Myelination of the right parahippocampal cingulum is associated with physical activity in young healthy adults.

Recent evidence suggests that individual differences in physical activity (PA) may be associated with individual differences in white matter microstructure and with grey matter volume of the hippocampus. Therefore, this study investigated the association between PA and white matter microstructure of pathways connecting to the hippocampus. A total of 33 young, healthy adults underwent magnetic resonance imaging (MRI). High angular resolution diffusion-weighted imaging and multi-component relaxometry MRI scans (multi-component driven equilibrium pulse observation of T1 and T2) were acquired for each participant. Activity levels (AL) of participants were calculated from 72-h actigraphy recordings. Tractography using the damped Richardson Lucy algorithm was used to reconstruct the fornix and bilateral parahippocampal cinguli (PHC). The mean fractional anisotropy (FA) and the myelin water fraction (MWF), a putative marker of myelination, were determined for each pathway. A positive correlation between both AL and FA and between AL and MWF were hypothesized for the three pathways. There was a selective positive correlation between AL and MWF in the right PHC (r = 0.482, p = 0.007). Thus, our results provide initial in vivo evidence for an association between myelination of the right PHC and PA in young healthy adults. Our results suggest that MWF may not only be more specific, but also more sensitive than FA to detect white matter microstructural alterations. If PA was to induce structural plasticity of the right PHC this may contribute to reverse structural alterations of the right PHC in neuropsychiatric disorder with hippocampal pathologies.

Cerebellar mechanisms for motor learning: Testing predictions from a large-scale computer simulation

The cerebellum is the major brain structure that contributes to our ability to improve movements through learning and experience. We have combined computer simulations with behavioral and lesion studies to investigate how modification of synaptic strength at two different sites within the cerebellum contributes to a simple form of motor learning—Pavlovian conditioning of the eyelid response. These studies are based on the wealth of knowledge about the intrinsic circuitry and physiology of the cerebellum and the straightforward manner in which this circuitry is engaged during eyelid conditioning. Thus, our simulations are constrained by the well-characterized synaptic organization of the cerebellum and further, the activity of cerebellar inputs during simulated eyelid conditioning is based on existing recording data. These simulations have allowed us to make two important predictions regarding the mechanisms underlying cerebellar function, which we have tested and confirmed with behavioral studies. The first prediction describes the mechanisms by which one of the sites of synaptic modification, the granule to Purkinje cell synapses (gr → Pkj) of the cerebellar cortex, could generate two time-dependent properties of eyelid conditioning—response timing and the ISI function. An empirical test of this prediction using small, electrolytic lesions of the cerebellar cortex revealed the pattern of results predicted by the simulations. The second prediction made by the simulations is that modification of synaptic strength at the other site of plasticity, the mossy fiber to deep nuclei synapses (mf → nuc), is under the control of Purkinje cell activity. The analysis predicts that this property should confer mf → nuc synapses with resistance to extinction. Thus, while extinction processes erase plasticity at the first site, residual plasticity at mf → nuc synapses remains. The residual plasticity at the mf → nuc site confers the cerebellum with the capability for rapid relearning long after the learned behavior has been extinguished. We confirmed this prediction using a lesion technique that reversibly disconnected the cerebellar cortex at various stages during extinction and reacquisition of eyelid responses. The results of these studies represent significant progress toward a complete understanding of how the cerebellum contributes to motor learning. ^

Análisis de la actividad neuronal y cerebral mediante técnicas de redes complejas

El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

Running enhances neurogenesis, learning, and long-term potentiation in mice

Running increases neurogenesis in the dentate gyrus of the hippocampus, a brain structure that is important for memory function. Consequently, spatial learning and long-term potentiation (LTP) were tested in groups of mice housed either with a running wheel (runners) or under standard conditions (controls). Mice were injected with bromodeoxyuridine to label dividing cells and trained in the Morris water maze. LTP was studied in the dentate gyrus and area CA1 in hippocampal slices from these mice. Running improved water maze performance, increased bromodeoxyuridine-positive cell numbers, and selectively enhanced dentate gyrus LTP. Our results indicate that physical activity can regulate hippocampal neurogenesis, synaptic plasticity, and learning.

A universal scaling law between gray matter and white matter of cerebral cortex

Neocortex, a new and rapidly evolving brain structure in mammals, has a similar layered architecture in species over a wide range of brain sizes. Larger brains require longer fibers to communicate between distant cortical areas; the volume of the white matter that contains long axons increases disproportionally faster than the volume of the gray matter that contains cell bodies, dendrites, and axons for local information processing, according to a power law. The theoretical analysis presented here shows how this remarkable anatomical regularity might arise naturally as a consequence of the local uniformity of the cortex and the requirement for compact arrangement of long axonal fibers. The predicted power law with an exponent of 4/3 minus a small correction for the thickness of the cortex accurately accounts for empirical data spanning several orders of magnitude in brain sizes for various mammalian species, including human and nonhuman primates.

Temporal distribution of the ganglion cell volleys in the normal rat optic nerve

We describe experiments on behaving rats with electrodes implanted on the cornea, in the optic chiasm, and on the visual cortex; in addition, two red light-emitting diodes (LED) are permanently attached to the skull over the left eye. Recordings timelocked to the LED flashes reveal both the local events at each electrode site and the orderly transfer of visual information from retina to cortex. The major finding is that every stimulus, regardless of its luminance, duration, or the state of retinal light adaptation, elicits an optic nerve volley with a latency of about 10 ms and a duration of about 300 ms. This phenomenon has not been reported previously, so far as we are aware. We conclude that the retina, which originates from the forebrain of the developing embryo, behaves like a typical brain structure: it translates, within a few hundred milliseconds, the chemical information in each pattern of bleached photoreceptors into a corresponding pattern of ganglion cell neuronal information that leaves via the optic nerve. The attributes of each rat ganglion cell appear to include whether the retinal neuropile calls on it to leave after a stimulus and, if so when, within a 300-ms poststimulus epoch. The resulting retinal analysis of the scene, on arrival at the cortical level, is presumed to participate importantly in the creation of visual perceptual experiences.

Lack of tissue glucocorticoid reactivation in 11β-hydroxysteroid dehydrogenase type 1 knockout mice ameliorates age-related learning impairments

11β-hydroxysteroid dehydrogenase type 1 (11β-HSD-1) intracellularly regenerates active corticosterone from circulating inert 11-dehydrocorticosterone (11-DHC) in specific tissues. The hippocampus is a brain structure particularly vulnerable to glucocorticoid neurotoxicity with aging. In intact hippocampal cells in culture, 11β-HSD-1 acts as a functional 11β-reductase reactivating inert 11-DHC to corticosterone, thereby potentiating kainate neurotoxicity. We examined the functional significance of 11β-HSD-1 in the central nervous system by using knockout mice. Aged wild-type mice developed elevated plasma corticosterone levels that correlated with learning deficits in the watermaze. In contrast, despite elevated plasma corticosterone levels throughout life, this glucocorticoid-associated learning deficit was ameliorated in aged 11β-HSD-1 knockout mice, implicating lower intraneuronal corticosterone levels through lack of 11-DHC reactivation. Indeed, aged knockout mice showed significantly lower hippocampal tissue corticosterone levels than wild-type controls. These findings demonstrate that tissue corticosterone levels do not merely reflect plasma levels and appear to play a more important role in hippocampal functions than circulating blood levels. The data emphasize the crucial importance of local enzymes in determining intracellular glucocorticoid activity. Selective 11β-HSD-1 inhibitors may protect against hippocampal function decline with age.

Expression of Drosophila mushroom body mutations in alternative genetic backgrounds: a case study of the mushroom body miniature gene (mbm).

Mutations in 12 genes regulating Drosophila melanogaster mushroom body (MB) development were each studied in two genetic backgrounds. In all cases, brain structure was qualitatively or quantitatively different after replacement of the "original" genetic background with that of the Canton Special wild-type strain. The mushroom body miniature gene (mbm) was investigated in detail. mbm supports the maintenance of MB Kenyon cell fibers in third instar larvae and their regrowth during metamorphosis. Adult mbm1 mutant females are lacking many or most Kenyon cell fibers and are impaired in MB-mediated associative odor learning. We show here that structural defects in mbm1 are apparent only in combination with an X-linked, dosage-dependent modifier (or modifiers). In the Canton Special genetic background, the mbm1 anatomical phenotype is suppressed, and MBs develop to a normal size. However, the olfactory learning phenotype is not fully restored, suggesting that submicroscopic defects persist in the MBs. Mutant mbm1 flies with full-sized MBs have normal retention but show a specific acquisition deficit that cannot be attributed to reductions in odor avoidance, shock reactivity, or locomotor behavior. We propose that polymorphic gene interactions (in addition to ontogenetic factors) determine MB size and, concomitantly, the ability to recognize and learn odors.

Prospective longitudinal voxel-based morphometry study of major depressive disorder in young individuals at high familial risk

BACKGROUND Previous neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development. METHOD Unaffected individuals (16-25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls ('low risk', n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures. RESULTS Significant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline. CONCLUSIONS These longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 +/- 1.9 years) and 14 matched controls (age: 71.4 +/- 0.9 years), each scanned twice (2.1 +/- 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials. (C) 2004 Elsevier Inc. All rights reserved.

Alcoholic neurobiology: Changes in dependence and recovery

This article presents the proceedings of a symposium held at the meeting of the International Society for Biomedical Research on Alcoholism (ISBRA) in Mannheim, Germany, in October, 2004. Chronic alcoholism follows a fluctuating course, which provides a naturalistic experiment in vulnerability, resilience, and recovery of human neural systems in response to presence, absence, and history of the neurotoxic effects of alcoholism. Alcohol dependence is a progressive chronic disease that is associated with changes in neuroanatomy, neurophysiology, neural gene expression, psychology, and behavior. Specifically, alcohol dependence is characterized by a neuropsychological profile of mild to moderate impairment in executive functions, visuospatial abilities, and postural stability, together with relative sparing of declarative memory, language skills, and primary motor and perceptual abilities. Recovery from alcoholism is associated with a partial reversal of CNS deficits that occur in alcoholism. The reversal of deficits during recovery from alcoholism indicates that brain structure is capable of repair and restructuring in response to insult in adulthood. Indirect support of this repair model derives from studies of selective neuropsychological processes, structural and functional neuroimaging studies, and preclinical studies on degeneration and regeneration during the development of alcohol dependence and recovery from dependence. Genetics and brain regional specificity contribute to unique changes in neuropsychology and neuroanatomy in alcoholism and recovery. This symposium includes state-of-the-art presentations on changes that occur during active alcoholism as well as those that may occur during recovery-abstinence from alcohol dependence. Included are human neuroimaging and neuropsychological assessments, changes in human brain gene expression, allelic combinations of genes associated with alcohol dependence and preclinical studies investigating mechanisms of alcohol induced neurotoxicity, and neuroprogenetor cell expansion during recovery from alcohol dependence.

An overview of psychological and neurobiological mechanisms by which early negative experiences increase risk of mood disorders

Objective: Early life experiences are associated with severe and long-lasting effects on behavioural and emotional functioning, which in turn are thought to increase the risk for unipolar depression and other disorders of affect regulation. The neurobiological and psychological mechanisms through which adverse early life experiences confer risk are poorly understood. Method: Alterations in brain structure and function in limbic and prefrontal cortical regions have been linked to early negative experiences and to mood disorders. Results: There are a number of psychological domains that may be dysfunctional in people with mood disorders, and which, if the dysfunction occurs prior to onset of mood symptoms, may signify a risk factor for depression. Cognitive dysfunction has been examined in patients with mood disorders, with some suggestion that changes in cognitive function may antedate the onset of mood symptoms, and may be exacerbated in those who experienced early negative trauma. Social cognition, including emotion comprehension, theory of mind and empathy, represent under-studied domains of psychological function that may be negatively influenced by early adverse experience. Temperament and personality factors may also leave people vulnerable to mood instability. Conclusion: This review summarizes the evidence for dysfunction in each of these domains for people with mood disorders.

The impact of general intellectual ability and white matter volume on the functional outcome of patients with bipolar disorder and their relatives

Background: There is substantial evidence that cognitive deficits and brain structural abnormalities are present in patients with Bipolar Disorder (BD) and in their first-degree relatives. Previous studies have demonstrated associations between cognition and functional outcome in BD patients but have not examined the role of brain morphological changes. Similarly, the functional impact of either cognition or brain morphology in relatives remains unknown. Therefore we focused on delineating the relationship between psychosocial functioning, cognition and brain structure, in relation to disease expression and genetic risk for BD. Methods: Clinical, cognitive and brain structural measures were obtained from 41 euthymic BD patients and 50 of their unaffected first-degree relatives. Psychosocial function was evaluated using the General Assessment of Functioning (GAF) scale. We examined the relationship between level of functioning and general intellectual ability (IQ), memory, attention, executive functioning, symptomatology, illness course and total gray matter, white matter and cerebrospinal fluid volumes. Limitations: Cross-sectional design. Results: Multiple regression analyses revealed that IQ, total white matter volume and a predominantly depressive illness course were independently associated with functional outcome in BD patients, but not in their relatives, and accounted for a substantial proportion (53%) of the variance in patients' GAF scores. There were no significant domain-specific associations between cognition and outcome after consideration of IQ. Conclusions: Our results emphasise the role of IQ and white matter integrity in relation to outcome in BD and carry significant implications for treatment interventions. © 2010 Elsevier B.V.

Dyslexia research at the turn of the 21st century:behavioural, neuroimaging and genetic findings

Behavioural studies have shown that dyslexics are a heterogeneous population and between-group comparisons are thus inadequate. Some subjects do not develop dyslexia despite having a deficit implicated in this disorder, which points to protective factors. Dyslexia co-occurs with ADHD, DCD, SLI, and SSD, so that future behavioural studies will need to screen and/or statistically control for other disorders. Studies of multiple cases of DPs with other developmental disorders are necessary. Neuroimaging findings show structural and/or functional brain abnormalities in language areas, V5/MT and the cerebellum. Future neuroimaging studies need to investigate the whole reading network and multiple cases. Six dyslexia risk genes have been found, mostly involved in neural migration, which may suggest dyslexia is a deficit of neuronal migration. However, it is not clear how these genes can restrict migration to specific brain areas. As a complex and heterogeneous disorder, dyslexia is likely to be associated with several mutated genes. ADHD and SSD are characterised by genetic risk factors which are partially shared with dyslexia, resulting in comorbidity. Future genetic studies need to focus on identifying other risk genes and pleiotropic genes involved in comorbidities, and linking genotypes implicated in dyslexia with brain structure. Any theory of dyslexia needs to take into account a multitude of risk and protective factors across behavioural, neural and genetic domains.

Programas de tertulia política en Twitter: un modelo neurocomunicativo de análisis del discurso

En este trabajo aplicamos a la red social Twitter un modelo de análisis del discurso político y mediático desarrollado en publicaciones previas, que permite hacer compatible el estudio de los datos discursivos con propuestas explicativas surgidas a propósito de la comunicación política (neurocomunicación) y de la comunicación digital (la red como quinto estado, convergencia, inteligencia colectiva). Asumimos que hay categorías del encuadre discursivo (frame) que pueden ser tratadas como indicadores de habilidades cognitivas y comunicativas. Analizamos estas categorías agrupándolas en tres dimensiones fundamentales: la intencional (ilocutividad del tuit, encuadre interpretativo de las etiquetas), referencial (temas, protagonistas), e interactiva (alineamiento estructural, predictibilidad; marcas de intertextualidad y dialogismo; afiliación partidista). El corpus consta de 4116 tuits: 3000 tuits pertenecientes a los programas Al Rojo Vivo (La Sexta: A3 Media), Las Mañanas Cuatro (Cuatro: Mediaset) y Los Desayunos de TVE (RTVE), 1116 tuits de seguidores de los programas, que corresponden a 45 tuits de cada programa. Los resultados confirman que el modelo permite establecer diferentes perfiles de subjetividad política en las cuentas de Twitter.