Bayesian multi-modal model comparison: a case study on the generators of the spike and the wave in generalized spike–wave complexes

We present a novel approach to assess the networks involved in the generation of spontaneous pathological brain activity based on multi-modal imaging data. We propose to use probabilistic fMRI-constrained EEG source reconstruction as a complement to EEG-correlated fMRI analysis to disambiguate between networks that co-occur at the fMRI time resolution. The method is based on Bayesian model comparison, where the different models correspond to different combinations of fMRI-activated (or deactivated) cortical clusters. By computing the model evidence (or marginal likelihood) of each and every candidate source space partition, we can infer the most probable set of fMRI regions that has generated a given EEG scalp data window. We illustrate the method using EEG-correlated fMRI data acquired in a patient with ictal generalized spike–wave (GSW) discharges, to examine whether different networks are involved in the generation of the spike and the wave components, respectively. To this effect, we compared a family of 128 EEG source models, based on the combinations of seven regions haemodynamically involved (deactivated) during a prolonged ictal GSW discharge, namely: bilateral precuneus, bilateral medial frontal gyrus, bilateral middle temporal gyrus, and right cuneus. Bayesian model comparison has revealed the most likely model associated with the spike component to consist of a prefrontal region and bilateral temporal–parietal regions and the most likely model associated with the wave component to comprise the same temporal–parietal regions only. The result supports the hypothesis of different neurophysiological mechanisms underlying the generation of the spike versus wave components of GSW discharges

The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging

Simultaneous EEG–fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG–fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG–fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG–fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Background: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. Methods: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA): 1. EEGs were divided into up to three phases: early ictal EEG change, clinical seizure onset and late ictal EEG change and convolved with a canonical haemodynamic response function (HRF) (canonical GLM analysis). 2. Seizures lasting three scans or longer were additionally modelled using a Fourier basis set across the entire event (Fourier GLM analysis). 3. Independent component analysis (ICA) was applied to the fMRI data to identify ictal BOLD patterns without EEG. The results were compared with intracranial EEG. Results: The canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG). Conclusion: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics

EEG correlated functional MRI and postoperative outcome in focal epilepsy

Background: The main challenge in assessing patients with epilepsy for resective surgery is localising seizure onset. Frequently, identification of the irritative and seizure onset zones requires invasive EEG. EEG correlated functional MRI (EEG-fMRI) is a novel imaging technique which may provide localising information with regard to these regions. In patients with focal epilepsy, interictal epileptiform discharge (IED) correlated blood oxygen dependent level (BOLD) signal changes were observed in approximately 50% of patients in whom IEDs are recorded. In 70%, these are concordant with expected seizure onset defined by non-invasive electroclinical information. Assessment of clinical validity requires post-surgical outcome studies which have, to date, been limited to case reports of correlation with intracranial EEG. The value of EEG-fMRI was assessed in patients with focal epilepsy who subsequently underwent epilepsy surgery, and IED correlated fMRI signal changes were related to the resection area and clinical outcome. Methods: Simultaneous EEG-fMRI was recorded in 76 patients undergoing presurgical evaluation and the locations of IED correlated preoperative BOLD signal change were compared with the resected area and postoperative outcome. Results: 21 patients had activations with epileptic activity on EEG-fMRI and 10 underwent surgical resection. Seven of 10 patients were seizure free following surgery and the area of maximal BOLD signal change was concordant with resection in six of seven patients. In the remaining three patients, with reduced seizure frequency post-surgically, areas of significant IED correlated BOLD signal change lay outside the resection. 42 of 55 patients who had no IED related activation underwent resection. Conclusion: These results show the potential value of EEG-fMRI in presurgical evaluation

Mapping preictal and ictal haemodynamic networks using video-electroencephalography and functional imaging

Ictal patterns on scalp-electroencephalography are often visible only after propagation, therefore rendering localization of the seizure onset zone challenging. We hypothesized that mapping haemodynamic changes before and during seizures using simultaneous video-electroencephalography and functional imaging will improve the localization of the seizure onset zone. Fifty-five patients with ≥2 refractory focal seizures/day, and who had undergone long-term video-electroencephalography monitoring were included in the study. ‘Preictal' (30 s immediately preceding the electrographic seizure onset) and ictal phases, ‘ictal-onset'; ‘ictalestablished' and ‘late ictal', were defined based on the evolution of the electrographic pattern and clinical semiology. The functional imaging data were analysed using statistical parametric mapping to map ictal phase-related haemodynamic changes consistent across seizures. The resulting haemodynamic maps were overlaid on co-registered anatomical scans, and the spatial concordance with the presumed and invasively defined seizure onset zone was determined. Twenty patients had typical seizures during functional imaging. Seizures were identified on video-electroencephalography in 15 of 20, on electroencephalography alone in two and on video alone in three patients. All patients showed significant ictal-related haemodynamic changes. In the six cases that underwent invasive evaluation, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone for all patients. The most statistically significant haemodynamic cluster within the presumed seizure onset zone was between 1.1 and 3.5 cm from the invasively defined seizure onset zone, which was resected in two of three patients undergoing surgery (Class I post-surgical outcome) and was not resected in one patient (Class III post-surgical outcome). In the remaining 14 cases, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone in six of eight patients with structural-lesions and five of six non-lesional patients. The most statistically significant haemodynamic cluster was localizable at sub-lobar level within the presumed seizure onset zone in six patients. The degree of concordance of haemodynamic maps was significantly better (P < 0.05) for the ictal-onset phase [entirely concordant/concordant plus (13/20; 65%) + some concordance (4/20; 20%) = 17/20; 85%] than ictal-established [entirely concordant/concordant plus (5/13; 38%) + some concordance (4/13; 31%) = 9/13; 69%] and late ictal [concordant plus (1/9; 11%) + some concordance (4/9; 44%) = 5/9; 55%] phases. Ictal propagation-related haemodynamic changes were also seen in symptomatogenic areas (9/20; 45%) and the default mode network (13/20; 65%). A common pattern of preictal changes was seen in 15 patients, starting between 98 and 14 s before electrographic seizure onset, and the maps had a degree of concordance with the presumed seizure onset zone in 10 patients. In conclusion, preictal and ictal haemodynamic changes in refractory focal seizures can non-invasively localize seizure onset at sub-lobar/gyral level when ictal scalp-electroencephalography is not helpfu

EEG-fMRI signatures of spontaneous brain activity in healthy volunteers and epilepsy patients

Background: Functional magnetic resonance imaging (fMRI) provides maps of haemodynamic activity with uniform resolution across the brain. Simultaneous recording of electroencephalography (EEG) during fMRI (EEG-fMRI) was developed to localize spontaneously occurring epileptiform discharges. In focal epilepsy, it can identify candidate brain regions for surgical removal as a treatment option in medically refractory epilepsy; and in generalized epilepsy syndromes reveals those involved during the EEG changes. In healthy subjects, EEG-fMRI has linked spontaneous ongoing EEG activity with fMRI resting state networks. Methods: After method refinements, patients with medically refractory focal epilepsy and those with generalized epilepsy were studied with EEG-fMRI and group analyses performed to identify typical sets of brain regions involved in the epileptic process. Findings: In individual patients with refractory focal epilepsy, EEG-fMRI can produce activity maps including the seizure onset zone and propagated epileptic activity. Clinically, these can be confirmatory of results from alternative diagnostic techniques, or alternatively serve to generate a hypothesis on the potential epileptic focus, but under certain conditions may also be of negative predictive value with respect to surgical treatment success. At the group level in patients with temporal lobe epilepsy and complex partial seizures as well as in patients with generalized epilepsy and absence seizures, altered resting state network activity during EEG changes were found in default mode brain regions fitting well the ictal semiology, because these are known to reduce their activity during states of reduced consciousness. In (1) lateralized temporal lobe epilepsies, (2) an unselected mix of focal epilepsies, and (3) generalized epilepsies, activity increases occurred in typical brain regions suggesting an associated “hub function”, namely ipsilateral to the presumed cortical focus in the hippocampus; in an area near the frontal piriform cortex; and bilaterally in the thalamus, respectively. These findings argue for a network rather than a zone concept of epilepsy

Functional MRI of focal and generalised interictal epileptiform discharges.

Localizing the source of epileptic discharges is important in gaining a greater understanding of the disease, classifying epilepsy, and identifying areas suitable for potentially curable surgical resection. Functional imaging measures haemodynamic, metabolic or neurochemical correlates to localise neural activity. Combining EEG with functional MRI (EEG-fMRI) allows the localisation of haemodynamic correlates of neuronal events recorded on surface EEG. The work in this thesis aims to identify the spatial haemodynamic correlates of interictal epileptiform discharges (IED) in patients with epilepsy using EEG-fMRI. Five studies form the main body of this thesis. In the first study, 46 patients with frequent generalised spike wave activity (GSW) were studied with EEG-fMRI on a 1.5 Tesla scanner. The main finding was of a characteristic pattern of fMRI signal decrease in frontal, parietal and posterior cingulate cortex, areas of association cortex, during GSW. In the second study, 4 patients from this first series were re-studied with a 3 Tesla scanner. A high degree of reproducibility was seen in the spatial distribution of fMRI changes. Perfusion MRI with an arterial spin label sequence was used that showed a decrease in blood flow to these areas during GSW. In the third study, a novel method for the analysis of fMRI data in epilepsy, temporal clustering analysis (TCA) was assessed. The technique was confounded by subject motion, and we were unable to reliably detect correlates of IED. The fourth study moves away from correlating visually identified IEDs on the EEG, and correlates power fluctuations in the delta frequency band with simultaneously acquired fMRI. Finally a combination of EEG-fMRI and MR tractography were used to study a patient with temporal lobe epilepsy. The issues surrounding potential use of EEG-fMRI as a clinical tool are discussed