally connected intrinsic connectivity networks. Activation in temporal lobe networks served as a predictor for naming and fluency impairment after ATLR and an increasing likelihood of significant decline with greater magnitude of left lateralisation. Impairment of awareness served as a significant classifying feature of clinical expression and was significantly associated with the inhibition of normal brain functions. Canonical intrinsic connectivity networks including the default mode network were recruited along an anterior-posterior anatomical axis and were not significantly associated with clinical signs

EEG-fMRI in epilepsy and sleep

This thesis used simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) to investigate both epilepsy and sleep. Initially, EEG-fMRI was used in a cohort of patients with complex epilepsy referred from a tertiary epilepsy clinic for both pre-surgical evaluation and diagnostic reasons. The results suggest a limited utility of EEG-fMRI in the epilepsy clinic with a very complex patient group. Following on, investigation of early blood oxygen level dependent (BOLD) signal changes in a group of patients with focal epilepsy demonstrated potentially meaningful BOLD changes occurring six seconds prior to interictal epileptiform discharges, and modelling less than this six seconds can result in overlap of the haemodynamic response function used to model BOLD changes. The same analysis was used to model endogenously occurring sleep paroxysms; K-complexes (KCs), vertex sharp waves (VSWs) and sleep spindles (SSs), finding early BOLD signal changes with SSs in group data. Finally, KCs and VSWs were investigated in more detail in a group of participants under both sleep deprived and non-deprived conditions, demonstrating an increase in overall activation for both KCs and VSWs following sleep deprivation. Overall, we find early BOLD changes are not restricted to pathological events and sleep deprivation can enhance BOLD responses