EEG–fMRI of epileptic spikes: Concordance with EEG source localization and intracranial EEG

Ten quick tips for clinical electroencephalographic (EEG) data acquisition and signal processing

Electroencephalography (EEG) is a medical engineering technique aimed at recording the electric activity of the human brain. Brain signals derived from an EEG device can be processed and analyzed through computers by using digital signal processing, computational statistics, and machine learning techniques, that can lead to scientifically-relevant results and outcomes about how the brain works. In the last decades, the spread of EEG devices and the higher availability of EEG data, of computational resources, and of software packages for electroencephalography analysis has made EEG signal processing easier and faster to perform for any researcher worldwide. This increased ease to carry out computational analyses of EEG data, however, has made it easier to make mistakes, as well. And these mistakes, if unnoticed or treated wrongly, can in turn lead to wrong results or misleading outcomes, with worrisome consequences for patients and for the advancements of the knowledge about human brain. To tackle this problem, we present here our ten quick tips to perform electroencephalography signal processing analyses avoiding common mistakes: a short list of guidelines designed for beginners on what to do, how to do it, and what not to do when analyzing EEG data with a computer. We believe that following our quick recommendations can lead to better, more reliable and more robust results and outcome in clinical neuroscientific research.

Optimizing spatial accuracy in electroencephalography reconstruction through diffuse optical tomography priors in the auditory cortex

Diffuse optical tomography (DOT) enhances the localization accuracy of neural activity measured with electroencephalography (EEG) while preserving EEG's high temporal resolution. However, the spatial resolution of reconstructed activity diminishes for deeper neural sources. In this study, we analyzed DOT-enhanced EEG localization of neural sources modeled at depths ranging from 11-25 mm in simulations. Our findings reveal systematic biases in reconstructed depth related to DOT channel length. To address this, we developed a data-informed method for selecting DOT channels to improve the spatial accuracy of DOT-enhanced EEG reconstruction. Using our method, the average absolute reconstruction depth errors of DOT reconstruction across all depths are 0.9 ± 0.6 mm, 1.2 ± 0.9 mm, and 1.2 ± 1.1 mm under noiseless, low-level noise, and high-level noise conditions, respectively. In comparison, using fixed channel lengths resulted in errors of 2.6 ± 1.5 mm, 5.0 ± 2.6 mm, and 7.3 ± 4.5 mm under the same conditions. Consequently, our method improved the depth accuracy of DOT reconstructions and facilitated the use of more accurate spatial priors for EEG reconstructions, enhancing the overall precision of the technique.

Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

Post-stimulus encoding of decision confidence in EEG: toward a brain-computer interface for decision making

Objective.When making decisions, humans can evaluate how likely they are to be correct. If this subjective confidence could be reliably decoded from brain activity, it would be possible to build a brain-computer interface (BCI) that improves decision performance by automatically providing more information to the user if needed based on their confidence. But this possibility depends on whether confidence can be decoded right after stimulus presentation and before the response so that a corrective action can be taken in time. Although prior work has shown that decision confidence is represented in brain signals, it is unclear if the representation is stimulus-locked or response-locked, and whether stimulus-locked pre-response decoding is sufficiently accurate for enabling such a BCI.Approach.We investigate the neural correlates of confidence by collecting high-density electroencephalography (EEG) during a perceptual decision task with realistic stimuli. Importantly, we design our task to include a post-stimulus gap that prevents the confounding of stimulus-locked activity by response-locked activity and vice versa, and then compare with a task without this gap.Main results.We perform event-related potential and source-localization analyses. Our analyses suggest that the neural correlates of confidence are stimulus-locked, and that an absence of a post-stimulus gap could cause these correlates to incorrectly appear as response-locked. By preventing response-locked activity from confounding stimulus-locked activity, we then show that confidence can be reliably decoded from single-trial stimulus-locked pre-response EEG alone. We also identify a high-performance classification algorithm by comparing a battery of algorithms. Lastly, we design a simulated BCI framework to show that the EEG classification is accurate enough to build a BCI and that the decoded confidence could be used to improve decision making performance particularly when the task difficulty and cost of errors are high.Significance.Our results show feasibility of non-invasive EEG-based BCIs to improve human decision making.

Invasive Computational Psychiatry

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.

Preictal neuronal and vascular activity precedes the onset of childhood absence seizure: direct current potential shifts and their correlation with hemodynamic activity

SIGNIFICANCE AIMS

The neurovascular mechanisms underlying the initiation of absence seizures and their dynamics are still not well understood. The objective of this study was to better noninvasively characterize the dynamics of the neuronal and vascular network at the transition from the interictal state to the ictal state of absence seizures and back to the interictal state using a combined electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and diffuse correlation spectroscopy (DCS) approach. The second objective was to develop hypotheses about the neuronal and vascular mechanisms that propel the networks to the 3-Hz spikes and wave discharges (SWDs) observed during absence seizures.

APPROACHES

We evaluated the simultaneous changes in electrical (neuronal) and optical dynamics [hemodynamic, with changes in (Hb) and cerebral blood flow] of 8 pediatric patients experiencing 25 typical childhood absence seizures during the transition from the interictal state to the absence seizure by simultaneously performing EEG, fNIRS, and DCS.

RESULTS

Starting from ∼ 20    s before the onset of the SWD, we observed a transient direct current potential shift that correlated with alterations in functional fNIRS and DCS measurements of the cerebral hemodynamics detecting the preictal changes.

DISCUSSION

Our noninvasive multimodal approach highlights the dynamic interactions between the neuronal and vascular compartments that take place in the neuronal network near the time of the onset of absence seizures in a very specific cerebral hemodynamic environment. These noninvasive approaches contribute to a better understanding of the electrical hemodynamic environment prior to seizure onset. Whether this may ultimately be relevant for diagnostic and therapeutic approaches requires further evaluation.

EEG-fMRI of epileptiform discharges: non-invasive investigation of the whole brain

Simultaneous EEG-fMRI is a unique and non-invasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the Default Mode Network (DMN) in absences and focal epilepsy, and proposed a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or MEG and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, pre-surgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.

Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data

BACKGROUND AND OBJECTIVES

Accurate delineation of the seizure-onset zone (SOZ) in focal drug-resistant epilepsy often requires stereo-EEG (SEEG) recordings. Our aims were to propose a truly objective and quantitative comparison between EEG/magnetoencephalography (MEG) source imaging (EMSI), EEG/fMRI responses for similar spikes with primary irritative zone (PIZ) and SOZ defined by SEEG and to evaluate the value of EMSI and EEG/fMRI to predict postsurgical outcome.

METHODS

We identified patients with drug-resistant epilepsy who underwent EEG/MEG, EEG/fMRI, and subsequent SEEG at the Epilepsy Service from the Montreal Neurological Institute and Hospital. We quantified multimodal concordance within the SEEG channel space as spatial overlap with PIZ/SOZ and distances to the spike-onset, spike maximum amplitude and seizure core intracerebral channels by applying a new methodology consisting of converting EMSI results into SEEG electrical potentials (EMSIe-SEEG) and projecting the most significant fMRI response on the SEEG channels (fMRIp-SEEG). Spatial overlaps with PIZ/SOZ (AUCPIZ, AUCSOZ) were assessed by using the area under the receiver operating characteristic curve (AUC). Here, AUC represents the probability that a randomly picked active contact exhibited higher amplitude when located inside the spatial reference than outside.

RESULTS

Seventeen patients were included. Mean spatial overlaps with the PIZ and SOZ were 0.71 and 0.65 for EMSIe-SEEG and 0.57 and 0.62 for fMRIp-SEEG. Good EMSIe-SEEG spatial overlap with the PIZ was associated with smaller distance from the maximum EMSIe-SEEG contact to the spike maximum amplitude channel (median distance 14 mm). Conversely, good fMRIp-SEEG spatial overlap with the SOZ was associated with smaller distances from the maximum fMRIp-SEEG contact to the spike-onset and seizure core channels (median distances 10 and 5 mm, respectively). Surgical outcomes were correctly predicted by EEG/MEG in 12 of 15 (80%) patients and EEG/fMRI in 6 of 11(54%) patients.

DISCUSSION

With the use of a unique quantitative approach estimating EMSI and fMRI results in the reference SEEG channel space, EEG/MEG and EEG/fMRI accurately localized the SOZ and the PIZ. Precisely, EEG/MEG more accurately localized the PIZ, whereas EEG/fMRI was more sensitive to the SOZ. Both neuroimaging techniques provide complementary localization that can help guide SEEG implantation and select good candidates for surgery.

Simultaneous EEG-fMRI: What Have We Learned and What Does the Future Hold?

Simultaneous EEG-fMRI has developed into a mature measurement technique in the past 25 years. During this time considerable technical and analytical advances have been made, enabling valuable scientific contributions to a range of research fields. This review will begin with an introduction to the measurement principles involved in EEG and fMRI and the advantages of combining these methods. The challenges faced when combining the two techniques will then be considered. An overview of the leading application fields where EEG-fMRI has made a significant contribution to the scientific literature and emerging applications in EEG-fMRI research trends is then presented.

Localizing Epileptic Foci Using Simultaneous EEG-fMRI Recording: Template Component Cross-Correlation

Conventional EEG-fMRI methods have been proven to be of limited use in the sense that they cannot reveal the information existing in between the spikes. To resolve this issue, the current study obtains the epileptic components time series detected on EEG and uses them to fit the Generalized Linear Model (GLM), as a substitution for classical regressors. This approach allows for a more precise localization, and equally importantly, the prediction of the future behavior of the epileptic generators. The proposed method approaches the localization process in the component domain, rather than the electrode domain (EEG), and localizes the generators through investigating the spatial correlation between the candidate components and the spike template, as well as the medical records of the patient. To evaluate the contribution of EEG-fMRI and concordance between fMRI and EEG, this method was applied on the data of 30 patients with refractory epilepsy. The results demonstrated the significant numbers of 29 and 24 for concordance and contribution, respectively, which mark improvement as compared to the existing literature. This study also shows that while conventional methods often fail to properly localize the epileptogenic zones in deep brain structures, the proposed method can be of particular use. For further evaluation, the concordance level between IED-related BOLD clusters and Seizure Onset Zone (SOZ) has been quantitatively investigated by measuring the distance between IED/SOZ locations and the BOLD clusters in all patients. The results showed the superiority of the proposed method in delineating the spike-generating network compared to conventional EEG-fMRI approaches. In all, the proposed method goes beyond the conventional methods by breaking the dependency on spikes and using the outside-the-scanner spike templates and the selected components, achieving an accuracy of 97%. Doing so, this method contributes to improving the yield of EEG-fMRI and creates a more realistic perception of the neural behavior of epileptic generators which is almost without precedent in the literature.

Association of EEG-fMRI Responses and Outcome After Epilepsy Surgery

BACKGROUND AND OBJECTIVES

To assess the utility of EEG-fMRI for epilepsy surgery, we evaluated surgical outcome in relation to the resection of the most significant EEG-fMRI response.

METHODS

Patients with postoperative neuroimaging and follow-up of at least 1 year were included. In EEG-fMRI responses, we defined as primary the cluster with the highest absolute t value located in the cortex and evaluated 3 levels of confidence for the results. The threshold for low confidence was t ≥ 3.1 (p < 0.005); the one for medium confidence corresponded to correction for multiple comparisons with a false discovery rate of 0.05; and a result reached high confidence when the primary cluster was much more significant than the next highest cluster. Concordance with the resection was determined by comparison to postoperative neuroimaging.

RESULTS

We evaluated 106 epilepsy surgeries in 84 patients. An increasing association between concordance and surgical outcome with higher levels of confidence was demonstrated. If the peak response was not resected, the surgical outcome was likely to be poor: for the high confidence level, no patient had a good outcome; for the medium and low levels, only 18% and 28% had a good outcome. The positive predictive value remained low for all confidence levels, indicating that removing the maximum cluster did not ensure seizure freedom.

DISCUSSION

Resection of the primary EEG-fMRI cluster, especially in high confidence cases, is necessary to obtain a good outcome but not sufficient.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that failure to resect the primary EEG-fMRI cluster is associated with poorer epilepsy surgery outcomes.

Numerical simulation of the radiofrequency safety of 128-channel hd-EEG nets on a 29-month-old whole-body model in a 3 Tesla MRI

This study investigates the radiofrequency (RF) induced heating in a pediatric whole-body voxel model with a high-density electroencephalogram (hd-EEG) net during magnetic resonance imaging (MRI) at 3 Tesla. A total of three cases were studied: no net (NoNet), a resistive hd-EEG (NeoNet), and a copper (CuNet) net. The maximum values of specific absorption rate averaged over 10g-mass (10gSAR) in the head were calculated with the NeoNet was 12.51 W/kg and in the case of the NoNet was 12.40 W/kg. In contrast, the CuNet case was 17.04 W/Kg. Temperature simulations were conducted to determine the RF-induced heating without and with hd-EEG nets (NeoNet and CuNet) during an MRI scan using an age-corrected and thermoregulated perfusion for the child model. The results showed that the maximum temperature estimated in the child's head was 38.38 °C for the NoNet, 38.43 °C for the NeoNet, and 43.05 °C for the CuNet. In the case of NeoNet, the maximum temperature estimated in the child's head remained compliant with IEC 60601 for the MRI RF safety limit. However, the case of CuNet estimated to exceed the RF safety limit, which may require an appropriate cooling period or a hardware design to suppress the RF-induced heating.

When Is Simultaneous Recording Necessary? A Guide for Researchers Considering Combined EEG-fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide non-invasive measures of brain activity at varying spatial and temporal scales, offering different views on brain function for both clinical and experimental applications. Simultaneous recording of these measures attempts to maximize the respective strengths of each method, while compensating for their weaknesses. However, combined recording is not necessary to address all research questions of interest, and experiments may have greater statistical power to detect effects by maximizing the signal-to-noise ratio in separate recording sessions. While several existing papers discuss the reasons for or against combined recording, this article aims to synthesize these arguments into a flow chart of questions that researchers can consider when deciding whether to record EEG and fMRI separately or simultaneously. Given the potential advantages of simultaneous EEG-fMRI, the aim is to provide an initial overview of the most important concepts and to direct readers to relevant literature that will aid them in this decision.

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.

Preoperative localization of seizure onset zones by magnetic source imaging, EEG-correlated functional MRI, and their combination

OBJECTIVE

Preoperative localization of seizure onset zones (SOZs) is an evolving field in the treatment of refractory epilepsy. Both magnetic source imaging (MSI), and the more recent EEG-correlated functional MRI (EEG-fMRI), have shown applicability in assisting surgical planning. The purpose of this study was to evaluate the capability of each method and their combination in localizing the seizure onset lobe (SL).

METHODS

The study included 14 patients who underwent both MSI and EEG-fMRI before undergoing implantation of intracranial EEG (icEEG) as part of the presurgical planning of the resection of an epileptogenic zone (EZ) during the years 2012-2018. The estimated location of the SL by each method was compared with the location determined by icEEG. Identification rates of the SL were compared between the different methods.

RESULTS

MSI and EEG-fMRI showed similar identification rates of SL locations in relation to icEEG results (88% ± 31% and 73% ± 42%, respectively; p = 0.281). The additive use of the coverage lobes of both methods correctly identified 100% of the SL, significantly higher than EEG-fMRI alone (p = 0.039) and nonsignificantly higher than MSI (p = 0.180). False-identification rates of the additive coverage lobes were significantly higher than MSI (p = 0.026) and EEG-fMRI (p = 0.027). The intersecting lobes of both methods showed the lowest false identification rate (13% ± 6%, p = 0.01).

CONCLUSIONS

Both MSI and EEG-fMRI can assist in the presurgical evaluation of patients with refractory epilepsy. The additive use of both tests confers a high identification rate in finding the SL. This combination can help in focusing implantation of icEEG electrodes targeting the SOZ.

What Triggers the Interictal Epileptic Spike? A Multimodal Multiscale Analysis of the Dynamic of Synaptic and Non-synaptic Neuronal and Vascular Compartments Using Electrical and Optical Measurements

Interictal spikes (IISs) may result from a disturbance of the intimate functional balance between various neuronal (synaptic and non-synaptic), vascular, and metabolic compartments. To better characterize the complex interactions within these compartments at different scales we developed a simultaneous multimodal-multiscale approach and measure their activity around the time of the IIS. We performed such measurements in an epileptic rat model (n = 43). We thus evaluated (1) synaptic dynamics by combining electrocorticography and multiunit activity recording in the time and time-frequency domain, (2) non-synaptic dynamics by recording modifications in light scattering induced by changes in the membrane configuration related to cell activity using the fast optical signal, and (3) vascular dynamics using functional near-infrared spectroscopy and, independently but simultaneously to the electrocorticography, the changes in cerebral blood flow using diffuse correlation spectroscopy. The first observed alterations in the measured signals occurred in the hemodynamic compartments a few seconds before the peak of the IIS. These hemodynamic changes were followed by changes in coherence and then synchronization between the deep and superficial neural networks in the 1 s preceding the IIS peaks. Finally, changes in light scattering before the epileptic spikes suggest a change in membrane configuration before the IIS. Our multimodal, multiscale approach highlights the complexity of (1) interactions between the various neuronal, vascular, and extracellular compartments, (2) neural interactions between various layers, (3) the synaptic mechanisms (coherence and synchronization), and (4) non-synaptic mechanisms that take place in the neuronal network around the time of the IISs in a very specific cerebral hemodynamic environment.

Functional connectivity of the irritative zone identified by electrical source imaging, and EEG-correlated fMRI analyses

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The irritative zone differs on Electrical Source Imaging (ESI) and EEG-fMRI.

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Findings differ in functional connectivity and show low temporal correlation.

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ESI and EEG-fMRI reveal distinct aspects of the irritative zone.

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The differences may reflect differences in temporal resolution of the techniques.

Objective

The irritative zone - the area generating epileptic spikes - can be studied non-invasively during the interictal period using Electrical Source Imaging (ESI) and simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI). Although the techniques yield results which may overlap spatially, differences in spatial localization of the irritative zone within the same patient are consistently observed. To investigate this discrepancy, we used Blood Oxygenation Level Dependent (BOLD) functional connectivity measures to examine the underlying relationship between ESI and EEG-fMRI findings.

Methods

Fifteen patients (age 20–54), who underwent presurgical epilepsy investigation, were scanned using a single-session resting-state EEG-fMRI protocol. Structural MRI was used to obtain the electrode localisation of a high-density 64-channel EEG cap. Electrical generators of interictal epileptiform discharges were obtained using a distributed local autoregressive average (LAURA) algorithm as implemented in Cartool EEG software. BOLD activations were obtained using both spike-related and voltage-map EEG-fMRI analysis. The global maxima of each method were used to investigate the temporal relationship of BOLD time courses and to assess the spatial similarity using the Dice similarity index between functional connectivity maps.

Results

ESI, voltage-map and spike-related EEG-fMRI methods identified peaks in 15 (100%), 13 (67%) and 8 (53%) of the 15 patients, respectively. For all methods, maxima were localised within the same lobe, but differed in sub-lobar localisation, with a median distance of 22.8 mm between the highest peak for each method. The functional connectivity analysis showed that the temporal correlation between maxima only explained 38% of the variance between the time course of the BOLD response at the maxima. The mean Dice similarity index between seed-voxel functional connectivity maps showed poor spatial agreement.

Significance

Non-invasive methods for the localisation of the irritative zone have distinct spatial and temporal sensitivity to different aspects of the local cortical network involved in the generation of interictal epileptiform discharges.

Interictal stereotactic-EEG functional connectivity in refractory focal epilepsies

Drug-refractory focal epilepsies are network diseases associated with functional connectivity alterations both during ictal and interictal periods. A large majority of studies on the interictal/resting state have focused on functional MRI-based functional connectivity. Few studies have used electrophysiology, despite its high temporal capacities. In particular, stereotactic-EEG is highly suitable to study functional connectivity because it permits direct intracranial electrophysiological recordings with relative large-scale sampling. Most previous studies in stereotactic-EEG have been directed towards temporal lobe epilepsy, which does not represent the whole spectrum of drug-refractory epilepsies. The present study aims at filling this gap, investigating interictal functional connectivity alterations behind cortical epileptic organization and its association with post-surgical prognosis. To this purpose, we studied a large cohort of 59 patients with malformation of cortical development explored by stereotactic-EEG with a wide spatial sampling (76 distinct brain areas were recorded, median of 13.2 per patient). We computed functional connectivity using non-linear correlation. We focused on three zones defined by stereotactic-EEG ictal activity: the epileptogenic zone, the propagation zone and the non-involved zone. First, we compared within-zone and between-zones functional connectivity. Second, we analysed the directionality of functional connectivity between these zones. Third, we measured the associations between functional connectivity measures and clinical variables, especially post-surgical prognosis. Our study confirms that functional connectivity differs according to the zone under investigation. We found: (i) a gradual decrease of the within-zone functional connectivity with higher values for epileptogenic zone and propagation zone, and lower for non-involved zones; (ii) preferential coupling between structures of the epileptogenic zone; (iii) preferential coupling between epileptogenic zone and propagation zone; and (iv) poorer post-surgical outcome in patients with higher functional connectivity of non-involved zone (within- non-involved zone, between non-involved zone and propagation zone functional connectivity). Our work suggests that, even during the interictal state, functional connectivity is reinforced within epileptic cortices (epileptogenic zone and propagation zone) with a gradual organization. Moreover, larger functional connectivity alterations, suggesting more diffuse disease, are associated with poorer post-surgical prognosis. This is consistent with computational studies suggesting that connectivity is crucial in order to model the spatiotemporal dynamics of seizures.10.1093/brain/awy214_video1awy214media15833456182001.

Spike-related haemodynamic responses overlap with high frequency oscillations in patients with focal epilepsy

Simultaneous scalp EEG/functional MRI measures non-invasively haemodynamic responses to interictal epileptic discharges, which are related to the epileptogenic zone. High frequency oscillations are also an excellent indicator of this zone, but are primarily recorded from intracerebral EEG. We studied the spatial overlap of these two important markers in patients with drug-resistant epilepsy to assess if their combination could help better define the extent of the epileptogenic zone. We included patients who underwent EEG-functional MRI and later intracerebral EEG. Based on intracerebral EEG findings, we separated patients with unifocal seizures from patients with multifocal or unknown onset seizures. Haemodynamic t-maps were coregistered with the intracerebral electrode positions. Each EEG channel was classified as pertaining to one of the following categories: primary haemodynamic cluster (maximum t-value), secondary cluster (t-value > 90% of the primary cluster) or outside the primary and secondary clusters. We marked high frequency oscillations (ripples: 80-250 Hz; fast ripples: 250-500 Hz) during 1 h of slow wave sleep, and compared their rates in each haemodynamic category. After classifying channels as high- or low-rate, the proportion of high-rate channels within the primary or primary plus secondary clusters was compared to the proportion expected by chance. Twenty-five patients, 11 with unifocal and 14 with multifocal/unknown seizure onsets, were studied. We found a significantly higher median high frequency oscillation rate in the primary cluster compared to secondary cluster and outside these two clusters for the unifocal group (P < 0.0001), but not for the multifocal/unknown group. For the unifocal group, the number of high-rate channels within the primary or primary plus secondary clusters was significantly higher than expected by chance. This held only for the high-ripple-rate channels in the multifocal/unknown group. At the patient level, most patients (18/25, or 72%) had at least one high-rate channel within a primary cluster. In patients with unifocal epilepsy, the maximum haemodynamic response (primary cluster) related to scalp interictal discharges overlaps with the tissue generating high frequency oscillations at high rates. If intracranial EEG is warranted, this response should be explored. As a tentative clinical use of the combination of these techniques we propose that higher high frequency oscillation rates inside than outside the maximum response indicates that the patient has indeed a focal epileptogenic zone demarcated by this response, whereas similar rates inside and outside may indicate a widespread epileptogenic zone or an epileptogenic zone not covered by the implantation.

Quantitative determination of concordance in localizing epileptic focus by component-based EEG-fMRI

BACKGROUND AND OBJECTIVE

Accurate seizure onset zone (SOZ) localization is an essential step in pre-surgical assessment of patients with refractory focal epilepsy. Complex pathophysiology of epileptic cerebral structures, seizure types and frequencies have not been considered as influential features for accurate identification of SOZ using EEG-fMRI. There is a crucial need to quantitatively measure concordance between presumed SOZ and IED-related BOLD response in different brain regions to improve SOZ delineation.

METHODS

A novel component-based EEG-fMRI approach is proposed to measure physical distance between BOLD clusters and selected component dipole location using patient-specific high resolution anatomical images. The method is applied on 18 patients with refractory focal epilepsy to localize epileptic focus and determine concordance quantitatively and compare between maximum BOLD cluster with identified component dipole. To measure concordance, distance from a voxel with maximal z-score of maximum BOLD to center of extracted component dipole is measured.

RESULTS

BOLD clusters to spikes distances for concordant (<25 mm), partially concordant (25-50 mm), and discordant (>50 mm) groups were significantly different (p < 0.0001). The results showed full concordance in 17 IED types (17.85 ± 4.69 mm), partial concordance in 4 (36.47 ± 8.84 mm), and nodiscordance, which is a significant rise compared to the existing literature. The proposed method is premised on the cross-correlation between the spike template outside the scanner and the highly-ranked extracted components. It successfully surpasses the limitations of conventional EEG-fMRI studies which are largely dependent on inside-scanner spikes. More significantly, the proposed method improves localization accuracy to 97% which marks a dramatic rise compared to conventional works.

CONCLUSIONS

This study demonstrated that BOLD changes were related to epileptic spikes in different brain regions in patients with refractory focal epilepsy. In a systematic quantitative approach, concordance levels based on the distance between center of maximum BOLD cluster and dipole were determined by component-based EEG-fMRI method. Therefore, component-based EEG-fMRI can be considered as a reliable predictor of SOZ in patients with focal epilepsy and included as part of clinical evaluation for patients with medically resistant epilepsy.

Presurgical intracranial investigations in epilepsy surgery

Identification and localization of the "epileptogenic process" in the brain of patients with drug-resistant epilepsy for surgical cure is the goal of presurgical investigations. Intracranial recordings are required when conflicting data between seizure clinical semiology and EEG prevent precise localization within one hemisphere or lateralization, when a visible lesion on MRI seems unrelated to the electroclinical data, or in MRI-negative cases. Two methods are currently used. The objective of the subdural grid electrocorticography with or without depth electrodes (SDG/DE) is the best possible identification of the area of onset of spontaneous seizures and localization of the eloquent cortex. The objective of stereoelectroencephalography (SEEG) is to define the epileptogenic zone (configured as a network) and its relation to an unmasked lesion. Two-dimensional (SDG) and three-dimensional (SEEG) brain sampling dictate different strategies for noninvasive presurgical phase I goals as well as for data analysis. SEEG must resolve several potential localization hypotheses in a manner that cannot be achieved with SDG. SDG operates through brain surface coverage, unlike SEEG, which samples networks. SDG estimates the extent of cortical resection through a lobar or sublobar localization of ictal onset and constraints from functional mapping. SEEG defines a tailored resection according to the results of anatomo-electro-clinical correlations in stereotaxic space that will guide the ablation of the epileptogenic zone. SEEG is currently expanding faster than SDG. The prerequisites (especially in the preimplantation hypothetical strategy) and technical tools (especially stimulation and functional mapping) in the two methods are very different. This chapter presents a comparative review of the rationale, indications, electrode implantation strategies, interpretation, and surgical decision making of these two approaches of presurgical evaluation for epilepsy surgery.

The spike onset zone: The region where epileptic spikes start and from where they propagate

OBJECTIVE

To determine whether the maximum hemodynamic response to scalp interictal epileptic discharges (IEDs) corresponds to the region where IEDs originate and from where they propagate.

METHODS

We studied 19 patients who underwent first an EEG-fMRI showing responses in the gray matter, and then intracranial EEG (iEEG). We coregistered the hemodynamic responses to the iEEG electrode contacts and analyzed IEDs in the iEEG channel adjacent to a maximum response (labeled the main channel), in relation to IEDs in other channels during a widespread intracranial IED event. IEDs in the main channel were aligned at their peak, and IEDs in each channel were averaged time-locked to these instants. The beginning and peak of IEDs in the averaged trace were identified, blinded to the identity of the main channel. The latency of IEDs was computed between the earliest and all other channels.

RESULTS

The median latency of IEDs in the main channel was significantly smaller than in other channels for either the peak (15.5 vs 67.5 milliseconds, p = 0.00037) or the beginning (46.5 vs 118.4 milliseconds, p = 0.000048). The latency of IED was significantly correlated to the distance from the maximum hemodynamic response (p < 0.0001 for either the peak or the beginning).

CONCLUSION

IED adjacent to a maximum hemodynamic response, which often corresponds to the seizure onset zone, is more likely to precede IEDs in remote locations during a widespread intracranial discharge. Thus, EEG-fMRI is a unique noninvasive method to reveal the origin of IEDs, which we propose to label the spike onset zone.

Exploration of the Pathophysiology of Chronic Pain Using Quantitative EEG Source Localization

Chronic pain affects more than 35% of the US adult population representing a major public health imperative. Currently, there are no objective means for identifying the presence of pain, nor for quantifying pain severity. Through a better understanding of the pathophysiology of pain, objective indicators of pain might be forthcoming. Brain mechanisms mediating the painful state were imaged in this study, using source localization of the EEG. In a population of 77 chronic pain patients, significant overactivation of the "Pain Matrix" or pain network, was found in brain regions including, the anterior cingulate, anterior and posterior insula, parietal lobule, thalamus, S1, and dorsolateral prefrontal cortex (DLPFC), consistent with those reported with conventional functional imaging, and extended to include the mid and posterior cingulate, suggesting that the increased temporal resolution of electrophysiological measures may allow a more precise identification of the pain network. Significant differences between those who self-report high and low pain were reported for some of the regions of interest (ROIs), maximally on left hemisphere in the DLPFC, suggesting encoding of pain intensity occurs in a subset of pain network ROIs. Furthermore, a preliminary multivariate logistic regression analysis was used to select quantitative-EEG features which demonstrated a highly significant predictive relationship of self-reported pain scores. Findings support the potential to derive a quantitative measure of the severity of pain using information extracted from a multivariate descriptor of the abnormal overactivation. Furthermore, the frequency specific (theta/low alpha band) overactivation in the regions reported, while not providing direct evidence, are consistent with a model of thalamocortical dysrhythmia as the potential mechanism of the neuropathic painful condition.

Neuroimaging in Epilepsy

In recent years, the field of neuroimaging has undergone dramatic development. Specifically, of importance for clinicians and researchers managing patients with epilepsies, new methods of brain imaging in search of the seizure-producing abnormalities have been implemented, and older methods have undergone additional refinement. Methodology to predict seizure freedom and cognitive outcome has also rapidly progressed. In general, the image data processing methods are very different and more complicated than even a decade ago. In this review, we identify the recent developments in neuroimaging that are aimed at improved management of epilepsy patients. Advances in structural imaging, diffusion imaging, fMRI, structural and functional connectivity, hybrid imaging methods, quantitative neuroimaging, and machine-learning are discussed. We also briefly summarize the potential new developments that may shape the field of neuroimaging in the near future and may advance not only our understanding of epileptic networks as the source of treatment-resistant seizures but also better define the areas that need to be treated in order to provide the patients with better long-term outcomes.

Combined electroencephalography-functional magnetic resonance imaging and electrical source imaging improves localization of pediatric focal epilepsy

OBJECTIVE

Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data to derive EEG-fMRI and electrical source imaging (ESI) maps. Their yield and their individual and combined ability to (1) localize the EZ and (2) predict seizure outcome were then evaluated.

METHODS

Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI hemodynamic responses and ESI. A single localization was derived from each individual test (EEG-fMRI global maxima [GM]/ESI maximum) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localization accuracy and its predictive performance, the individual and combined test localizations were compared to the presumed EZ and to the postsurgical outcome.

RESULTS

Fifty-two of 53 patients had significant maps: 47 of 53 for EEG-fMRI, 44 of 53 for ESI, and 34 of 53 for both. The EZ was well characterized in 29 patients; 26 had an EEG-fMRI GM localization that was correct in 11, 22 patients had ESI localization that was correct in 17, and 12 patients had combined EEG-fMRI and ESI that was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8 of 20 patients, and by the ESI maximum in 13 of 16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9 of 9 patients, including 3 with no lesion visible on MRI.

INTERPRETATION

EEG-fMRI combined with ESI provides a simple unbiased localization that may predict surgery better than each individual test, including in MRI-negative patients. Ann Neurol 2017;82:278-287.

Spatiotemporal mapping of epileptic spikes using simultaneous EEG-functional MRI

Epileptic spikes occur on the sub-second timescale and are known to involve not only epileptic foci but also large-scale distributed brain networks. There is likely to be a sequence of neural activity in multiple brain regions that occurs within the duration of a single spike, but standard electroencephalography-functional magnetic resonance imaging analyses, which use only the timing of the spikes to model the functional magnetic resonance imaging data, cannot determine the sequence of these activations. Our aim in this study is to temporally resolve these spatial activations to observe the spatiotemporal dynamics of the spike-related neural activity at a sub-second timescale. We studied eight focal epilepsy patients (age 11-42 years, six female) and used amplitude features of the electroencephalogram specific to different spike components (early and late peaks and troughs) to encode temporal information into our functional magnetic resonance imaging models. This enables us to associate each activation with a specific model of each of the spike components to infer the temporal order of these spike-related spatial activations. In seven of eight patients the distributed networks were associated with the late spike component. The focal activations were more variably coupled with time epochs, but tended to precede the distributed network effects. We also found that incorporating electroencephalogram features into the models increased sensitivity and in six patients revealed additional regions unseen in the standard analysis result. This included strong bilateral thalamus activation in two patients. We demonstrate the clinical utility of this approach in a patient who recently underwent a successful surgical resection of the region where we saw enhanced activation using electroencephalogram amplitude information specific to the early spike component. This focal cluster of activation was larger and more precisely tracked the anatomy compared to what was seen using the standard timing-based analysis. Our novel electroencephalography-functional magnetic resonance imaging data fusion approach, which utilizes information based on the single spike variability across all electroencephalogram channels, has the potential to help us better understand epileptic networks and aid in the interpretation of functional magnetic resonance imaging activation maps during treatment planning.

A study of the electro-haemodynamic coupling using simultaneously acquired intracranial EEG and fMRI data in humans

In current fMRI studies designed to map BOLD changes related to interictal epileptiform discharges (IED), which are recorded on simultaneous EEG, the information contained in the morphology and field extent of the EEG events is exclusively used for their classification. Usually, a BOLD predictor based on IED onset times alone is constructed, effectively treating all events as identical. We used intracranial EEG (icEEG)-fMRI data simultaneously recorded in humans to investigate the effect of including any of the features: amplitude, width (duration), slope of the rising phase, energy (area under the curve), or spatial field extent (number of contacts over which the sharp wave was observed) of the fast wave of the IED (the sharp wave), into the BOLD model, to better understand the neurophysiological origin of sharp wave-related BOLD changes, in the immediate vicinity of the recording contacts. Among the features considered, the width was the only one found to explain a significant amount of additional variance, suggesting that the amplitude of the BOLD signal depends more on the duration of the underlying field potential (reflected in the sharp wave width) than on the degree of neuronal activity synchrony (reflected in the sharp wave amplitude), and, consequently, that including inter-event variations of the sharp wave width in the BOLD signal model may increase the sensitivity of forthcoming EEG-fMRI studies of epileptic activity.

A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies

Due to its high temporal resolution, electroencephalography (EEG) is widely used to study functional and effective brain connectivity. Yet, there is currently a mismatch between the vastness of studies conducted and the degree to which the employed analyses are theoretically understood and empirically validated. We here provide a simulation framework that enables researchers to test their analysis pipelines on realistic pseudo-EEG data. We construct a minimal example of brain interaction, which we propose as a benchmark for assessing a methodology's general eligibility for EEG-based connectivity estimation. We envision that this benchmark be extended in a collaborative effort to validate methods in more complex scenarios. Quantitative metrics are defined to assess a method's performance in terms of source localization, connectivity detection and directionality estimation. All data and code needed for generating pseudo-EEG data, conducting source reconstruction and connectivity estimation using baseline methods from the literature, evaluating performance metrics, as well as plotting results, are made publicly available. While this article covers only EEG modeling, we will also provide a magnetoencephalography version of our framework online.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.

Interneurons contribute to the hemodynamic/metabolic response to epileptiform discharges

Interpretation of hemodynamic responses in epilepsy is hampered by an incomplete understanding of the underlying neurovascular coupling, especially the contributions of excitation and inhibition. We made simultaneous multimodal recordings of local field potentials (LFPs), firing of individual neurons, blood flow, and oxygen level in the somatosensory cortex of anesthetized rats. Epileptiform discharges induced by bicuculline injections were used to trigger large local events. LFP and blood flow were robustly coupled, as were LFP and tissue oxygen. In a parametric linear model, LFP and the baseline activities of cerebral blood flow and tissue partial oxygen tension contributed significantly to blood flow and oxygen responses. In an analysis of recordings from 402 neurons, blood flow/tissue oxygen correlated with the discharge of putative interneurons but not of principal cells. Our results show that interneuron activity is important in the vascular and metabolic responses during epileptiform discharges.

Concordance of Epileptic Networks Associated with Epileptic Spikes Measured by High-Density EEG and Fast fMRI

Objective

The present study aims to investigate whether a newly developed fast fMRI called MREG (magnetic resonance encephalography) measures metabolic changes related to interictal epileptic discharges (IED). For this purpose BOLD changes are correlated with the IED distribution and variability.

Methods

Patients with focal epilepsy underwent EEG-MREG using a 64 channel cap. IED voltage maps were generated using 32 and 64 channels and compared regarding their correspondence to the BOLD response. The extents of IEDs (defined as number of channels with >50% of maximum IED negativity) were correlated with the extents of positive and negative BOLD responses. Differences in inter-spike variability were investigated between interictal epileptic discharges (IED) sets with and without concordant positive or negative BOLD responses.

Results

17 patients showed 32 separate IED types. In 50% of IED types the BOLD changes could be confirmed by another independent imaging method. The IED extent significantly correlated with the positive BOLD extent (p = 0.04). In 6 patients the 64-channel EEG voltage maps better reflected the positive or negative BOLD response than the 32-channel EEG; in all others no difference was seen. Inter-spike variability was significantly lower in IED sets with than without concordant positive or negative BOLD responses (with p = 0.04).

Significance

Higher density EEG and fast fMRI seem to improve the value of EEG-fMRI in epilepsy. The correlation of positive BOLD and IED extent could suggest that widespread BOLD responses reflect the IED network. Inter-spike variability influences the likelihood to find IED concordant positive or negative BOLD responses, which is why single IED analysis may be promising.

Patient specific hemodynamic response functions associated with interictal discharges recorded via simultaneous intracranial EEG-fMRI

Simultaneous collection of scalp EEG and fMRI has become an important tool for studying the hemodynamic changes associated with interictal epileptiform discharges (IEDs) in persons with epilepsy, and has become a standard presurgical assessment tool in some centres. We previously demonstrated that performing EEG-fMRI using intracranial electrodes (iEEG-fMRI) is of low risk to patients in our research centre, and offers unique insight into BOLD signal changes associated with IEDs recorded from very discrete sources. However, it is unknown whether the BOLD response corresponding to IEDs recorded by iEEG-fMRI follows the canonical hemodynamic response. We therefore scanned 11 presurgical epilepsy patients using iEEG-fMRI, and assessed the hemodynamic response associated with individual IEDs using two methods: assessment of BOLD signal changes associated with isolated IEDs at the location of the active intracranial electrode, and by estimating subject-specific impulse response functions to isolated IEDs. We found that the hemodynamic response associated with the intracranially recorded discharges varied by patient and by spike location. The observed shape and timing differences also deviated from the canonical hemodynamic response function traditionally used in many fMRI experiments. It is recommended that future iEEG-fMRI studies of IEDs use a flexible hemodynamic response model when performing parametric tests to accurately characterize these data.

Network analysis of EEG related functional MRI changes due to medication withdrawal in focal epilepsy

Anti-epileptic drugs (AEDs) have a global effect on the neurophysiology of the brain which is most likely reflected in functional brain activity recorded with EEG and fMRI. These effects may cause substantial inter-subject variability in studies where EEG correlated functional MRI (EEG-fMRI) is used to determine the epileptogenic zone in patients who are candidate for epilepsy surgery. In the present study the effects on resting state fMRI are quantified in conditions with AED administration and after withdrawal of AEDs. EEG-fMRI data were obtained from 10 patients in the condition that the patient was on the steady-state maintenance doses of AEDs as prescribed (condition A) and after withdrawal of AEDs (condition B), at the end of a clinically standard pre-surgical long term video-EEG monitoring session. Resting state networks (RSN) were extracted from fMRI. The epileptic component (ICE) was identified by selecting the RSN component with the largest overlap with the EEG-fMRI correlation pattern. Changes in RSN functional connectivity between conditions A and B were quantified. EEG-fMRI correlation analysis was successful in 30% and 100% of the cases in conditions A and B, respectively. Spatial patterns of ICEs are comparable in conditions A and B, except for one patient for whom it was not possible to identify the ICE in condition A. However, the resting state functional connectivity is significantly increased in the condition after withdrawal of AEDs (condition B), which makes resting state fMRI potentially a new tool to study AED effects. The difference in sensitivity of EEG-fMRI in conditions A and B, which is not related to the number of epileptic EEG events occurring during scanning, could be related to the increased functional connectivity in condition B.

A Comparison of Independent Component Analysis (ICA) of fMRI and Electrical Source Imaging (ESI) in Focal Epilepsy Reveals Misclassification Using a Classifier

Interictal epileptiform discharges (IEDs) can produce haemodynamic responses that can be detected by electroencephalography-functional magnetic resonance imaging (EEG-fMRI) using different analysis methods such as the general linear model (GLM) of IEDs or independent component analysis (ICA). The IEDs can also be mapped by electrical source imaging (ESI) which has been demonstrated to be useful in presurgical evaluation in a high proportion of cases with focal IEDs. ICA advantageously does not require IEDs or a model of haemodynamic responses but its use in EEG-fMRI of epilepsy has been limited by its ability to separate and select epileptic components. Here, we evaluated the performance of a classifier that aims to filter all non-BOLD responses and we compared the spatial and temporal features of the selected independent components (ICs). The components selected by the classifier were compared to those components selected by a strong spatial correlation with ESI maps of IED sources. Both sets of ICs were subsequently compared to a temporal model derived from the convolution of the IEDs (derived from the simultaneously acquired EEG) with a standard haemodynamic response. Selected ICs were compared to the patients' clinical information in 13 patients with focal epilepsy. We found that the misclassified ICs clearly related to IED in 16/25 cases. We also found that the classifier failed predominantly due to the increased spectral range of fMRIs temporal responses to IEDs. In conclusion, we show that ICA can be an efficient approach to separate responses related to epilepsy but that contemporary classifiers need to be retrained for epilepsy data. Our findings indicate that, for ICA to contribute to the analysis of data without IEDs to improve its sensitivity, classification strategies based on data features other than IC time course frequency is required.

Co-localization between the BOLD response and epileptiform discharges recorded by simultaneous intracranial EEG-fMRI at 3 T

Objectives

Simultaneous scalp EEG-fMRI can identify hemodynamic changes associated with the generation of interictal epileptiform discharges (IEDs), and it has the potential of becoming a standard, non-invasive technique for pre-surgical assessment of patients with medically intractable epilepsy. This study was designed to assess the BOLD response to focal IEDs recorded via simultaneous intracranial EEG-functional MRI (iEEG-fMRI).

Methods

Twelve consecutive patients undergoing intracranial video EEG monitoring were recruited for iEEG-fMRI studies at 3 T. Depth, subdural strip, or grid electrodes were implanted according to our standard clinical protocol. Subjects underwent 10–60 min of continuous iEEG-fMRI scanning. IEDs were marked, and the most statistically significant clusters of BOLD signal were identified (Z-score 2.3, p value < 0.05). We assessed the concordance between the locations of the BOLD response and the IED. Concordance was defined as a distance <1.0 cm between the IED and BOLD response location. Negative BOLD responses were not studied in this project.

Results

Nine patients (7 females) with a mean age of 31 years (range 22–56) had 11 different types of IEDs during fMR scanning. The IEDs were divided based on the location of the active electrode contact into mesial temporal, lateral temporal, and extra-temporal. Seven (5 left) mesial temporal IED types were recorded in 5 patients (110–2092 IEDs per spike location). Six of these IEDs had concordant BOLD response in the ipsilateral mesial temporal structures, <1 cm from the most active contact. One of the two subjects with left lateral temporal IEDs had BOLD responses concordant with the location of the most active contact, as well other ipsilateral and contralateral sites. Notably, the remaining two subjects with extratemporal discharges showed no BOLD signal near the active electrode contact.

Conclusions

iEEG-fMRI is a feasible and low-risk method for assessment of hemodynamic changes of very focal IEDs that may not be recorded by scalp EEG. A high concordance rate between the location of the BOLD response and IEDs was seen for mesial temporal (6/7) IEDs. Significant BOLD activation was also seen in areas distant from the active electrode and these sites exhibited maximal BOLD activation in the majority of cases. This implies that iEEG-fMRI may further describe the areas involved in the generation of IEDs beyond the vicinity of the electrode(s).

•

Intracranial EEG-fMRI is feasible and poses low risk.

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Intracranial EEG-fMRI has high yield of significant BOLD clusters.

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The locations of the active electrode and BOLD signal are concordant.

In vivo imaging of epileptic foci in rats using a miniature probe integrating diffuse optical tomography and electroencephalographic source localization

OBJECTIVE

The goal of this work is to establish a new dual-modal brain-mapping technique based on diffuse optical tomography (DOT) and electroencephalographic source localization (ESL) that can chronically/intracranially record optical/electroencephalography (EEG) data to precisely map seizures and localize the seizure-onset zone and associated epileptic brain network.

METHODS

The dual-modal imaging system was employed to image seizures in an experimental acute bicuculline methiodide rat model of focal epilepsy. Depth information derived from DOT was used as constraint in ESL to enhance the image reconstruction. Groups of animals were compared based on localization of seizure foci, either at different positions or at different depths.

RESULTS

This novel imaging technique successfully localized the seizure-onset zone in rat induced by bicuculline methiodide injected at a depth of 1, 2, and 3 mm, respectively. The results demonstrated that the incorporation of the depth information from DOT into the ESL image reconstruction resulted in more accurate and reliable ESL images. Although the ESL images showed a horizontal shift of the source localization, the DOT identified the seizure focus accurately. In one case, when the bicuculline methiodide (BMI) was injected at a site outside the field of view (FOV) of the DOT/ESL interface, ESL gave false-positive detection of the focus, while DOT showed negative detection.

SIGNIFICANCE

This study represents the first to identify seizure-onset zone using implantable DOT. In addition, the combination of DOT/ESL has never been documented in neuroscience and epilepsy imaging. This technology will enable us to precisely measure the neural activity and hemodynamic response at exactly the same tissue site and at both cortical and subcortical levels.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG-fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG-fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG-fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.

Simultaneous EEG-fMRI in Human Epilepsy

Electroencephalography (EEG) has been used to study and characterize epilepsy for decades, but has a limited ability to localize epileptiform activity to a specific brain region. With recent technological advances, high-quality EEG can now be recorded during functional magnetic resonance imaging (fMRI), which characterizes brain activity through local changes in blood oxygenation. By combining these techniques, the specific timing of interictal events can be identified on the EEG at millisecond resolution and spatially localized with fMRI at millimeter resolution. As a result, simultaneous EEG-fMRI provides the opportunity to better investigate the spatiotemporal mechanisms of the generation of epileptiform activity in the brain. This article discusses the technical considerations and their solutions for recording simultaneous EEG-fMRI and the results of studies to date. It also addresses the application of EEG-fMRI to epilepsy in humans, including clinical applications and ongoing challenges.

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data

Electroencephalography (EEG) data simultaneously acquired with functional magnetic resonance imaging (fMRI) data are preprocessed to remove gradient artifacts (GAs) and ballistocardiographic artifacts (BCAs). Nonetheless, these data, especially in the gamma frequency range, can be contaminated by residual artifacts produced by mechanical vibrations in the MRI system, in particular the cryogenic pump that compresses and transports the helium that chills the magnet (the helium-pump). However, few options are available for the removal of helium-pump artifacts. In this study, we propose a recursive approach of EEG-segment-based principal component analysis (rsPCA) that enables the removal of these helium-pump artifacts. Using the rsPCA method, feature vectors representing helium-pump artifacts were successfully extracted as eigenvectors, and the reconstructed signals of the feature vectors were subsequently removed. A test using simultaneous EEG-fMRI data acquired from left-hand (LH) and right-hand (RH) clenching tasks performed by volunteers found that the proposed rsPCA method substantially reduced helium-pump artifacts in the EEG data and significantly enhanced task-related gamma band activity levels (p=0.0038 and 0.0363 for LH and RH tasks, respectively) in EEG data that have had GAs and BCAs removed. The spatial patterns of the fMRI data were estimated using a hemodynamic response function (HRF) modeled from the estimated gamma band activity in a general linear model (GLM) framework. Active voxel clusters were identified in the post-/pre-central gyri of motor area, only from the rsPCA method (uncorrected p<0.001 for both LH/RH tasks). In addition, the superior temporal pole areas were consistently observed (uncorrected p<0.001 for the LH task and uncorrected p<0.05 for the RH task) in the spatial patterns of the HRF model for gamma band activity when the task paradigm and movement were also included in the GLM.

Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds

There is currently a lack of knowledge about electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) specificity. Our aim was to define sensitivity and specificity of blood oxygen level dependent (BOLD) responses to interictal epileptic spikes during EEG-fMRI for detecting the ictal onset zone (IOZ). We studied 21 refractory focal epilepsy patients who had a well-defined IOZ after a full presurgical evaluation and interictal spikes during EEG-fMRI. Areas of spike-related BOLD changes overlapping the IOZ in patients were considered as true positives; if no overlap was found, they were treated as false-negatives. Matched healthy case-controls had undergone similar EEG-fMRI in order to determine true-negative and false-positive fractions. The spike-related regressor of the patient was used in the design matrix of the healthy case-control. Suprathreshold BOLD changes in the brain of controls were considered as false positives, absence of these changes as true negatives. Sensitivity and specificity were calculated for different statistical thresholds at the voxel level combined with different cluster size thresholds and represented in receiver operating characteristic (ROC)-curves. Additionally, we calculated the ROC-curves based on the cluster containing the maximal significant activation. We achieved a combination of 100% specificity and 62% sensitivity, using a Z-threshold in the interval 3.4–3.5 and cluster size threshold of 350 voxels. We could obtain higher sensitivity at the expense of specificity. Similar performance was found when using the cluster containing the maximal significant activation. Our data provide a guideline for different EEG-fMRI settings with their respective sensitivity and specificity for detecting the IOZ. The unique cluster containing the maximal significant BOLD activation was a sensitive and specific marker of the IOZ.

EEG/fMRI contributions to our understanding of genetic generalized epilepsies

The first reports of combined EEG and fMRI used for evaluation of epileptic spikes date back to the mid-90s. At that time, the technique was called EEG-triggered fMRI--the "triggered" corresponded to an epilepsy specialist reviewing live EEG while the patient was located in the scanner; after the spike was identified, a scan was initiated to collect the data. Since then major progress has been made in combined EEG/fMRI data collection and analyses. These advances allow studying the electrophysiology of genetic generalized epilepsies (GGEs) in vivo in greater detail than ever. In addition to continuous data collection, we now have better methods for removing physiologic and fMRI-related artifacts, more advanced understanding of the hemodynamic response functions, and better computational methods to address the questions regarding the origins of the epileptiform discharge generators in patients with GGEs. These advances have allowed us to examine numerous cohorts of children and adults with GGEs while not only looking for spike and wave generators but also examining specific types of GGEs (e.g., juvenile myoclonic epilepsy or childhood absence epilepsy), drug-naïve patients, effects of medication resistance, or effects of epileptiform abnormalities and/or seizures on brain connectivity. While the discussion is ongoing, the prevailing thought is that the GGEs as a group are a network disorder with participation from multiple nodes including the thalami and cortex with the clinical presentation depending on which node of the participating network is affected by the disease process. This review discusses the contributions of EEG/fMRI to our understanding of GGEs.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

Spatial correlation of hemodynamic changes related to interictal epileptic discharges with electric and magnetic source imaging

INTRODUCTION

Blood oxygenation level-dependent (BOLD) signal changes at the time of interictal epileptic discharges (IEDs) identify their associated vascular/hemodynamic responses. BOLD activations and deactivations can be found within the epileptogenic zone but also at a distance. Source imaging identifies electric (ESI) and magnetic (MSI) sources of IEDs, with the advantage of a higher temporal resolution. Therefore, the objective of our study was to evaluate the spatial concordance between ESI/MSI and BOLD responses for similar IEDs.

METHODS

Twenty-one patients with similar IEDs in simultaneous electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) and in simultaneous EEG/magnetoencephalogram (MEG) recordings were studied. IEDs in EEG/fMRI acquisition were analyzed in an event-related paradigm within a general linear model (GLM). ESI/MSI of averaged IEDs was performed using the Maximum Entropy on the Mean. We assessed the spatial concordance between ESI/MSI and clusters of BOLD activations/deactivations with surface-based metrics.

RESULTS

ESI/MSI were concordant with one BOLD cluster for 20/21 patients (concordance with activation: 14/21 patients, deactivation: 6/21 patients, no concordance: 1/21 patients; concordance with MSI only: 3/21, ESI only: 2/21). These BOLD clusters exhibited in 19/20 cases the most significant voxel. BOLD clusters that were spatially concordant with ESI/MSI were concordant with IEDs from invasive recordings in 8/11 patients (activations: 5/8, deactivations: 3/8).

CONCLUSION

As the results of BOLD, ESI and MSI are often concordant, they reinforce our confidence in all of them. ESI and MSI confirm the most significant BOLD cluster within BOLD maps, emphasizing the importance of these clusters for the definition of the epileptic focus.