Download Free Cortical Connectivity Book in PDF and EPUB Free Download. You can read online Cortical Connectivity and write the review.

By means of quantitative analysis of the tissue components in the cortex of the mouse, this book presents an overall picture of the cortical network which is then related to various theories on cortical function. Centering around the idea of a diffuse network in a fairly homogeneous population of excitatory neurons, that of the pyramidal cells, it shows that the whole organisation in the cortical skeleton of pryramidal cells corresponds well with the idea of an associative memory and with the theory of cell assemblies. Provides the reader with information on quantitative neuroanatomy and also on the methods used, in particular those that vary from the norm.
Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this b
This book has brought together leading investigators who work in the new arena of brain connectomics. This includes ‘macro-connectome’ efforts to comprehensively chart long-distance pathways and functional networks; ‘micro-connectome’ efforts to identify every neuron, axon, dendrite, synapse, and glial process within restricted brain regions; and ‘meso-connectome’ efforts to systematically map both local and long-distance connections using anatomical tracers. This book highlights cutting-edge methods that can accelerate progress in elucidating static ‘hard-wired’ circuits of the brain as well as dynamic interactions that are vital for brain function. The power of connectomic approaches in characterizing abnormal circuits in the many brain disorders that afflict humankind is considered. Experts in computational neuroscience and network theory provide perspectives needed for synthesizing across different scales in space and time. Altogether, this book provides an integrated view of the challenges and opportunities in deciphering brain circuits in health and disease.
The study and modulation of cortical connections is a rapidly growing area in neuroscience. This unique book by prominent researchers in the field covers recent advances in this area. The first section of the book describes studies of cortical connections, modulation of cortical connectivity and changes in cortical connections with activities such as motor learning and grasping in primates. The second section covers the use of non-invasive brain stimulation to study and modulate cortical connectivity in humans. The last section describes changes in brain connectivity in neurological and psychiatric diseases, and potential new treatments that manipulate brain connectivity. This book provides an up-to-date view of the study of cortical connectivity, and covers its role in both fundamental neuroscience and potential clinical applications.
Volume 5 of Cerebral Cortex completes the sequence of three volumes on the individual functional areas of the cerebral cortex by covering the somatosensory and motor areas. However, the chapters on these areas lead naturally to a series of others on patterns of connectivity in the cortex, intracortical and subcortical, so that the volume as a whole achieves a much broader viewpoint. The individual chapters on the sensory-motor areas reflect the considerable diversity of interest within the field, for each of the authors has given his or her chapter a different emphasis, reflecting in part topical interest and in part the body of data resulting from work in a particular species. In considering the functional organization of the somatosensory cortex, Robert Dykes and Andre Ruest have chosen to concentrate on the nature of the mapping process and its significance. Harold Burton, in his chapter on the somatosensory fields buried in the sylvian fissure, shows how critical is an understanding of this mapping process in the functional subdivision of the cortex. A frequently overlooked subdivision of the cortex, the vestibular region, is given the emphasis it deserves in a chapter by John Fredrickson and Allan Rubin. The further functional subdivisions that occur within the first somatosensory area are given an anatom ical basis in the review by Edward Jones of connectivity in the primate sensory motor cortex.
In the last ten years many different brain imaging devices have conveyed a lot of information about the brain functioning in different experimental conditions. In every case, the biomedical engineers, together with mathematicians, physicists and physicians are called to elaborate the signals related to the brain activity in order to extract meaningful and robust information to correlate with the external behaviour of the subjects. In such attempt, different signal processing tools used in telecommunications and other field of engineering or even social sciences have been adapted and re-used in the neuroscience field. The present book would like to offer a short presentation of several methods for the estimation of the cortical connectivity of the human brain. The methods here presented are relatively simply to implement, robust and can return valuable information about the causality of the activation of the different cortical areas in humans using non invasive electroencephalographic recordings. The knowledge of such signal processing tools will enrich the arsenal of the computational methods that a engineer or a mathematician could apply in the processing of brain signals.
This book brings together leading investigators who represent various aspects of brain dynamics with the goal of presenting state-of-the-art current progress and address future developments. The individual chapters cover several fascinating facets of contemporary neuroscience from elementary computation of neurons, mesoscopic network oscillations, internally generated assembly sequences in the service of cognition, large-scale neuronal interactions within and across systems, the impact of sleep on cognition, memory, motor-sensory integration, spatial navigation, large-scale computation and consciousness. Each of these topics require appropriate levels of analyses with sufficiently high temporal and spatial resolution of neuronal activity in both local and global networks, supplemented by models and theories to explain how different levels of brain dynamics interact with each other and how the failure of such interactions results in neurologic and mental disease. While such complex questions cannot be answered exhaustively by a dozen or so chapters, this volume offers a nice synthesis of current thinking and work-in-progress on micro-, meso- and macro- dynamics of the brain.
The macro connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform cognitive functions. It embodies the notion of representing, analysing, and understanding all connections within the brain as a network, while the subdivision of the brain into interacting cortical units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Parcellations derived from anatomical brain atlases or random parcellations are traditionally used for node identification, however these approaches do not always fully reflect the functional/structural organisation of the brain. Connectivity-driven methods have arisen only recently, aiming to delineate parcellations that are more faithful to the underlying connectivity. Such parcellation methods face several challenges, including but not limited to poor signal-to-noise ratio, the curse of dimensionality, and functional/structural variations inherent in individual brains, which are only limitedly addressed by the current state of the art. In this thesis, we present robust and fully-automated methods for the subdivision of the entire human cerebral cortex based on connectivity information. Our contributions are four-fold: First, we propose a clustering approach to delineate a cortical parcellation that provides a reliable abstraction of the brain's functional organisation. Second, we cast the parcellation problem as a feature reduction problem and make use of manifold learning and image segmentation techniques to identify cortical regions with distinct structural connectivity patterns. Third, we present a multi-layer graphical model that combines within- and between-subject connectivity, which is then decomposed into a cortical parcellation that can represent the whole population, while accounting for the variability across subjects. Finally, we conduct a large-scale, systematic comparison of existing parcellation methods, with a focus on providing some insight into the reliability of brain parcellations in terms of reflecting the underlying connectivity, as well as, revealing their impact on network analysis. We evaluate the proposed parcellation methods on publicly available data from the Human Connectome Project and a plethora of quantitative and qualitative evaluation techniques investigated in the literature. Experiments across multiple resolutions demonstrate the accuracy of the presented methods at both subject and group levels with regards to reproducibility and fidelity to the data. The neuro-biological interpretation of the proposed parcellations is also investigated by comparing parcel boundaries with well-structured properties of the cerebral cortex. Results show the advantage of connectivity-driven parcellations over traditional approaches in terms of better fitting the underlying connectivity. However, the benefit of using connectivity to parcellate the brain is not always as clear regarding the agreement with other modalities and simple network analysis tasks carried out across healthy subjects. Nonetheless, we believe the proposed methods, along with the systematic evaluation of existing techniques, offer an important contribution to the field of brain parcellation, advancing our understanding of how the human cerebral cortex is organised at the macroscale.
In the last ten years many different brain imaging devices have conveyed a lot of information about the brain functioning in different experimental conditions. In every case, the biomedical engineers, together with mathematicians, physicists and physicians are called to elaborate the signals related to the brain activity in order to extract meaningful and robust information to correlate with the external behavior of the subjects. In such attempt, different signal processing tools used in telecommunications and other field of engineering or even social sciences have been adapted and re-used in the neuroscience field. The present book would like to offer a short presentation of several methods for the estimation of the cortical connectivity of the human brain. The methods here presented are relatively simply to implement, robust and can return valuable information about the causality of the activation of the different cortical areas in humans using non invasive electroencephalographic recordings. The knowledge of such signal processing tools will enrich the arsenal of the computational methods that a engineer or a mathematician could apply in the processing of brain signals. Table of Contents: Introduction / Estimation of the Effective Connectivity from Stationary Data by Structural Equation Modeling / Estimation of the Functional Connectivity from Stationary Data by Multivariate Autoregressive Methods / Estimation of Cortical Activity by the use of Realistic Head Modeling / Application: Estimation of Connectivity from Movement-Related Potentials / Application to High-Resolution EEG Recordings in a Cognitive Task (Stroop Test) / Application to Data Related to the Intention of Limb Movements in Normal Subjects and in a Spinal Cord Injured Patient / The Instantaneous Estimation of the Time-Varying Cortical Connectivity by Adaptive Multivariate Estimators / Time-Varying Connectivity from Event-Related Potentials