Hierarchical modularity in human brain functional networks

The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions

Structure Learning in Coupled Dynamical Systems and Dynamic Causal Modelling

Identifying a coupled dynamical system out of many plausible candidates, each of which could serve as the underlying generator of some observed measurements, is a profoundly ill posed problem that commonly arises when modelling real world phenomena. In this review, we detail a set of statistical procedures for inferring the structure of nonlinear coupled dynamical systems (structure learning), which has proved useful in neuroscience research. A key focus here is the comparison of competing models of (ie, hypotheses about) network architectures and implicit coupling functions in terms of their Bayesian model evidence. These methods are collectively referred to as dynamical casual modelling (DCM). We focus on a relatively new approach that is proving remarkably useful; namely, Bayesian model reduction (BMR), which enables rapid evaluation and comparison of models that differ in their network architecture. We illustrate the usefulness of these techniques through modelling neurovascular coupling (cellular pathways linking neuronal and vascular systems), whose function is an active focus of research in neurobiology and the imaging of coupled neuronal systems

Neuroenhancement: Enhancing brain and mind in health and in disease

AbstractHumans have long used cognitive enhancement methods to expand the proficiency and range of the various mental activities that they engage in, including writing to store and retrieve information, and computers that allow them to perform myriad activities that are now commonplace in the internet age. Neuroenhancement describes the use of neuroscience-based techniques for enhancing cognitive function by acting directly on the human brain and nervous system, altering its properties to increase performance. Cognitive neuroscience has now reached the point where it may begin to put theory derived from years of experimentation into practice. This special issue includes 16 articles that employ or examine a variety of neuroenhancement methods currently being developed to increase cognition in healthy people and in patients with neurological or psychiatric illness. This includes transcranial electromagnetic stimulation methods, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), along with deep brain stimulation, neurofeedback, behavioral training techniques, and these and other techniques in conjunction with neuroimaging. These methods can be used to improve attention, perception, memory and other forms of cognition in healthy individuals, leading to better performance in many aspects of everyday life. They may also reduce the cost, duration and overall impact of brain and mental illness in patients with neurological and psychiatric illness. Potential disadvantages of these techniques are also discussed. Given that the benefits of neuroenhancement outweigh the potential costs, these methods could potentially reduce suffering and improve quality of life for everyone, while further increasing our knowledge about the mechanisms of human cognition

Characterising brain connectivity along the lifespan in a rodent model of healthy ageing

The brain parenchyma undergoes several structural changes throughout life, which have a ma- jor impact on its physiological evolution, and which are behaviorally reflected as changes in cognition and ability. A key question is how age-related structural alterations impact the func- tion of the different areas. Functional connectivity, measured as correlation between brain re- gions during the resting state Magnetic Resonance Imaging (MRI), is a quantitative measure of function that can be reliably used to characterize the evolution of the communication between regions across the lifespan. However, most of the works so far have done it with a hypothesis driven approach. The present work aims to identify the functional connectivity patterns of the whole brain during resting state in a rodent model of healthy ageing. For this purpose, we have followed the standard workflow recently proposed in a consensus paper on functional imag- ing processing in preclinical MRI. We have set up a longitudinal functional MRI experiment to measure functional connectivity in rats at different times. Independent component analysis has been used to identify characteristic resting-state networks and compare them between three different ages, corresponding to adulthood to early senescence. The goal is to highlight region- , sex-, and age-specific patterns that drive the physiological decline in cognition observed in senescence, with potential to identify vulnerable regions in and define targets for intervention. Our results uncovered patterns of increased functional connectivity between adulthood and senescence in several key regions controlling the functions known to be affected by age. Such increase in connectivity can be explained as a compensatory mechanism that allows the brain to cope with reduced microstructural integrity. The study of healthy ageing in absence of disease sets the baseline for the identification of pathological conditionsEl parénquima cerebral experimenta varios cambios estructurales a lo largo de la vida, que tienen un gran impacto en su evolución fisiológica, y que se reflejan conductualmente como cambios en la cognición y la capacidad. Una cuestión clave es cómo repercuten las alteraciones estructurales relacionadas con la edad en la función de las distintas áreas. La conectividad fun- cional, medida como correlación entre regiones cerebrales durante la Resonancia Magnética (RM) en estado de reposo, es una medida cuantitativa de la función que puede utilizarse de forma fiable para caracterizar la evolución de la comunicación entre regiones a lo largo de la vida. Sin embargo, la mayoría de los trabajos realizados hasta ahora lo han hecho con un en- foque basado en hipótesis. El presente trabajo pretende identificar los patrones de conectividad funcional de todo el cerebro durante el estado de reposo en un modelo de roedor de envejec- imiento sano. Para ello, hemos seguido el flujo de trabajo estándar propuesto recientemente en un documento de consenso sobre el procesamiento de imágenes funcionales en RM preclínica. Hemos establecido un experimento de RM funcional longitudinal para medir la conectividad funcional en ratas en diferentes momentos. Se ha utilizado el análisis de componentes indepen- dientes para identificar redes características en estado de reposo y compararlas entre tres edades diferentes, correspondientes a la edad adulta y a la senescencia temprana. El objetivo es destacar los patrones específicos de región, sexo y edad que impulsan el declive fisiológico de la cogni- ción observado en la senescencia, con potencial para identificar regiones vulnerables y definir objetivos de intervención. Nuestros resultados descubrieron patrones de aumento de la conec- tividad funcional entre la edad adulta y la senescencia en varias regiones clave que controlan las funciones que se sabe que se ven afectadas por la edad. Este aumento de la conectividad puede explicarse como un mecanismo compensatorio que permite al cerebro hacer frente a la reducción de la integridad microestructural. El estudio del envejecimiento sano en ausencia de enfermedad sienta las bases para la identificación de condiciones patológicasEl parènquima cerebral experimenta diversos canvis estructurals al llarg de la vida, que tenen un gran impacte en la seua evolució fisiològica, i que es reflecteixen conductualment com a canvis en la cognició i la capacitat. Una qüestió clau és com repercuteixen les alteracions estructurals relacionades amb l’edat en la funció de les diferents àrees. La connectivitat funcional, mesurada com a correlació entre regions cerebrals durant la Ressonància Magnètica (RM) en estat de repòs, és una mesura quantitativa de la funció que pot utilitzar-se de manera fiable per a carac- teritzar l’evolució de la comunicació entre regions al llarg de la vida. No obstant això, la majoria dels treballs realitzats fins ara ho han fet amb un enfocament basat en hipòtesi. El present tre- ball pretén identificar els patrons de connectivitat funcional de tot el cervell durant l’estat de repòs en un model de rosegador d’envelliment sa. Per a això, hem seguit el flux de treball estàndard proposat recentment en un document de consens sobre el processament d’imatges funcionals en RM preclínica. Hem establit un experiment de RM funcional longitudinal per a mesurar la connectivitat funcional en rates en diferents moments. S’ha utilitzat l’anàlisi de com- ponents independents per a identificar xarxes característiques en estat de repòs i comparar-les entre tres edats diferents, corresponents a l’edat adulta i a la senescència primerenca. L’objectiu és destacar els patrons específics de regió, sexe i edat que impulsen el declivi fisiològic de la cognició observat en la senescència, amb potencial per a identificar regions vulnerables i definir objectius d’intervenció. Els nostres resultats van descobrir patrons d’augment de la connec- tivitat funcional entre l’edat adulta i la senescència en diverses regions clau que controlen les funcions que se sap que es veuen afectades per l’edat. Aquest augment de la connectivitat pot explicar-se com un mecanisme compensatori que permet al cervell fer front a la reducció de la integritat microestructural. L’estudi de l’envelliment sa en absència de malaltia estableix les bases per a la identificació de condicions patològique