Variability of the hemodynamic response as a function of age and frequency of epileptic discharge in children with epilepsy

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: A longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold (BH) task is commonly used to understand cerebrovascular reactivity (CVR) in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's BH data set from the Nathan Kline Institute (NKI) Rockland Sample (aged 6-18 years old at enrollment). A general linear model approach was applied to derive CVR from BH data. To model both the longitudinal and cross-sectional effects of age on BH response, we used mixed-effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased BH BOLD signals in multiple networks across age, in which linear and logarithmic mixed-effects models provided the best fit with the lowest Akaike information criterion scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes that occur with age.

The Role of Blood Oxygen Level Dependent Signal Variability in Pediatric Neuroscience: A Systematic Review

BACKGROUND

As pediatric BOLD Signal Variability (SV) analysis is relatively novel, there is a need to provide a foundational framework that gives researchers an entry point into engaging with the topic. This begins with clarifying the definition of BOLD signal variability by identifying and categorizing the various metrics utilized to measure BOLD SV.

METHODS

A systematic review of the literature was conducted. Inclusion criteria were restricted to studies utilizing any metric of BOLD SV and with individuals younger than 18 in the study population. The definition of BOLD SV was any measure of intra-individual variability in the BOLD signal. Five databases were searched: Psychinfo, Healthstar, MEDLINE, Embase, and Scopus.

RESULTS

A total of 17 observational studies, including male (n = 1796) and female (n = 1324) pediatric participants were included. Eight studies quantified variability as the amount of deviation from the average BOLD signal, seven used complexity-based metrics, three used correlation measures of variability, and one used the structure of the hemodynamic response function. In this study, 10 methods of quantifying signal variability were identified. Associations and trends in BOLD SV were commonly found with age, factors specific to mental and/or neurological disorders such as attention deficit disorder, epilepsy, psychotic symptoms, and performance on psychological and behavioral tasks.

CONCLUSIONS

BOLD SV is a potential biomarker of neurodevelopmental and neurological conditions and symptom severity in mental disorders for defined pediatric populations. Studies that establish clinical trends and identify the mechanisms underlying BOLD SV with a low risk of bias are needed before clinical applications can be utilized by physicians.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: a longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold task is commonly used to understand cerebrovascular reactivity in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's breath-hold dataset from the Nathan Kline Institute (NKI) Rockland Sample (ages 6 to 18 years old at enrollment). A general linear model (GLM) approach was applied to derive cerebrovascular reactivity from breath-hold data. To model both the longitudinal and cross-sectional effects of age on breath-hold response, we used mixed effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased breath-hold BOLD signal in multiple networks across age, in which linear and logarithmic mixed effects models provided the best fit with the lowest Akaike Information Criterion (AIC) scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes which occur with age.

Clinical Usefulness of Simultaneous Electroencephalography and Functional Magnetic Resonance Imaging in Children With Focal Epilepsy

Background and Purpose

The current study analyzed the interictal epileptiform discharge (IED)-related hemodynamic response and aimed to determine the clinical usefulness of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) in defining the epileptogenic zone (EZ) in children with focal epilepsy.

Methods

Patients with focal epilepsy showing IEDs on conventional EEG were evaluated using EEG-fMRI. Statistical analyses were performed using the times of spike as events modeled with multiple hemodynamic response functions. The area showing the most significant t-value for blood-oxygen-level-dependent (BOLD) changes was compared with the presumed EZ. Moreover, BOLD responses between -9 and +9 s around the spike times were analyzed to track the hemodynamic response patterns over time.

Results

Half (n=13) of 26 EEG-fMRI investigations of 19 patients were successful. Two patients showed 2 different types of spikes, resulting in 15 analyses. The maximum BOLD response was concordant with the EZ in 11 (73.3%) of the 15 analyses. In 10 (66.7%) analyses, the BOLD response localized the EZs more specifically. Focal BOLD responses in the EZs occurred before IEDs in 11 analyses and were often widespread after IEDs. Hemodynamic response patterns were consistent in the same epilepsy syndrome or when repeating the investigation in the same patients.

Conclusions

EEG-fMRI can provide additional information for localizing the EZ in children with focal epilepsy, and also reveal the pathogenesis of pediatric epilepsy by evaluating the patterns in the hemodynamic response across time windows of IEDs.

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.

Bilateral epileptic networks in congenital and acquired corpus callosum defects: EEG-fMRI study

OBJECTIVES

Electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) allows imaging of brain-wide epileptic networks, and demonstrates that focal interictal epileptic activity is sometimes accompanied by bilateral functional activations. The corpus callosum (CC) facilitates bilateral spread of epileptic activity and at times targeted surgically for drug-resistant epilepsy (DRE). We hypothesized that focal epileptic networks are more unilateral in patients lacking intact CC.

METHODS

We included focal DRE patients who underwent pre-surgical EEG-fMRI and had CC agenesis (group A, n = 5), patients who previously underwent anterior callosotomy as treatment for drop attacks and continued having seizures (group B, n = 6), and control group of patients with focal epilepsy and intact CC (group C, n = 9). Blood-oxygenation-level-dependent (BOLD) signal maps were generated for interictal epileptic discharges. To quantify bi-hemispheric distribution of epileptic networks, laterality indices were compared between groups. Anatomical and diffusion-weighted imaging demonstrated white matter pathways.

RESULTS

96% of studies demonstrated bilateral activations. Laterality indices were similar in groups A and C, whereas group B demonstrated a more bilateral network than group C (p = 0.028). Diffusion-weighted and anatomical imaging showed aberrant white matter pathways and larger anterior commissure in groups A and B. 68% of studies showed maximal activation cluster concordant with the presumed epileptic focus, 28% showed non-maximal activation at presumed focus.

SIGNIFICANCE

Focal epileptic activity is associated with bilateral functional activations despite lack of intact CC, and is associated with stronger contralateral activation in patients after anterior callosotomy compared to controls. These findings disprove our initial hypothesis, and combined with white matter structural imaging, may indicate that the CC is not a sole route of propagation of epileptic activity, which might spread via anterior commissure. Our study demonstrates the utility of EEG-fMRI in assessing epileptic networks and potentially aiding in tailoring surgical treatments in DRE patients with callosal anomalies, and in callosal surgeries.

Neurovascular networks in epilepsy: Correlating ictal blood perfusion with intracranial electrophysiology

Perfusion patterns observed in Subtraction Ictal SPECT Co-registered to MRI (SISCOM) assist in focus localization and surgical planning for patients with medically intractable focal epilepsy. While the localizing value of SISCOM has been widely investigated, its relationship to the underlying electrophysiology has not been extensively studied and is therefore not well understood. In the present study, we set to investigate this relationship in a cohort of 70 consecutive patients who underwent ictal and interictal SPECT studies and subsequent stereo-electroencephalography (SEEG) monitoring for localization of the epileptogenic focus and surgical intervention. Seizures recorded during SEEG evaluation (SEEG seizures) were matched to semiologically-similar seizures during the preoperative ictal SPECT evaluation (SPECT seizures) by comparing the semiological changes in the course of each seizure. The spectral changes of the ictal SEEG with respect to interictal ones over 7 traditional frequency bands (0.1 to 150Hz) were analyzed at each SEEG site. Neurovascular (SEEG/SPECT) relations were assessed by comparing the estimated spectral power density changes of the SEEG at each site with the perfusion changes (SISCOM z-scores) estimated from the acquired SISCOM map at that site. Across patients, a significant correlation (p<0.05) was observed between spectral changes during the SEEG seizure and SISCOM perfusion z-scores. Brain sites with high perfusion z-score exhibited higher increased SEEG power in theta to ripple frequency bands with concurrent suppression in delta and theta frequency bands compared to regions with lower perfusion z-score. The dynamics of the correlation of SISCOM perfusion and SEEG spectral power from ictal onset to seizure end and immediate postictal period were also derived. Forty-six (46) of the 70 patients underwent resective epilepsy surgery. SISCOM z-score and power increase in beta to ripple frequency bands were significantly higher in resected than non-resected sites in the patients who were seizure-free following surgery. This study provides for the first time concrete evidence that both hyper-perfusion and hypo-perfusion patterns observed in SISCOM maps have strong electrophysiological underpinnings, and that integration of the information from SISCOM and SEEG can shed light on the location and dynamics of the underlying epileptic brain networks, and thus advance our anatomo-electro-clinical understanding and approaches to targeted diagnostic and therapeutic interventions.

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data

EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular 'bridge' between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response's variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.

Physiological Gaussian process priors for the hemodynamics in fMRI analysis

BACKGROUND

Inference from fMRI data faces the challenge that the hemodynamic system that relates neural activity to the observed BOLD fMRI signal is unknown.

NEW METHOD

We propose a new Bayesian model for task fMRI data with the following features: (i) joint estimation of brain activity and the underlying hemodynamics, (ii) the hemodynamics is modeled nonparametrically with a Gaussian process (GP) prior guided by physiological information and (iii) the predicted BOLD is not necessarily generated by a linear time-invariant (LTI) system. We place a GP prior directly on the predicted BOLD response, rather than on the hemodynamic response function as in previous literature. This allows us to incorporate physiological information via the GP prior mean in a flexible way, and simultaneously gives us the nonparametric flexibility of the GP.

RESULTS

Results on simulated data show that the proposed model is able to discriminate between active and non-active voxels also when the GP prior deviates from the true hemodynamics. Our model finds time varying dynamics when applied to real fMRI data.

COMPARISON WITH EXISTING METHOD(S)

The proposed model is better at detecting activity in simulated data than standard models, without inflating the false positive rate. When applied to real fMRI data, our GP model in several cases finds brain activity where previously proposed LTI models does not.

CONCLUSIONS

We have proposed a new non-linear model for the hemodynamics in task fMRI, that is able to detect active voxels, and gives the opportunity to ask new kinds of questions related to hemodynamics.

Mapping the Effect of Interictal Epileptic Activity Density During Wakefulness on Brain Functioning in Focal Childhood Epilepsies With Centrotemporal Spikes

Childhood epilepsy with centrotemporal spikes (CECTS) is the most common type of “self-limited focal epilepsies.” In its typical presentation, CECTS is a condition reflecting non-lesional cortical hyperexcitability of rolandic regions. The benign evolution of this disorder is challenged by the frequent observation of associated neuropsychological deficits and behavioral impairment. The abundance (or frequency) of interictal centrotemporal spikes (CTS) in CECTS is considered a risk factor for deficits in cognition. Herein, we captured the hemodynamic changes triggered by the CTS density measure (i.e., the number of CTS for time bin) obtained in a cohort of CECTS, studied by means of video electroencephalophy/functional MRI during quite wakefulness. We aim to demonstrate a direct influence of the diurnal CTS frequency on epileptogenic and cognitive networks of children with CECTS. A total number of 8,950 CTS (range between 27 and 801) were recorded in 23 CECTS (21 male), with a mean number of 255 CTS/patient and a mean density of CTS/30 s equal to 10,866 ± 11.46. Two independent general linear model models were created for each patient based on the effect of interest: “individual CTS” in model 1 and “CTS density” in model 2. Hemodynamic correlates of CTS density revealed the involvement of a widespread cortical–subcortical network encompassing the sensory-motor cortex, the Broca's area, the premotor cortex, the thalamus, the putamen, and red nucleus, while in the CTS event-related model, changes were limited to blood–oxygen-level-dependent (BOLD) signal increases in the sensory-motor cortices. A linear relationship was observed between the CTS density hemodynamic changes and both disease duration (positive correlation) and age (negative correlation) within the language network and the bilateral insular cortices. Our results strongly support the critical role of the CTS frequency, even during wakefulness, to interfere with the normal functioning of language brain networks.

Antiepileptic Drug of Levetiracetam Decreases Centrotemporal Spike-Associated Activation in Rolandic Epilepsy

The objective was to study the modulation effects of levetiracetam on the fMRI activation/deactivation patterns associated with centrotemporal spikes (CTS) in Rolandic epilepsy. Forty patients with Rolandic epilepsy, including levetiracetam-medicated patients (n = 20) and drug-naive patients (n = 20), were studied. Single and sequential hemodynamic response functions-based EEG-fMRI analysis was performed to detect dynamic activation/deactivation associated with CTS. Comparisons of spatiotemporal features of activation/deactivation were performed between the two groups. Both the groups (CTS were detected in 12 cases of levetiracetam-medicated group, and 11 cases of drug-naive group) showed CTS-associated activation in the Rolandic cortex, whereas activation strength, time-to-peak delay, and overall activation were diminished in the levetiracetam-medicated group. Moreover, the drug-naive group showed deactivation in the regions engaged in higher cognition networks compared with the levetiracetam-medicated group. Levetiracetam inhibits CTS-associated activation intensity and alters the temporal pattern of this activation in the epileptogenic regions, and it also affects the brain deactivation related to higher cognition networks. The findings sheds a light on the pharmocological mechanism of levetiracetam therapy on Rolandic epilepsy.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

OBJECTIVE

Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown.

APPROACH

Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF).

MAIN RESULTS

We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements.

SIGNIFICANCE

The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

Multimodal investigation of epileptic networks: The case of insular cortex epilepsy

The insula is a deep cortical structure sharing extensive synaptic connections with a variety of brain regions, including several frontal, temporal, and parietal structures. The identification of the insular connectivity network is obviously valuable for understanding a number of cognitive processes, but also for understanding epilepsy since insular seizures involve a number of remote brain regions. Ultimately, knowledge of the structure and causal relationships within the epileptic networks associated with insular cortex epilepsy can offer deeper insights into this relatively neglected type of epilepsy enabling the refining of the clinical approach in managing patients affected by it. In the present chapter, we first review the multimodal noninvasive tests performed during the presurgical evaluation of epileptic patients with drug refractory focal epilepsy, with particular emphasis on their value for the detection of insular cortex epilepsy. Second, we review the emerging multimodal investigation techniques in the field of epilepsy, that aim to (1) enhance the detection of insular cortex epilepsy and (2) unveil the architecture and causal relationships within epileptic networks. We summarize the results of these approaches with emphasis on the specific case of insular cortex epilepsy.

The spatiotemporal substrates of autobiographical recollection: Using event-related ICA to study cognitive networks in action

Higher cognitive functions depend upon dynamically unfolding brain network interactions. Autobiographical recollection - the autonoetic re-experiencing of context rich, emotionally laden, personally experienced episodes - is an excellent example of such a process. Autobiographical recollection unfolds over time, with different cognitive processes engaged at different times throughout. In this paper we apply a recently developed analysis technique - event related independent components analysis (eICA) - to study the spatiotemporal dynamics of neural activity supporting autobiographical recollection. Participants completed an in-scanner autobiographical recollection paradigm in which the recalled episodes varied in chronological age and emotional content. By combining eICA with these cognitive manipulations we show that the brain-wide response to autobiographical recollection comprises brain networks with (i) different sensitivities to psychological aspects of the to-be-recollected material and (ii) distinct temporal profiles of activity during recollection. We identified networks with transient activations (in language and cognitive control related regions) and deactivations (in auditory and sensorimotor regions) to each autobiographical probe question, as well as networks with responses that are sustained over the course of the recollection period. These latter networks together overlapped spatially with the broader default mode network (DMN), indicating subspecialisation within the DMN. The vividness of participants' recollection was associated with the magnitude of activation in left dorsolateral prefrontal cortex and deactivation in visual association cortices. We interpret our results in the context of current theories of the spatial and temporal organisation of the human autobiographical memory system. Our findings demonstrate the utility of eICA as a tool for studying higher cognitive functions. The application of eICA to high spatial and temporal resolution datasets identifies in a single experimental protocol spatially specific networks that are recruited during cognitive activity, as well as the temporal order of activation of these networks.

RF Heating of Gold Cup and Conductive Plastic Electrodes during Simultaneous EEG and MRI

PURPOSE

To investigate the heating of EEG electrodes during magnetic resonance imaging (MRI) scans and to better understand the underlying physical mechanisms with a focus on the antenna effect.

MATERIALS AND METHODS

Gold cup and conductive plastic electrodes were placed on small watermelons with fiberoptic probes used to measure electrode temperature changes during a variety of 1.5T and 3T MRI scans. A subset of these experiments was repeated on a healthy human volunteer.

RESULTS

The differences between gold and plastic electrodes did not appear to be practically significant. For both electrode types, we observed heating below 4°C for straight wires whose lengths were multiples of ½ the radiofrequency (RF) wavelength and stronger heating (over 15°C) for wire lengths that were odd multiples of ¼ RF wavelength, consistent with the antenna effect.

CONCLUSIONS

The antenna effect, which has received little attention so far in the context of EEG-MRI safety, can play as significant a role as the loop effect (from electromagnetic induction) in the heating of EEG electrodes, and therefore wire lengths that are odd multiples of ¼ RF wavelength should be avoided. These results have important implications for the design of EEG electrodes and MRI studies as they help to minimize the risk to patients undergoing MRI with EEG electrodes in place.

Examining the relationship between home literacy environment and neural correlates of phonological processing in beginning readers with and without a familial risk for dyslexia: an fMRI study

Developmental dyslexia is a language-based learning disability characterized by persistent difficulty in learning to read. While an understanding of genetic contributions is emerging, the ways the environment affects brain functioning in children with developmental dyslexia are poorly understood. A relationship between the home literacy environment (HLE) and neural correlates of reading has been identified in typically developing children, yet it remains unclear whether similar effects are observable in children with a genetic predisposition for dyslexia. Understanding environmental contributions is important given that we do not understand why some genetically at-risk children do not develop dyslexia. Here, we investigate for the first time the relationship between HLE and the neural correlates of phonological processing in beginning readers with (FHD+, n = 29) and without (FHD-, n = 21) a family history of developmental dyslexia. We further controlled for socioeconomic status to isolate the neurobiological mechanism by which HLE affects reading development. Group differences revealed stronger correlation of HLE with brain activation in the left inferior/middle frontal and right fusiform gyri in FHD- compared to FHD+ children, suggesting greater impact of HLE on manipulation of phonological codes and recruitment of orthographic representations in typically developing children. In contrast, activation in the right precentral gyrus showed a significantly stronger correlation with HLE in FHD+ compared to FHD- children, suggesting emerging compensatory networks in genetically at-risk children. Overall, our results suggest that genetic predisposition for dyslexia alters contributions of HLE to early reading skills before formal reading instruction, which has important implications for educational practice and intervention models.

Multichannel continuous electroencephalography-functional near-infrared spectroscopy recording of focal seizures and interictal epileptiform discharges in human epilepsy: a review

Functional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging technique as it allows noninvasive and long-term monitoring of cortical hemodynamics. Recent work by our group and others has revealed the potential of fNIRS, combined with electroencephalography (EEG), in the context of human epilepsy. Hemodynamic brain responses attributed to epileptic events, such as seizures and interictal epileptiform discharges (IEDs), are routinely observed with a good degree of statistical significance and in concordance with clinical presentation. Recording done with over 100 channels allows sufficiently large coverage of the epileptic focus and other areas. Three types of seizures have been documented: frontal lobe seizures, temporal lobe seizures, and posterior seizures. Increased oxygenation was observed in the epileptic focus in most cases, while rapid but similar hemodynamic variations were identified in the contralateral homologous region. While investigating IEDs, it was shown that their hemodynamic effect is observable with fNIRS, that their response is associated with significant (inhibitive) nonlinearities, and that the sensitivity and specificity of fNIRS to localize the epileptic focus can be estimated in a sample of 40 patients. This paper first reviews recent EEG-fNIRS developments in epilepsy research and then describes applications to the study of focal seizures and IEDs.

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings.

Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes.

Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s.

Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s.

Using patient-specific hemodynamic response function in epileptic spike analysis of human epilepsy: a study based on EEG-fNIRS

Functional near-infrared spectroscopy (fNIRS) can be combined with electroencephalography (EEG) to continuously monitor the hemodynamic signal evoked by epileptic events such as seizures or interictal epileptiform discharges (IEDs, aka spikes). As estimation methods assuming a canonical shape of the hemodynamic response function (HRF) might not be optimal, we sought to model patient-specific HRF (sHRF) with a simple deconvolution approach for IED-related analysis with EEG-fNIRS data. Furthermore, a quadratic term was added to the model to account for the nonlinearity in the response when IEDs are frequent. Prior to analyzing clinical data, simulations were carried out to show that the HRF was estimable by the proposed deconvolution methods under proper conditions. EEG-fNIRS data of five patients with refractory focal epilepsy were selected due to the presence of frequent clear IEDs and their unambiguous focus localization. For each patient, both the linear sHRF and the nonlinear sHRF were estimated at each channel. Variability of the estimated sHRFs was seen across brain regions and different patients. Compared with the SPM8 canonical HRF (cHRF), including these sHRFs in the general linear model (GLM) analysis led to hemoglobin activations with higher statistical scores as well as larger spatial extents on all five patients. In particular, for patients with frequent IEDs, nonlinear sHRFs were seen to provide higher sensitivity in activation detection than linear sHRFs. These observations support using sHRFs in the analysis of IEDs with EEG-fNIRS data.

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.

Reading, listening and memory-related brain activity in children with early-stage temporal lobe epilepsy of unknown cause-an fMRI study

BACKGROUND AND AIMS

The changes in functional brain organization associated with paediatric epilepsy are largely unknown. Since children with epilepsy are at risk of developing learning difficulties even before or shortly after the onset of epilepsy, we assessed the functional organization of memory and language in paediatric patients with temporal lobe epilepsy (TLE) at an early stage in epilepsy.

METHODS

Functional magnetic resonance imaging was used to measure the blood oxygenation level-dependent (BOLD) response to four cognitive tasks measuring reading, story listening, memory encoding and retrieval in a population-based group of children with TLE of unknown cause (n = 21) and of normal intelligence and a healthy age and gender-matched control group (n = 21).

RESULTS

Significant BOLD response differences were found only in one of the four tasks. In the story listening task, significant differences were found in the right hemispheric temporal structures, thalamus and basal ganglia. Both activation and deactivation differed significantly between the groups, activation being increased and deactivation decreased in the TLE group. Furthermore, the patients with abnormal electroencephalograms (EEGs) showed significantly increased activation bilaterally in the temporal structures, basal ganglia and thalamus relative to those with normal EEGs. The patients with normal interictal EEGs had a significantly stronger deactivation than those with abnormal EEGs or the controls, the differences being located outside the temporal structures.

CONCLUSIONS

Our results suggest that TLE entails a widespread disruption of brain networks. This needs to be taken into consideration when evaluating learning abilities in patients with TLE. The thalamus seems to play an active role in TLE. The changes in deactivation may reflect neuronal inhibition.

The effect of medial temporal lobe epilepsy on visual memory encoding

Effective visual memory encoding, a function important for everyday functioning, relies on episodic and semantic memory processes. In patients with medial temporal lobe epilepsy (MTLE), memory deficits are common as the structures typically involved in seizure generation are also involved in acquisition, maintenance, and retrieval of episodic memories. In this study, we used group independent component analysis (GICA) combined with Granger causality analysis to investigate the neuronal networks involved in visual memory encoding during a complex fMRI scene-encoding task in patients with left MTLE (LMTLE; N=28) and in patients with right MTLE (RMTLE; N=18). Additionally, we built models of memory encoding in LMTLE and RMTLE and compared them with a model of healthy memory encoding (Nenert et al., 2014). For those with LMTLE, we identified and retained for further analyses and model generation 7 ICA task-related components that were attributed to four different networks: the frontal and posterior components of the DMN, visual network, auditory-insular network, and an "other" network. For those with RMTLE, ICA produced 9 task-related components that were attributed to the somatosensory and cerebellar networks in addition to the same networks as in patients with LMTLE. Granger causality analysis revealed group differences in causality relations within the visual memory network and MTLE-related deviations from normal network function. Our results demonstrate differences in the networks for visual memory encoding between those with LMTLE and those with RMTLE. Consistent with previous studies, the organization of memory encoding is dependent on laterality of seizure focus and may be mediated by functional reorganization in chronic epilepsy. These differences may underlie the observed differences in memory abilities between patients with LMTLE and patients with RMTLE and highlight the modulating effects of epilepsy on the network for memory encoding.

Methods and utility of EEG-fMRI in epilepsy

Brain activity data in general and more specifically in epilepsy can be represented as a matrix that includes measures of electrophysiology, anatomy and behaviour. Each of these sub-matrices has a complex interaction depending upon the brain state i.e., rest, cognition, seizures and interictal periods. This interaction presents significant challenges for interpretation but also potential for developing further insights into individual event types. Successful treatments in epilepsy hinge on unravelling these complexities, and also on the sensitivity and specificity of methods that characterize the nature and localization of underlying physiological and pathological networks. Limitations of pharmacological and surgical treatments call for refinement and elaboration of methods to improve our capability to localise the generators of seizure activity and our understanding of the neurobiology of epilepsy. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI), by potentially circumventing some of the limitations of EEG in terms of sensitivity, can allow the mapping of haemodynamic networks over the entire brain related to specific spontaneous and triggered epileptic events in humans, and thereby provide new localising information. In this work we review the published literature, and discuss the methods and utility of EEG-fMRI in localising the generators of epileptic activity. We draw on our experience and that of other groups, to summarise the spectrum of information provided by an increasing number of EEG-fMRI case-series, case studies and group studies in patients with epilepsy, for its potential role to elucidate epileptic generators and networks. We conclude that EEG-fMRI provides a multidimensional view that contributes valuable clinical information to localize the epileptic focus with potential important implications for the surgical treatment of some patients with drug-resistant epilepsy, and insights into the resting state and cognitive network dynamics.

BOLD responses related to focal spikes and widespread bilateral synchronous discharges generated in the frontal lobe

OBJECTIVE

To investigate whether specific frontal regions have a tendency to generate widespread bilateral synchronous discharges (WBSDs) and others focal spikes and to determine the regions most involved when WBSDs occur; to assess the relationships between the extent of electroencephalography (EEG) discharges and the extent of metabolic changes measured by EEG/functional magnetic resonance imaging (fMRI).

METHODS

Thirty-seven patients with interictal epileptic discharges (IEDs) with frontocentral predominance underwent EEG/fMRI. Patients were divided into a Focal (20 patients) group with focal frontal spikes and a WBSD group (17 patients). Maps of hemodynamic responses related to IEDs were compared between the two groups.

RESULTS

The mean number ± SD of IEDs in the Focal group was 137.5 ± 38.1 and in the WBSD group, 73.5 ± 16.6 (p = 0.07). The volume of hemodynamic responses in the WBSD group was significantly larger than in the Focal group (mean, 243.3 ± 41.1 versus 114.8 ± 27.4 cm(3), p = 0.01). Maximum hemodynamic responses occurred in both groups in the following regions: dorsolateral prefrontal, mesial prefrontal, cingulate, and supplementary motor cortices. Maxima in premotor and motor cortex, frontal operculum, frontopolar, and orbitofrontal regions were found only in the Focal group, and maxima in thalamus and caudate only occurred in the WBSD group. Thalamic responses were significantly more common in the WBSD group (14/17) than in the Focal group (7/20), p = 0.004. Deactivation in the default mode network was significantly more common in the WBSD group (14/17) than in the Focal group (10/20), p = 0.04.

SIGNIFICANCE

The spatial distribution and extent of blood oxygen level-dependent (BOLD) responses correlate well with electrophysiologic changes. Focal frontal spikes and WBSDs are not region specific in the frontal lobe, and the same frontal region can generate focal and generalized discharges. This suggests that widespread discharges reflect widespread epileptogenicity rather than a focal discharge located in a region favorable to spreading. The thalamus plays an important role in bilateral synchronization.

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.

Conceptualizing lennox-gastaut syndrome as a secondary network epilepsy

Lennox–Gastaut Syndrome (LGS) is a category of severe, disabling epilepsy, characterized by frequent, treatment-resistant seizures, and cognitive impairment. Electroencephalography (EEG) shows characteristic generalized epileptic activity that is similar in those with lesional, genetic, or unknown causes, suggesting a common underlying mechanism. The condition typically begins in young children, leaving many severely disabled with recurring seizures throughout their adult life. Scalp EEG of the tonic seizures of LGS is characterized by a diffuse high-voltage slow transient evolving into generalized low-voltage fast activity, likely reflecting sustained fast neuronal firing over a wide cortical area. The typical interictal discharges (runs of slow spike-and-wave and bursts of generalized paroxysmal fast activity) also have a “generalized” electrical field, suggesting widespread cortical involvement. Recent brain mapping studies have begun to reveal which cortical and subcortical regions are active during these “generalized” discharges. In this critical review, we examine findings from neuroimaging studies of LGS and place these in the context of the electrical and clinical features of the syndrome. We suggest that LGS can be conceptualized as “secondary network epilepsy,” where the epileptic activity is expressed through large-scale brain networks, particularly the attention and default-mode networks. Cortical lesions, when present, appear to chronically interact with these networks to produce network instability rather than triggering each individual epileptic discharge. LGS can be considered as “secondary” network epilepsy because the epileptic manifestations of the disorder reflect the networks being driven, rather than the specific initiating process. In this review, we begin with a summation of the clinical manifestations of LGS and what this has revealed about the underlying etiology of the condition. We then undertake a systematic review of the functional neuroimaging literature in LGS, which leads us to conclude that LGS can best be conceptualized as “secondary network epilepsy.”

Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome

The effects of interictal epileptiform discharges on neurocognitive development in children with medically-intractable epilepsy are poorly understood. Such discharges may have a deleterious effect on the brain's intrinsic connectivity networks, which reflect the organization of functional networks at rest, and in turn on neurocognitive development. Using a combined functional magnetic resonance imaging-magnetoencephalography approach, we examine the effects of interictal epileptiform discharges on intrinsic connectivity networks and neurocognitive outcome. Functional magnetic resonance imaging was used to determine the location of regions comprising various intrinsic connectivity networks in 26 children (7-17 years), and magnetoencephalography data were reconstructed from these locations. Inter-regional phase synchronization was then calculated across interictal epileptiform discharges and graph theoretical analysis was applied to measure event-related changes in network topology in the peri-discharge period. The magnitude of change in network topology (network resilience/vulnerability) to interictal epileptiform discharges was associated with neurocognitive outcomes and functional magnetic resonance imaging networks using dual regression. Three main findings are reported: (i) large-scale network changes precede and follow interictal epileptiform discharges; (ii) the resilience of network topologies to interictal discharges is associated with stronger resting-state network connectivity; and (iii) vulnerability to interictal discharges is associated with worse neurocognitive outcomes. By combining the spatial resolution of functional magnetic resonance imaging with the temporal resolution of magnetoencephalography, we describe the effects of interictal epileptiform discharges on neurophysiological synchrony in intrinsic connectivity networks and establish the impact of interictal disruption of functional networks on cognitive outcome in children with epilepsy. The association between interictal discharges, network changes and neurocognitive outcomes suggests that it is of clinical importance to suppress discharges to foster more typical brain network development in children with focal epilepsy.

An investigation of positive and inverted hemodynamic response functions across multiple visual areas

Recent studies have demonstrated significant regional variability in the hemodynamic response function (HRF), highlighting the difficulty of correctly interpreting functional MRI (fMRI) data without proper modeling of the HRF. The focus of this study was to investigate the HRF variability within visual cortex. The HRF was estimated for a number of cortical visual areas by deconvolution of fMRI blood oxygenation level dependent (BOLD) responses to brief, large-field visual stimulation. Significant HRF variation was found across visual areas V1, V2, V3, V4, VO-1,2, V3AB, IPS-0,1,2,3, LO-1,2, and TO-1,2. Additionally, a subpopulation of voxels was identified that exhibited an impulse response waveform that was similar, but not identical, to an inverted version of the commonly described and modeled positive HRF. These voxels were found within the retinotopic confines of the stimulus and were intermixed with those showing positive responses. The spatial distribution and variability of these HRFs suggest a vascular origin for the inverted waveforms. We suggest that the polarity of the HRF is a separate factor that is independent of the suppressive or activating nature of the underlying neuronal activity. Correctly modeling the polarity of the HRF allows one to recover an estimate of the underlying neuronal activity rather than discard the responses from these voxels on the assumption that they are artifactual. We demonstrate this approach on phase-encoded retinotopic mapping data as an example of the benefits of accurately modeling the HRF during the analysis of fMRI data.

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.

Hemodynamic response function (HRF) in epilepsy patients with hippocampal sclerosis and focal cortical dysplasia

Simultaneous recording of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) has recently been applied for mapping the hemodynamic changes related to epileptic activity. The aim of this study is to compare the hemodynamic response function (HRF) to epileptic spikes in patients with focal cortical dysplasia (FCD) and those with hippocampal sclerosis (HS). In EEG-fMRI studies, the HRF represents the temporal evolution of blood oxygenation level-dependent signal changes. Several studies demonstrated that amplitude and latency of the HRF are variable in patients with epilepsy. However, the consistency of HRF parameters with underlying brain pathology is unknown. In this study, we examined 14 patients with FCD and 12 with unilateral HS selected from our EEG-fMRI database and compared the amplitude and latency of the HRF peak. We analyzed (1) HRFs in peak activation clusters, (2) HRFs in peak deactivation clusters, and (3) the maximum absolute responses within the EEG spike field, activation or deactivation. We found that the HRF peak amplitude in deactivation clusters was larger in the HS group than in the FCD when the deactivation occurred in default mode network (DMN) regions. This result suggests that spikes in patients with HS affect the DMN more strongly than those with FCD. However, if we focus on the maximum absolute t-value in the spike field, there is no significant difference between the two groups. The current study indicates that it is not necessary to use different HRF models for EEG-fMRI studies in patients with FCD and HS.

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.

Functional brain activation to emotional and nonemotional faces in healthy children: evidence for developmentally undifferentiated amygdala function during the school-age period

The amygdala is a key region in emotion processing. In particular, fMRI studies have demonstrated that the amygdala is active during the viewing of emotional faces. Previous research has consistently found greater amygdala responses to fearful than to neutral faces in adults, convergent with a focus in the animal literature on the amygdala's role in fear processing. Studies have shown that the amygdala also responds differentially to other facial emotion types in adults. Yet the literature regarding when this differential amygdala responsivity develops is limited and mixed. Thus, the goal of the present study was to examine amygdala responses to emotional and neutral faces in a relatively large sample of healthy school-age children (N = 52). Although the amygdala was active in response to emotional and neutral faces, the results did not support the hypothesis that the amygdala responds differentially to emotional faces in 7- to 12-year-old children. Nonetheless, amygdala activity was correlated with the severity of subclinical depression symptoms and with emotional regulation skills. Additionally, sex differences were observed in frontal, temporal, and visual regions, as well as effects of pubertal development in visual regions. These findings suggest important differences in amygdala reactivity in childhood.

Fast fMRI provides high statistical power in the analysis of epileptic networks

EEG-fMRI is a unique method to combine the high temporal resolution of EEG with the high spatial resolution of MRI to study generators of intrinsic brain signals such as sleep grapho-elements or epileptic spikes. While the standard EPI sequence in fMRI experiments has a temporal resolution of around 2.5-3s a newly established fast fMRI sequence called MREG (Magnetic-Resonance-Encephalography) provides a temporal resolution of around 100ms. This technical novelty promises to improve statistics, facilitate correction of physiological artifacts and improve the understanding of epileptic networks in fMRI. The present study compares simultaneous EEG-EPI and EEG-MREG analyzing epileptic spikes to determine the yield of fast MRI in the analysis of intrinsic brain signals. Patients with frequent interictal spikes (>3/20min) underwent EEG-MREG and EEG-EPI (3T, 20min each, voxel size 3×3×3mm, EPI TR=2.61s, MREG TR=0.1s). Timings of the spikes were used in an event-related analysis to generate activation maps of t-statistics. (FMRISTAT, |t|>3.5, cluster size: 7 voxels, p<0.05 corrected). For both sequences, the amplitude and location of significant BOLD activations were compared with the spike topography. 13 patients were recorded and 33 different spike types could be analyzed. Peak T-values were significantly higher in MREG than in EPI (p<0.0001). Positive BOLD effects correlating with the spike topography were found in 8/29 spike types using the EPI and in 22/33 spikes types using the MREG sequence. Negative BOLD responses in the default mode network could be observed in 3/29 spike types with the EPI and in 19/33 with the MREG sequence. With the latter method, BOLD changes were observed even when few spikes occurred during the investigation. Simultaneous EEG-MREG thus is possible with good EEG quality and shows higher sensitivity in regard to the localization of spike-related BOLD responses than EEG-EPI. The development of new methods of analysis for this sequence such as modeling of physiological noise, temporal analysis of the BOLD signal and defining appropriate thresholds is required to fully profit from its high temporal resolution.

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.

Mapping brain activity using event-related independent components analysis (eICA): specific advantages for EEG-fMRI

Event-related analyses of functional MRI (fMRI) typically assume that the onset and offset of neuronal activity match stimuli onset and offset, and that evoked fMRI signal changes follow the canonical haemodynamic response function (HRF). Some event types, however, may be unsuited to this approach: brief stimuli might elicit an extended neuronal response; anticipatory effects might result in activity preceding the event; or altered neurovascular coupling may result in a non-canonical HRF. An example is interictal epileptiform discharges (IEDs), which may show a non-canonical HRF and fMRI signal changes preceding their onset as detected on EEG. In such cases, less constrained analyses - capable of detecting early, non-canonical responses - may be necessary. A consequence of less constrained analyses, however, is that artefactual sources of signal change - motion or physiological noise for example - may also be detected and mixed with the neuronally-generated signals. In this paper, to address this issue, we describe an event-related independent components analysis (eICA) that identifies different sources of event-related signal change that can then be separately assessed to identify likely artefacts and separate primary from propagated activity. We also describe a group analysis that identifies eICA components that are spatially and temporally consistent across subjects and provides an objective approach for selecting group-specific components likely to be of neural origin. We apply eICA to patients with rolandic epilepsy - with stereotypical IEDs arising from a focus in the rolandic fissure - and demonstrate that a single event-related component, concordant with this source location, is detected.

Mapping interictal epileptic discharges using mutual information between concurrent EEG and fMRI

OBJECTIVE

The mapping of haemodynamic changes related to interictal epileptic discharges (IED) in simultaneous electroencephalography (EEG) and functional MRI (fMRI) studies is usually carried out by means of EEG-correlated fMRI analyses where the EEG information specifies the model to test on the fMRI signal. The sensitivity and specificity critically depend on the accuracy of EEG detection and the validity of the haemodynamic model. In this study we investigated whether an information theoretic analysis based on the mutual information (MI) between the presence of epileptic activity on EEG and the fMRI data can provide further insights into the haemodynamic changes related to interictal epileptic activity. The important features of MI are that: 1) both recording modalities are treated symmetrically; 2) no requirement for a-priori models for the haemodynamic response function, or assumption of a linear relationship between the spiking activity and BOLD responses, and 3) no parametric model for the type of noise or its probability distribution is necessary for the computation of MI.

METHODS

Fourteen patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI and intracranial EEG and/or surgical resection with positive postoperative outcome (seizure freedom or considerable reduction in seizure frequency) was available in 7/14 patients. We used nonparametric statistical assessment of the MI maps based on a four-dimensional wavelet packet resampling method. The results of MI were compared to the statistical parametric maps obtained with two conventional General Linear Model (GLM) analyses based on the informed basis set (canonical HRF and its temporal and dispersion derivatives) and the Finite Impulse Response (FIR) models.

RESULTS

The MI results were concordant with the electro-clinically or surgically defined epileptogenic area in 8/14 patients and showed the same degree of concordance as the results obtained with the GLM-based methods in 12 patients (7 concordant and 5 discordant). In one patient, the information theoretic analysis improved the delineation of the irritative zone compared with the GLM-based methods.

DISCUSSION

Our findings suggest that an information theoretic analysis can provide clinically relevant information about the BOLD signal changes associated with the generation and propagation of interictal epileptic discharges. The concordance between the MI, GLM and FIR maps support the validity of the assumptions adopted in GLM-based analyses of interictal epileptic activity with EEG-fMRI in such a manner that they do not significantly constrain the localization of the epileptogenic zone.

The transient effect of interictal spikes from a frontal focus on language-related gamma activity

Interictal spike activity arising from an epileptic focus may cause transient subclinical changes in language function. We retrospectively studied four patients with a seizure focus of the left frontal lobe who underwent language mapping via electrocorticography. In three patients, we could group language task trials into 'spike' and 'non-spike' trials, based upon occurrence of spikes arising from the seizure onset zone during presentation of question stimuli. In one patient, we demonstrated a reduction in language-related gamma activity (80-100Hz) at one dorsal superior frontal site outside the seizure onset zone; reduction in mean peak amplitude of 58.4% of baseline reference (95% C.I.: 31.6% to 85.1%). This site was located near the seizure onset zone and was associated with the greatest spike rate among sites of similar function. This is the first preliminary study to show an effect of interictal spikes upon language-related gamma activity of the lateral frontal lobe.

Representation and propagation of epileptic activity in absences and generalized photoparoxysmal responses

Although functional imaging studies described networks associated with generalized epileptic activity, propagation patterns within these networks are not clear. In this study, electroencephalogram (EEG)-based coherent source imaging dynamic imaging of coherent sources (DICS) was applied to different types of generalized epileptiform discharges, namely absence seizures (10 patients) and photoparoxysmal responses (PPR) (eight patients) to describe the representation and propagation of these discharges in the brain. The results of electrical source imaging were compared to EEG-functional magnetic resonance imaging (fMRI) which had been obtained from the same data sets of simultaneous EEG and fMRI recordings. Similar networks were described by DICS and fMRI: (1) absence seizures were associated with thalamic involvement in all patients. Concordant results were also found for brain areas of the default mode network and the occipital cortex. (2) Both DICS and fMRI identified the occipital, parietal, and the frontal cortex in a network associated with PPR. (3) However, only when PPR preceded a generalized tonic-clonic seizure, the thalamus was involved in the generation of PPR as shown by both imaging techniques. Partial directed coherence suggested that during absences, the thalamus acts as a pacemaker while PPR could be explained by a cortical propagation from the occipital cortex via the parietal cortex to the frontal cortex. In conclusion, the electrical source imaging is not only able to describe similar neuronal networks as revealed by fMRI, including deep sources of neuronal activity such as the thalamus, but also demonstrates interactions interactions within these networks and sheds light on pathogenetic mechanisms of absence seizures and PPR.

Nonlinear hemodynamic responses in human epilepsy: a multimodal analysis with fNIRS-EEG and fMRI-EEG

Functional magnetic resonance imaging (fMRI) combined with electroencephalography (fMRI-EEG) is a neuroimaging technique based on the blood oxygenation level dependent (BOLD) signal which has been shown to be useful in the study of epilepsy for the localization of the epileptogenic focus. Functional near-infrared spectroscopy (fNIRS) combined with EEG (fNIRS-EEG) is another imaging technique based on the measurement of oxygenated and deoxygenated hemoglobin with complementary clinical potential in epilepsy, for continuous patient monitoring, language lateralization, and focus localization. In this work fMRI-EEG and fNIRS-EEG are used to quantify nonlinear hemodynamic responses in three cases of human refractory focal epilepsy, by using the Volterra kernel expansion up to second order. Prior to analyzing real data, extensive simulations are carried out to show that nonlinearities are estimable. The Volterra methodology is then applied to multimodal data recorded from 3 epileptic patients selected for their frequent spiking activity. Care is taken to account for variability of hemodynamic responses due to other causes than Volterra nonlinearities. Statistically significant nonlinearities are observed for all patients and all modalities. Good concordance between fNIRS and fMRI is found for both the amplitude of the Volterra responses, and, with limitations, in the localization of the epileptic focus and regions of inverted responses (negative BOLD signals). In one patient, Volterra nonlinearities allowed epileptic focus identification with fMRI, while analyses without nonlinearities failed to see it. In simulations when nonlinearities were included, analysis without Volterra nonlinearities performed poorly. These two observations suggest routinely checking for nonlinearities in functional imaging of patients presenting with frequent spikes.

A semi-automatic method to determine electrode positions and labels from gel artifacts in EEG/fMRI-studies

The analysis of simultaneous EEG and fMRI data is generally based on the extraction of regressors of interest from the EEG, which are correlated to the fMRI data in a general linear model setting. In more advanced approaches, the spatial information of EEG is also exploited by assuming underlying dipole models. In this study, we present a semi automatic and efficient method to determine electrode positions from electrode gel artifacts, facilitating the integration of EEG and fMRI in future EEG/fMRI data models. In order to visualize all electrode artifacts simultaneously in a single view, a surface rendering of the structural MRI is made using a skin triangular mesh model as reference surface, which is expanded to a "pancake view". Then the electrodes are determined with a simple mouse click for each electrode. Using the geometry of the skin surface and its transformation to the pancake view, the 3D coordinates of the electrodes are reconstructed in the MRI coordinate frame. The electrode labels are attached to the electrode positions by fitting a template grid of the electrode cap in which the labels are known. The correspondence problem between template and sample electrodes is solved by minimizing a cost function over rotations, shifts and scalings of the template grid. The crucial step here is to use the solution of the so-called "Hungarian algorithm" as a cost function, which makes it possible to identify the electrode artifacts in arbitrary order. The template electrode grid has to be constructed only once for each cap configuration. In our implementation of this method, the whole procedure can be performed within 15 min including import of MRI, surface reconstruction and transformation, electrode identification and fitting to template. The method is robust in the sense that an electrode template created for one subject can be used without identification errors for another subject for whom the same EEG cap was used. Furthermore, the method appears to be robust against spurious or missing artifacts. We therefore consider the proposed method as a useful and reliable tool within the larger toolbox required for the analysis of co-registered EEG/fMRI data.