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The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. Written by investigators who have played an important role in developing the subject and in its pedagogical exposition, the current volume addresses the need for a textbook in this interdisciplinary area. The book is written for a broad spectrum of readers ranging from physical scientists, mathematicians, and statisticians wishing to educate themselves about neuroscience, to biologists who would like to learn time series analysis methods in particular and refresh their mathematical and statistical knowledge in general, through self-pedagogy. It may also be used as a supplement for a quantitative course in neurobiology or as a textbook for instruction on neural signal processing. The first part of the book contains a set of essays meant to provide conceptual background which are not technical and shall be generally accessible. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above (also available as part of the Chronux data analysis platform from http://chronux.org), and the fourth part contains special topics.
I think, therefore I am. The legendary pronouncement of philosopher René Descartes lingers as accepted wisdom in the Western world nearly four centuries after its author's death. But does thought really come first? Who actually runs the show: we, our thoughts, or the neurons firing within our brains? Walter J. Freeman explores how we control our behavior and make sense of the world around us. Avoiding determinism both in sociobiology, which proposes that persons' genes control their brains' functioning, and in neuroscience, which posits that their brains' disposition is molded by chemistry and environmental forces, Freeman charts a new course--one that gives individuals due credit and responsibility for their actions. Drawing upon his five decades of research in neuroscience, Freeman utilizes the latest advances in his field as well as perspectives from disciplines as diverse as mathematics, psychology, and philosophy to explicate how different human brains act in their chosen diverse ways. He clarifies the implications of brain imaging, by which neural activity can be observed during the course of normal movements, and shows how nonlinear dynamics reveals order within the fecund chaos of brain function.
Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field. The consideration of time or dynamics is fundamental for all aspects of mental activity—perception, cognition, and emotion—because the main feature of brain activity is the continuous change of the underlying brain states even in a constant environment. The application of nonlinear dynamics to the study of brain activity began to flourish in the 1990s when combined with empirical observations from modern morphological and physiological observations. This book offers perspectives on brain dynamics that draw on the latest advances in research in the field. It includes contributions from both theoreticians and experimentalists, offering an eclectic treatment of fundamental issues. Topics addressed range from experimental and computational approaches to transient brain dynamics to the free-energy principle as a global brain theory. The book concludes with a short but rigorous guide to modern nonlinear dynamics and their application to neural dynamics.
Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field. - Offers an in-depth overview of the rapidly evolving field of computational psychiatry - Written for academics, researchers, advanced students and clinicians in the fields of computational neuroscience, clinical neuroscience, psychiatry, clinical psychology, neurology and cognitive neuroscience - Provides a comprehensive survey of work from leaders in this field and a presentation of a range of computational psychiatry methods and approaches geared towards a broad array of psychiatric problems
In the last few years, advances in human structural and functional neuroimaging (fMRI, PET, EEG/MEG) have resulted in an explosion of studies investigating the anatomical and functional connectivity between different regions of the brain. More and more studies have employed resting and task-related connectivity analyses to assess functional interactions, and diffusion-weighted tractography to study white matter organization. Many of these studies have addressed normal human function, but recently, a number of investigators have turned their attention to examining brain disorders. The study of brain disorders is a complex endeavor; not only does it require understanding the normal brain, and the regions involved in a particular function, but also it needs a deeper understanding of brain networks and their dynamics. This Research Topic will provide the scientific community with an overview of how to apply connectivity methods to study brain disease, and with perspectives on what are the strength and limitations of each modality. For this Research Topic, we solicit both reviews and original research articles on the use of brain connectivity analysis, with non-human or human models, to explore neurological, psychiatric, developmental and neurodegenerative disorders from a system perspective. Connectivity studies that have focused on one or more of the following will be of particular interest: (1) detection of abnormal functional/structural connectivity; (2) neural plasticity, assessed by changes in connectivity, in patients with brain disorders; (3) assessment of therapy using connectivity measures; (4) relation of connectivity changes to behavioral changes.
From Brain Dynamics to the Mind: Spatiotemporal Neuroscience explores how the self and consciousness is related to neural events. Sections in the book cover existing models used to describe the mind/brain problem, recent research on brain mechanisms and processes and what they tell us about the self, consciousness and psychiatric disorders. The book presents a spatiotemporal approach to understanding the brain and the implications for artificial intelligence, novel therapies for psychiatric disorders, and for ethical, societal and philosophical issues. Pulling concepts from neuroscience, psychology and philosophy, the book presents a modern and complete look at what we know, what we can surmise, and what we may never know about the distinction between brain and mind. - Reviews models of understanding the mind/brain problem - Identifies neural processes involved in consciousness, sense of self and brain function - Includes concepts and research from neuroscience, psychology, cognitive science and philosophy - Discusses implications for AI, novel therapies for psychiatric disorders and issues of ethics - Suggests experimental designs and data analyses for future research on the mind/brain issue
Connectomic Deep Brain Stimulation (DBS) covers this highly efficacious treatment option for movement disorders such as Parkinson's Disease, Essential Tremor and Dystonia. The book examines its impact on distributed brain networks that span across the human brain in parallel with modern-day neuroimaging concepts and the connectomics of the brain. It asks several questions, including which cortical areas should DBS electrodes be connected in order to generate the highest possible clinical improvement? Which connections should be avoided? Could these connectomic insights be used to better understand the mechanism of action of DBS? How can they be transferred to individual patients, and more. This book is suitable for neuroscientists, neurologists and functional surgeons studying DBS. It provides practical advice on processing strategies and theoretical background, highlighting and reviewing the current state-of-the-art in connectomic surgery. - Written to provide a "hands-on" approach for neuroscience graduate students, as well as medical personnel from the fields of neurology and neurosurgery - Includes preprocessing strategies (such as co-registration, normalization, lead localization, VTA estimation and fiber-tracking approaches) - Presents references (key articles, books and protocols) for additional detailed study - Provides data analysis boxes in each chapter to help with data interpretation
How does the brain code and process incoming information, how does it recog nize a certain object, how does a certain Gestalt come into our awareness? One of the key issues to conscious realization of an object, of a Gestalt is the attention de voted to the corresponding sensory input which evokes the neural pattern underly ing the Gestalt. This requires that the attention be devoted to one set of objects at a time. However, the attention may be switched quickly between different objects or ongoing input processes. It is to be expected that such mechanisms are reflected in the neural dynamics: Neurons or neuronal assemblies which pertain to one object may fire, possibly in rapid bursts at a time. Such firing bursts may enhance the synaptic strength in the corresponding cell assembly and thereby form the substrate of short-term memory. However, we may well become aware of two different objects at a time. How can we avoid that the firing patterns which may relate to say a certain type of move ment (columns in V5) or to a color (V 4) of one object do not become mixed with those of another object? Such a blend may only happen if the presentation times be come very short (below 20-30 ms). One possibility is that neurons pertaining to one cell assembly fire syn chronously. Then different cell assemblies firing at different rates may code different information.
A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience.
How we raise young children is one of today's most highly personalized and sharply politicized issues, in part because each of us can claim some level of "expertise." The debate has intensified as discoveries about our development-in the womb and in the first months and years-have reached the popular media. How can we use our burgeoning knowledge to assure the well-being of all young children, for their own sake as well as for the sake of our nation? Drawing from new findings, this book presents important conclusions about nature-versus-nurture, the impact of being born into a working family, the effect of politics on programs for children, the costs and benefits of intervention, and other issues. The committee issues a series of challenges to decision makers regarding the quality of child care, issues of racial and ethnic diversity, the integration of children's cognitive and emotional development, and more. Authoritative yet accessible, From Neurons to Neighborhoods presents the evidence about "brain wiring" and how kids learn to speak, think, and regulate their behavior. It examines the effect of the climate-family, child care, community-within which the child grows.