Repolitisations féministes et queer du cerveau

L’histoire des relations entre biologie et politique féministe est tendue et contradictoire. Cela paraît d’autant plus flagrant aujourd’hui à l’âge d’or des neurosciences qui ramènent les arguments de supériorité masculine, le caractère inéluctable des différences de genre et la prédominance de l’hétérosexualité à une affaire de cerveau. Dans cet article, nous analysons les points d’intersection propres aux sciences du cerveau et du féminisme. Ces deux champs de recherche entretiennent selon nous des rapports conflictuels mais parfois aussi productifs, y compris dans leurs rapports à l’activisme politique. Ces rapports peuvent être caractérisés en référence à trois directions de recherche principales : des « déstabilisations », des « reconstructions » et des « recontextualisations ». En guise de conclusion, nous terminons par quelques réflexions sur les conditions sociologiques de l’engagement dans une économie politique des neurosciences.[1] [1]Traduit de l’anglais par Marc Gagnepain. Pour une brève présentation de l’article et du dossier thématique dans lequel il s’inscrit, nous renvoyons le/la lecteur/trice à l’article introductif de Bovet, Kraus, Panese, Pidoux et Stücklin, « Les neurosciences à l’épreuve de la clinique et des sciences sociales. Regards croisés ».

What do we mean by Female and Male in Neurocognitive Experiments on Language?

For several years now, neuroscientific research has been striving towards fundamental answers to questions about the relevance of sex/gender to language processing in the brain. This research has been effected through the search for sex/gender differences in the neurobiology of language processing. Thus, the main aim has ever been to focus on the differentiation of the sexes/genders, failing to define what sex, what gender, what female or male is in neurolingustic research. In other words, although neuroscientific findings have provided key insights into the brain functioning of women and men, neuropsychology has rarely questioned the complexity of the sex/gender variable beyond biology. What does “female” or “male” mean in human neurocognition; how are operationalisations implemented along the axes of “femaleness” or “maleness”; or what biological evidence is used to register the variables sex and/or gender? In the neurosciences as well as in neurocognitive research, questions such as these have so far not been studied in detail, even if they are highly significant for the scientific process. Instead, the variable of sex/gender has always been thought as solely dichotomous (as either female or male), oppositional and exclusionary of each other. Here, this theoretical contribution sets in. Based on findings in neuroscience and concepts in gender theory, this poster is dedicated to the reflection about what sex/gender is in the neuroscience of language processing. Following this aim, two levels of interest will be addressed. First: How do we define sex/gender at the level of participants? And second: How do we define sex/gender at the level of the experimental task? For the first, a multifactorial registration (work in progress) of the variable sex/gender will be presented, i.e. a tool that records sex/gender in terms of biology and social issues as well as on a spectrum between femaleness and maleness. For the second, the compulsory dichotomy of a gendered task when neurolinguistically approaching our cognitions of sex/gender will be explored.

Searching for the majority: algorithms of voluntary control.

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.

ANALYSIS OF β8 INTEGRIN IN NEUROGENESIS AND NEUROVASCULAR HOMEOSTASIS

Neurogenesis in the adult mouse brain occurs within the subventricular zone (SVZ) of the lateral ventricle. In the SVZ, neural stem cells (NSC) reside in a specialized microenvironment, or vascular niche, consisting of blood vessels and their basement membranes. Most NSCs in the SVZ differentiate into progenitor cells, which further differentiate to generate neuroblasts, which then migrate from the SVZ to the olfactory bulbs (OB) along the rostral migratory stream (RMS). ECM-mediated adhesion and signaling within the vascular niche likely contribute to proper NSC self-renewal, survival, differentiation and neuroblast motility. The mechanisms that control these events are poorly understood. Previous studies from our group and others have shown that loss of the ECM receptor, αvβ8 integrin, in NSCs in the embryonic mouse brain leads to severe developmental vascular defects and premature death. Here, the functions of αvβ8 integrin in the adult brain have been examined using mice that have been genetically manipulated to lack a functional β8 integrin gene. This study reveals that loss of β8 integrin leads to widespread defects in homeostasis of the neurovascular unit, including increased intracerebral blood vessels with enhanced perivascular astrogliosis. Additionally, β8 integrin dependent defects in NSC proliferation, survival, and differentiation, as well as neuroblast migration in the RMS were observed both in vivo and in vitro. The defects correlated, in part, with diminished integrin-mediated activation of TGFβ, an ECM ligand of β8 integrin. Collectively, these data identify important adhesion and signaling functions for β8 integrin in the regulation of neural stem and progenitor cells in the SVZ as well as in neuroblast migration along the RMS in the adult brain.

The Role of the Androgen Receptor Cofactor p44/WDR77 in Astrocyte Activation

Astrogliosis is induced by neuronal damage and is also a pathological feature of the major aging-related neurodegenerative disorders. The mechanisms that control the cascade of astrogliosis have not been well established. In a previous study, we identified a novel androgen receptor (AR)-interacting protein (p44/WDR77) and found that it plays a critical role in the control of proliferation and differentiation of prostate epithelial cells. In the present study, we found that deletion of the p44 gene in the mouse brain caused accelerated aging with dramatic astrogliosis. The p44/WDR77 is expressed in astrocytes and loss of p44/WDR77 expression in astrocytes leads to astrogliosis. Our results reveal a novel role of p44/WDR77 in astrocytes, which may explain the well-documented role of androgens in suppression of astrogliosis. While many of detailed mechanisms of astrocyte activation remain to be elucidated, a number pathways have been implicated in astrocyte activation including p21Cip1 and the NF-kB pathway. Astrocytic activation induced by p44/WDR77 gene deletion was associated with a significant increase of p21Cip1 expression and NF-kB activation characterized by p65 nuclear localization. We found that down-regulation of p21Cip1 expression inhibited astrocyte activation induced by the p44/WDR77 deletion and was accompanied by a decreased p65 nuclear localization. While p21Cip1 role in astrocyte activation and NF-kB activation is not well understood, studies of other cell cycle regulators have implicated cell cycle control systems as modulators of astrocyte activation, thus p21Cip1 could induce secondary effect to induce p65 nuclear localization. However, p65 knockdown completely relieved the inhibition of astrocyte growth induced by the p44/WDR77 deletion, while p21Cip1 knockdown only partially recovered this inhibition. Thus, NF-kB activity performs additional regulatory actions not mediated by p21Cip1. These analyses imply that p4/WDR77 suppresses astrocyte activation through modulating p21Cip1 expression and NF-kB activation.

Prevalence of Premature Ovarian Failure in Women with Tuberous Sclerosis

Tuberous Sclerosis Complex (TSC) is an autosomal dominant tumor suppressor disorder characterized by hamartomas, or benign growths, in various organ systems. Inactivating mutations in either the TSC1 or the TSC2 gene cause most cases of TSC. Recently, the use of ovarian specific conditional knock-out mouse models has demonstrated a crucial role of the TSC genes in ovarian function. Mice with complete deletion of Tsc1 or Tsc2 showed accelerated ovarian follicle activation and subsequent premature follicular depletion, consistent with the human condition premature ovarian failure (POF). POF is defined in women as the cessation of menses before the age of 40 and elevated levels of follicle stimulating hormone (FSH). The prevalence of POF is estimated to be 1%, affecting a substantial number of women in the general population. Nonetheless, the etiology of most cases of POF remains unknown. Based on the mouse model results, we hypothesized that the human TSC1 and TSC2 genes are likely to be crucial for ovarian development and function. Moreover, since women with TSC already have one inactivated TSC gene, we further hypothesized that they may show a higher prevalence of POF. To test this hypothesis, we surveyed 1000 women with TSC belonging to the Tuberous Sclerosis Alliance, a national support organization. 182 questionnaires were analyzed for information on menstrual and reproductive function, as well as TSC. This self-reported data revealed 8 women (4.4%) with possible POF, as determined by menstrual history report and additional supportive data. This prevalence is much higher than 1% in the general population. Data from all women suggested other reproductive pathology associated with TSC such as a high rate of miscarriage (41.2%) and menstrual irregularity of any kind (31.2%). These results establish a previously unappreciated effect of TSC on women’s reproductive health. Moreover, these data suggest that perturbations in the cellular pathways regulated by the TSC genes may play an important role in reproductive function.

BRAIN ACTIVATION AND CONNECTIVITY IN NON-DISABLED MULTIPLE SCLEROSIS PATIENTS

Multiple sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. There is no cure for MS and current therapies have limited efficacy. While the majority of individuals with MS develop significant clinical disability, a subset experiences a disease course with minimal impairment even in the presence of significant apparent tissue damage on magnetic resonance imaging (MRI). The current studies combined functional MRI and diffusion tensor imaging (DTI) to elucidate brain mechanisms associated with lack of clinical disability in patients with MS. Recent evidence has implicated cortical reorganization as a mechanism to limit the clinical manifestation of the disease. Functional MRI was used to test the hypothesis that non-disabled MS patients (Expanded Disability Status Scale ≤ 1.5) show increased recruitment of cognitive control regions (dorsolateral prefrontal and anterior cingulate cortex) while performing sensory, motor and cognitive tasks. Compared to matched healthy controls, patients increased activation of cognitive control brain regions when performing non-dominant hand movements and the 2-back working memory task. Using dynamic causal modeling, we tested whether increased cognitive control recruitment is associated with alterations in connectivity in the working memory functional network. Patients exhibited similar network connectivity to that of control subjects when performing working memory tasks. We subsequently investigated the integrity of major white matter tracts to assess structural connectivity and its relation to activation and functional integration of the cognitive control system. Patients showed substantial alterations in callosal, inferior and posterior white matter tracts and less pronounced involvement of the corticospinal tracts and superior longitudinal fasciculi (SLF). Decreased structural integrity within the right SLF in patients was associated with decreased performance, and decreased activation and connectivity of the cognitive control system when performing working memory tasks. These studies suggest that patient with MS without clinical disability increase cognitive control system recruitment across functional domains and rely on preserved functional and structural connectivity of brain regions associated with this network. Moreover, the current studies show the usefulness of combining brain activation data from functional MRI and structural connectivity data from DTI to improve our understanding of brain adaptation mechanisms to neurological disease.

Associative processing and paranormal belief

In the present study we introduce a novel task for the quantitative assessment of both originality and speed of individual associations. This 'BAG' (Bridge-the-Associative-Gap) task was used to investigate the relationships between creativity and paranormal belief. Twelve strong 'believers' and 12 strong 'skeptics' in paranormal phenomena were selected from a large student population (n > 350). Subjects were asked to produce single-word associations to word pairs. In 40 trials the two stimulus words were semantically indirectly related and in 40 other trials the words were semantically unrelated. Separately for these two stimulus types, response commonalities and association latencies were calculated. The main finding was that for unrelated stimuli, believers produced associations that were more original (had a lower frequency of occurrence in the group as a whole) than those of the skeptics. For the interpretation of the result we propose a model of association behavior that captures both 'positive' psychological aspects (i.e., verbal creativity) and 'negative' aspects (susceptibility to unfounded inferences), and outline its relevance for psychiatry. This model suggests that believers adopt a looser response criterion than skeptics when confronted with 'semantic noise'. Such a signal detection view of the presence/absence of judgments for loose semantic relations may help to elucidate the commonalities between creative thinking, paranormal belief and delusional ideation.

An fMRI-Study on context-specificity of inhibitory functions in alcohol-dependency: Preliminary results

Introduction: Alcohol-dependency is a common disease with many negative consequences in the daily life. A typical symptom of alcoholic-patients is the persistent and uncontrollable desire to consume alcohol. Inspite of different treatments, alcohol-dependency has a relapse rate of about 85%. This high rate is facilitated by a dysfunction of cognitive control-processes. In order to understand this disease sustaining factor, the present study investigated the neurophysiological correlates of inhibition of alcoholic-patients in a neutral as well as an alcohol-related context. Methods: A total of 18 participants, (9 alcohol-dependent-patients (age range: 27-62 years), 9 healthy controls (age range: 29-60 years)) have been measured with functional magnetic resonance imaging while they participated in an alcohol-specific Go/NoGo-Task. Neurophysiological correlates of inhibition in an alcohol-related as well as a neutral context were compared in both groups. Results: When comparing correct stop-trials in alcohol-related to neutral context, only alcohol-dependent patients showed significant hyperactivation in frontal regions (superior and medial gyrus frontalis, anterior gyrus cinguli, gyrus paracentralis and the gyrus praecentralis). No significant differences were found in any of the behavioral analyses. Discussion: These preliminary results thus indicate that successful inhibition in a drug-related context demands additional resources in patients. Especially the hyperactivation of the anterior gyrus cinguli might be important because of its involvement in decision-processes. In the absent of deficits in behavioral data, this suggests that alcohol-dependent patients need more neuronal activity to achieve the same performance-level like healthy controls.

A Functionalist Perspective on Social Anxiety and Avoidant Personality Disorder

A developmental-evolutionary perspective is used to synthesize basic research from the neurosciences, ethology, genetics, and developmental psychology into a unified framework for understanding the nature and origins of social anxiety and avoidant personality disorder. Evidence is presented that social anxiety disorder (social phobia) and avoidant personality disorder may be alternate conceptualizations of the same disorder because they have virtually the same symptoms and genetic basis, and respond to the same pharmacologic and psychotherapeutic interventions. A functionalist perspective on social anxiety is formulated to (a) explain the origins of normative states of anxiety, (b) outline developmental pathways in the transition from normative anxiety to social anxiety and avoidant personality disorders, and (c) account for the processes leading to gender-differentiated patterns of anxiety-related disorders after puberty.

A Pre-Clinical Assessment of Minocycline for Treatment of Chronic Neuropathic Pain after Spinal Cord Injury

Patients living with a spinal cord injury (SCI) often develop chronic neuropathic pain (CNP). Unfortunately, the clinically approved, current standard of treatment, gabapentin, only provides temporary pain relief. This treatment can cause numerous adverse side effects that negatively affect the daily lives of SCI patients. There is a great need for alternative, effective treatments for SCI-dependent CNP. Minocycline, an FDA-approved antibiotic, has been widely prescribed for the treatment of acne for several decades. However, recent studies demonstrate that minocycline has neuroprotective properties in several pre-clinical rodent models of CNS trauma and disease. Pre-clinical studies also show that short-term minocycline treatment can prevent the onset of CNP when delivered during the acute stage of SCI and can also transiently attenuate established CNP when delivered briefly during the chronic stage of SCI. However, the potential to abolish or attenuate CNP via long-term administration of minocycline after SCI is unknown. The purpose of this study was to investigate the potential efficacy and safety of long-term administration of minocycline to abolish or attenuate CNP following SCI. A severe spinal contusion injury was administered on adult, male, Sprague-Dawley rats. At day 29 post-injury, I initiated a three-week treatment regimen of daily administration with minocycline (50 mg/kg), gabapentin (50 mg/kg) or saline. The minocycline treatment group demonstrated a significant reduction in below-level mechanical allodynia and above- level hyperalgesia while on their treatment regimen. After a ten-day washout period of minocycline, the animals continued to demonstrate a significant reduction in below-level mechanical allodynia and above-level hyperalgesia. However, minocycline-treated animals exhibited abnormal weight gain and hepatotoxicity compared to gapabentin-treated or vehicle-treated subjects.The results support previous findings that minocycline can attenuate CNP after SCI and suggested that minocycline can also attenuate CNP via long-term delivery of minocycline after SCI (36). The data also suggested that minocycline had a lasting effect at reducing pain symptoms. However, the adverse side effects of long-term use of minocycline should not be ignored in the rodent model. Gabapentin treatment caused a significant decrease in below-level mechanical allodynia and below-level hyperalgesia during the treatment regimen. Because gabapentin treatment has an analgesic effect at the concentration I administered, the results were expected. However, I also found that gabapentin-treated animals demonstrated a sustained reduction in pain ten days after treatment withdrawal. This result was unexpected because gabapentin has a short half-life of 1.7 hours in rodents and previous studies have demonstrated that pre-drug pain levels return shortly after withdrawal of treatment. Additionally, the gabapentin-treated animals demonstrated a significant and sustained increase in rearing events compared with all other treatment groups which suggested that gabapentin treatment was not only capable of reducing pain long-term but may also significantly improve trunk stability or improve motor function recovery.

The neocortical column

In the middle of the twentieth century, Rafael Lorente de Nó (1902?1990) introduced the fundamental concept of the ?elementary cortical unit of operation,? proposing that the cerebral cortex is formed of small cylinders containing vertical chains of neurons (Lorente de Nó, 1933, 1938). On the basis of this idea, the hypothesis was later developed of the columnar organization of the cerebral cortex, primarily following the physiological and anatomical studies of Vernon Mountcastle, David Hubel, Torsten Wiesel, János Szentágothai, Ted Jones, and Pasko Rakic (for a review of these early studies, see Mountcastle, 1998). The columnar organization hypothesis is currently the most widely adopted to explain the cortical processing of information, making its study of potential interest to any researcher interested in this tissue, both in a healthy and pathological state. However, it is frequently remarked that the nomenclature surrounding this hypothesis often generates problems, as the term ?Column? is used freely and promiscuously to refer to multiple, distinguishable entities, such as cellular or dendritic minicolumns or afferent macrocolumns, with respective diameters of menor que50 and 200?500 ?m. Another problem is the degree to which classical criteria may need to be modified (shared response properties, shared input, and common output) and if so, how. Moreover, similar problems arise when we consider the need to define area-specific and species-specific variations. Finally, and what is more an ultimate goal than a problem, it is still necessary to achieve a better fundamental understanding of what columns are and how they are used in cortical processes. Accordingly, it is now very important to translate recent technical advances and new findings in the neurosciences into practical applications for neuroscientists, clinicians, and for those interested in comparative anatomy and brain evolution.

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.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

Copy Number Variations in DISC1 and DISC1-Interacting Partners in Major Mental Illness

Acknowledgements We would like to thank all of the patients, relatives and control individuals who participated in the study. We are indebted to the late Prof. Walter Muir, Chair of Developmental Psychiatry and Honorary Consultant in Learning Disability Psychiatry, University of Edinburgh, who initiated these studies and whose work was dedicated to the welfare of the patients who generously participated. We are also grateful to Mrs. Pat Malloy for her assistance with DNA collection and MAQ assays screening of the Scottish samples. The Scottish sample collection was supported by a grant from the Chief Scientist Office (CSO), part of the Scottish Government Health and Social Care Directorates. This research was funded by grants from the CSO to B.S.P. (grant CZB/4/610), The Academy of Medical Sciences/Wellcome Trust to M.J. (grant R41455) and The RS Macdonald Charitable Trust (grant D21419 together with J.H.), the Swedish Research Council (grants 2003-5158 and 2006-4472), the Medical Faculty, Umeå University, and the County Councils of Västerbotten and Norrbotten, Sweden, as well as by grants from the Fund for Scientific Research Flanders (FWO-F), the Industrial Research Fund (IWT) and the Special Research Fund of the University of Antwerp, Belgium. M.J. is funded by a Wellcome Trust Clinical Research Fellowship for MB PhD graduates (R42811). We acknowledge the contribution of the personnel of the VIB Genetic Service Facility (http://www.vibgeneticservicefacility.be/) for the genetic analysis of the Swedish samples. Research nurses Gunnel Johansson, Lotta Kronberg, Tage Johansson and Lisbeth Bertilsson are thankfully acknowledged for their help and expertise. The Betula Study was funded by the Swedish Research Council (grants 345-2003-3883 and 315-2004-6977). We also acknowledge the contribution by the staff in the Betula project