Spatial filters and automated spike detection based on brain topographies improve sensitivity of EEG–fMRI studies in focal epilepsy

EEG-fMRI: Ballistocardiogram Artifact Reduction by Surrogate Method for Improved Source Localization

For the analysis of simultaneous EEG-fMRI recordings, it is vital to use effective artifact removal tools. This applies in particular to the ballistocardiogram (BCG) artifact which is difficult to remove without distorting signals of interest related to brain activity. Here, we documented the use of surrogate source models to separate the artifact-related signals from brain signals with minimal distortion of the brain activity of interest. The artifact topographies used for surrogate separation were created automatically using principal components analysis (PCA-S) or by manual selection of artifact components utilizing independent components analysis (ICA-S). Using real resting-state data from 55 subjects superimposed with simulated auditory evoked potentials (AEP), both approaches were compared with three established BCG artifact removal methods: Blind Source Separation (BSS), Optimal Basis Set (OBS), and a mixture of both (OBS-ICA). Each method was evaluated for its applicability for ERP and source analysis using the following criteria: the number of events surviving artifact threshold scans, signal-to-noise ratio (SNR), error of source localization, and signal variance explained by the dipolar model. Using these criteria, PCA-S and ICA-S fared best overall, with highly significant differences to the established methods, especially in source localization. The PCA-S approach was also applied to a single subject Berger experiment performed in the MRI scanner. Overall, the removal of BCG artifacts by the surrogate methods provides a substantial improvement for the analysis of simultaneous EEG-fMRI data compared to the established methods.

Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data

Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

Artifact Reduction in Simultaneous EEG-fMRI: A Systematic Review of Methods and Contemporary Usage

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a technique that combines temporal (largely from EEG) and spatial (largely from fMRI) indicators of brain dynamics. It is useful for understanding neuronal activity during many different event types, including spontaneous epileptic discharges, the activity of sleep stages, and activity evoked by external stimuli and decision-making tasks. However, EEG recorded during fMRI is subject to imaging, pulse, environment and motion artifact, causing noise many times greater than the neuronal signals of interest. Therefore, artifact removal methods are essential to ensure that artifacts are accurately removed, and EEG of interest is retained. This paper presents a systematic review of methods for artifact reduction in simultaneous EEG-fMRI from literature published since 1998, and an additional systematic review of EEG-fMRI studies published since 2016. The aim of the first review is to distill the literature into clear guidelines for use of simultaneous EEG-fMRI artifact reduction methods, and the aim of the second review is to determine the prevalence of artifact reduction method use in contemporary studies. We find that there are many published artifact reduction techniques available, including hardware, model based, and data-driven methods, but there are few studies published that adequately compare these methods. In contrast, recent EEG-fMRI studies show overwhelming use of just one or two artifact reduction methods based on literature published 15–20 years ago, with newer methods rarely gaining use outside the group that developed them. Surprisingly, almost 15% of EEG-fMRI studies published since 2016 fail to adequately describe the methods of artifact reduction utilized. We recommend minimum standards for reporting artifact reduction techniques in simultaneous EEG-fMRI studies and suggest that more needs to be done to make new artifact reduction techniques more accessible for the researchers and clinicians using simultaneous EEG-fMRI.

Treatment of infantile spasms: why do we know so little?

INTRODUCTION

Infantile spasm (IS) is an epileptic syndrome with typical onset within the first 2 years of life. This condition might be caused by several etiologies. IS is associated with pathological neuronal networks; however, definite hypotheses on neurobiological processes are awaited.

AREAS COVERED

Changes in NMDA and GABA_B receptors and increase of Ca²⁺ conductance are some of the possible pathophysiological mechanisms. Animal models can help, but most have only some features of IS. Outcome is strongly affected by etiology and the timing of treatment, which relies still on ACTH, oral steroids, and vigabatrin. No significant differences in terms of efficacy have been documented, though a combination of ACTH and vigabatrin seems to be associated with better long-term outcomes. Despite the increasing knowledge about the etiology and pathophysiology of IS, in the last years, no new treatment approaches have been recognized to be able to modify the neurobiological process underlying IS. Precision medicine has far to come in IS.

EXPERT OPINION

Recently, no new therapeutic options for IS have emerged, probably due to the lack of reliable animal models and to the extreme variability in etiologies. Consequently, the outlook for patients and families is poor and early recognition and intervention remain research priorities.

Multifocal epilepsy in children is associated with increased long-distance functional connectivity: An explorative EEG-fMRI study

OBJECTIVE

Multifocal epileptic activity is an unfavourable feature of a number of epileptic syndromes (Lennox-Gastaut syndrome, West syndrome, severe focal epilepsies) which suggests an overall vulnerability of the brain to pathological synchronization. However, the mechanisms of multifocal activity are insufficiently understood. This explorative study investigates whether pathological connectivity within brain areas of the default mode network as well as thalamus, brainstem and retrosplenial cortex may predispose individuals to multifocal epileptic activity.

METHODS

33 children suffering from multifocal and monofocal (control group) epilepsies were investigated using EEG-fMRI recordings during sleep. The blood oxygenated level dependent (BOLD) signal of 15 regions of interest was extracted and temporally correlated (resting-state functional connectivity).

RESULTS

Patients with monofocal epilepsies were characterized by strong correlations between the corresponding interhemispheric homotopic regions. This pattern of correlations with pronounced short-distance and weak long-distance functional connectivity resembles the connectivity pattern described for healthy children. Patients with multifocal epileptic activity, however, demonstrated significantly stronger correlations between a large number of regions of the default mode network as well as thalamus and brainstem, with a significant increase in long-distance connectivity compared to children with monofocal epileptic activity. In the group of patients with multifocal epilepsies there were no differences in functional connectivity between patients with or without Lennox-Gastaut syndrome.

CONCLUSION

This explorative study shows that multifocal activity is associated with generally increased long-distance functional connectivity in the brain. It can be suggested that this pronounced connectivity may represent either a risk to pathological over-synchronization or a consequence of the multifocal epileptic activity.

EEG synchronization measures predict epilepsy-related BOLD-fMRI fluctuations better than commonly used univariate metrics

OBJECTIVE

We hypothesize that the hypersynchronization associated with epileptic activity is best described by EEG synchronization measures, and propose to use these as predictors of epilepsy-related BOLD fluctuations.

METHODS

We computed the phase synchronization index (PSI) and global field synchronization (GFS), within two frequency bands, a broadband (1-45 Hz) and a narrower band focused on the presence of epileptic activity (3-10 Hz). The associated epileptic networks were compared with those obtained using conventional unitary regressors and two power-weighted metrics (total power and root mean square frequency), on nine simultaneous EEG-fMRI datasets from four epilepsy patients, exhibiting inter-ictal epileptiform discharges (IEDs).

RESULTS

The average PSI within 3-10 Hz achieved the best performance across several measures reflecting reliability in all datasets. The results were cross-validated through electrical source imaging of the IEDs. The applicability of PSI when no IEDs are recorded on the EEG was evaluated on three additional patients, yielding partially plausible networks in all cases.

CONCLUSIONS

Epileptic networks can be mapped based on the EEG PSI metric within an IED-specific frequency band, performing better than commonly used EEG metrics.

SIGNIFICANCE

This is the first study to investigate EEG synchronization measures as potential predictors of epilepsy-related BOLD fluctuations.

Marker-based ballistocardiographic artifact correction improves spike identification in EEG-fMRI of focal epilepsy patients

OBJECTIVES

Ballistocardiographic (BCG) artifacts resemble interictal epileptic discharges (IEDs) and can lead to incorrect IED identification in EEG-fMRI. This study investigates IEDs marked in EEGs corrected using information from a moiré phase tracking (MPT) marker.

METHODS

EEG-fMRI from 18 patients was processed with conventional methods for BCG removal, while 9 patients used a MPT marker. IEDs were marked first without ECG information. In a second review, suspicious IEDs synchronous with the BCG were discarded. After each review, an event-related fMRI analysis was performed on the marked IEDs.

RESULTS

No difference was found in the proportion of suspicious IEDs in the 2 patient groups. However, the distribution of IED timings was significantly related to the cardiac cycle in 11 of 18 patients recorded without MPT marker, but only 2 of 9 patients with marker. In patients recorded without marker, failing to discard suspicious IEDs led to more inaccurate fMRI maps and more distant activations.

CONCLUSIONS

BCG artifact correction based on MPT recordings allowed a more straightforward identification of IEDs that did not require ECG information in the large majority of patients.

SIGNIFICANCE

Marker-based ballistocardiographic artifact correction greatly facilitates the study of the generators of interictal discharges with EEG-fMRI.

Ballistocardiogram artifact correction taking into account physiological signal preservation in simultaneous EEG-fMRI

The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artifact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artifact occurrences using an Optimal Basis Set (OBS) or Average Artifact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artifact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3T and 7T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artifact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3T/7T. Although more significant improvements were achieved at 7T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations.

Alpha desynchronization and fronto-parietal connectivity during spatial working memory encoding deficits in ADHD: A simultaneous EEG-fMRI study

The underlying mechanisms of alpha band (8-12 Hz) neural oscillations are of importance to the functioning of attention control systems as well as to neuropsychiatric conditions that are characterized by deficits of that system, such as attention deficit hyperactivity disorder (ADHD). The objectives of the present study were to test if visual encoding-related alpha event-related desynchronization (ERD) correlates with fronto-parieto-occipital connectivity, and whether this is disrupted in ADHD during spatial working memory (SWM) performance. We acquired EEG concurrently with fMRI in thirty boys (12-16 yrs. old, 15 with ADHD), during SWM encoding. Psychophysiological connectivity analyses indicated that alpha ERD during SWM encoding was associated with both occipital activation and fronto-parieto-occipital functional connectivity, a finding that expands on prior associations between alpha ERD and occipital activation. This finding provides novel support for the interpretation of alpha ERD (and the associated changes in occipital activation) as a phenomenon that involves, and perhaps arises as a result of, top-down network interactions. Alpha ERD was associated less strongly with occipital activity, but associated more strongly with fronto-parieto-occipital connectivity in ADHD, consistent with a compensatory attentional response. Additionally, we illustrate that degradation of EEG data quality by MRI-amplified motion artifacts is robust to existing cleaning algorithms and is significantly correlated with hyperactivity symptoms and the ADHD Combined Type diagnosis. We conclude that persistent motion-related MR artifacts in EEG data can increase variance and introduce bias in interpretation of group differences in populations characterized by hypermobility--a clear limitation of current-state EEG-fMRI methodology.

Multivariate analyses applied to fetal, neonatal and pediatric MRI of neurodevelopmental disorders

Multivariate analysis (MVA) is a class of statistical and pattern recognition methods that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of medical neuroimaging-related challenges including identifying variables associated with a measure of clinical importance (i.e. patient outcome), creating diagnostic tests, assisting in characterizing developmental disorders, understanding disease etiology, development and progression, assisting in treatment monitoring and much more. Compared to adults, imaging of developing immature brains has attracted less attention from MVA researchers. However, remarkable MVA research growth has occurred in recent years. This paper presents the results of a systematic review of the literature focusing on MVA technologies applied to neurodevelopmental disorders in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. The goal of this manuscript is to provide a concise review of the state of the scientific literature on studies employing brain MRI and MVA in a pre-adult population. Neurological developmental disorders addressed in the MVA research contained in this review include autism spectrum disorder, attention deficit hyperactivity disorder, epilepsy, schizophrenia and more. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in pediatric/neonatal/fetal brain MRI, the field is still young and considerable research growth remains ahead of us.

Intrinsic brain activity as a diagnostic biomarker in children with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is often associated with neural circuit dysfunction, particularly during the transient active state characterized by interictal epileptiform discharges (IEDs). Little is known, however, about the functional neural circuit abnormalities in BECTS without IEDs, or if such abnormalities could be used to differentiate BECTS patients without IEDs from healthy controls (HCs) for early diagnosis. To this end, we conducted resting-state functional magnetic resonance imaging (RS-fMRI) and simultaneous Electroencephalogram (EEG) in children with BECTS (n = 43) and age-matched HC (n = 28). The simultaneous EEG recordings distinguished BECTS with IEDs (n = 20) from without IEDs (n = 23). Intrinsic brain activity was measured in all three groups using the amplitude of low frequency fluctuation at rest. Compared to HC, BECTS patients with IEDs exhibited an intrinsic activity abnormality in the thalamus, suggesting that thalamic dysfunction could contribute to IED emergence while patients without IEDs exhibited intrinsic activity abnormalities in middle frontal gyrus and superior parietal gyrus. Using multivariate pattern classification analysis, we were able to differentiate BECTS without IEDs from HCs with 88.23% accuracy. BECTS without epileptic transients can be distinguished from HC and BECTS with IEDs by unique regional abnormalities in resting brain activity. Both transient abnormalities as reflected by IEDs and chronic abnormalities as reflected by RS-fMRI may contribute to BECTS development and expression. Intrinsic brain activity and multivariate pattern classification techniques are promising tools to diagnose and differentiate BECTS syndromes. Hum Brain Mapp 36:3878-3889, 2015. © 2015 Wiley Periodicals, Inc.

A reliable and time-saving semiautomatic spike-template-based analysis of interictal EEG-fMRI

OBJECTIVE

A prerequisite for the implementation of interictal electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in the presurgical work-up for epilepsy surgery is straightforward processing. We propose a new semi-automatic method as alternative for the challenging and time-consuming visual spike identification.

METHODS

Our method starts from a patient-specific spike-template, built by averaging spikes recorded on the EEG outside the scanner. Spatiotemporal cross-correlations between the template and the EEG measured during fMRI were calculated. To minimize false-positive detections, this time course of cross-correlations was binarized by means of a spike-template-specific threshold determined in healthy controls. To inform our model for statistical parametric mapping, this binarized regressor was convolved with the canonical hemodynamic response function. We validated our "template-based" method in 21 adult patients with refractory focal epilepsy with a well-defined epileptogenic zone and interictal spikes during EEG-fMRI. Sensitivity and specificity for detecting the epileptogenic zone were calculated and represented in receiver operating characteristic (ROC) curves. Our approach was compared with a previously proposed semiautomatic "topography-based" method that used the topographic amplitude distribution of spikes as a starting point for correlation-based fitting.

RESULTS

Good diagnostic performance could be reached with our template-based method. The optimal area under the ROC curve was 0.77. Diagnostic performance of the topography-based method was overall low.

SIGNIFICANCE

Our new template-based method is more standardized and time-saving than visual spike identification on intra-scanner EEG recordings, and preserves good diagnostic performance for detecting the epileptogenic zone.

Mapping (and modeling) physiological movements during EEG-fMRI recordings: the added value of the video acquired simultaneously

BACKGROUND

During resting-state EEG-fMRI studies in epilepsy, patients' spontaneous head-face movements occur frequently. We tested the usefulness of synchronous video recording to identify and model the fMRI changes associated with non-epileptic movements to improve sensitivity and specificity of fMRI maps related to interictal epileptiform discharges (IED).

NEW METHODS

Categorization of different facial/cranial movements during EEG-fMRI was obtained for 38 patients [with benign epilepsy with centro-temporal spikes (BECTS, n=16); with idiopathic generalized epilepsy (IGE, n=17); focal symptomatic/cryptogenic epilepsy (n=5)]. We compared at single subject- and at group-level the IED-related fMRI maps obtained with and without additional regressors related to spontaneous movements. As secondary aim, we considered facial movements as events of interest to test the usefulness of video information to obtain fMRI maps of the following face movements: swallowing, mouth-tongue movements, and blinking.

RESULTS

Video information substantially improved the identification and classification of the artifacts with respect to the EEG observation alone (mean gain of 28 events per exam).

COMPARISON WITH EXISTING METHOD

Inclusion of physiological activities as additional regressors in the GLM model demonstrated an increased Z-score and number of voxels of the global maxima and/or new BOLD clusters in around three quarters of the patients. Video-related fMRI maps for swallowing, mouth-tongue movements, and blinking were comparable to the ones obtained in previous task-based fMRI studies.

CONCLUSIONS

Video acquisition during EEG-fMRI is a useful source of information. Modeling physiological movements in EEG-fMRI studies for epilepsy will lead to more informative IED-related fMRI maps in different epileptic conditions.

Altered regional homogeneity in rolandic epilepsy: a resting-state FMRI study

Children with rolandic epilepsy (RE) are often associated with cognitive deficits and behavioral problems. Findings from neurophysiological and neuroimaging studies in RE have now demonstrated dysfunction not only in rolandic focus, but also in distant neuronal circuits. Little is known, however, about whether there is distributed abnormal spontaneous brain activity in RE. Using resting-state functional magnetic resonance imaging (RS-fMRI), the present study aimed to determine whether children with RE show abnormal local synchronization during resting state and, if so, whether these changes could be associated with the behavioral/clinical characteristics of RE. Regional homogeneity (ReHo) in children with RE (n = 30) and healthy children (n = 20) was computed on resting-state functional MRI data. In comparison with healthy children, children with RE showed increased ReHo in the central, premotor, and prefrontal regions, while they showed decreased ReHo in bilateral orbitofrontal cortex and temporal pole. In addition, the ReHo value in the left orbitofrontal cortex negatively was corrected with performance intelligence quotient in the children with RE. The aberrant local synchronization, not strictly related to primary site of the typical rolandic focus, indicates the neuropathophysiological mechanism of RE. The study findings may shed new light on the understanding of neural correlation of neuropsychological deficiencies in the children with RE.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

EEG-fMRI in atypical benign partial epilepsy

Atypical benign partial epilepsy (ABPE) is a subgroup among the idiopathic focal epilepsies of childhood. Aim of this study was to investigate neuronal networks underlying ABPE and compare the results with previous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) studies of related epilepsy syndromes. Ten patients with ABPE underwent simultaneous EEG-fMRI recording. In all 10 patients several types of interictal epileptiform discharges (IEDs) were recorded. Individual IED-associated blood oxygen level-dependent (BOLD) signal changes were analyzed in a single subject analysis for each IED type (33 studies). A group analysis was also performed to determine common BOLD signal changes across the patients. IED-associated BOLD signal changes were found in 31 studies. Focal BOLD signal changes concordant with the spike field (21 studies) and distant cortical and subcortical BOLD signal changes (31 studies) were detected. The group analysis revealed a thalamic activation. This study demonstrated that ABPE is characterized by patterns similar to studies in rolandic epilepsy (focal BOLD signal changes in the spike field) as well as patterns observed in continuous spikes and waves during slow sleep (CSWS) (distant BOLD signal changes in cortical and subcortical structures), thereby underscoring that idiopathic focal epilepsies of childhood form a spectrum of overlapping syndromes.

Simultaneous EEG and fMRI recordings (EEG-fMRI) in children with epilepsy

By combining electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) it is possible to describe blood oxygenation level-dependent (BOLD) signal changes related to EEG patterns. This way, EEG-pattern-associated networks of hemodynamic changes can be detected anywhere in the brain with good spatial resolution. This review summarizes EEG-fMRI studies that have been performed in children with epilepsy. EEG-fMRI studies in focal epilepsy (structural and nonlesional cases, benign epilepsy with centrotemporal spikes), generalized epilepsy (especially absence epilepsy), and epileptic encephalopathies (West syndrome, Lennox-Gastaut syndrome, continuous spike and waves during slow sleep, and Dravet syndrome) are presented. Although EEG-fMRI was applied mainly to localize the region presumably generating focal interictal discharges in focal epilepsies, EEG-fMRI identified underlying networks in patients with generalized epilepsies and thereby contributed to a better understanding of these epilepsies. In epileptic encephalopathies a specific fingerprint of hemodynamic changes associated with the particular syndrome was detected. The value of the EEG-fMRI technique for diagnosis and investigation of pathogenetic mechanisms of different forms of epilepsy is discussed.

Improving sensitivity of EEG-fMRI studies in epilepsy: the role of sleep-specific activity

Using simultaneous recordings of EEG and functional MRI (EEG-fMRI) in patients with focal epilepsy, recent studies have revealed insufficient sensitivity and a lack of correspondence between epileptic EEG foci and activation patterns in some patients. In this study of children with focal epilepsy, we explore whether sleep-specific activity (sleep spindles, k-complexes and vertex sharp waves) may increase the sensitivity of EEG-fMRI of interictal epileptiform discharges (IED). When considering the sleep-specific activity in a statistical model, it was possible to increase the statistical significance of the activated voxels inside of the expected source of the IED and to reduce the number of activated voxels outside of it. According to this study, it could be worthwhile to include sleep-specific activity into the model by analyzing EEG-fMRI data in epilepsy.

EEG-fMRI reveals activation of brainstem and thalamus in patients with Lennox-Gastaut syndrome

PURPOSE

Even if etiologies of Lennox-Gastaut syndrome (LGS) are diverse, the multiple causes converge into a final common pathway that results in this specific epilepsy phenotype. There is little knowledge, however, about neuronal networks that may be a part of this pathway.

METHODS

To investigate these networks, 11 children with LGS and 9 control children with multifocal epileptic activity were investigated using simultaneous recordings of EEG and functional MRI (EEG-fMRI) in a 3 Tesla scanner.

KEY FINDINGS

Individual and group analyses revealed significant activation of brainstem and thalamus (especially centromedian and anterior thalamus) associated with epileptiform discharges in patients with LGS. None of the patients with multifocal epileptic activity presented with the same hemodynamic activation pattern.

SIGNIFICANCE

Because brainstem activation has been associated with infantile spasms, which often evolve into LGS, and thalamus activation has been observed in patients with primary (idiopathic generalized syndromes) and secondary (focal epilepsies) bilateral synchrony, the described network in LGS may represent the common pathogenetic pathway of these different conditions.

Looking for neuronal currents using MRI: an EEG-fMRI investigation of fast MR signal changes time-locked to frequent focal epileptic discharges

RATIONALE

Reproducible direct measurement of neuronal electrical activity using MRI signal changes due to local magnetic field perturbations would represent a step change in neuroimaging methods. While some previous studies using experiments based on evoked and spontaneous activity provided encouraging results no clear demonstration of neuronal current-related MR changes in the human brain has emerged to date. The availability of simultaneously acquired EEG-fMRI in patients with frequent interictal epileptic discharges (IED), which have significantly greater amplitude than evoked potentials, offers the opportunity to further investigate the phenomenon.

METHODS

We re-analysed simultaneously acquired EEG-fMRI data in 6 epilepsy patients with very frequent focal IED and a well-localised generator. A model of MRI signal changes due to fast activity and BOLD signal changes was used to identify fast MR signal changes, potentially directly reflecting neuronal activity. Simultaneously-acquired EEG allowed the comparison of electrical source localisation (ESI), clinical epilepsy localisation and BOLD signal changes with the fast MR signal changes.

RESULTS

Clusters of IED-related fast MR signal change were observed in all cases. Spatial correspondence between the IED-related fast MR, BOLD, ESI clusters and irritative zone (IZ) was observed in one slice of a single dataset. The other IED-related fast MR clusters were remote from electro-clinically determined generators of interictal activity. The sign and magnitude of the fast MR signal changes varied across regions and subjects.

CONCLUSION

The observed fast MR changes cannot be confidently attributed to the direct effect of neuronal currents due to lack of spatial concordance with generators of interictal activity, IED-related BOLD clusters and ESI estimates.

Avoiding the ballistocardiogram (BCG) artifact of EEG data acquired simultaneously with fMRI by pulse-triggered presentation of stimuli

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data could offer a much deeper understanding of brain function, e.g. in the analysis of tempo-spatial dynamics of brain activity in cognitive processing. However, more sophisticated analysis methods such as single-trial coupling of EEG and fMRI are often handicapped by the limited quality of EEGs acquired in the MRI scanner. In particular, the ballistocardiogram (BCG) artifact is still a relevant problem. Methods that are currently available typically remove the BCG artifact either in post-recording or real-time signal processing. Here, we would like to suggest a new strategy to avoid BCG artifacts during data acquisition. In our proposal, stimuli are presented pulse-triggered (PT), thus avoiding interference of BCG artifacts with the evoked potentials investigated during EEG recording. This method is based on the observation that the main influence of the BCG artifact is generally limited to the time interval of 150-500 ms post-QRS complex. Based on real measurements, we simulated different signal presentation methods relative to the onset of the BCG artifact for 14 subjects. Stimuli were either presented independently of the BCG artifact or pulse-triggered at fixed time-points (280 ms, 480 ms and 680 ms post-QRS complex) and with a jitter (short: 120 ms or long: 240 ms). In combination with an averaged artifact subtraction method signal distortion was reduced at best by 47%.

How wrong can we be? The effect of inaccurate mark-up of EEG/fMRI studies in epilepsy

OBJECTIVE

The aim of this investigation was to determine the effect of inaccurate or inconsistent marking up of events in the EEG on statistical analysis of EEG/fMRI studies of patients with epilepsy.

METHODS

EEGs obtained during EEG/fMRI studies conducted on 10 patients with epilepsy and six normal control subjects were reviewed. All clear epileptiform events were marked up in the patient EEGs, as were all small movement-related artefacts in the patient and control subject EEGs. We then considered the effect on the numbers of voxels above threshold in the resulting Statistical Parametric Mapping (SPM) analysis if events were omitted, mislabelled, or if event times were inconsistently marked up.

RESULTS

Omitting true epileptiform events resulted in a decrease in the number of voxels that survive statistical threshold. Mixing epileptiform and non-epileptiform events in the SPM analysis generally (but not always) decreased the number of voxels that survived threshold. Inconsistent event mark-up had little effect if the inconsistency was small (<200 ms), but had more effect if it was large (>500 ms).

CONCLUSION

It is important to accurately mark-up EEGs acquired during EEG/fMRI studies in order to get the best results from subsequent analyses.

SIGNIFICANCE

Our study reveals the consequences of inaccurate review of the EEG in EEG/fMRI studies and suggests guidelines for the review of EEG in these investigations which, if followed, should result in studies of acceptable quality.

Understanding gradient artefacts in simultaneous EEG/fMRI

Implementation of concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recording results in the generation of large artefacts that can compromise the quality of EEG data. While much effort has been devoted towards studying the temporal variation of the artefact waveforms produced by time-varying magnetic field gradients, the spatial variation of the artefact voltage across EEG leads has not previously been investigated in any depth. The aim of this work is to develop an improved understanding of the spatial characteristics of the gradient artefacts and the mechanism which underlies their generation. This paper therefore presents physical models of the artefacts produced by the temporally-varying magnetic field gradients required for MRI. Novel analytic expressions for the artefact voltage that account for realistic shifts and rotations of the human head were calculated from electromagnetic theory, assuming a spherical, homogeneous head and longitudinal wirepaths for the EEG cap. These were then corroborated by comparison with numerical simulations using actual EEG wirepaths and with experimental measurements on an agar phantom and human head. The numerical simulations produced accurate reproductions of experimentally measured spatial patterns for both the spherical phantom and human head in a variety of orientations and gradient fields; correlation coefficients were as high as 0.98 for the phantom and 0.95 for the human head. Furthermore, it was determined that artefact voltages for both longitudinal and transverse gradients could be decreased by adjusting the subject's axial position with respect to the gradient coils. The accuracy of the modelled spatial maps along with the ability to model gradient artefacts for any given head orientation are a step towards developing improved artefact correction algorithms that incorporate motion tracking of the subject and selective filtering based on calculated spatial artefact templates, leading to greater fidelity in simultaneous EEG/fMRI data.