Can postictal memory predict postoperative memory in patients with temporal lobe epilepsy?

We investigated the contribution of postictal memory testing for lateralizing the epileptic focus and predicting memory outcome after surgery for temporal lobe epilepsy (TLE). Forty-five patients with TLE underwent interictal, postictal, and postoperative assessment of verbal and nonverbal memory. Surgery consisted of anterior temporal lobectomy (36), selective isolated amygdalohippocampectomy (6), or amygdalohippocampectomy coupled to lesionectomy (3). Postictal and postoperative but not interictal memory were significantly lower in left TLE than in right TLE. Nonverbal memory showed no significant difference in left TLE versus right TLE in all conditions. Postictal memory was significantly correlated with postoperative memory, but the effect disappeared when the lateralization of the focus was considered. Postictal verbal memory is a useful bedside tool that can help lateralize the epileptic focus. Larger studies are needed to further estimate its predictive value of the postoperative outcome.

Duplication of the sodium channel gene cluster on 2q24 in children with early onset epilepsy

Sodium channel gene aberrations are associated with a wide range of seizure disorders, particularly Dravet syndrome. They usually consist of missense or truncating gene mutations or deletions. Duplications involving multiple genes encoding for different sodium channels are not widely known. This article summarizes the clinical, radiologic, and genetic features of patients with 2q24 duplication involving the sodium channel gene cluster.

Cognitive impairment and cortical reorganization in children with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is associated with mild cognitive deficits, especially language impairment. This study aimed to clarify whether children with BECTS with left- or right-hemispheric, or bilateral focus have specific neuropsychological language deficits when compared to healthy controls, whether these deficits correlate functionally with language network organization (typical vs. atypical), and whether cofactors such as duration, handedness, and medication have a relevant impact on language reorganization processes.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Effects of anticonvulsants on human p450c17 (17alpha-hydroxylase/17,20 lyase) and 3beta-hydroxysteroid dehydrogenase type 2.

PURPOSE Women with epilepsy apparently have a higher incidence of polycystic ovary syndrome (PCOS) than do women without epilepsy. Whether the underlying disease or the antiepileptic drug (AED) treatment is responsible for this increased risk is unknown, although clinical reports implicate valproic acid (VPA) as a potential cause. The steroidogenic enzymes 3beta HSDII (3beta-hydroxysteroid dehydrogenase) and P450c17 (17alpha-hydroxylase/17,20 lyase) are essential for C19 steroid biosynthesis, which is enhanced during adrenarche and in PCOS. METHODS To determine whether the AEDs VPA, carbamazepine (CBZ), topiramate (TPM), or lamotrigine (LYG) directly affect the activities of human 3beta HSDII and P450c17, we added them to yeast expressing human P450c17 or 3beta HSDII and assayed enzymatic activities in the microsomal fraction. RESULTS Concentrations of VPA < or = 10 mM had no effect on activities of P450c17; however, VPA inhibited 3beta HSDII activity starting at 0.3 mM (reference serum unbound concentration, 0.035-0.1 mM) with an IC50 of 10.1 mM. CBZ, TPM, and LTG did not influence 3beta HSDII or P450c17 activities at typical reference serum unbound concentrations, but did inhibit 3beta HSDII and P450c17 at concentrations >10-fold higher. CONCLUSIONS None of the tested AEDs influenced 3beta HSDII or P450c17 activities at concentrations normally used in AED therapy. However, VPA started to inhibit 3beta HSDII activity at concentrations 3 times above the typical reference serum unbound concentration. Because inhibition of 3beta HSDII activity will shift steroidogenesis toward C19 steroid production when P450c17 activities are unchanged, very high doses of VPA may promote C19 steroid biosynthesis, thus resembling PCOS. CBZ, TPM, and LTG influenced 3beta HSDII and P450c17 only at toxic concentrations.

Seizures in patients with Alzheimer's disease or vascular dementia: a population-based nested case-control analysis

PURPOSE Patients with Alzheimer's disease (AD) have an increased risk of developing seizures or epilepsy. Little is known about the role of risk factors and about the risk of developing seizures/epilepsy in patients with vascular dementia (VD). The aim of this study was to assess incidence rates (IRs) of seizures/epilepsy in patients with AD, VD, or without dementia, and to identify potential risk factors of seizures or epilepsy. METHODS We conducted a follow-up study with a nested case-control analysis using the United Kingdom-based General Practice Research Database (GPRD). We identified patients aged ≥65 years with an incident diagnosis of AD or VD between 1998 and 2008 and a matched comparison group of dementia-free patients. Conditional logistic regression was used to estimate the odds ratio (OR) with a 95% confidence interval (CI) of developing seizures/epilepsy in patients with AD or VD, stratified by age at onset and duration of dementia as well as by use of antidementia drugs. KEY FINDINGS Among 7,086 cases with AD, 4,438 with VD, and 11,524 matched dementia-free patients, we identified 180 cases with an incident diagnosis of seizures/epilepsy. The IRs of epilepsy/seizures for patients with AD or VD were 5.6/1,000 person-years (py) (95% CI 4.6-6.9) and 7.5/1,000 py (95% CI 5.7-9.7), respectively, and 0.8/1,000 py (95% CI 0.6-1.1) in the dementia-free group. In the nested case-control analysis, patients with longer standing (≥3 years) AD had a slightly higher risk of developing seizures or epilepsy than those with a shorter disease duration, whereas in patients with VD the contrary was observed. SIGNIFICANCE Seizures or epilepsy were substantially more common in patients with AD and VD than in dementia-free patients. The role of disease duration as a risk factor for seizures/epilepsy seems to differ between AD and VD.

POLG DNA testing as an emerging standard of care before instituting valproic acid therapy for pediatric seizure disorders.

PURPOSE: To review our clinical experience and determine if there are appropriate signs and symptoms to consider POLG sequencing prior to valproic acid (VPA) dosing in patients with seizures. METHODS: Four patients who developed VPA-induced hepatotoxicity were examined for POLG sequence variations. A subsequent chart review was used to describe clinical course prior to and after VPA dosing. RESULTS: Four patients of multiple different ethnicities, age 3-18 years, developed VPA-induced hepatotoxicity. All were given VPA due to intractable partial seizures. Three of the patients had developed epilepsia partialis continua. The time from VPA exposure to liver failure was between 2 and 3 months. Liver failure was reversible in one patient. Molecular studies revealed homozygous p.R597W or p.A467T mutations in two patients. The other two patients showed compound heterozygous mutations, p.A467T/p.Q68X and p.L83P/p.G888S. Clinical findings and POLG mutations were diagnostic of Alpers-Huttenlocher syndrome. CONCLUSION: Our cases underscore several important findings: POLG mutations have been observed in every ethnic group studied to date; early predominance of epileptiform discharges over the occipital region is common in POLG-induced epilepsy; the EEG and MRI findings varying between patients and stages of the disease; and VPA dosing at any stage of Alpers-Huttenlocher syndrome can precipitate liver failure. Our data support an emerging proposal that POLG gene testing should be considered in any child or adolescent who presents or develops intractable seizures with or without status epilepticus or epilepsia partialis continua, particularly when there is a history of psychomotor regression.

Recommendations for HLA-B*15:02 and HLA-A*31:01 genetic testing to reduce the risk of carbamazepine-induced hypersensitivity reactions.

OBJECTIVE To systematically review evidence on genetic risk factors for carbamazepine (CBZ)-induced hypersensitivity reactions (HSRs) and provide practice recommendations addressing the key questions: (1) Should genetic testing for HLA-B*15:02 and HLA-A*31:01 be performed in patients with an indication for CBZ therapy to reduce the occurrence of CBZ-induced HSRs? (2) Are there subgroups of patients who may benefit more from genetic testing for HLA-B*15:02 or HLA-A*31:01 compared to others? (3) How should patients with an indication for CBZ therapy be managed based on their genetic test results? METHODS A systematic literature search was performed for HLA-B*15:02 and HLA-A*31:01 and their association with CBZ-induced HSRs. Evidence was critically appraised and clinical practice recommendations were developed based on expert group consensus. RESULTS Patients carrying HLA-B*15:02 are at strongly increased risk for CBZ-induced Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) in populations where HLA-B*15:02 is common, but not CBZ-induced hypersensitivity syndrome (HSS) or maculopapular exanthema (MPE). HLA-B*15:02-positive patients with CBZ-SJS/TEN have been reported from Asian countries only, including China, Thailand, Malaysia, and India. HLA-B*15:02 is rare among Caucasians or Japanese; no HLA-B*15:02-positive patients with CBZ-SJS/TEN have been reported so far in these groups. HLA-A*31:01-positive patients are at increased risk for CBZ-induced HSS and MPE, and possibly SJS/TEN and acute generalized exanthematous pustulosis (AGEP). This association has been shown in Caucasian, Japanese, Korean, Chinese, and patients of mixed origin; however, HLA-A*31:01 is common in most ethnic groups. Not all patients carrying either risk variant develop an HSR, resulting in a relatively low positive predictive value of the genetic tests. SIGNIFICANCE This review provides the latest update on genetic markers for CBZ HSRs, clinical practice recommendations as a basis for informed decision making regarding the use of HLA-B*15:02 and HLA-A*31:01 genetic testing in patients with an indication for CBZ therapy, and identifies knowledge gaps to guide future research. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Dynamic directed interictal connectivity in left and right temporal lobe epilepsy.

OBJECTIVE There is increasing evidence that epileptic activity involves widespread brain networks rather than single sources and that these networks contribute to interictal brain dysfunction. We investigated the fast-varying behavior of epileptic networks during interictal spikes in right and left temporal lobe epilepsy (RTLE and LTLE) at a whole-brain scale using directed connectivity. METHODS In 16 patients, 8 with LTLE and 8 with RTLE, we estimated the electrical source activity in 82 cortical regions of interest (ROIs) using high-density electroencephalography (EEG), individual head models, and a distributed linear inverse solution. A multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to the source signal of all ROIs. A nonparametric statistical test assessed differences between spike and baseline epochs. Connectivity results between RTLE and LTLE were compared between RTLE and LTLE and with neuropsychological impairments. RESULTS Ipsilateral anterior temporal structures were identified as key drivers for both groups, concordant with the epileptogenic zone estimated invasively. We observed an increase in outflow from the key driver already before the spike. There were also important temporal and extratemporal ipsilateral drivers in both conditions, and contralateral only in RTLE. A different network pattern between LTLE and RTLE was found: in RTLE there was a much more prominent ipsilateral to contralateral pattern than in LTLE. Half of the RTLE patients but none of the LTLE patients had neuropsychological deficits consistent with contralateral temporal lobe dysfunction, suggesting a relationship between connectivity changes and cognitive deficits. SIGNIFICANCE The different patterns of time-varying connectivity in LTLE and RTLE suggest that they are not symmetrical entities, in line with our neuropsychological results. The highest outflow region was concordant with invasive validation of the epileptogenic zone. This enhanced characterization of dynamic connectivity patterns could better explain cognitive deficits and help the management of epilepsy surgery candidates.

Altered directed functional connectivity in temporal lobe epilepsy in the absence of interictal spikes: A high density EEG study.

OBJECTIVE In patients with epilepsy, seizure relapse and behavioral impairments can be observed despite the absence of interictal epileptiform discharges (IEDs). Therefore, the characterization of pathologic networks when IEDs are not present could have an important clinical value. Using Granger-causal modeling, we investigated whether directed functional connectivity was altered in electroencephalography (EEG) epochs free of IED in left and right temporal lobe epilepsy (LTLE and RTLE) compared to healthy controls. METHODS Twenty LTLE, 20 RTLE, and 20 healthy controls underwent a resting-state high-density EEG recording. Source activity was obtained for 82 regions of interest (ROIs) using an individual head model and a distributed linear inverse solution. Granger-causal modeling was applied to the source signals of all ROIs. The directed functional connectivity results were compared between groups and correlated with clinical parameters (duration of the disease, age of onset, age, and learning and mood impairments). RESULTS We found that: (1) patients had significantly reduced connectivity from regions concordant with the default-mode network; (2) there was a different network pattern in patients versus controls: the strongest connections arose from the ipsilateral hippocampus in patients and from the posterior cingulate cortex in controls; (3) longer disease duration was associated with lower driving from contralateral and ipsilateral mediolimbic regions in RTLE; (4) aging was associated with a lower driving from regions in or close to the piriform cortex only in patients; and (5) outflow from the anterior cingulate cortex was lower in patients with learning deficits or depression compared to patients without impairments and to controls. SIGNIFICANCE Resting-state network reorganization in the absence of IEDs strengthens the view of chronic and progressive network changes in TLE. These resting-state connectivity alterations could constitute an important biomarker of TLE, and hold promise for using EEG recordings without IEDs for diagnosis or prognosis of this disorder.

Desarrollo de una herramienta para el análisis de imágenes cerebrales multimodales

En la actualidad, el desarrollo de las tecnologías de adquisición y análisis de imagen médica permiten la implementación de aplicaciones con fines clínicos y de investigación que resulten en un mejor conocimiento de la fisiopatología humana y, en la práctica, un mejor tratamiento a los pacientes. Utilizando imágenes de resonancia magnética nuclear y de tomografía por emisión de fotón único (SPECT), se han desarrollado los algoritmos de registro necesarios para ser integrados en dos procedimientos de uso clínico. En el primero de estos procedimientos, el objetivo es la localización del foco epileptogénico en casos de epilepsia fármacorresistente mediante el protocolo denominado SISCOM. En este contexto, se ha implementado un algoritmo de registro rígido para el corregistro de Resonancia Magnética e imagen SPECT interictal, así como un algoritmo de registro afín que ayuda a la segmentación de imágenes SPECT. Así mismo, se han validado y caracterizado ambos algoritmos y la librería sobre la que se han desarrollado. El segundo procedimiento tiene por objeto la cuantificación de neurotransmisores dopaminérgicos para el diagnóstico de Enfermedad de Parkinson. En este contexto, se ha implementado un algoritmo de registro SPECT-template necesario para realizar correctamente la cuantificación.

Validación, caracterización y aplicación clínica en neuroimagen multimodalidad de técnicas de registro basadas en Teoría de la Información

La correcta validación y evaluación de cualquier algoritmo de registro incluido en la línea de procesamiento de cualquier aplicación clínica, es fundamental para asegurar la calidad y fiabilidad de los resultados obtenidos con ellas. Ambas características son imprescindibles, además, cuando dicha aplicación se encuentra en el área de la planificación quirúrgica, en la que las decisiones médicas influyen claramente en la invasividad sobre el paciente. El registro de imágenes es un proceso de alineamiento entre dos o más de éstas de forma que las características comunes se encuentren en el mismo punto del espacio. Este proceso, por tanto, se hace imprescindible en aquellas aplicaciones en las que existe la necesidad de combinar la información disponible en diferentes modalidades (fusión de imágenes) o bien la comparación de imágenes intra-modalidad tomadas de diferentes pacientes o en diferentes momentos. En el presente Trabajo Fin de Máster, se desarrolla un conjunto de herramientas para la evaluación de algoritmos de registro y se evalúan en la aplicación sobre imágenes multimodalidad a través de dos metodologías: 1) el uso de imágenes cuya alineación se conoce a priori a través de unos marcadores fiables (fiducial markers) eliminados de las imágenes antes del proceso de validación; y 2) el uso de imágenes sintetizadas con las propiedades de cierta modalidad de interés, generadas en base a otra modalidad objetivo y cuya des-alineación es controlada y conocida a priori. Para la primera de las metodologías, se hizo uso de un proyecto (RIRE – Retrospective Image Registration Evaluation Project) ampliamente conocido y que asegura la fiabilidad de la validación al realizarse por terceros. En la segunda, se propone la utilización de una metodología de simulación de imágenes SPECT (Single Photon Emission Computed Tomography) a partir de imágenes de Resonancia Magnética (que es la referencia anatómica). Finalmente, se realiza la modularización del algoritmo de registro validado en la herramienta FocusDET, para la localización del Foco Epileptógeno (FE) en Epilepsia parcial intratable, sustituyendo a la versión anterior en la que el proceso de registro se encontraba embebido en dicho software, dificultando enormemente cualquier tarea de revisión, validación o evaluación.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.