This work was funded by grants from Instituto de Salud Carlos III, through PI10/00160 and PI12/02839, partially supported by F.E.D.E.R and from Mutua Madrile&#241;a. A.S-G. is the recipient of a postdoctoral fellowship from Mutua Madrile&#241;a. 3D simulation were created using BioDigital Human software (<a href="http://www.biodigital.com">www.biodigital.com</a>) and ZygoteBody Professional software (www.zygotebody.com)

In the protocol described below, steps 1, 2 and 3 belong to both the research and clinical protocols, which are both strictly followed from every mesial TLE candidate for resection surgery selected only by clinical criteria. Steps 4 and 5 belong exclusively to the research protocol. Both procedures are in accordance with the guidelines of the Ethical Committee of the Hospital de la Princesa.
1. Pre-implantation Procedures
<ol>
	<li>Explain the experimental procedures to the participant, specifying which points correspond to the research and which ones are applicable to clinical practice, remarking that the research procedure is in no way modifying the clinical procedure. Pay special attention to explaining the potential risks of the surgical implantation of electrodes. Obtain a signed informed consent form the participant.</li>
	<li>For all candidates for resection surgery, perform presurgical neurological and neuropsychological examinations18.
	<ol>
		<li>Evaluate the patient by interictal single photon emission computer tomography (SPECT) with 99Tc-HmPAO, magnetic resonance imaging (MRI) 1.5 T and video-electroencephalography (v-EEG) using 25 scalp electrodes according to the 10 - 20 international system and Maudsley&#39;s protocol18.</li>
		<li>During the presurgical v-EEG recording stay, progressively taper the antiepileptic drugs from the second day to the fourth day (approximately one-third of the dose per day).</li>
	</ol>
	</li>
</ol>
2. Implantation Procedures (Surgery)
<ol>
	<li>Administer antiepileptic drugs pre-operatively, and perform surgery under general anesthesia (3 mg/kg propofol bolus, followed by 0.2 - 0.3 mg/kg fentanyl and 0.5 mg/kg rocuronium).</li>
	<li>Insert two six-contact FOEs with a 1-cm center-to-center distance bilaterally into the ambient cisterns using Kirschner&#39;s technique19.
	<ol>
		<li>Place the patient on the operating table in the supine position, with the neck gently extended at 15 degrees. Prepare the patient&#39;s cheek with an iodine solution, starting at the incision site and circling outward, and drape the area immediately surrounding the incision site.</li>
		<li>Puncture the skin with a 20-gauge spinal needle according to Hartel&#39;s landmarks20: an entry point approximately 3 cm lateral to the ipsilateral side of the oral commissure toward a point immediately inferior to the ipsilateral pupil in the anterior-posterior plane and a point approximately 2.5 cm anterior to the external auditory meatus in the lateral plane.</li>
		<li>Advance the needle toward the region of the foramen ovale under fluoroscopic guidance. Use the lateral views provided by the fluoroscopy images to determine the position of the needle tip. When the needle passes the foramen ovale, remove the stylet, replace it with an electrode, and advance it into the ambient cistern (Figure 1A).</li>
	</ol>
	</li>
	<li>Assess correct implantation by fluoroscopic imaging in the operating room21; this is important to exclude penetration into the foramina of the skull base, such as the inferior orbital fissure (located anterior to the foramen ovale) and the jugular foramen (located posterior to it). Such misplaced cannulation could potentially lead to serious neurovascular injury22.</li>
	<li>Once the electrodes are correctly positioned in the ambient cisterns, secure them to the skin with drapes. Wake up the patient, and lead him or her to the recovery room.</li>
</ol>
3. Acquisition of FOE Recordings
<ol>
	<li>Return the patient to the v-EEG room for a stay of approximately 5.2 &#177; 2.4 days (mean &#177; SD).</li>
	<li>Place 19 electrodes according to the international 10-20 system.
	<ol>
		<li>Measure the distance between the nasion (bridge of the nose) and the inion (occipital protuberance) using a measuring tape, and mark with a marker the middle point (location of the Cz electrode). Measure and mark the point 10% of the distance above the nasion (location of the Fpz electrode).
		<ol>
			<li>Repeat the same procedure for the inion (location of the Oz electrode), marking the distances 20% from the Cz in both the nasion and inion directions (locations of the Fz and PZ electrodes, respectively).</li>
		</ol>
		</li>
		<li>Measure the distances between both preauricular points, and mark the distances 10% above the left and right preauricular points (T3 and T4 electrodes, respectively). Then, mark the distances 20% above both T3 and T4 in the Cz direction to obtain the locations of C3 and C4.</li>
		<li>Create a circumference using the measuring tape to link the Fpz and Oz at 5% of the distances above both electrodes at FP1 (left) and FP2 (right) in the front and at O1 (left) and O2 (right) in the back.</li>
		<li>In the same circumference, add 10% of the distance upward in the inion direction to obtain the position of F7, add 10% to reach T3 (it should be located above the line between the preauricular points), and add another 10% to obtain T5 (O1 electrode). Mark each electrode position and repeat the same procedure for the right (even) electrodes.</li>
		<li>Measure and mark the intersection (F3 electrode location) halfway between F7 and Fz and 20% of the distance upward from Fp1 in the F3 direction. Repeat this process in each quadrant of the head to obtain F4 (front-right position), P3 (back-left position) and P4 (back-left position).</li>
		<li>Clean and dry the skin. Place a moderate quantity of collodion with conductive gel in each electrode cup, and position the electrodes in the prepped areas. Dry the collodion with a hair dryer.</li>
	</ol>
	</li>
	<li>Connect all of the electrodes (scalp and FOEs) by wires to the electrode box, which is already connected to an electroencephalographer. Ensure that the electrode signals are good, and verify that the scalp electrodes impedances are under 10 k&#937; using the electroencephalographer.</li>
	<li>Acquire digital scalp electroencephalogram (EEG) data and FOE data at 1,024 Hz using a video synchronized electroencephalographer (v-EEG), and filter the data using a band-pass filter in the range 0.5 - 100 Hz and a Notch filter (50 Hz) with the electroencephalographer.</li>
	<li>Progressively remove the antiepileptic drugs from the second to the fourth day (approximately one-third of the dose per day) to increase the likelihood of seizures. This step depends on the particular drug prescription of each patient.</li>
	<li>Use both interictal paroxysmal and ictal activities to approximately locate the ictogenic areas by identifying the electrodes/channel where epileptogenic elements appear23, including the slow-wave complex, polyspikes, runs of rapid spikes, sharp waves, sharp-and-slow-wave complex, slow sharp waves, spikes and spike and slow waves. Record the times of seizure onset and end, as well as any other clinical signs or occurrences relevant to the study. There is a one-to-one mapping between the electrodes location in the patient&#39;s head and the head model in the EEG software which allows identifying anatomically where the epileptogenic activity appears.</li>
	<li>When the study is finished, remove the FOEs at the v-EEG unit by gently pulling them out while the patient&#39;s mouth remains half-opened. Do not systematically perform imaging after FOE removal, except when neurological symptoms appear. In such cases, perform an urgent computed tomography (CT) scan.</li>
</ol>
4. FOE Signal Preprocessing
<ol>
	<li>Export the data stored on the electroencephalographer at 200 Hz in ASCII format in epochs suitable for numerical analysis of approximately 30 min of seizure activity (already identified by an expert neurophysiologist) (Figure 1C). Avoid epochs containing artifacts, such as saturated electrical activity, muscle activity, and electrode displacements.</li>
	<li>Open the exported files using any UNIX stream editor, and remove all non-numerical characters from the exported data files, leaving only time stamps and channel voltages. Save the modified files for further numerical analysis. 
	NOTE: From now on, perform all calculations using R packages from the R repository or homemade codes (Table 1).</li>
	<li>Using R software, install the required R packages, and load the modified data files into the R environment. Order all channels, assigning each one to a particular column of the array that contains all of the data, eliminating empty channels and referencing them to an average mid-line reference (Fz + Cz + Pz)/3.
	<ol>
		<li>Use the Fast Fourier Transform algorithm (R function: fft) and plot the resulting variable to check for the effective removal of the line frequency (approximately 50 Hz). Use the frequency domain to filter other spurious frequencies that may contaminate the signals.</li>
	</ol>
	</li>
	<li>Convert the loaded data to a multivariate time-series object (mts) of 28 columns &#8212; 16 scalp and 12 FOEs &#8212; using the R function ts. Divide the mts object into non-overlapping temporal windows of 5 seconds each (1,000 data points at 200 Hz) to reduce the file size and optimize computation time.</li>
</ol>
5. Post-processing Calculations (Complex Network Analysis)
NOTE: Calculate the measures described below in each temporal window, starting at 5 min before seizure onset (60 windows) and ending at 5 minutes after seizure onset (60 windows), with the aim of visualizing the temporal evolution.
<ol>
	<li>Calculate univariate measures, spectral power, excitability and spectral entropy for each individual column/channel without considering the correlations between different time series.
	<ol>
		<li>Calculate excitability (S) for each voltage activity time series using a homemade code according to the equation proposed by Schindler24 (see supplemental file). S &#62; 2.5 is considered epileptogenic, an empirically determined threshold17,25,26.</li>
		<li>For each activity time series, calculate the power spectral density using a homemade code for the Delta (&#62;0.5 Hz and &#60;4 Hz), Theta (4 - 7 Hz), Alpha (7 - 14 Hz), Beta (14 - 30 Hz) and Gamma (&#62;30).</li>
		<li>Calculate Shannon entropy with a homemade code using the power spectral density of each time series instead of the corresponding probability time series. Average the individual spectral entropy (SE) values obtained for each channel over a set of electrodes. Shannon entropy is explained in the supplemental file. 
		NOTE: A decrease in SE should be interpreted as a decrease in the number of frequencies of the spectrum because SE is the entropy of the spectrum.</li>
	</ol>
	</li>
	<li>Network measures 
	NOTE: This section assesses the interactions between different time series of electrodes.
	<ol>
		<li>Calculate the functional connectivity between each pair of voltage time series in each temporal window using the absolute value of the linear cross-correlation coefficient computed at zero lag (R function: ccf). 
		NOTE:To eliminate non-representative values of synchronization, establish a threshold based on previous studies17,25,26. Use a threshold of 0.5 in this particular case.</li>
		<li>Install the igraph R package27. Create an igraph object from the adjacency matrix (R function: graph.adjacency). Use the correlation matrix obtained in the previous step, specifying that the graph is weighted and undirected.</li>
		<li>In each temporal window calculate the average path length (APL) (R function average.path.length) for the entire network (scalp+FOE), and for each of the four sub-networks: left scalp, right scalp, left FOE and right FOE. In exactly the same way, calculate the density of links (DoL) (R function: graph.density), modularity (Mod) (R function: modularity) and the Average clustering coefficient (ACC) (R function: transitivity).</li>
		<li>Repeat the previous steps 5.2.1 through 5.2.3 using phase synchronization (homemade R code) as an estimate of functional connectivity instead of the cross-correlation function.</li>
	</ol>
	</li>
	<li>To represent the size effects in the variable changes, calculate the standardized mean difference (SMD) (R function from package MBESS: smd), between the preictal and the ictal stages as well as between the preictal and postictal stages.
	<ol>
		<li>Taking the preictal as the baseline, select thirty seconds (6 values) five minutes before seizure onset mark, as the preictal value. A similar temporal window of 30 s can be chosen during the seizure in order to quantify the change, respect to the preictal stage, by using the SMD.</li>
		<li>In a similar fashion, 5 min after seizure ends, select a temporal window of 30 s in order to quantify the change during the postictal stage (in respect to the preictal stage).</li>
	</ol>
	</li>
</ol>

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G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Utility+of+foramen+ovale+electrodes+in+temporal+lobe+epilepsy+surgery.">Utility of foramen ovale electrodes in temporal lobe epilepsy surgery.</a> Recent Advances in Epilepsy. , 1-8 (2008).</li></ol>

The authors have no conflicts of interest to disclose.

Traditionally, epilepsy was studied under a zone-oriented approach, which isolated the importance of particular areas, essentially the seizure onset zone, as the unique cause of seizures. Very recently, a true network approach that emphasizes the importance of interactions between cortical areas has been favored over the classical zone-oriented perspective13-17,28. However, the current body of evidence for epilepsy as a network disease is still highly fragmented, and more research is needed. The present work aims to reanalyze data provided by traditional methods as the FOE, under the complex network approach. The protocol presented here describes a step by step methodological procedure to perform a complex network and spectral analysis of semi-invasive recordings in TLE patients.
The application of the technique described above has demonstrated the usefulness of the network approach as compared with the more traditional localized or zone-oriented perspectives. In recent works17,29 it was shown that, using the very same procedure as the one described here, an imbalance in the mesial connectivity in refractory TLE patients is apparent. Mesial connectivity is reduced in the ipsilateral side both during the interictal29 and ictal17,29 stages. This result could not be anticipated by looking solely at the areas where the epileptogenic activity arises. This somehow surprising result was also described by using network theories on fMRI signals30,31. Moreover, the application of the combined technique of FOE+network theory has shown the equivalence of mesial activity during seizures and under the effects of a promoter of epileptogenic activity, as it is the pharmacological administration of etomidate32.
The technique described here is capable of detecting mesial network imbalance in short interictal recordings lasting at most one or two hours29. In this way, a drastic reduction in the analysis time and patient hospital stay could be achieved. In addition, from a therapeutic perspective, the existing imbalance in TLE patients could be &#34;resolved&#34; by using chronically implanted (by neurosurgeons) devices, as much as the way it is done in deep brain stimulation.
To obtain optimal results using the information provided in this protocol, some issues should be considered in advance. First, the implantation of the electrodes should be performed by an experienced neurosurgeon because their incorrect placement could produce severe neurological consequences and misleading recordings. Furthermore, the selection of appropriate epochs for further analysis relies entirely on the neurophysiologist&#39;s interpretation of the raw EEG; therefore, experience in clinical EEG analysis is mandatory. The data format of the exported files from the electroencephalograph depends on the particular brand; consequently, good programming skills are needed to adapt the scripts to different data formats. Finally, to ensure the reliability of the data, quality controls should be applied to the results. Overestimation and false positives are likely to appear when working with a high number of correlations. In such cases, statistical methods to improve sensitivity should be used. In this regard, it is important to establish a threshold in the correlations to discard values that are not representative of a true underlying synchronization. Thus, in this protocol, an edge between nodes i and j will be only considered to exist if the absolute value of the correlation between these nodes is greater than 0.5, a criterion previously employed17,26. Other thresholds in the range of 0.2 to 0.8 should be employed to verify similar results and to ensure a smooth transition from one threshold to the following threshold. In addition to thresholds, other methodologies may be used to obtain reliable results, such as Bonferroni correction or surrogate data testing. Moreover, when working with EEG data, it is important to keep in mind that brain networks are complex systems with non-linear dynamics; therefore, in addition to the linear correlation, other non-linear synchronization measures should be used to ensure the quality of the results, such as mutual information or phase synchronization33.
Calculating connectivity directly from scalp electrodes, as it is partially done in this work, entails some risks. The main problem rest in the contamination effect due to volume conduction, always present with scalp recording. One way to overcome this issue is by working on the sources space, an appealing alternative employed by many researches. Another approach demands the use of measures of synchronization which minimizes the contamination of amplitude effects. By using the phase synchronization (also known as Phase Locking Value) we minimize the effect of volume conduction, as it was demonstrated in several works34.
As in other invasive neurophysiological techniques, recordings from FOE cannot be obtained from control subjects, a fact that severely limits the use of certain research protocols. Data from FOE recordings provide valuable information about mesial temporal lobe activity17,29,35, especially during lateralization to the epileptogenic side in TLE patients33. Compared with invasive techniques, the FOE technique is non-traumatic for the brain and involves relatively simple manipulation, and its recordings are of high quality over long periods of time11. Compared to MRI, FOE recordings provide better time resolution of electrocortical activity. In addition, many possibilities exist to explore measures other than those used in this work. These facts also increase the possibility of analyzing several biomedical recordings simultaneously. These advantages of FOE recordings combined with complex network and spectral analysis make this technique a powerful tool for epilepsy research with potential applications in clinical practice.

Epilepsy is a disabling disease that affects 1 - 2% of the world&#39;s population. In the majority of cases, seizures &#8212; the hallmarks of epilepsy &#8212; can be completely controlled or abolished with anti-epileptic drugs. However, approximately 30% of epilepsy patents are refractory to drug therapies. In the most common type of epilepsy, the temporal lobe epilepsy (TLE)1, fortunately surgery is a valid alternative to improve the patient&#39;s condition. Results from meta-analyses show that almost two thirds of drug-resistant TLE patients are seizure-free in the first two to three years after the resective surgery2,3, although this proportion varies across several factors, most notably, the type of hippocampal sclerosis2. A critical step for a successful outcome is the accurate localization of the so-called epileptic focus, the cortical area responsible for the generation of seizures, which is typically located in the mesial area of the temporal lobe. However, even in those cases where the epileptic focus has been correctly identified and resected during the surgery, a significant minority of patients either remains with post-operative seizures or must be placed under strict antiepileptic drug treatment to control seizures. Therefore, a new perspective has emerged in which attention is no longer focused solely on isolated areas, instead cortical interactions now constitute the fundamental issue. This &#34;network&#34; approach is grounded in the connectome concept4, which focuses attention in the neural connections between different areas rather than highlighting the role of compartmentalized structures. This new paradigm was found in graph theory, a mathematical framework devoted to the study of topological and statistical properties of graphs, the appropriate tool to express its fundamental findings. Under this perspective, the brain is considered as a set of nodes interconnected by links5-9 such that nodes are represented by the cortical areas covered by the electrodes and the links between them are given by the degree of synchronization. Thus, this network approach has been used in the analysis of invasive electrode recordings and has provided new information to promote the understanding of the underlying mechanism of seizure generation and propagation.
Among the many invasive neurophysiological techniques routinely employed in most epilepsy centers around the world, the foramen ovale electrode (FOE) is particularly remarkable. FOE is a semi-invasive technique because there is no need to perform a craniotomy, which reduces surgery-related complications10. Additionally, the location of FOE in the ambient cistern11 makes them especially convenient for recording mesial activity from several cortical structures involved in seizure generation and propagation, such as the entorhinal cortex. Therefore, its use since its appearance is widespread in the presurgical evaluation of drug-resistant TLE patients. Traditionally, this technique is used to locate irritative activity in the form of interictal epileptogenic spikes and sharp-waves, and more importantly, to accurately identify the area of mesial seizure onset.
The new definition proposed from the Commission on Classification and Terminology from the International League against Epilepsy (ILAE) suggests that seizures originate at some point within particular networks12. Moreover, several studies have demonstrated that seizures are caused by abnormal network activity rather than by an isolated pathological area13-16. Clearly, this new perspective requires reanalysis of previously acquired information using new numerical methods, such as complex network methodology. Although the practical use of these analyses is still incipient in clinical practice, several research studies have demonstrated their value13-17.
The protocol described below is the combination of a clinical practice routinely performed on drug-resistant TLE epilepsy patients with a novel technique of network analysis. The method allows for the evaluation of the temporal evolution of mesial network parameters. The bilateral insertion of FOE into the ambient cistern simultaneously records the electrocortical activity at several mesial areas of the temporal lobes. A network approach applied to the recording 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.

<table><tbody><tr><td>Foramen Ovale Electrodes</td><td>AD-Tech, Racine,&lt;br/&gt; USA</td><td>FO06K-SP10X-000</td><td>Six-contact platinum&amp;nbsp;</td></tr><tr><td>Electroencephalograph</td><td>XLTEK, Canada</td><td>XLT-EEG32T</td><td>Natus XLTEK</td></tr><tr><td>MRI machine</td><td>General Electric</td><td></td><td></td></tr><tr><td>SPEC machine</td><td>General Electric</td><td></td><td></td></tr></tbody></table>

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.

The final position of the FOE is in the ambient cistern, as seen in the axial and sagittal MRI (Figure 1A upper panels). The contacts of the FOE record electrical activity from several mesial structures of the temporal lobe (Figure 1A lower panel). After the surgery (Figure 1B left panel), the patient is dispatched to the video-EEG room, where scalp electrodes are placed according with the 10 - 20 system (Figure 1B right). During the stay at the video-EEG room, the patient is continuously monitored, saving for further analysis scalp and FOE recordings, as well video and vital constants. A typical raw scalp and FOE signals (Figure 1C) show the appearance of a seizure at the left FOE and its spread to scalp and right FOE contacts.
Representation of the epileptogenic activity by using the excitability (S) (Figure 2) corresponding to the raw EEG recordings from Figure 1C, during the transition from the preictal to the ictal and postictal periods. Seizure onset is marked with a solid vertical line and time (x-axis) are referred to this point. A value of S (excitability) &#62;2.5 represented irritative or epileptogenic activity17,25,26. Higher excitability (reddish colors) appeared firstly with higher intensity on the left FOE contacts (LFOE). This result is concordant with a left mesial temporal lobe epilepsy as informed by an expert neurophysiologist.
Temporal dynamics of several network measures as well as the spectral entropy (Figure 3) during the transition from the preictal to the ictal and postictal stages, corresponding to the same seizure displayed in Figure 1C and 2. Seizure onset is marked with a solid vertical line and time (x-axis) are referred to this point. In this case, the network was built upon the whole set of electrodes, including both scalp and FOE. DoL and ACC values were higher during seizures, with a decrease in the APL and Mod, suggesting an increase in the overall connectivity. During this period also, lower levels of SE were observed and sustained after the excitability (dotted vertical lines) disappears.
The analysis of the network measures ACC, DoLs and APL and the SE for each FOE (right and left) (Figure 4) during the transition from the preictal to the ictal and postictal stages. Seizure onset is marked with a solid vertical line and time (x-axis) are referred to this point. The evolution of this measures correspond to the same seizure of Figures 1, 2 and 3. The ipsilateral (left) mesial ACC, DoLs and APL presented earlier and higher changes than the contralateral values, which could be explained by the location of the seizure onset zone in the left temporal lobe. In this case, Mod could not be calculated because no subdivisions were available.
A representative video of the functional connectivity (Figure 5) during the same seizure of Figure 1, 2, 3, and 4 presents a critical change just after the seizure onset (Time 0). At that point the connectivity between all the electrodes increase dramatically, as can be seen by an increase of the number of links and the thickness (intensity) of that edges. This increase starts between the left FOE at time 0.1 and 0.2, and spreads to the contralateral side before reaching the whole network.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>fft</td>
			<td>4.3</td>
			<td>(stats package) Computes the Fast Fourier Transform of a signal.</td>
		</tr>
		<tr>
			<td>ts</td>
			<td>4.4</td>
			<td>(stats package) Creates a multivariate time-series object (mts). The sampling frequency should be provided.</td>
		</tr>
		<tr>
			<td>Excitability</td>
			<td>5.1.1</td>
			<td>(homemade) function based on diff R function. Computes the absolute value of the slope of the signal and then normalize it to the standard deviation short baseline period. Threshold should be provided.</td>
		</tr>
		<tr>
			<td>Power spectral Density and Spectral Entropy</td>
			<td>5.1.2</td>
			<td>(Homemade) function based on spectrum and entropy R functions. Compute the normalized power spectrum and the Shannon entropy of the normalized power spectrum</td>
		</tr>
		<tr>
			<td>ccf</td>
			<td>5.2.1</td>
			<td>(base package) calculates the linear cross-correlation of mts object by using Pearson correlation at zero lag, generating a correlation matrix. Absolute values should be calculated.&#160;</td>
		</tr>
		<tr>
			<td>graph.adjacency</td>
			<td>5.2.2</td>
			<td>(igraph package)&#160; Creates an igraph graph, the basic object used by the following igraph functions</td>
		</tr>
		<tr>
			<td>average.path.length</td>
			<td>5.2.3</td>
			<td>(igraph package) determines the average path length of the&#160; graph, by computing the average number of steps along the shortest paths through all of the network nodes.&#160;</td>
		</tr>
		<tr>
			<td>graph.density</td>
			<td>5.2.3</td>
			<td>(igraph package) Computes the density of links of the graph by computing the ratio between the actual number of links and all possible links of the network.</td>
		</tr>
		<tr>
			<td>modularity</td>
			<td>5.2.3</td>
			<td>(igraph package) Determines the modularity of the graph, by computing which groups of nodes are more connected between them than with other nodes of the network</td>
		</tr>
		<tr>
			<td>transitivity</td>
			<td>5.2.3</td>
			<td>(igraph package) Determines the average clustering coefficient of the graph, by computing the proportion of neighboring nodes that are also neighbors of one another</td>
		</tr>
		<tr>
			<td>Phase synchronization</td>
			<td>5.2.4</td>
			<td>(homemade) function based in fft R function that calculates the mean phase coherence to obtain values between zero and one</td>
		</tr>
		<tr>
			<td>smd</td>
			<td>5.3</td>
			<td>(MBESS package) Determines the standard mean difference -size effects- by computing the difference in mean between groups relative to the pooled difference&#160;</td>
		</tr>
	</tbody>
</table>
Table 1: R functions Used for Data Processing.
<img alt="Figure 1" src="/files/ftp_upload/54746/54746fig1.jpg" /> 
Figure 1: Foramen Ovale Electrodes. (A) Final position of FOE into the ambient cistern. Upper panels show an axial (left) and sagittal (right) MRI images displaying the FOE contacts location (white arrows). A human specimen (cadaver) with an inserted FOE (lower panel, contacts marked with white arrows). (B) FOE and scalp electrodes setup. Patients head just after the FOE insertion surgery (left panel) and during the video-EEG stay (right panel). (C) FOE and scalp recordings. Complex partial seizure from a left TLE patient (5 min after and before seizure onset). RFOE1-RFOE6 stands for right FOE#1 to #6 and LFOE1-LFOE6 stands for left FOE#1 to #6. Seizure onset is marked by a vertical red line and a white arrow head. <a href="http://cloudflare.jove.com/files/ftp_upload/54746/54746fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54746/54746fig2.jpg" /> 
Figure 2: Representation of a Complex Partial Seizure from a Left TLE Patient Quantified by Excitability. The color scale quantifies the excitability level (S) for each electrode. The right foramen ovale electrode (RFOE) and left foramen ovale electrode (LFOE) represent the contacts of the right and left foramen ovale electrodes (y-axis), respectively. The x-axis marks the time (in min) relative to seizure onset (thick vertical line) as determined by an expert neurophysiologist. <a href="http://cloudflare.jove.com/files/ftp_upload/54746/54746fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54746/54746fig3.jpg" /> 
Figure 3: Entire Network (scalp+FOE) Measures from the Same Patient and Same Seizure from Figure 2. The average clustering coefficient (ACC), average path length (APL), density of links (DoLs), modularity (Mod) and spectral entropy (SE) for the entire network (scalp + FOE) are represented. The vertical dotted lines represent the excitability (S). The x-axis marks the time relative to seizure onset (thick vertical solid line). A moving average over ten consecutive windows is represented by a thick solid black line. <a href="http://cloudflare.jove.com/files/ftp_upload/54746/54746fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54746/54746fig4.jpg" /> 
Figure 4: Mesial Measures of the Same Patient from Figure 2 and 3. The average clustering coefficient (ACC), average path length (APL), density of links (DoLs) and spectral entropy (SE) for both the left and the right foramen ovale electrodes (FOEs). The vertical dotted lines mark the excitability. The x-axis marks the time relative to seizure onset (thick vertical solid line). A moving average over ten consecutive windows is represented by a thick solid black line. <a href="http://cloudflare.jove.com/files/ftp_upload/54746/54746fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54746/54746fig5.jpg" /> 
Figure 5: Dynamic of Connectivity Pattern during a Complex Partial Seizure. Links intensity is represented by the thickness of the edges. Times (lower numbers) are relative to the seizure onset (Time 0). Each frame is 5 sec long. Left and right foramen ovale electrodes (L1-L6 and R1-R6) are represented by coral and blue circles, respectively. Left and right scalp electrodes are represented by orange and cyan circles, respectively. <a href="http://cloudflare.jove.com/files/ftp_upload/54746/Figure_5.mp4" target="_blank">Please click here to download this movie.</a>

Watch this Scientific Journal Video about Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients at JoVE.com

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

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 ...

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12.1K Views.  Instituto de Investigación Sanitaria Hospital de la Princesa. 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.

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

Performing Behavioral Tasks in Subjects with Intracranial Electrodes

Patients having stereo-electroencephalography (SEEG) electrode, subdural grid or depth electrode implants have a multitude of electrodes implanted in different areas of their brain for the localization of their seizure focus and eloquent areas. After implantation, the patient must remain in the hospital until the pathological area of brain is found and possibly resected. During this time, these patients offer a unique opportunity to the research community because any number of behavioral paradigms can be performed to uncover the neural correlates that guide behavior. Here we present a method for recording brain activity from intracranial implants as subjects perform a behavioral task designed to assess decision-making and reward encoding. All electrophysiological data from the intracranial electrodes are recorded during the behavioral task, allowing for the examination of the many brain areas involved in a single function at time scales relevant to behavior. Moreover, and unlike animal studies, human patients can learn a wide variety of behavioral tasks quickly, allowing for the ability to perform more than one task in the same subject or for performing controls. Despite the many advantages of this technique for understanding human brain function, there are also methodological limitations that we discuss, including environmental factors, analgesic effects, time constraints and recordings from diseased tissue. This method may be easily implemented by any institution that performs intracranial assessments; providing the opportunity to directly examine human brain function during behavior.

Patients implanted with intracranial electrodes provide a unique opportunity to record neurological data from multiple areas of the brain while the patient performs behavioral tasks. Here, we present a method of recording from implanted patients that can be reproducible at other institutions with access to this patient population.

Patients having stereo-electroencephalography (SEEG) electrode, subdural grid or depth electrode implants have a multitude of electrodes implanted in ...

Behavior

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.

The Default Mode Network (DMN) in Temporal Lobe Epilepsy (TLE) is analyzed in the resting state of the brain using seed-based functional connectivity MRI (fcMRI).

Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal ...

Multi-electrode Array Recordings of Human Epileptic Postoperative Cortical Tissue

Epilepsy, affecting about 1% of the population, comprises a group of neurological disorders characterized by the periodic occurrence of seizures, which disrupt normal brain function. Despite treatment with currently available antiepileptic drugs targeting neuronal functions, one third of patients with epilepsy are pharmacoresistant. In this condition, surgical resection of the brain area generating seizures remains the only alternative treatment. Studying human epileptic tissues has contributed to understand new epileptogenic mechanisms during the last 10 years. Indeed, these tissues generate spontaneous interictal epileptic discharges as well as pharmacologically-induced ictal events which can be recorded with classical electrophysiology techniques. Remarkably, multi-electrode arrays (MEAs), which are microfabricated devices embedding an array of spatially arranged microelectrodes, provide the unique opportunity to simultaneously stimulate and record field potentials, as well as action potentials of multiple neurons from different areas of the tissue. Thus MEAs recordings offer an excellent approach to study the spatio-temporal patterns of spontaneous interictal and evoked seizure-like events and the mechanisms underlying seizure onset and propagation. Here we describe how to prepare human cortical slices from surgically resected tissue and to record with MEAs interictal and ictal-like events ex vivo.

We here describe how to perform multi-electrode array recordings of human epileptic cortical tissue. Epileptic tissue resection, slice preparation and multi-electrode array recordings of interictal and ictal events are demonstrated in detail.

Epilepsy, affecting about 1% of the population, comprises a group of neurological disorders characterized by the periodic occurrence of seizures, which ...

Investigating the Function of Deep Cortical and Subcortical Structures Using Stereotactic Electroencephalography: Lessons from the Anterior Cingulate Cortex

Stereotactic Electroencephalography (SEEG) is a technique used to localize seizure foci in patients with medically intractable epilepsy. This procedure involves the chronic placement of multiple depth electrodes into regions of the brain typically inaccessible via subdural grid electrode placement. SEEG thus provides a unique opportunity to investigate brain function. In this paper we demonstrate how SEEG can be used to investigate the role of the dorsal anterior cingulate cortex (dACC) in cognitive control. We include a description of the SEEG procedure, demonstrating the surgical placement of the electrodes. We describe the components and process required to record local field potential (LFP) data from consenting subjects while they are engaged in a behavioral task. In the example provided, subjects play a cognitive interference task, and we demonstrate how signals are recorded and analyzed from electrodes in the dorsal anterior cingulate cortex, an area intimately involved in decision-making. We conclude with further suggestions of ways in which this method can be used for investigating human cognitive processes.

Stereotactic Electroencephalography (SEEG) is an operative technique used in epilepsy surgery to help localize seizure foci. It also affords a unique opportunity to investigate brain function. Here we describe how SEEG can be used to investigate cognitive processes in human subjects.

Stereotactic Electroencephalography (SEEG) is a technique used to localize seizure foci in patients with medically intractable epilepsy. This procedure ...

Neuroscience

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and neurodegenerative diseases as well as epilepsies. This powerful technique does not only provide valuable insights into the underlying pathophysiological mechanisms, i.e., the etiopathogenesis of CNS related diseases, it also facilitates the development of new translational, i.e., therapeutic approaches. Whereas competing techniques that make use of recorder systems used in jackets or tethered systems suffer from their unphysiological restraining to semi-restraining character, radiotelemetric EEG recordings overcome these disadvantages. Technically, implantable EEG radiotelemetry allows for precise and highly sensitive measurement of epidural and deep, intracerebral EEGs under various physiological and pathophysiological conditions. First, we present a detailed protocol of a straight forward, successful, quick and efficient technique for epidural (surface) EEG recordings resulting in high-quality electrocorticograms. Second, we demonstrate how to implant deep, intracerebral EEG electrodes, e.g., in the hippocampus (electrohippocampogram). For both approaches, a computerized 3D stereotaxic electrode implantation system is used. The radiofrequency transmitter itself is implanted into a subcutaneous pouch in both mice and rats. Special attention also has to be paid to pre-, peri- and postoperative treatment of the experimental animals. Preoperative preparation of mice and rats, suitable anesthesia as well as postoperative treatment and pain management are described in detail.

Non-restraining EEG radiotelemetry is a valuable methodological approach to record in vivo long-term electroencephalograms from freely moving rodents. This detailed protocol describes stereotaxic epidural and deep intracerebral electrode placement in different brain regions in order to obtain reliable recordings of CNS rhythmicity and CNS related behavioral stages.

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and ...

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 ...

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

Although electroencephalography (EEG) is widely used as a non-invasive technique for recording neural activities of the brain, our understanding of the neurogenesis of EEG is still very limited. Local field potentials (LFPs) recorded via a multi-laminar microelectrode can provide a more detailed account of simultaneous neural activity across different cortical layers in the neocortex, but the technique is invasive. Combining EEG and LFP measurements in a pre-clinical model can greatly enhance understanding of the neural mechanisms involved in the generation of EEG signals, and facilitate the derivation of a more realistic and biologically accurate mathematical model of EEG. A simple procedure for acquiring concurrent and co-localized EEG and multi-laminar LFP signals in the anesthetized rodent is presented here. We also investigated whether EEG signals were significantly affected by a burr hole drilled in the skull for the insertion of a microelectrode. Our results suggest that the burr hole has a negligible impact on EEG recordings.

This protocol describes a simple method for concurrent recording of co-localized electroencephalography (EEG) and multi-laminar local field potential in an anesthetized rat. A burr hole drilled in the skull for the insertion of a microelectrode is shown to produce negligible distortion of the EEG signal.

Although electroencephalography (EEG) is widely used as a non-invasive technique for recording neural activities of the brain, our understanding of the ...

Recording and Modulation of Epileptiform Activity in Rodent Brain Slices Coupled to Microelectrode Arrays

Temporal lobe epilepsy (TLE) is the most common partial complex epileptic syndrome and the least responsive to medications. Deep brain stimulation (DBS) is a promising approach when pharmacological treatment fails or neurosurgery is not recommended. Acute brain slices coupled to microelectrode arrays (MEAs) represent a valuable tool to study neuronal network interactions and their modulation by electrical stimulation. As compared to conventional extracellular recording techniques, they provide the added advantages of a greater number of observation points and a known inter-electrode distance, which allow studying the propagation path and speed of electrophysiological signals. However, tissue oxygenation may be greatly impaired during MEA recording, requiring a high perfusion rate, which comes at the cost of decreased signal-to-noise ratio and higher oscillations in the experimental temperature. Electrical stimulation further stresses the brain tissue, making it difficult to pursue prolonged recording/stimulation epochs. Moreover, electrical modulation of brain slice activity needs to target specific structures/pathways within the brain slice, requiring that electrode mapping be easily and quickly performed live during the experiment. Here, we illustrate how to perform the recording and electrical modulation of 4-aminopyridine (4AP)-induced epileptiform activity in rodent brain slices using planar MEAs. We show that the brain tissue obtained from mice outperforms rat brain tissue and is thus better suited for MEA experiments. This protocol guarantees the generation and maintenance of a stable epileptiform pattern that faithfully reproduces the electrophysiological features observed with conventional field potential recording, persists for several hours, and outlasts sustained electrical stimulation for prolonged epochs. Tissue viability throughout the experiment is achieved thanks to the use of a small-volume custom recording chamber allowing for laminar flow and quick solution exchange even at low (1 mL/min) perfusion rates. Quick MEA mapping for real-time monitoring and selection of stimulating electrodes is performed by a custom graphic user interface (GUI).

We illustrate how to perform recording and electrical modulation of 4-aminopyridine-induced epileptiform activity in rodent brain slices using microelectrode arrays. A custom recording chamber maintains tissue viability throughout prolonged experimental sessions. Live electrode mapping and selection of stimulating pairs are performed by a custom graphical user interface.

Temporal lobe epilepsy (TLE) is the most common partial complex epileptic syndrome and the least responsive to medications. Deep brain stimulation (DBS) ...

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 ...

Improving Outcomes in Anteromesial Temporal Lobe Resections - A Demonstration of Resecting the Temporal Piriform Cortex

Anteromesial temporal lobe resection (ATLR) is a useful treatment option for drug-resistant mesial temporal lobe epilepsy (DRmTLE). Growing evidence suggests the piriform cortex plays a crucial role in the generation and propagation of seizures in DRmTLE - and that the resection of the temporal portion of the piriform cortex is associated with significantly improved rates of seizure freedom. 
Here, we present the resection of the temporal portion of the piriform cortex in ATLR, using high-resolution preoperative probabilistic tractography algorithms and fused anatomical masks of the structures of interest into the intraoperative neuronavigation and microscope head-up display (HUD). 
All patients undergoing comprehensive preoperative assessment and investigations for DRmTLE provided informed, written consent to record an intraoperative video of the procedure. Patients were identified by an expert multidisciplinary team of epileptologists, epilepsy neurosurgeons, neuropsychologists, neuropsychiatrists, and electrophysiologists at a large epilepsy surgery center. The preoperative imaging pipeline included the delineation of critical structures. This included the temporal piriform cortex, and high-resolution probabilistic tractography for essential tracts at risk (e.g., optic radiation and inferior fronto-occipital fasciculus). These were co-registered to the preoperative volumetric neuronavigation scan and uploaded to the intra-operative neuronavigation system. 
Presented here is a step-by-step procedure of ATLR, including the resection of the temporal portion of the piriform cortex. The protocol combines Advanced structural and diffusion MR imaging and intraoperative visual aids to integrate anatomical masks of critical grey matter structures and white matter tracts into the surgical workflow in the operating room.

Here, we demonstrate an approach to intraoperative neurosurgical guidance in anteromesial temporal lobe resections, specifically highlighting the use of tractography and anatomical masks to aid safe resection of the temporal portion of the piriform cortex - an area increasingly regarded as a crucial surgical target in drug-resistant mesial temporal lobe epilepsy.

Anteromesial temporal lobe resection (ATLR) is a useful treatment option for drug-resistant mesial temporal lobe epilepsy (DRmTLE). Growing evidence ...

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

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