This work is supported by the Research Grants Program of the Epilepsy Foundation &amp; American Epilepsy Society and the Faculty Career Development Fellowship of Harvard Medical School, Office for Faculty Development.

The authors have nothing to disclose.

Converging evidence from animal and human studies has shown that HFOs are a new potential biomarker for epileptogenic tissue. Despite this evidence, HFOs have very limited use in clinical practice for the diagnosis or monitoring of epilepsy, mostly because: (i) there is no formal and global definition for HFOs; (ii) different research groups use different methodology for recording and analyzing the data; (iii) the noninvasive detection of HFOs with neuroimaging techniques is challenging; and (iv) the review process of HFOs is time-consuming and impractical, especially for multichannel EEG or MEG recordings with a high number of sensors. In an effort to provide a global standardized methodology that promotes the systematic use of HFOs in clinical practice, the methodology that is followed at Boston Children&#39;s Hospital for the noninvasive recording, detection, and localization of interictal HFOs from pediatric patients with epilepsy is presented. Representative results of HFOs detected with simultaneous scalp EEG and MEG from two children with medically refractory epilepsy are also presented.
Critical steps within the protocol
The proposed methodology includes the following critical steps: (i) the performance of high Signal-to-Noise-Ratio (SNR) EEG and MEG simultaneous recordings of interictal activity from pediatric patients with medically refractory epilepsy (steps 2.1.1 and 2.1.2); (ii) the careful preprocessing and selection of data with interictal discharges (steps 3.1 and 3.2); (iii) the visual review of the identified HFOs events with high specificity (steps 4.3.1, 4.3.2, and 4.3.3); and (iv) the reliable localization of the HFOs using an appropriate localization method (step 5.2).
The most critical step in this protocol is the visual review of the HFO events identified by the automatic detector. A rigorous review of the automatically detected HFOs is crucial to discard HFOs of noncerebral origin. However, fatigue or distraction of the human reviewer during the visual inspection of multichannel EEG and MEG data may lead to errors, reducing the specificity of the detection process.
Modifications and troubleshooting
We avoid the use of the Signal Space Projection (SSP) and Signal Space Separation (SSS) methods72,73 in order to ensure that there was no distortion of the HFO activity from their application. These methods are often used by most of the users of the particular MEG vendor to suppress external interferences and to correct for head movements72. Further studies are necessary in order to ensure that the application of these methods do not affect or distort the HFO activity or do not produce spurious effects that may resemble human HFOs. Minor modifications of the minimum threshold of the z-score of the signal envelope (step 4.1.1.3) and the threshold of activation values (step 5.2.6) may be needed to improve the sensitivity of the algorithm in the detection of HFOs and restrict the localization of the HFOs zone in a more focal area.
Limitations of the technique
The described method presents limitations that should be further addressed in future studies. First, it does not consider HFOs occurring only in the MEG or EEG signals, and it does not include the automatic detection of HFOs in the MEG signals, which implies that some actual low SNR MEG HFOs might escape visual inspection74. Furthermore, the sensitivity and specificity of the proposed method to detect the HFOs and its ability to localize them with high accuracy should be validated with simultaneous recordings of scalp EEG, MEG, and iEEG75. Our data have shown that single ECDs indicated an extended irritative zone compared to the focal HFOs zone. However, when the ECDs were averaged, then the dipole location was quite close to the HFO zone for both patients. Our data are indicative of the specificity of the 2 methods showing a possible higher specificity of the HFO zone for epileptogenicity (particularly for patient 2 for whom the HFO zone was overlapping with the SOZ) compared to the irritative zone, although secure conclusions cannot be drawn from such a small cohort of patients. More importantly, the localization of the HFO sources does not directly imply localizing the EZ that is responsible for seizures. Our findings should be validated against the outcome of the epilepsy surgery that we plan to do in a future study. Finally, to record the EEG data, a 70-channel system was used. Yet, in most centers the standard clinical EEG setting is used that records data from 19 electrodes placed according to the 10 - 20 system. More advanced pediatric EEG systems with much higher number of channels (up to 256) are currently available in the market. The use of these systems may further improve the localization accuracy of the HFOs zone detected with scalp EEG.
Significance of the technique with respect to existing/alternative methods
To our best knowledge, this is the first study that reports the noninvasive localization of interictal HFOs with simultaneous EEG and MEG, and also investigates the concordance of the localization results with those from intracranial recordings. The noninvasive recording, detection, and localization of HFOs is challenging. This is because HFOs are very weak signals generated by small brain regions on the order of cubic millimeters16,76 and furthermore hindered by noise and brain background activity. A recent study proposed that HFOs recorded non-invasively with scalp EEG represent the sum of activity of multiple spatially distributed focal and coherent sources60. So far, few studies28,29,37,38,60 managed to show that HFOs can be detected non-invasively using scalp EEG and MEG; even fewer localized this activity by solving the inverse problem37-38.
Here, evidence of interictal HFOs are presented which have been detected with simultaneous scalp EEG and MEG from two pediatric patients with epilepsy. HFOs were localized by using a previously described framework38. The representative data suggest that the noninvasive localization of interictal HFOs is feasible by using source imaging techniques performed on either scalp EEG or MEG recordings, assuming that an appropriate localization technique is used. This is in line with a previous study that used a phantom construction resembling HFOs generators, which indicates that HFOs can be noninvasively detected and accurately localized with MEG32.
The detection and labeling of interictal HFOs is traditionally performed through the visual inspection of data from human EEG experts. Although this approach is often regarded as the gold standard, it presents serious limitations since it has poor inter-reviewer reliability77,78, and is not applicable to large MEG and EEG datasets with high number of sensors. Crucial to the application of HFOs in clinical practice is the development of algorithms that detect the HFOs automatically from scalp recordings reducing the need for human input. The visual identification of scalp HFOs is in fact quite challenging due to: (i) the low SNR of HFOs on the scalp; (ii) the lower rates of HFOs in scalp recordings compared to intracranial ones, which implies the analysis of much longer recording times; and (iii) the high number of channels to analyze, particularly in high-density EEG or MEG. Several algorithms for automatic and semi-automatic detection of HFOs have been proposed in the last decade54. Earlier detectors relied on thresholds in the time domain, in order to identify events that can be distinguished from ongoing background activity49,80. Recent advances suggest also incorporating information from the frequency domain, assuming that an HFO must appear as a short-lived event with an isolated spectral peak at a distinct frequency50,56,81. Semi-automated methods seem to be the most appropriate approach for the application of HFOs in clinical practice. These methods involve 2 stages: (i) initial automatic detection of events that has high sensitivity, and (ii) visual review of events by an expert, which has high specificity. This approach provides higher specificity compared to the fully automated methods and ensures that the final reviewed events are actual HFOs of cerebral origin.
Here, a semi-automated method is presented that enables the detection of HFOs from interictal scalp EEG and MEG recordings. The proposed method extends previously described techniques for the detection of HFOs from scalp EEG60 by incorporating in the identification criteria two important features: (i) the automatic time-frequency analysis of the HFO events; and (ii) the temporal concurrence of HFOs events in both MEG and EEG recordings.
Future applications or directions after mastering this technique
The reliable localization of HFOs with non-invasive neuroimaging methods, such as scalp EEG and MEG, is critical. Mastering, improving, and validating the proposed protocol will provide physicians with a reliable, noninvasively recordable biomarker for the identification of the EZ. The development of such a biomarker has the potential to reduce the requirement for long-term monitoring and invasive intracranial recordings leading to a significant improvement in the presurgical evaluation procedure in pediatric patients. It would not only help to identify the epileptogenic tissue for surgery, but would also permit definitive differential diagnosis of epilepsy from acute symptomatic seizures, requiring an entirely different treatment approach, and from non-epileptic seizures sparing the need for long-term monitoring in some patients. Further, this might allow assessment of efficacy of therapeutic interventions without waiting for another seizure to occur.

Pediatric epilepsy is a common neurological disorder with a prevalence rate of 4 - 6 per 1,000 children1. It can have a major impact on children&#39;s development2 and may significantly affect their adult life. Long-term follow-up studies in childhood-onset epilepsy indicate that approximately 30% of patients with epilepsy become medically intractable3-6, and usually require resective epileptic surgery. In many of these patients, epilepsy surgery leads to significant reduction in seizure frequency and often to seizure freedom. To be successful, epilepsy surgery should achieve a seizure-free state with minimal or no functional deficits. This requires careful delineation of the Epileptogenic Zone (EZ)7, the &#39;area of cortex that is indispensable for the generation of epileptic seizures&#39;8. The EZ cannot be measured directly; its location is estimated based on concordant data from a multitude of tests that identify other cortical zones. Invasive intracranial electroencephalography (iEEG) serves as the gold standard for the localization of the seizure onset zone (SOZ), the region where seizures are generated and originate on ictal recordings. However iEEG is costly, reliant on cooperation of the child, carries some risk for infection and bleeding9, and may induce additional neurological damage during the implantation10. Furthermore, the recordings may lead to erroneous conclusions since large areas of the brain are left unexplored. Thus, a robust presurgical biomarker that helps in the identification of the EZ is needed to the success of surgical epilepsy treatment.
Pathological HFOs&#160;(80 - 500 Hz)11,12 have emerged over the last decade as a biomarker for the identification of the epileptogenic tissue that may improve the presurgical diagnosis and surgical outcome of patients with epilepsy13. Reports using microelectrodes combined with depth EEG&#160;electrodes showed the presence of HFOs in patients with epilepsy. HFOs were also found using standard macroelectrodes during the ictal and interictal periods. Recent studies have shown that HFOs identify the SOZ with higher sensitivity and specificity compared to the irritative zone14,15, the zone that generates the IEDs, and that the surgical removal of the HFO-generating tissue correlates with better outcomes than the removal of the SOZ or the irritative zone15. HFOs are commonly categorized as ripples (80 - 250 Hz) or fast ripples (250 - 500 Hz). Fast ripples have been more closely linked to pathological activity and to the localization of the SOZ16, but investigations of human intracranial recordings indicate that both ripples and fast ripples increase in epileptogenic regions17.
Despite these promising findings, HFOs are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: (i) the lack of a formal and global definition for HFOs; (ii) the consequent heterogeneity of the methodological approaches used for their study; and (iii) the practical difficulties to detect and localize them noninvasively from scalp recordings. The latter stems from the fact that electrodes are far away from the source of the signal, the signal might be blurred by background noise and muscle activity, and the signal might be distorted by the scalp or the fontanels and sutures in the skull, especially in infant patients. Moreover, it is difficult to distinguish between normal and abnormal HFOs18,19 since both ripples and fast ripples are present even in normal human brain tissue20. Early studies reported HFOs in scalp EEG in only a small (0.2&#160;- 3.4%) portion of patients with epilepsy21-23. However, recent studies have shown that HFOs can be detected noninvasively with scalp EEG. Ictally, HFOs have been reported at the onset of epileptic spasms in children (50 - 100 Hz24, 40 - 120 Hz25), as well as at the onset of tonic seizures in Lennox-Gastaut syndrome (50 - 100 Hz)26. Interictal HFOs (70 - 200 Hz) were first observed on scalp EEG in children with sleep-induced electrical status epilepticus27. Then, interictal HFOs (80 - 200 Hz) were identified in the scalp EEG of patients with focal epilepsy with higher rates inside the SOZ28. Interestingly, HFOs were more frequent in patients with high numbers of interictal epileptiform discharges (IEDs), and they were found to be more specific than IEDs for the SOZ29, highlighting the relation of HFOs with epileptogenicity.
MEG&#160;seems to present significant advantages compared to scalp EEG for the noninvasive detection and localization of HFOs: (i) high frequency activity in MEG is less susceptible than EEG to contamination from muscular activity30-31, (ii) MEG signals are not distorted by skull conductivity and less distorted than EEG by unfused regions of the cranial bone such as fontanel or suture, and (iii) MEG sensor arrays have higher density compared to EEG that always faces the problem of salt bridges between electrodes when the head is small, as with children. Evidence from phantom constructions that simulate HFOs generators suggested that HFOs can be detected and localized with high localization accuracy (2 - 3 mm) with MEG32. Several recent studies reported HFOs in the MEG signals recorded from patients with epilepsy in the ripple frequency band33-38. Time-frequency analysis has shown that MEG data contain high frequency components related to the EZ33-36. However, only a few studies have identified interictal HFOs as visible events standing out of the background signal in the time domain, as typically done with iEEG37-38. Van Klink et al.37 detected HFOs in the ripple band using virtual channels constructed with beamforming techniques based on spatial information obtained from IEDs. Von Ellenrieder et al.38 detected HFOs in MEG signals from the physical sensors independently of the IEDs and used the Maximum Entropy on the Mean (MEM) method to localize their sources and to investigate their correlation with the EZ. Rampp et al. (2010) also detected epileptic high gamma oscillations with MEG, which were spike-locked or spike-independent, and localized this activity with minimum-norm source analysis39. They found that characteristics of these fast oscillations (i.e., clear onset of full-band average and maximum amplitude of oscillations) were highly associated with the SOZ. HFOs were also detected with MEG during ictal activity in pediatric patients with epileptic spasms40. However, MEG presents some distinct limitations compared to scalp EEG: (i) it is insensitive to sources that have a radial orientation with respect to the center of the head, (ii) it does not allow long recordings that increase the possibility to detect and record ictal events, and (iii) its sensors cannot conform to the shape of head of each individual since the helmet and sensor array within the helmet are all fixed in shape. Thus, the ideal setup that maximizes the possibility to detect and localize the epileptogenic activity is by combining information from both scalp EEG and MEG.
In this study, we aim to illustrate the methodology we follow for the noninvasive detection of interictal HFOs by using simultaneous recordings of scalp EEG and MEG from pediatric patients with medically refractory epilepsy. We present the setup of the recordings and the pipeline of data analysis using a semi-automated method that we have developed for the detection of HFO events in simultaneous MEG and EEG data. Finally, we also present the localization of the underlying generators of scalp HFOs, obtained by solving the inverse problem, and compare it with the SOZ as this was defined by the epileptologists.

<table><tbody><tr><td>VectorView MEG system</td><td>Elekta-Neuromag, Finland</td><td></td><td>MEG System</td></tr><tr><td>Magentically Shielded Room</td><td>Imedco, Hagendorf, Switzerland</td><td></td><td>Three-layer MSR</td></tr><tr><td>EEG system</td><td>Elekta-Neuromag, Finland</td><td></td><td>70 Channel EEG system</td></tr><tr><td>3D digitizer</td><td>Polhemus, Colchester, VT</td><td></td><td></td></tr></tbody></table>

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.

Pediatric patients with refractory epilepsy were recruited from the Epilepsy Clinic of Boston Children&#39;s Hospital (Boston, USA). Here, representative data from 2 patients are presented: a 15-year-old girl with encephalomalacia of the right middle cerebral artery (MCA) region (patient 1), and an 11-year-old boy with left parietal/superior temporal encephalomalacia (patient 2). The data were collected as part of their presurgical workup for surgery. Simultaneous MEG and EEG recordings were performed at the Athinoula A. Martinos Center for Biomedical Imaging.
For both patients, HFOs were identified in the ripple frequency band (80 - 150 Hz) occurring in both EEG and MEG and overlying IEDs. Figure 4 presents 10 s of simultaneous scalp EEG and MEG data with interictal activity (upper panels) from patient 1. The same figure also reports an extended time scale portion (2 s) of the signals, which shows the detected HFOs in the time domain (middle panels) and in the time-frequency plane (lower panel). This patient showed a rate of 8.8 HFOs/min. For clarity, the display of the time-frequency plane is restricted from 80 - 150 Hz because no prominent activity was observed for frequencies above 150 Hz. In patient 1, the automatic detection identified 248 HFOs events within 8.65 min of recordings. After visual review of the detected events, 76 events were kept that were considered to be real HFOs, obtaining a rate of 8.8 HFOs/min.
<img alt="Figure 4" src="/files/ftp_upload/54883/54883fig4.jpg" /> 
Figure 4: HFOs Overlaid on IEDs Detected from Scalp EEG and MEG. Upper panel: IEDs from patient 1 detected from scalp EEG (left) and MEG (right). 10 s of data filtered from 1 - 70 Hz. Middle panel: Extended time scale display (2 s) of the EEG and MEG data highlighted with grey background in the upper panel. Data are filtered from 80 - 150 Hz. Lower panel: Time-frequency plane of 2 representative EEG and MEG channels. <a href="http://cloudflare.jove.com/files/ftp_upload/54883/54883fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Figure 5 presents the HFOs localization results for patient 1 from both scalp EEG and MEG. Both techniques localized the HFOs at the vicinity of the lesion in a location close to the right temporo-parietal junction. MEG and EEG presented slightly different localization results: MEG activity was located more anteriorly compared to EEG and closer to the posterior boundary of the lesion. The distance between the two maxima of wMEM activity for the MEG and EEG was 15.0 mm. HFOs localization was also adjacent to the irritative zone as this was defined by MEG. The Euclidian distance between the averaged ECDs and the maximum wMEM activity was 18.7 mm for the MEG and 28.0 mm for the scalp EEG. For patient 2, we identified 8 min of data during slow-wave non-REM sleep with IED and minimal artifacts that we used for the HFO analysis.
The number of scalp HFOs was significantly lower than in patient 1 showing a rate of 0.4 HFOs/min. Figure 6 presents the source localization results of scalp HFOs for MEG and scalp EEG, the IEDs localized by MEG using ECDs, and the location of HFOs detected by iEEG. The distance between the 2 maxima of wMEM activity for the MEG and EEG was 16.4 mm. The distance between the averaged ECDs and the maximum wMEM activity was 10.9 mm for the MEG and 24.1 mm for the EEG. The HFO zone identified noninvasively by scalp EEG and MEG was at the same location where the HFOs were identified invasively with iEEG. The electrodes with the highest number of HFOs were LA51, LA52, and LA53, as shown in Figure 6, whose localization was concordant with the HFO activity localized noninvasively.
<img alt="Figure 5" src="/files/ftp_upload/54883/54883fig5.jpg" /> 
Figure 5: Localization of HFOs and IEDs. HFOs zone localized by using the wMEM with MEG and EEG from patient 1 overlaid on patient&#39;s MRI (left). The HFOs map represents the average of the normalized activation values thresholded at 60% of the maximum activity. IEDs localized by ECDs with MEG (right). The locations and orientations of the ECDs are indicated in cyan. The purple triangle indicates the location of the averaged ECDs (46 ECDs), and the red rectangle the location of the ECD from averaged IEDs (28 IEDs). For the averaging of the IEDs, we identified spikes with similar morphology. <a href="http://cloudflare.jove.com/files/ftp_upload/54883/54883fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/54883/54883fig6.jpg" /> 
Figure 6: Spatial Concordance between the HFO Zone Localized Noninvasively with Scalp EEG and MEG, the Irritative Zone, and the HFO Zone Localized Invasively with iEEG. Upper panels: Localization of HFOs from patient 2 with scalp EEG (left) and MEG (middle), and localization of IEDs with MEG (right) overlaid on patient&#39;s MRI. The HFOs map represents the average of the normalized activation values thresholded at 60% of the maximum activity. Cyan circles and bars indicate the locations and orientations of the ECDs. The purple triangle indicates the location of the averaged ECDs (30 ECDs), and the red rectangle the location of the ECD from averaged IEDs (21 IEDs). Lower panels: Localization of HFOs on iEEG (left) and 2 s&#160;of recordings from channels with the highest HFO rate. Implanted electrodes are shown on the patient&#39;s MRI. The electrode location is obtained by co-registering the post-implanted computed tomography (CT) and MR images. The electrodes with the highest rate of HFOs are highlighted on the map of the grid implanted on the patient&#39;s cortex. <a href="http://cloudflare.jove.com/files/ftp_upload/54883/54883fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The representative results presented here indicate the potential use of the described technique in the clinical setting for the noninvasive identification and localization of HFOs during the pre-surgical evaluation of pediatric patients with medically refractory epilepsy. For both patients, HFOs were localized concordant for scalp EEG and MEG (see Figure 5). Localization differences of few mm may be attributed to the superior localization ability of high-density MEG compared to scalp EEG70, or may represent different underlying generators71. The localization was also concordant with the irritative zone as this was defined by MEG (see Figure 5 - right panel). In patient 2, data from iEEG were also available. The HFOs zone localized noninvasively with scalp EEG and MEG was concordant with the HFOs zone defined invasively with iEEG (see Figure 6). The outcomes of the proposed method can guide the placement of grids during epilepsy surgery for the potential identification of the EZ.

Watch this Scientific Journal Video about Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy at JoVE

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

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20.2K Views.  Boston Children's Hospital, Harvard Medical School.  High Frequency Trillingen (HFO) naar voren zijn gekomen als prechirurgische biomarkers voor de identificatie van de epileptogene zone bij pediatrische patiënten met medisch refractaire epilepsie. Een methodologie voor de niet-invasieve opname, detectie en lokalisatie van HFO met gelijktijdige hoofdhuid elektro-encefalogram (EEG) en magneto (MEG) wordt gepresenteerd. 

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

Surgical Management of Meatal Stenosis with Meatoplasty

Meatal stenosis is a common urologic complication after circumcision. Children present to their primary care physicians with complaints of deviated urinary stream, difficult-to-aim, painful urination, and urinary frequency. Clinical exam reveals a pinpoint meatus and if the child is asked to urinate, he will usually have an upward, thin, occasionally forceful urinary stream with incomplete bladder emptying. The mainstay of management is meatoplasty (reconstruction of the distal urethra /meatus). This educational video will demonstrate how this is performed.

Meatoplasty, surgical management of meatal stenosis.

Meatal stenosis is a common urologic complication after circumcision.  Children present to their primary care physicians with complaints of deviated ...

Infant Auditory Processing and Event-related Brain Oscillations

Rapid auditory processing and acoustic change detection abilities play a critical role in allowing human infants to efficiently process the fine spectral and temporal changes that are characteristic of human language. These abilities lay the foundation for effective language acquisition; allowing infants to hone in on the sounds of their native language. Invasive procedures in animals and scalp-recorded potentials from human adults suggest that simultaneous, rhythmic activity (oscillations) between and within brain regions are fundamental to sensory development; determining the resolution with which incoming stimuli are parsed. At this time, little is known about oscillatory dynamics in human infant development. However, animal neurophysiology and adult EEG data provide the basis for a strong hypothesis that rapid auditory processing in infants is mediated by oscillatory synchrony in discrete frequency bands. In order to investigate this, 128-channel, high-density EEG responses of 4-month old infants to frequency change in tone pairs, presented in two rate conditions (Rapid: 70 msec ISI and Control: 300 msec ISI) were examined. To determine the frequency band and magnitude of activity, auditory evoked response averages were first co-registered with age-appropriate brain templates. Next, the principal components of the response were identified and localized using a two-dipole model of brain activity. Single-trial analysis of oscillatory power showed a robust index of frequency change processing in bursts of Theta band (3 - 8 Hz) activity in both right and left auditory cortices, with left activation more prominent in the Rapid condition. These methods have produced data that are not only some of the first reported evoked oscillations analyses in infants, but are also, importantly, the product of a well-established method of recording and analyzing clean, meticulously collected, infant EEG and ERPs. In this article, we describe our method for infant EEG net application, recording, dynamic brain response analysis, and representative results.

High-density electroencephalography (dEEG) is being used increasingly to study brain development and plasticity in the early years of life. Here we present an application of sophisticated analysis techniques that builds on traditional EEG recording to understand the oscillatory dynamics of rapid auditory processing in the infant brain.

Rapid auditory processing and acoustic change detection abilities play a critical role in allowing human infants to efficiently process the fine spectral ...

Behavior

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.

Here, we present a protocol to record brain and heart bio signals in mice using simultaneous video, electroencephalography (EEG), and electrocardiography (ECG). We also describe methods to analyze the resulting EEG-ECG recordings for seizures, EEG spectral power, cardiac function, and heart rate variability.

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can ...

Genetics

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 ...

Studying Brain Function in Children Using Magnetoencephalography

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the human brain. MEG is quiet and less likely to induce claustrophobia compared with magnetic resonance imaging (MRI). It is therefore a promising tool for investigating brain function in young children. However, analysis of MEG data from pediatric populations is often complicated by head movement artefacts which arise as a consequence of the requirement for a spatially-fixed sensor array that is not affixed to the child's head. Minimizing head movements during MEG sessions can be particularly challenging as young children are often unable to remain still during experimental tasks. The protocol presented here aims to reduce head movement artefacts during pediatric MEG scanning. Prior to visiting the MEG laboratory, families are provided with resources that explain the MEG system and the experimental procedures in simple, accessible language. An MEG familiarization session is conducted during which children are acquainted with both the researchers and the MEG procedures. They are then trained to keep their head still whilst lying inside an MEG simulator. To help children feel at ease in the novel MEG environment, all of the procedures are explained through the narrative of a space mission. To minimize head movement due to restlessness, children are trained and assessed using fun and engaging experimental paradigms. In addition, children's residual head movement artefacts are compensated for during the data acquisition session using a real-time head movement tracking system. Implementing these child-friendly procedures is important for improving data quality, minimizing participant attrition rates in longitudinal studies, and ensuring that families have a positive research experience.

This article introduces a child-friendly research protocol designed to improve data quality by reducing head movement during pediatric magnetoencephalography (MEG). We familiarize families with the MEG environment, train children to remain still using an MEG simulator, and correct for residual head movement artefacts using a real-time head movement detection system.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the ...

Neuroscience

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.

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 ...

Bioengineering

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 ...

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 ...

Consistent Induction and Recording of Seizure-Like Activity Using CMOS-HD-MEAs

High-Quality Seizure-Like Activity from Acute Brain Slices Using a Complementary Metal-Oxide-Semiconductor High-Density Microelectrode Array System

Complementary metal-oxide-semiconductor high-density microelectrode array (CMOS-HD-MEA) systems can record neurophysiological activity from cell cultures and ex vivo brain slices in unprecedented electrophysiological detail. CMOS-HD-MEAs were first optimized to record high-quality neuronal unit activity from cell cultures but have also been shown to produce quality data from acute retinal and cerebellar slices. Researchers have recently used CMOS-HD-MEAs to record local field potentials (LFPs) from acute, cortical rodent brain slices. One LFP of interest is seizure-like activity. While many users have produced brief, spontaneous epileptiform discharges using CMOS-HD-MEAs, few users reliably produce quality seizure-like activity. Many factors may contribute to this difficulty, including electrical noise, the inconsistent nature of producing seizure-like activity when using submerged recording chambers, and the limitation that 2D CMOS-MEA chips only record from the surface of the brain slice. The techniques detailed in this protocol should enable users to consistently induce and record high-quality seizure-like activity from acute brain slices with a CMOS-HD-MEA system. In addition, this protocol outlines the proper treatment of CMOS-HD-MEA chips, the management of solutions and brain slices during experimentation, and equipment maintenance.

Author Spotlight: Unraveling Seizure Dynamics and Novel Therapeutics for Status Epilepticus Using CMOS High-Density Microelectrode Array Systems

Here, we outline a protocol for using complementary metal-oxide-semiconductor high-density microelectrode array systems (CMOS-HD-MEAs)&#160;to record seizure-like activity from ex vivo brain slices.

Complementary metal-oxide-semiconductor high-density microelectrode array (CMOS-HD-MEA) systems can record neurophysiological activity from cell cultures ...

 Simultaneous Electroencephalography and Magnetoencephalography to Identify Seizure-Prone Brain Regions 

Source:&#160;<a style='text-decoration:none;' href='https://app.jove.com/v/54883/interictal-high-frequency-oscillations-detected-with-simultaneous'><span style='-webkit-text-decoration-skip:none;font-family:Arial,sans-serif;font-size:12pt;font-style:normal;font-variant:normal;font-weight:400;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre-wrap;'>Papadelis, C.,&#160;et al.,<span style='-webkit-text-decoration-skip:none;font-family:Arial,sans-serif;font-size:12pt;font-style:normal;font-variant:normal;font-weight:400;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre-wrap;'> Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy.&#160;J. Vis. Exp.<span style='-webkit-text-decoration-skip:none;font-family:Arial,sans-serif;font-size:12pt;font-style:normal;font-variant:normal;font-weight:400;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre-wrap;'> (2016).</a> &#160;This video demonstrates the method of using electroencephalography (EEG) and magnetoencephalography (MEG) recordings to identify interictal epileptiform discharges (IEDs) and high-frequency oscillations (HFOs) to locate seizure-prone regions in the brain.

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

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