In this EBook, we highlight how newly emerging techniques for non-invasive manipulation of the human brain, combined with simultaneous recordings of neural activity, contribute to the understanding of brain functions and neural dynamics in humans. A growing body of evidence indicates that the neural dynamics (e.g., oscillations, synchrony) are important in mediating information processing and networking for various functions in the human brain. Most of previous studies on human brain dynamics, however, show correlative relationships between brain functions and patterns of neural dynamics measured by imaging methods such as electroencephalography (EEG), magnetoencephalography (MEG), near-infrared spectroscopy (NIRS), positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). In contrast, manipulative approaches by non-invasive brain stimulation (NIBS) have been developed and extensively used. These approaches include transcranial magnetic stimulation (TMS) and transcranial electric stimulation (tES) such as transcranial direct current stimulation (tDCS), alternating current stimulation (tACS), and random noise stimulation (tRNS), which can directly manipulate neural dynamics in the intact human brain. Although the neural-correlate approach is a strong tool, we think that manipulative approaches have far greater potential to show causal roles of neural dynamics in human brain functions. There have been technical challenges with using manipulative methods together with imaging methods. However, thanks to recent technical developments, it has become possible to use combined methods such as TMS–EEG coregistration. We can now directly measure and manipulate neural dynamics and analyze functional consequences to show causal roles of neural dynamics in various brain functions. Moreover, these combined methods can probe brain excitability, plasticity and cortical networking associated with information processing in the intact human brain. The contributors to this EBook have succeeded in showcasing cutting-edge studies and demonstrate the huge impact of their approaches on many areas in human neuroscience and clinical applications.

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.

One of the Most Rapidly Advancing Fields in Modern Neuroscience The success of molecular biology and the new tools derived from molecular genetics have revolutionized pain research and its translation to therapeutic effectiveness. Bringing together recent advances in modern neuroscience regarding genetic studies in mice and humans and the practical

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

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.

Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

Within our knowledge, the series of the International Conference on Cognitive Neurodynamics (ICCN) is the only conference series dedicating to cognitive neurodynamis. This volume is the proceedings of the 3rd International Conference on Cognitive Neurodynamics held in 2011, which reviews the progress in this field since the 1st ICCN - 2007. The topics include: Neural coding and realistic neural network dynamics, Neural population dynamics, Firing Oscillations and Patterns in Neuronal Networks, Brain imaging, EEG, MEG, Sensory and Motor Dynamics, Global cognitive function, Multi-scalar Neurodynamics - from Physiology to Systems Theory, Neural computing, Emerging Technologies for Brain Computer Interfaces, Neural dynamics of brain disorders.