This work was partially supported by the College of Medicine, the Vice President for Research, UK HealthCare, and the Research Priority Area at the University of Kentucky as part of the College of Medicine Alliance Initiative and Dr. Jihye Bae&#39;s Start-Up funds provided by the Department of Electrical and Computer Engineering at the University of Kentucky. The authors thank the volunteer participants for the recording and the Epilepsy-Neuroimaging Research Alliance team members, especially Dr. Brian Gold for leading the alliance team, Dr. Sridhar Sunderam for research mentorship, and Susan V. Hollar and Emily Ashcraft for patient care and management.

<ol>
	<li>Ngugi, A. K., Bottomley, C., Kleinschmidt, I., Sander, J. W., Newton, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+the+burden+of+active+and+life-time+epilepsy:+a+meta-analytic+approach.">Estimation of the burden of active and life-time epilepsy: a meta-analytic approach.</a> Epilepsia. 51 (5), 883-890 (2010).</li><li>Kwan, P., Brodie, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Early+Identification+of+refractory+epilepsy.">Early Identification of refractory epilepsy.</a> The New England Journal of Medicine. 342 (5), 314-319 (2000).</li><li>Menon, V., Crottaz-Herbette, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+EEG+and+fMRI+studies+of+human+brain+function.">Combined EEG and fMRI studies of human brain function.</a> International Review of Neurobiology. 66, 291-321 (2005).</li><li>Gotman, J., Pittau, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combining+EEG+and+fMRI+in+the+study+of+epileptic+discharges.">Combining EEG and fMRI in the study of epileptic discharges.</a> Epilepsia. 52, 38-42 (2011).</li><li>Pittau, F., Dubeau, F., Gotman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Contribution+of+EEG/fMRI+to+the+definition+of+the+epileptic+focus.">Contribution of EEG/fMRI to the definition of the epileptic focus.</a> Neurology. 78 (19), 1479-1487 (2012).</li><li>Ikemoto, S., von Ellenrieder, N., Gotman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electroencephalography-functional+magnetic+resonance+imaging+of+epileptiform+discharges:+Noninvasive+investigation+of+the+whole+brain.">Electroencephalography-functional magnetic resonance imaging of epileptiform discharges: Noninvasive investigation of the whole brain.</a> Epilepsia. 63 (11), 2725-2744 (2022).</li><li>Mullinger, K. J., Castellone, P., Bowtell, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Best+current+practice+for+obtaining+high+quality+EEG+data+during+simultaneous+fMRI.">Best current practice for obtaining high quality EEG data during simultaneous fMRI.</a> Journal of Visualized Experiments. (76), e50283 (2013).</li><li>Douglas, P. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Method+for+simultaneous+fMRI/EEG+data+collection+during+a+focused+attention+suggestion+for+differential+thermal+sensation.">Method for simultaneous fMRI/EEG data collection during a focused attention suggestion for differential thermal sensation.</a> Journal of Visualized Experiments. (83), e3298 (2014).</li><li>Nguyen, T., Potter, T., Karmonik, C., Grossman, R., Zhang, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Concurrent+EEG+and+functional+MRI+recording+and+integration+analysis+for+dynamic+cortical+activity+imaging.">Concurrent EEG and functional MRI recording and integration analysis for dynamic cortical activity imaging.</a> Journal of Visualized Experiments. (136), e56417 (2018).</li><li>Khoo, H. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliable+acquisition+of+electroencephalography+data+during+simultaneous+electroencephalography+and+functional+MRI.">Reliable acquisition of electroencephalography data during simultaneous electroencephalography and functional MRI.</a> Journal of Visualized Experiments. (169), e62247 (2021).</li><li>Allen, P. J., Josephs, O., Turner, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+removing+imaging+artifact+from+continuous+EEG+recorded+during+functional+MRI.">A method for removing imaging artifact from continuous EEG recorded during functional MRI.</a> Neuroimage. 12 (2), 230-239 (2000).</li><li>Smith, S. J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EEG+in+the+diagnosis,+classification,+and+management+of+patients+with+epilepsy.">EEG in the diagnosis, classification, and management of patients with epilepsy.</a> Journal of Neurology, Neurosurgery, and Psychiatry. 76, 2-7 (2005).</li><li>Manganotti, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Continuous+EEG-fMRI+in+patients+with+partial+epilepsy+and+focal+interictal+slow-wave+discharges+on+EEG.">Continuous EEG-fMRI in patients with partial epilepsy and focal interictal slow-wave discharges on EEG.</a> Magnetic Resonance Imaging. 26 (8), 1089-1100 (2008).</li><li>Reiher, J., Beaudry, M., Leduc, C. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+intermittent+rhythmic+delta+activity+(TIRDA)+in+the+diagnosis+of+complex+partial+epilepsy:+sensitivity,+specificity+and+predictive+value.">Temporal intermittent rhythmic delta activity (TIRDA) in the diagnosis of complex partial epilepsy: sensitivity, specificity and predictive value.</a> The Canadian Journal of Neurological Sciences. 16 (4), 398-401 (1989).</li><li>Geyer, J. D., Bilir, E., Faught, R. E., Kuzniecky, R., Gilliam, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Significance+of+interictal+temporal+lobe+delta+activity+for+localization+of+the+primary+epileptogenic+region.">Significance of interictal temporal lobe delta activity for localization of the primary epileptogenic region.</a> Neurology. 52 (1), 202-205 (1999).</li><li>Koupparis, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Association+of+EEG-fMRI+responses+and+outcome+after+epilepsy+surgery.">Association of EEG-fMRI responses and outcome after epilepsy surgery.</a> Neurology. 97 (15), e1523-1536 (2021).</li><li>Gotman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Has+recording+of+seizures+become+obsolete.">Has recording of seizures become obsolete.</a> Revue Neurologique. , 00865 (2023).</li><li>Pascual-Marqui, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Standardized+low-resolution+brain+electromagnetic+tomography+(sLORETA):+technical+details.">Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details.</a> Methods and Findings in Experimental and Clinical Pharmacology. 24, 5-12 (2002).</li><li>Hallez, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+on+solving+the+forward+problem+in+EEG+source+analysis.">Review on solving the forward problem in EEG source analysis.</a> Journal of Neuroengineering and Rehabilitation. 4, 46 (2007).</li><li>Tadel, F., Baillet, S., Mosher, J. C., Pantazis, D., Leahy, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brainstorm:+a+user-friendly+application+for+MEG/EEG+analysis.">Brainstorm: a user-friendly application for MEG/EEG analysis.</a> Computational Intelligence and Neuroscience. 2011, 879716 (2011).</li><li>Srinivasan, R., Tucker, D. M., Murias, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimating+the+spatial+Nyquist+of+the+human+EEG.">Estimating the spatial Nyquist of the human EEG.</a> Behavior Research Methods, Instruments, &amp; Computers. 30, 8-19 (1998).</li><li>Michel, C. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EEG+source+imaging.">EEG source imaging.</a> Clinical Neurophysiology. 115 (10), 2195-2222 (2004).</li><li>Abreu, R., Leal, A., Figueiredo, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EEG-informed+fMRI:+A+review+of+data+analysis+methods.">EEG-informed fMRI: A review of data analysis methods.</a> Frontiers in Human Neuroscience. 12, 29 (2018).</li><li>Saletu, B., Anderer, P., Saletu-Zyhlarz, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EEG+topography+and+tomography+(LORETA)+in+the+classification+and+evaluation+of+the+pharmacodynamics+of+psychotropic+drugs.">EEG topography and tomography (LORETA) in the classification and evaluation of the pharmacodynamics of psychotropic drugs.</a> Clinical EEG Neuroscience. 37 (2), 66-80 (2006).</li><li>Windmann, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+midazolam+premedication+on+intraoperative+EEG+signatures+in+elderly+patients.">Influence of midazolam premedication on intraoperative EEG signatures in elderly patients.</a> Clinical Neurophysiology. 130 (9), 1673-1681 (2019).</li><li>Nishida, M., Zestos, M. M., Asano, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial-temporal+patterns+of+electrocorticographic+spectral+changes+during+midazolam+sedation.">Spatial-temporal patterns of electrocorticographic spectral changes during midazolam sedation.</a> Clinical Neurophysiology. 127 (2), 1223-1232 (2016).</li><li>Forsyth, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+local+spectral+modulation,+and+temporal+correlation,+of+simultaneously+recorded+EEG/fMRI+signals+during+ketamine+and+midazolam+sedation.">Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG/fMRI signals during ketamine and midazolam sedation.</a> Psychopharmacology. 235 (12), 3479-3493 (2018).</li></ol>

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This experimental protocol is unique in providing a smooth transition of patients with epilepsy from the EMU to the scanning room, allowing it to be used in clinical and research settings. The use of FDA-approved MR conditional electrodes is an essential component for both clinical recordings during the time spent in the EMU and for safe transfer to MRI without having to remove or exchange the scalp electrodes from the patient. In the EMU, the MR conditional electrodes are connected to an amplifier for simultaneous video and EEG monitoring. For EEG-fMRI recordings, an MR conditional EEG amplifier and an MRI scanner can be used with a 20-channel head-coil, which accommodates the size of the electrode set and connecting wires. It must be noted that before conducting the simultaneous EEG-fMRI recordings in patients with epilepsy, a test run with a healthy subject is highly recommended to confirm the proper operation of all equipment and to become familiar with each required step.
In addition, concrete organization of the team and careful selection of patients also play a significant role in this protocol. To be viable for both clinical and research settings, it is required to have a structured team of epileptologists, nursing staff, EEG technologists, and engineers. For patient selection, the above-listed inclusion and exclusion criteria must be firmly considered.
Furthermore, it is important to address that when EEG-informed fMRI analysis is conducted, clear presence of the key features of EEGs must exist to guide the corresponding BOLD changes in fMRI. Therefore, when conducting the EEG-fMRI recording, it is important to consider patients who have previously demonstrated target EEG features. During the interictal period in patients with epilepsy, IEDs, which are abnormal and suggest epileptogenic potential, are a well-known EEG feature to reference to the BOLD changes16, even though the example here does not include this case. When targeting to obtain IEDs in the interictal EEG-fMRI recordings, experimenters should consider patients with frequent IEDs (at least three IEDs/hour) observed by a scalp EEG, in order to ensure sufficient epileptiform discharges during a scanning session. The number of IEDs can be determined from the EEG monitoring in the EMU, or from referencing the IED frequency seen in the subjects&#39; prior EEG recordings if they exist. The obtained recordings of interictal EEG-fMRI data can bring benefits to understanding and potentially localizing the seizure onset zone17.
Once a clean EEG is obtained after processing the artifact removal steps, further EEG analysis can be applied. For example, EEG source imaging (ESI) can be obtained by applying standardized low-resolution brain electromagnetic tomography (sLORETA)18 to estimate the brain&#39;s corresponding electrical activity on the cortical surface. The estimated sources can be obtained by inverting the computed lead field matrix based on the head, outer skull, inner skull, and cortex layers created from the patient&#39;s MRI using the boundary element method19. There are numerous publicly available toolboxes to obtain EEG source imaging, and Brainstorm is one popularly used MATLAB-based toolbox20.
When ESI is considered using the processed EEG, the total number of electrodes and their distributions must be carefully taken into account so that they can reasonably cover the entire head. The minimum number of electrodes necessary to implement ESI is 32 channels21,22, which is more than the standard number of electrodes used in clinical settings. Thus, it is recommended to include extra channels to cover the entire head with reasonable spacing. The channel selection in this study includes 21 channels, which are conventionally used in the clinic for EEG monitoring, and 11 additional channels to cover the head entirely (Figure 1).
Here, we do not include details of fMRI analysis, since this is out of the scope of our study. However, a possible direction is EEG-informed fMRI analysis23. For instance, the occurrence time of IEDs can be saved as event triggers to correlate with the fMRI, which can lead to a routine event-related fMRI analysis. In this case, a generalized linear model analysis can be used to find the brain regions showing changes in fMRI signal at the time of IEDs.
We point out that a recently published study10 has shown it is possible to use a carbon wire loop system when a more robust artifact removal technique is required16. However, we want to apprise that the integration of the carbon wire loop system in our experimental setting with the MR conditional electrode has not been investigated yet.
Even though this study specifically focuses on the interictal period of epilepsy, the introduced protocol for simultaneous EEG-fMRI can be further extended to the ictal or postictal period. However, specific considerations must be followed when any customized settings are considered. For the postictal phase, an important concern that we are cognizant of is that the patient is given a benzodiazepine prior to transport to the MRI. As for the frequency analysis of EEGs, it has been reported that benzodiazepines do not necessarily alter the specific frequency bands24,25, and in the case of modest changes, these are confined to the somatosensory-motor region26 or frontal lobes27. Furthermore, with respect to simultaneous EEG-fMRI, delta EEG-BOLD correlations showed no changes after benzodiazepine injection compared to a control with saline injection27. The BOLD signal was decreased in only the small areas of Heschel&#39;s gyrus and supplementary motor area.

Epilepsy afflicts nearly 70 million people worldwide1. As many as one out of every 150 people with poorly controlled epilepsy succumb to a sudden unexpected death in epilepsy (SUDEP) every year. Furthermore, roughly 30%-40% of epilepsy cases are refractory to medical management2. Neurosurgical treatment in the form of resection, disconnection, or neuromodulation can be a life-changing and life-saving measure for patients with refractory epilepsy.
Simultaneous electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) is a unique combined technique that measures brain activities noninvasively, and has provided benefits for understanding and localizing seizure onset in epilepsy3,4,5,6. Scalp EEGs can be used to lateralize and localize seizure onset zones, but they have relatively poor spatial resolution due to limited capabilities with respect to assessing deep epileptogenic sources. While fMRI has good spatial resolution throughout the brain, including deep regions, fMRI alone is not specific to seizures. However, scalp EEGs can inform the interpretation of blood oxygen level-dependent (BOLD) activation or deactivation areas in fMRI, thereby producing an fMRI technique that is specific to epilepsy. Thus, the implementation of simultaneous EEG-fMRI can be used to map spatiotemporal processes relevant to localizing both the &#39;where&#39; and &#39;when&#39; of epileptic events.
Explanations of how to conduct simultaneous EEG-fMRI are provided in the previous studies7,8,9,10. However, EEG-fMRI has been underutilized in epilepsy, especially in clinical settings. There exists a study that provides a general procedure for EEG-fMRI recordings, background, and examples of possible EEG analysis7. Also, a study emphasizing hypnotic induction along with temperature measures in simultaneous EEG-fMRI recordings has been conducted8. Furthermore, an expanded EEG-fMRI study to introduce a spatiotemporal and fMRI-constrained EEG source imaging method has been proposed9,10. In addition, the use of a carbon wire loop to effectively remove artifacts from EEG-fMRI has been considered10. However, all these studies fail to address challenges in conducting EEG-fMRI studies in a clinical research setting. In particular, the use of the EEG cap restricts the feasibility of these protocols in clinical settings, and details about patient management are also missing. In this study, we provide an EEG-fMRI recording protocol that can be used in both clinical and research settings for patients with epilepsy. This unique protocol allows an easy patient transition from an epilepsy monitoring unit (EMU) to the scanning room. In addition, the protocol provides the potential to expand its application to postictal period recordings with epilepsy patients. For EEG-fMRI, post-processing is a crucial step in removing artifacts caused by MRI gradients and physiological artifacts, such as those related to heartbeat. Thus, we also provide step-by-step procedures to remove EEG artifacts using a standard template removal method11 for clinical review.

<table><tbody><tr><td>3T Magnetom Prisma fit MRI scanner</td><td>Siemens Healthineers</td><td></td><td></td></tr><tr><td>Abralyt HiCl, 10 g.</td><td>EASYCAP GmbH</td><td></td><td>Conductive gel for ECG electrode.</td></tr><tr><td>BrainAmp MR plus 32-channel</td><td>Brain Products GmbH</td><td>S-BP-01300</td><td></td></tr><tr><td>BrainVision Analyzer Version 2.2.0.7383</td><td>Brain Products GmbH</td><td></td><td>EEG analysis software.</td></tr><tr><td>BrainVision Interface Box 32 inputs</td><td>Ives EEG Solutions, LLC</td><td>BVI-32</td><td></td></tr><tr><td>BrainVision Recorder License with dongle</td><td>Brain Products GmbH</td><td>S-BP-170-3000</td><td></td></tr><tr><td>BrainVision Recorder Version 1.23.0003</td><td>Brain Products GmbH</td><td></td><td>EEG recording software.</td></tr><tr><td>Collodion (non-flexible)</td><td>Mavidon</td><td></td><td>Glue to secure EEG electrodes.</td></tr><tr><td>Fiber Optic cable (30m one line)</td><td>Brain Products GmbH</td><td>S-BP-345-3020</td><td></td></tr><tr><td>Gold Cup Electrode set, 32 channel</td><td>Ives EEG Solutions, LLC</td><td>GCE-32</td><td>2+ items are recommended when managing multiple subjects with overlapped/close period of Epilepsy Monitoring Unit (EMU) stay.</td></tr><tr><td>Gold Cup Electrodes</td><td>Ives EEG Solutions, LLC</td><td>GCE-EKG</td><td></td></tr><tr><td>Harness, 32 lead, reusable</td><td>Ives EEG Solutions, LLC</td><td>HAR-32</td><td>2+ items are recommended when managing multiple subjects with overlapped/close period of&amp;nbsp; Epilepsy Monitoring Unit (EMU) stay.</td></tr><tr><td>MR-sled kit including 100% and 75% length base plates, low profile (3 cm) block legs for each base plate, ramp, and strap systems as hand configured</td><td>Brain Products GmbH</td><td>BV-79123-PRISMA SKYRA</td><td></td></tr><tr><td>Natus NeuroWorks EEG</td><td>Natus</td><td></td><td>Software used for EEG monitoring at the Epilepsy Monitoring Unit (EMU).</td></tr><tr><td>Nuprep Skin Prep Gel</td><td>Weaver and Co.</td><td></td><td></td></tr><tr><td>Passive starter set, including consumables (gel, syringes, dispensing tips, adhesive washers, etc.) to facilitate out of the box data acquisition</td><td>Brain Products GmbH</td><td>S-C-5303</td><td></td></tr><tr><td>SyncBox compl. Extension box for phase sync recordings</td><td>Brain Products GmbH</td><td>S-BP-02675</td><td>Syncbox</td></tr><tr><td>syngo MR XA30</td><td>Siemens Healthineers</td><td></td><td>Software used for the MRI scanner.</td></tr><tr><td>Ten 20 Conductive Neurodiagnostic Electrode Paste</td><td>Weaver and Co.</td><td></td><td>Conductive gel for EEG electrodes.</td></tr><tr><td>TriggerBox Kit for BrainAmp</td><td>Brain Products GmbH</td><td>S-BP-110-9010</td><td>Triggerbox; This Kit allows to expand the trigger width from the scanner so that the trigger signal can be detected on the BrainVision Recorder properly. This kit may not be required depending on the characteristics of the trigger signal provided by the scanner.</td></tr><tr><td>Xltek EMU40EX amplifier</td><td>Natus</td><td></td><td>An amplifier used at the Epilepsy Monitoring Unit (EMU).</td></tr></tbody></table>

equipment setup and artifact removal for simultaneous electroencephalogram and functional magnetic resonance imaging for clinical review in epilepsy

Simultaneous electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) is a unique combined technique that provides synergy in the understanding and localization of seizure onset in epilepsy. However, reported experimental protocols for EEG-fMRI recordings fail to address details about conducting such procedures on epilepsy patients. In addition, these protocols are limited solely to research settings. To fill the gap between patient monitoring in an epilepsy monitoring unit (EMU) and conducting research with an epilepsy patient, we introduce a unique EEG-fMRI recording protocol of epilepsy during the interictal period. The use of an MR conditional electrode set, which can also be used in the EMU for a simultaneous scalp EEG and video recording, allows an easy transition of EEG recordings from the EMU to the scanning room for concurrent EEG-fMRI recordings. Details on the recording procedures using this specific MR conditional electrode set are provided. In addition, the study explains step-by-step EEG processing procedures to remove the imaging artifacts, which can then be used for clinical review. This experimental protocol promotes an amendment to the conventional EEG-fMRI recording for enhanced applicability in both clinical (i.e., EMU) and research settings. Furthermore, this protocol provides the potential to expand this modality to postictal EEG-fMRI recordings in the clinical setting.

When a patient is admitted to the EMU, a simultaneous scalp EEG and video are recorded. One purpose of the EEG monitoring by a neurologist is to evaluate for epileptiform discharges, which can potentially inform the localization of the seizure onset. When extraordinary dynamics of specific EEG channels are distinguished, the electrode locations can be associated with seizure localization. During the interictal period, interictal epileptiform discharges (IEDs), including spikes and sharp waves, are traditionally considered as markers of areas of epileptogenicity. Furthermore, the obtained recordings of interictal EEG-fMRI data can be advantageous to understand and localize the seizures. To validate this EEG-fMRI recording and EEG processing protocol, we evaluate the quality of the EEG by comparing the postprocessed EEG to the one from the EMU, and we confirm that the same distinguishable EEG characteristic is observed in both cases.
Focal delta slow activity is typically suggestive of an underlying brain structural lesion or an area where the neurons are not functioning as expected, which is often observed after strokes, head injuries, brain infections, or dementia. However, it is not uncommon for patients with focal epilepsy to demonstrate focal delta activity near or at the site of their epileptogenic zone. In addition, although focal delta activity is less specific than IEDs, it can specify localized structural pathology corresponding to seizure onset in epilepsy12. Furthermore, focal interictal slow waves in EEGs correspond to focal BOLD activation on fMRI that matches the epileptogenic area in patients with partial epilepsy13.
It is notable that, in temporal lobe onset epilepsy, a type of delta activity called temporal intermittent rhythmic delta (TIRDA) is sometimes present, and it is considered an IED equivalent14. On the contrary, temporal intermittent polymorphic delta (TIPDA) is not considered an IED equivalent15. In the processed EEG data, clear focal left temporal slow waves (TIPDA) are present, which is observed from the EEG recorded at the EMU (Figure 7). Although this delta activity is not IED equivalent, it suggests left temporal neuronal dysfunction.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64919/64919fig01.jpg" /> 
Figure 1: An example of 32 electrode selections for simultaneous EEG-fMRI recording. In the clinic, 21 channels are commonly considered for EEG monitoring. To fulfill a minimum number of electrodes to conduct EEG source imaging (ESI), 11 additional channels are included to cover the head entirely. All electrodes are gold cups to avoid MR effects. In the figure, different colors are used to distinguish different electrodes, and the colors match the physical cable colors. Each rectangular box in the bottom indicates one junction to be connected to a harness, which will be connected to an amplifier for recording. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64919/64919fig02.jpg" /> 
Figure 2: Electrode placements. (A) Placement of the electrodes on the patient&#39;s scalp and (B) arrangement of the cable junctions. The left images in (A) and (B) provide a top-front view, and the right images provide a left-side view of the patient. The red arrows in (B) indicate the placement of gauze pads. This helps to avoid imaging artifacts. The areas circled in blue in (B) show how the cable junctions are arranged. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64919/64919fig03.jpg" /> 
Figure 3: Equipment connection in the monitoring room. (A) An overview of the USB 2 adapter, Syncbox, and Triggerbox connection. Detailed picture of (B) the USB 2 adapter and Syncbox cable connections, (C) the Syncbox and the fiber optic cable connection, and (D) the cable connections in the Triggerbox. The star marks on (B), (C), and (D) show the location of the USB cables to be connected to the recording PC. A schematic diagram of the EEG recording system and the connections required between the hardware is provided in Figure 1 in Mullinger et al.7. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64919/64919fig04.jpg" /> 
Figure 4: Equipment connection in the scanning room. (A) An overview of the EEG amplifier connection in the scanner. (B) Wrapped cables from the interface box to connect the EEG electrodes (the red cable is for the ECG measure). (C) Connection of the interface box and the EEG amplifier and MR safe sandbags placed to reduce MR artifacts. (D) Connection of the amplifier (top) and the battery (bottom) and connection of the fiber optic cable from the Syncbox in the monitoring room to the amplifier. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64919/64919fig05.jpg" /> 
Figure 5: Screenshot of workspace settings on the EEG recording software. The number of channels and sampling rate can be set under the amplifier settings. In addition, the specification of each channel can be modified, if necessary, by clicking the table at the bottom. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/64919/64919fig06.jpg" /> 
Figure 6: EEG artifact removal pipeline with representative examples. The raw EEG traces are displayed in the bottom left. The bottom middle plot shows EEG traces after applying MR artifact correction and a high pass filter of 0.5 Hz on the raw EEG. The bottom right plot displays EEG traces after applying CB artifact correction and a notch filter of 60 Hz on the processed EEG. The EEG traces are displayed under common ground mode to effectively visualize how each process influences each recorded channel. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/64919/64919fig07.jpg" /> 
Figure 7: Comparison of the processed EEG from a simultaneous EEG-fMRI recording (left) and an EEG recorded at the EMU (right). The red circle indicates focal left temporal slow waves at the same channels. The EEG traces are displayed in a double banana format, which is traditionally considered in the clinic. <a href="https://www.jove.com/files/ftp_upload/64919/64919fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy at JoVE.c

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

This article details simultaneous electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) recording procedures that can be used in both clinical and research settings. EEG processing procedures to remove imaging artifacts for clinical review are also included. This study focuses on the example of epilepsy during the interictal period.

Simultaneous electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) is a unique combined technique that provides synergy in the ...

equipment-setup-artifact-removal-for-simultaneous

Research

JoVE Journal

Bioengineering

1.8K Views.  University of Kentucky. In deze video introduceren we een uniek, EEG-fMRI-opnameprotocol dat zowel in de kliniek als in onderzoeksomgevingen kan worden gebruikt. Gelijktijdige EEG-fMRI is een techniek die synergie biedt in het begrijpen en lokaliseren van het begin van aanvallen en epilepsie. Implementatie van gelijktijdige EEG-fMRI kan worden gebruikt om de ruimtelijke temporele processen van epileptische gebeurtenissen in kaart te brengen, die neurochirurgische behandeling kunnen begeleiden voor patiënten met med...

Video: Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Simultaneous EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the high spatial accuracy of fMRI. The data from these two modalities can be combined in a number of ways, but all rely on the acquisition of high quality EEG and fMRI data. EEG data acquired during simultaneous fMRI are affected by several artifacts, including the gradient artefact (due to the changing magnetic field gradients required for fMRI), the pulse artefact (linked to the cardiac cycle) and movement artifacts (resulting from movements in the strong magnetic field of the scanner, and muscle activity). Post-processing methods for successfully correcting the gradient and pulse artifacts require a number of criteria to be satisfied during data acquisition. Minimizing head motion during EEG-fMRI is also imperative for limiting the generation of artifacts.
Interactions between the radio frequency (RF) pulses required for MRI and the EEG hardware may occur and can cause heating. This is only a significant risk if safety guidelines are not satisfied. Hardware design and set-up, as well as careful selection of which MR sequences are run with the EEG hardware present must therefore be considered.
The above issues highlight the importance of the choice of the experimental protocol employed when performing a simultaneous EEG-fMRI experiment. Based on previous research we describe an optimal experimental set-up. This provides high quality EEG data during simultaneous fMRI when using commercial EEG and fMRI systems, with safety risks to the subject minimized. We demonstrate this set-up in an EEG-fMRI experiment using a simple visual stimulus. However, much more complex stimuli can be used. Here we show the EEG-fMRI set-up using a Brain Products GmbH (Gilching, Germany) MRplus, 32 channel EEG system in conjunction with a Philips Achieva (Best, Netherlands) 3T MR scanner, although many of the techniques are transferable to other systems.

Simultaneous electroencephalography (EEG) and functional Magnetic Resonance imaging (fMRI) is a powerful neuroimaging tool. However, the inside of an MRI scanner forms a difficult environment for EEG data recording and safety must be considered whenever operating EEG equipment inside a scanner. Here, we present an optimised EEG-fMRI data acquisition protocol.

Simultaneous  EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the  high spatial accuracy of fMRI. The data  from these two ...

Behavior

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth

Traditional mechanical testing often results in the destruction of the sample, and in the case of long term tissue engineered construct studies, the use of destructive assessment is not acceptable. A proposed alternative is the use of an imaging process called magnetic resonance elastography. Elastography is a nondestructive method for determining the engineered outcome by measuring local mechanical property values (i.e., complex shear modulus), which are essential markers for identifying the structure and functionality of a tissue. As a noninvasive means for evaluation, the monitoring of engineered constructs with imaging modalities such as magnetic resonance imaging (MRI) has seen increasing interest in the past decade1. For example, the magnetic resonance (MR) techniques of diffusion and relaxometry have been able to characterize the changes in chemical and physical properties during engineered tissue development2. The method proposed in the following protocol uses microscopic magnetic resonance elastography (&mu;MRE) as a noninvasive MR based technique for measuring the mechanical properties of small soft tissues3. MRE is achieved by coupling a sonic mechanical actuator with the tissue of interest and recording the shear wave propagation with an MR scanner4. Recently, &mu;MRE has been applied in tissue engineering to acquire essential growth information that is traditionally measured using destructive mechanical macroscopic techniques5. In the following procedure, elastography is achieved through the imaging of engineered constructs with a modified Hahn spin-echo sequence coupled with a mechanical actuator. As shown in Figure 1, the modified sequence synchronizes image acquisition with the transmission of external shear waves; subsequently, the motion is sensitized through the use of oscillating bipolar pairs. Following collection of images with positive and negative motion sensitization, complex division of the data produce a shear wave image. Then, the image is assessed using an inversion algorithm to generate a shear stiffness map6. The resulting measurements at each voxel have been shown to strongly correlate (R2&gt;0.9914) with data collected using dynamic mechanical analysis7. In this study, elastography is integrated into the tissue development process for monitoring human mesenchymal stem cell (hMSC) differentiation into adipogenic and osteogenic constructs as shown in Figure 2.

The procedure demonstrates the methodology of magnetic resonance elastography for monitoring the engineered outcome of adipose and osteogenic tissue engineered constructs through noninvasive local assessment of the mechanical properties using microscopic magnetic resonance elastography (&mu;MRE).

Traditional mechanical testing often results in the destruction of the sample, and in the case of long term tissue engineered construct studies, the use ...

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning1, auditory processing2 and visual-spatial attention3. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function1-5. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication6 and control7. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform8,9 and the SIGFRIED10 method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation.
Prerequisites and Planning:
Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure.
In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort.
At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5th Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment.
Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software8,9. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator.
A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS).
Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping10.
The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

We present a method for collecting electrocorticographic signals for research purposes from humans who are undergoing invasive epilepsy monitoring. We show how to use the BCI2000 software platform for data collection, signal processing and stimulus presentation. Specifically, we demonstrate SIGFRIED, a BCI2000-based tool for real-time functional brain mapping.

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), ...

Neuroscience

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator&#39;s coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.

This paper describes a method for collecting and analyzing electroencephalography (EEG) data during concurrent transcranial magnetic stimulation (TMS) guided by activations revealed with functional magnetic resonance imaging (fMRI). A method for TMS artifact removal and extraction of event related potentials is described as well as considerations in paradigm design and experimental setup.

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological ...

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases.

Resting-state functional-connectivity MRI has identified abnormalities in patients with a wide range of neuropsychiatric disorders, including epilepsy due to malformations of cortical development. Transcranial Magnetic Stimulation in combination with EEG can demonstrate that patients with epilepsy have cortical hyperexcitability in regions with abnormal connectivity.

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations ...

Medicine

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Approximately 30% of epilepsy patients are refractory to antiepileptic drugs. In these cases, surgery is the only alternative to eliminate/control seizures. However, a significant minority of patients continues to exhibit post-operative seizures, even in those cases in which the suspected source of seizures has been correctly localized and resected. The protocol presented here combines a clinical procedure routinely employed during the pre-operative evaluation of temporal lobe epilepsy (TLE) patients with a novel technique for network analysis. The method allows for the evaluation of the temporal evolution of mesial network parameters. The bilateral insertion of foramen ovale electrodes (FOE) into the ambient cistern simultaneously records electrocortical activity at several mesial areas in the temporal lobe. Furthermore, network methodology applied to the recorded time series tracks the temporal evolution of the mesial networks both interictally and during the seizures. In this way, the presented protocol offers a unique way to visualize and quantify measures that considers the relationships between several mesial areas instead of a single area.

This protocol describes a procedure to track the evolution of mesial network measures in temporal lobe epilepsy (TLE) patients. It is based on the combination of intracranial recordings with a novel numerical technique for data analysis. Specifically, we present a protocol for network analyses of foramen ovale recordings.

Approximately 30% of epilepsy patients are refractory to antiepileptic drugs. In these cases, surgery is the only alternative to eliminate/control ...

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery.
The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.

High Frequency Oscillations (HFOs) have emerged as presurgical biomarkers for the identification of the epileptogenic zone in pediatric patients with medically refractory epilepsy. A methodology for the noninvasive recording, detection, and localization of HFOs with simultaneous scalp electroencephalography (EEG) and magnetoencephalography (MEG) is presented.

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency ...

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.

This article provides a straightforward protocol for acquiring good quality electroencephalography (EEG) data during simultaneous EEG and functional magnetic resonance imaging by utilizing readily available medical products.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG ...

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain activity. Multimodal methods have sought to combine the high temporal resolution of EEG with the spatial precision of fMRI, but the complexity of this approach is currently in need of improvement. The protocol presented here describes the recently developed spatiotemporal fMRI-constrained EEG source imaging method, which seeks to rectify source biases and improve EEG-fMRI source localization through the dynamic recruitment of fMRI sub-regions. The process begins with the collection of multimodal data from concurrent EEG and fMRI scans, the generation of 3D cortical models, and independent EEG and fMRI processing. The processed fMRI activation maps are then split into multiple priors, according to their location and surrounding area. These are taken as priors in a two-level hierarchical Bayesian algorithm for EEG source localization. For each window of interest (defined by the operator), specific segments of the fMRI activation map will be identified as active to optimize a parameter known as model evidence. These will be used as soft constraints on the identified cortical activity, increasing the specificity of the multimodal imaging method by reducing cross-talk and avoiding erroneous activity in other conditionally active fMRI regions. The method generates cortical maps of activity and time-courses, which may be taken as final results, or used as a basis for further analyses (analyses of correlation, causation, etc.) While the method is somewhat limited by its modalities (it will not find EEG-invisible sources), it is broadly compatible with most major processing software, and is suitable for most neuroimaging studies.

An EEG-fMRI multimodal imaging method, known as the spatiotemporal fMRI-constrained EEG source imaging method, is described here. The presented method employs conditionally-active fMRI sub-maps, or priors, to guide EEG source localization in a manner that improves spatial specificity and limits erroneous results.

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain ...

Biology

Integrating MEG and HD-EEG in Pediatric Epilepsy Localization

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

For children with drug-resistant epilepsy (DRE), seizure freedom relies on the delineation and resection (or ablation/disconnection) of the epileptogenic zone (EZ) while preserving the eloquent brain areas. The development of a reliable and noninvasive localization method that provides clinically useful information for the localization of the EZ is, therefore, crucial to achieving successful surgical outcomes. Electric and magnetic source imaging (ESI and MSI) have been increasingly utilized in the presurgical evaluation of these patients showing promising findings in the delineation of epileptogenic as well as eloquent brain areas. Moreover, the combination of ESI and MSI into a single solution, namely electromagnetic source imaging (EMSI), performed on simultaneous high-density electroencephalography (HD-EEG) and magnetoencephalography (MEG) recordings has shown higher source localization accuracy than either modality alone. Despite these encouraging findings, such techniques are performed in only a few tertiary epilepsy centers, are rarely recorded simultaneously, and are underutilized in pediatric cohorts. This study illustrates the experimental setup for recording simultaneous MEG and HD-EEG data as well as the methodological framework for analyzing these data aiming to localize the irritative zone, the seizure onset zone, and eloquent brain areas in children with DRE. More specifically, the experimental setups are presented for (i) recording and localizing interictal and ictal epileptiform activity during sleep and (ii) recording visual-, motor-, auditory-, and somatosensory-evoked responses and mapping relevant eloquent brain areas (i.e., visual, motor, auditory, and somatosensory) during visuomotor task, as well as auditory and somatosensory stimulations. Detailed steps of the data analysis pipeline are further presented for performing EMSI as well as individual ESI and MSI using equivalent current dipole (ECD) and dynamic statistical parametric mapping (dSPM).

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Magnetoencephalography (MEG) and high-density electroencephalography (HD-EEG) are rarely recorded simultaneously, although they yield confirmatory and complementary information. Here, we illustrate the experimental setup for recording simultaneous MEG and HD-EEG and the methodology for analyzing these data aiming to localize epileptogenic and eloquent brain areas in children with drug-resistant epilepsy.

For children with drug-resistant epilepsy (DRE), seizure freedom relies on the delineation and resection (or ablation/disconnection) of the epileptogenic ...

Equipment Setup and Artifact Removal for Simultaneous Electroencephalogram and Functional Magnetic Resonance Imaging for Clinical Review in Epilepsy

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