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

The hemodynamic response to co-occurring interictal epileptiform discharges and high-frequency oscillations localizes the seizure-onset zone

OBJECTIVE

To use intracranial electroencephalography (EEG) to characterize functional magnetic resonance imaging (fMRI) activation maps associated with high-frequency oscillations (HFOs) (80-250 Hz) and examine their proximity to HFO- and seizure-generating tissue.

METHODS

Forty-five patients implanted with intracranial depth electrodes underwent a simultaneous EEG-fMRI study at 3 T. HFOs were detected algorithmically from cleaned EEG and visually confirmed by an experienced electroencephalographer. HFOs that co-occurred with interictal epileptiform discharges (IEDs) were subsequently identified. fMRI activation maps associated with HFOs were generated that occurred either independently of IEDs or within ±200 ms of an IED. For all significant analyses, the Maximum, Second Maximum, and Closest activation clusters were identified, and distances were measured to both the electrodes where the HFOs were observed and the electrodes involved in seizure onset.

RESULTS

We identified 108 distinct groups of HFOs from 45 patients. We found that HFOs with IEDs produced fMRI clusters that were closer to the local field potentials of the corresponding HFOs observed within the EEG than HFOs without IEDs. In addition to the fMRI clusters being closer to the location of the EEG correlate, HFOs with IEDs generated Maximum clusters with greater z-scores and larger volumes than HFOs without IEDs. We also observed that HFOs with IEDs resulted in more discrete activation maps.

SIGNIFICANCE

Intracranial EEG-fMRI can be used to probe the hemodynamic response to HFOs. The hemodynamic response associated with HFOs that co-occur with IEDs better identifies known epileptic tissue than HFOs that occur independently.

Modeling the Hemodynamic Response Function Using EEG-fMRI Data During Eyes-Open Resting-State Conditions and Motor Task Execution

Being able to accurately quantify the hemodynamic response function (HRF) that links the blood oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) signal to the underlying neural activity is important both for elucidating neurovascular coupling mechanisms and improving the accuracy of fMRI-based functional connectivity analyses. In particular, HRF estimation using BOLD-fMRI is challenging particularly in the case of resting-state data, due to the absence of information about the underlying neuronal dynamics. To this end, using simultaneously recorded electroencephalography (EEG) and fMRI data is a promising approach, as EEG provides a more direct measure of neural activations. In the present work, we employ simultaneous EEG-fMRI to investigate the regional characteristics of the HRF using measurements acquired during resting conditions. We propose a novel methodological approach based on combining distributed EEG source space reconstruction, which improves the spatial resolution of HRF estimation and using block-structured linear and nonlinear models, which enables us to simultaneously obtain HRF estimates and the contribution of different EEG frequency bands. Our results suggest that the dynamics of the resting-state BOLD signal can be sufficiently described using linear models and that the contribution of each band is region specific. Specifically, it was found that sensory-motor cortices exhibit positive HRF shapes, whereas the lateral occipital cortex and areas in the parietal cortex, such as the inferior and superior parietal lobule exhibit negative HRF shapes. To validate the proposed method, we repeated the analysis using simultaneous EEG-fMRI measurements acquired during execution of a unimanual hand-grip task. Our results reveal significant associations between BOLD signal variations and electrophysiological power fluctuations in the ipsilateral primary motor cortex, particularly for the EEG beta band, in agreement with previous studies in the literature.

Safety of Intracranial Electroencephalography During Functional Electromagnetic Resonance Imaging in Humans at 1.5 Tesla Using a Head Transmit RF Coil: Histopathological and Heat-Shock Immunohistochemistry Observations

OBJECTIVES

Simultaneous intracranial EEG and functional MRI (icEEG-fMRI) recordings in humans, whereby EEG is recorded from electrodes implanted inside the cranium during fMRI scanning, were made possible following safety studies on test phantoms and our specification of a rigorous data acquisition protocol. In parallel with this work, other investigations in our laboratory revealed the damage caused by the EEG electrode implantation procedure at the cellular level. The purpose of this report is to further explore the safety of performing MRI, including simultaneous icEEG-fMRI data acquisitions, in the presence of implanted intra-cranial EEG electrodes, by presenting some histopathological and heat-shock immunopositive labelling observations in surgical tissue samples from patients who underwent the scanning procedure.

METHODS

We performed histopathology and heat shock protein expression analyses on surgical tissue samples from nine patients who had been implanted with icEEG electrodes. Three patients underwent icEEG-fMRI and structural MRI (sMRI); three underwent sMRI only, all at similar time points after icEEG implantation; and three who did not undergo functional or sMRI with icEEG electrodes.

RESULTS

The histopathological findings from the three patients who underwent icEEG-fMRI were similar to those who did not, in that they showed no evidence of additional damage in the vicinity of the electrodes, compared to cases who had no MRI with implanted icEEG electrodes. This finding was similar to our observations in patients who only underwent sMRI with implanted icEEG electrodes.

CONCLUSION

This work provides unique evidence on the safety of functional MRI in the presence of implanted EEG electrodes. In the cases studied, icEEG-fMRI performed in accordance with our protocol based on low-SAR (≤0.1 W/kg) sequences at 1.5T using a head-transmit RF coil, did not result in measurable additional damage to the brain tissue in the vicinity of implanted electrodes. Furthermore, while one cannot generalize the results of this study beyond the specific electrode implantation and scanning conditions described herein, we submit that our approach is a useful framework for the post-hoc safety assessment of MR scanning with brain implants.

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially.

Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes.

Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps.

Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.

Clinical safety of intracranial EEG electrodes in MRI at 1.5 T and 3 T: a single-center experience and literature review

PURPOSE

Intracranial electroencephalography (EEG) can be a critical part of presurgical evaluation for drug resistant epilepsy. With the increasing use of intracranial EEG, the safety of these electrodes in the magnetic resonance imaging (MRI) environment remains a concern, particularly at higher field strengths. However, no studies have reported the MRI safety experience of intracranial electrodes at 3 T. We report an MRI safety review of patients with intracranial electrodes at 1.5 and 3 T.

METHODS

One hundred and sixty-five consecutive admissions for intracranial EEG monitoring were reviewed. A total of 184 MRI scans were performed on 135 patients over 140 admissions. These included 118 structural MRI studies at 1.5 T and 66 functional MRI studies at 3 T. The magnetic resonance (MR) protocols avoided the use of high specific energy absorption rate sequences that could result in electrode heating. The intracranial implantations included 114 depth, 15 subdural, and 11 combined subdural and depth electrodes. Medical records were reviewed for patient-reported complications and radiologic complications related to these studies. Pre-implantation, post-implantation, and post-explantation imaging studies were reviewed for potential complications.

RESULTS

No adverse events or complications were seen during or after MRI scanning at 1.5 or 3 T apart from those attributed to electrode implantation. There was also no clinical or imaging evidence of worsening of pre-existing implantation-related complications after MR imaging.

CONCLUSION

No clinical or radiographic complications are seen when performing MRI scans at 1.5 or 3 T on patients with implanted intracranial EEG electrodes while avoiding high specific energy absorption rate sequences.

Temperature Measurements in the Vicinity of Human Intracranial EEG Electrodes Exposed to Body-Coil RF for MRI at 1.5T

The application of intracranial electroencephalography (icEEG) recording during functional magnetic resonance imaging (icEEG-fMRI) has allowed the study of the hemodynamic correlates of epileptic activity and of the neurophysiological basis of the blood oxygen level-dependent (BOLD) signal. However, the applicability of this technique is affected by data quality issues such as signal drop out in the vicinity of the implanted electrodes. In our center we have limited the technique to a quadrature head transmit and receive RF coil following the results of a safety evaluation. The purpose of this study is to gather further safety-related evidence for performing icEEG-fMRI using a body RF-transmit coil, to allow the greater flexibility afforded by the use of modern, high-density receive arrays, and therefore parallel imaging with benefits such as reduced signal drop-out and distortion artifact. Specifically, we performed a set of empirical temperature measurements on a 1.5T Siemens Avanto MRI scanner with the body RF-transmit coil in a range of electrode and connector cable configurations. The observed RF-induced heating during a high-SAR sequence was maximum in the immediate vicinity of a depth electrode located along the scanner's central axis (range: 0.2-2.4°C) and below 0.5°C at the other electrodes. Also for the high-SAR sequence, we observed excessive RF-related heating in connection cable configurations that deviate from our recommended setup. For the low-SAR sequence, the maximum observed temperature increase across all configurations was 0.3°C. This provides good evidence to allow simultaneous icEEG-fMRI to be performed utilizing the body transmit coil on the 1.5T Siemens Avanto MRI scanner at our center with acceptable additional risk by following a well-defined protocol.

Changing concepts in presurgical assessment for epilepsy surgery

Candidates for epilepsy surgery must undergo presurgical evaluation to establish whether and how surgical treatment can stop seizures without causing neurological deficits. Various techniques, including MRI, PET, single-photon emission CT, video-EEG, magnetoencephalography and invasive EEG, aim to identify the diseased brain tissue and the involved network. Recent technical and methodological developments, encompassing both advances in existing techniques and new combinations of technologies, are enhancing the ability to define the optimal resection strategy. Multimodal interpretation and predictive computer models are expected to aid surgical planning and patient counselling, and multimodal intraoperative guidance is likely to increase surgical precision. In this Review, we discuss how the knowledge derived from these new approaches is challenging our way of thinking about surgery to stop focal seizures. In particular, we highlight the importance of looking beyond the EEG seizure onset zone and considering focal epilepsy as a brain network disease in which long-range connections need to be taken into account. We also explore how new diagnostic techniques are revealing essential information in the brain that was previously hidden from view.

Hydrogel-Based Organic Subdural Electrode with High Conformability to Brain Surface

A totally soft organic subdural electrode has been developed by embedding an array of poly(3,4-ethylenedioxythiophene)-modified carbon fabric (PEDOT-CF) into the polyvinyl alcohol (PVA) hydrogel substrate. The mesh structure of the stretchable PEDOT-CF allowed stable structural integration with the PVA substrate. The electrode performance for monitoring electrocorticography (ECoG) was evaluated in saline solution, on ex vivo brains, and in vivo animal experiments using rats and porcines. It was demonstrated that the large double-layer capacitance of the PEDOT-CF brings low impedance at the frequency of brain wave including epileptic seizures, and PVA hydrogel substrate minimized the contact impedance on the brain. The most important unique feature of the hydrogel-based ECoG electrode was its shape conformability to enable tight adhesion even to curved, grooved surface of brains by just being placed. In addition, since the hydrogel-based electrode is totally organic, the simultaneous ECoG-fMRI measurements could be conducted without image artifacts, avoiding problems induced by conventional metallic electrodes.

BOLD mapping of human epileptic spikes recorded during simultaneous intracranial EEG-fMRI: The impact of automated spike classification

OBJECTIVES

Simultaneous intracranial EEG and functional MRI (icEEG-fMRI) can be used to map the haemodynamic (BOLD) changes associated with the generation of IEDs. Unlike scalp EEG-fMRI, in most patients who undergo icEEG-fMRI, IEDs recorded intracranially are numerous and show variability in terms of field amplitude and morphology. Therefore, visual marking can be highly subjective and time consuming. In this study, we applied an automated spike classification algorithm, Wave_clus (WC), to IEDs marked visually on icEEG data acquired during simultaneous fMRI acquisition. The motivation of this work is to determine whether using a potentially more consistent and unbiased automated approach can produce more biologically meaningful BOLD patterns compared to the BOLD patterns obtained based on the conventional, visual classification.

METHODS

We analysed simultaneous icEEG-fMRI data from eight patients with severe drug resistant epilepsy, and who subsequently underwent resective surgery that resulted in a good outcome: confirmed epileptogenic zone (EZ). For each patient two fMRI analyses were performed: one based on the conventional visual IED classification and the other based on the automated classification. We used the concordance of the IED-related BOLD maps with the confirmed EZ as an indication of their biological meaning, which we compared for the automated and visual classifications for all IED originating in the EZ.

RESULTS

Across the group, the visual and automated classifications resulted in 32 and 24 EZ IED classes respectively, for which 75% vs 83% of the corresponding BOLD maps were concordant. At the single-subject level, the BOLD maps for the automated approach had greater concordance in four patients, and less concordance in one patient, compared to those obtained using the conventional visual classification, and equal concordance for three remaining patients. These differences did not reach statistical significance.

CONCLUSION

We found automated IED classification on icEEG data recorded during fMRI to be feasible and to result in IED-related BOLD maps that may contain similar or greater biological meaning compared to the conventional approach in the majority of the cases studied. We anticipate that this approach will help to gain significant new insights into the brain networks associated with IEDs and in relation to postsurgical outcome.

EEG-Informed fMRI: A Review of Data Analysis Methods

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

Exploring the advantages of multiband fMRI with simultaneous EEG to investigate coupling between gamma frequency neural activity and the BOLD response in humans

We established an optimal combination of EEG recording during sparse multiband (MB) fMRI that preserves high-resolution, whole-brain fMRI coverage while enabling broad-band EEG recordings which are uncorrupted by MRI gradient artefacts (GAs). We first determined the safety of simultaneous EEG recording during MB fMRI. Application of MB factor = 4 produced <1°C peak heating of electrode/hardware during 20 min of GE-EPI data acquisition. However, higher SAR sequences require specific safety testing, with greater heating observed using PCASL with MB factor = 4. Heating was greatest in the electrocardiogram channel, likely due to it possessing longest lead length. We investigated the effect of MB factor on the temporal signal-to-noise ratio for a range of GE-EPI sequences (varying MB factor and temporal interval between slice acquisitions). We found that, for our experimental purpose, the optimal acquisition was achieved with MB factor = 3, 3mm isotropic voxels, and 33 slices providing whole head coverage. This sequence afforded a 2.25 s duration quiet period (without GAs) in every 3 s TR. Using this sequence, we demonstrated the ability to record gamma frequency (55-80 Hz) EEG oscillations, in response to right index finger abduction, that are usually obscured by GAs during continuous fMRI data acquisition. In this novel application of EEG-MB fMRI to a motor task, we observed a positive correlation between gamma and BOLD responses in bilateral motor regions. These findings support and extend previous work regarding coupling between neural and hemodynamic measures of brain activity in humans and showcase the utility of EEG-MB fMRI for future investigations.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers

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We created a validation method for the evaluation of automated classification of interictal spikes.

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We used a modified version of Wave_clus (WC) to automatically classify the data of 5 patients.

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WC classification was similar to EEG reviewers providing an unbiased evaluation of the clinical data.

Objective

To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data.

Method

Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers’ spike identification and individual spike class labels visually and quantitatively.

Results

The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers.

Conclusions

WC performance is indistinguishable to that of EEG reviewers’ suggesting it could be a valid clinical tool for the assessment of IEDs.

Significance

WC can be used to provide quantitative analysis of epileptic spikes.

Functional connectomics from a "big data" perspective

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field.

Phase-amplitude coupling and the BOLD signal: A simultaneous intracranial EEG (icEEG) - fMRI study in humans performing a finger-tapping task

Although it has been consistently found that local blood-oxygen-level-dependent (BOLD) changes are better modelled by a combination of the power of multiple EEG frequency bands rather than by the power of a unique band alone, the local electro-haemodynamic coupling function is not yet fully characterised. Electrophysiological studies have revealed that the strength of the coupling between the phase of low- and the amplitude of high- frequency EEG activities (phase–amplitude coupling - PAC) has an important role in brain function in general, and in preparation and execution of movement in particular. Using electrocorticographic (ECoG) and functional magnetic resonance imaging (fMRI) data recorded simultaneously in humans performing a finger-tapping task, we investigated the single-trial relationship between the amplitude of the BOLD signal and the strength of PAC and the power of α, β, and γ bands, at a local level. In line with previous studies, we found a positive correlation for the γ band, and negative correlations for the PAC_βγ strength, and the α and β bands. More importantly, we found that the PAC_βγ strength explained variance of the amplitude of the BOLD signal that was not explained by a combination of the α, β, and γ band powers. Our main finding sheds further light on the distinct nature of PAC as a functionally relevant mechanism and suggests that the sensitivity of EEG-informed fMRI studies may increase by including the PAC strength in the BOLD signal model, in addition to the power of the low- and high- frequency EEG bands.

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First study of single-trial correlations between the phase amplitude coupling strength and BOLD.

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Intracranial EEG and fMRI data simultaneously recorded in humans during a motor task.

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PAC_βγ strength explains variance of BOLD in addition a combination of α, β, and γ band powers.