Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States

BACKGROUND: EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction. METHODS: Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other. RESULTS: Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7. CONCLUSION: To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology

Revealing epilepsy type using a computational analysis of interictal EEG

This is the final version. Available from Nature Research via the DOI in this record.All materials (functional networks and code) are available upon request from the corresponding author.Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG.Medical Research Council (MRC)Wellcome TrustEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome Trus

Dynamic brain network states in human generalized spike-wave discharges

Generalized spike-wave discharges in idiopathic generalized epilepsy are conventionally assumed to have abrupt onset and offset. However, in rodent models, discharges emerge during a dynamic evolution of brain network states, extending several seconds before and after the discharge. In human idiopathic generalized epilepsy, simultaneous EEG and functional MRI shows cortical regions may be active before discharges, and network connectivity around discharges may not be normal. Here, in human idiopathic generalized epilepsy, we investigated whether generalized spike-wave discharges emerge during a dynamic evolution of brain network states. Using EEG-functional MRI, we studied 43 patients and 34 healthy control subjects. We obtained 95 discharges from 20 patients. We compared data from patients with discharges with data from patients without discharges and healthy controls. Changes in MRI (blood oxygenation level-dependent) signal amplitude in discharge epochs were observed only at and after EEG onset, involving a sequence of parietal and frontal cortical regions then thalamus (P < 0.01, across all regions and measurement time points). Examining MRI signal phase synchrony as a measure of functional connectivity between each pair of 90 brain regions, we found significant connections (P < 0.01, across all connections and measurement time points) involving frontal, parietal and occipital cortex during discharges, and for 20 s after EEG offset. This network prominent during discharges showed significantly low synchrony (below 99% confidence interval for synchrony in this network in non-discharge epochs in patients) from 16 s to 10 s before discharges, then ramped up steeply to a significantly high level of synchrony 2 s before discharge onset. Significant connections were seen in a sensorimotor network in the minute before discharge onset. This network also showed elevated synchrony in patients without discharges compared to healthy controls (P = 0.004). During 6 s prior to discharges, additional significant connections to this sensorimotor network were observed, involving prefrontal and precuneus regions. In healthy subjects, significant connections involved a posterior cortical network. In patients with discharges, this posterior network showed significantly low synchrony during the minute prior to discharge onset. In patients without discharges, this network showed the same level of synchrony as in healthy controls. Our findings suggest persistently high sensorimotor network synchrony, coupled with transiently (at least 1 min) low posterior network synchrony, may be a state predisposing to generalized spike-wave discharge onset. Our findings also show that EEG onset and associated MRI signal amplitude change is embedded in a considerably longer period of evolving brain network states before and after discharge events

FIACH: A biophysical model for automatic retrospective noise control in fMRI

Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults

Eeg-fmri In The Presurgical Evaluation Of Temporal Lobe Epilepsy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)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. Methods 30 patients undergoing presurgical evaluation and proceeding to temporal lobe (TL) resection were studied. Interictal epileptiform discharges (IEDs) were identified on intra-MRI EEG and used to build a model of haemodynamic changes. In addition, topographic electroencephalographic correlation maps were calculated between the average IED during videoEEG and intra-MRI EEG, and used as a condition. This allowed the analysis of all data irrespective of the presence of IED on intra-MRI EEG. Mean follow-up after surgery was 46 months. International League Against Epilepsy (ILAE) outcomes 1 and 2 were considered good, and 3-6 poor, surgical outcome. Haemodynamic maps were classified according to the presence (Concordant) or absence (Discordant) of Blood Oxygen Level-Dependent (BOLD) change in the TL overlapping with the surgical resection. Results The proportion of patients with good surgical outcome was significantly higher (13/16; 81%) in the Concordant than in the Discordant group (3/14; 21%) (chi(2) test, Yates correction, p=0.003) and multivariate analysis showed that Concordant BOLD maps were independently related to good surgical outcome (p=0.007). Sensitivity and specificity of EEG-fMRI results to identify patients with good surgical outcome were 81% and 79%, respectively, and positive and negative predictive values were 81% and 79%, respectively. Interpretation The presence of significant BOLD changes in the area of resection on interictal EEG-fMRI in patients with TLE retrospectively confirmed the epileptogenic zone. Surgical resection including regions of haemodynamic changes in the TL may lead to better postoperative outcome.876642649Department of Health's NIHR Biomedical Research CentresCentral and East London NIHR CLRNSao Paulo Research Foundation (FAPESP) [2009/54552-9, 2011/03477-7]Swiss National Science Foundation [SNSF 141165, 140332]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Interictal activity is an important contributor to abnormal intrinsic network connectivity in paediatric focal epilepsy

Patients with focal epilepsy have been shown to have reduced functional connectivity in intrinsic connectivity networks (ICNs), which has been related to neurocognitive development and outcome. However, the relationship between interictal epileptiform discharges (IEDs) and changes in ICNs remains unclear, with evidence both for and against their influence. EEG-fMRI data was obtained in 27 children with focal epilepsy (mixed localisation and aetiologies) and 17 controls. A natural stimulus task (cartoon blocks verses blocks where the subject was told "please wait") was used to enhance the connectivity within networks corresponding to ICNs while reducing potential confounds of vigilance and motion. Our primary hypothesis was that the functional connectivity within visual and attention networks would be reduced in patients with epilepsy. We further hypothesized that controlling for the effects of IEDs would increase the connectivity in the patient group. The key findings were: (1) Patients with mixed epileptic foci showed a common connectivity reduction in lateral visual and attentional networks compared with controls. (2) Having controlled for the effects of IEDs there were no connectivity differences between patients and controls. (3) A comparison within patients revealed reduced connectivity between the attentional network and basal ganglia associated with interictal epileptiform discharges. We also found that the task activations were reduced in epilepsy patients but that this was unrelated to IED occurrence. Unexpectedly, connectivity changes in ICNs were strongly associated with the transient effects of interictal epileptiform discharges. Interictal epileptiform discharges were shown to have a pervasive transient influence on the brain's functional organisation