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.

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.

This volume is based on contributions to the second Brain Dynamics Conference, held in Berlin on August 10-14, 1987, as a satellite conference of the Budapest Congress of the International Brain Research Organization. Like the volume resulting from the first conference, Dynamics of Sensory and Cognitive Processing by the Brain, the present work covers new approaches to brain function, with emphasis on electromagnetic fields, EEG, event-related potentials, connectivistic views, and neural networks. Close attention is also paid to research in the emerging field of deterministic chaos and strange attractors. The diversity of this collection of papers reflects a multipronged advance in a hitherto relatively neglected domain, i. e., the study of signs of dynamic processes in organized neural tissue in order both to explain them and to exploit them for clues to system function. The need is greater than ever for new windows. This volume reflects a historical moment, the moment when a relatively neglected field of basic research into available signs of dynamic processes ongoing in organized neural tissue is expanding almost explosively to complement other approaches. From the topics treated, this book should appeal, as did its predecessor, to neuroscientists, neurologists, scientists studying complex systems, artificial intelligence, and neural networks, psychobiologists, and all basic and clinical investigators concerned with new techniques of monitoring and analyzing the brain's electromagnetic activity.

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.

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.

Experts explore the maturation of nonlinear brain dynamics from a developmental perspective and consider the relationship of neurodevelopmental disorders to early disruption in dynamic coordination. This volume in the Strüngmann Forum Reports series explores the complex mechanisms that accompany the dynamic processes by which the brain evolves and matures. Integrating perspectives from multiple disciplines, the book identifies knowledge gaps and proposes innovative ways forward for this emerging area of cross-disciplinary study. The contributors examine maturation of nonlinear brain dynamics across systems from a developmental perspective and relate these organizing networks to the establishment of normative cognition and pathology seen in many neurodevelopmental disorders. The book looks at key mechanistic questions, including: What role does dynamic coordination play in the establishment and maintenance of brain networks and structural and functional connectivity? How are local and global functional networks assembled and transformed over normative development? To what degree do oscillatory patterns vary across development? What is the impact of critical periods, and which factors initiate and terminate such periods? It also explores the potential of new technologies and techniques to enhance understanding of normative development and to enable early identification and remediation of neurodevelopmental and neuropsychiatric disorders that may result from early disruption in dynamic coordination. Contributors Sylvain Baillet, Yehezkel Ben-Ari, April A. Benasich, Olivier Bertrand, Gyorgy Buzsáki, Alain Chédotal, Sam M. Doesburg, Gordin Fishell, Adriana Galván, Jennifer N. Gelinas, Jay Giedd, Pierre Gressens, Ileana L. Hanganu-Opatz, Rowshanak Hashemiyoon, Takao K. Hensch, Suzana Herculano-Houzel, Mark Hübener, Mark, Matthias Kaschube, Michael S. Kobor, Bryan Kolb, Thorsten Kolling, Jean-Philippe Lachaux, Ulman Lindenberger, Heiko J. Luhmann, Hannah Monyer, Sarah R. Moore, Charles A. Nelson III, Tomáš Paus, Patrick L. Purdon, Pasko Rakic, Urs Ribary, Akira Sawa, Terrence J. Sejnowski, Wolf Singer, Cheryl L. Sisk, Nicholas C. Spitzer, Michael P. Stryker, Migranka Sur, Peter J. Uhlhaas

It is a well-known fact of neurophysiology that neuronal responses to identically presented stimuli are extremely variable. This variability has in the past often been regarded as "noise." At the single neuron level, interspike interval (ISI) histograms constructed during either spontaneous or stimulus evoked activity reveal a Poisson type distribution. These observations have been taken as evidence that neurons are intrinsically "noisy" in their firing properties. In fact, the use of averaging techniques, like post-stimulus time histograms (PSTH) or event-related potentials (ERPs) have largely been justified based on the presence of what was believed to be noise in the neuronal responses. More recent attempts to measure the information content of single neuron spike trains have revealed that a surprising amount of information can be coded in spike trains even in the presence of trial-to-trial variability. Multiple single unit recording experiments have suggested that variability formerly attributed to noise in single cell recordings may instead simply reflect system-wide changes in cellular response properties. These observations raise the possibility that, at least at the level of neuronal coding, the variability seen in single neuron responses may not simply reflect an underlying noisy process. They further raise the very distinct possibility that noise may in fact contain real, meaningful information which is available for the nervous system in information processing. To understand how neurons work in concert to bring about coherent behavior and its breakdown in disease, neuroscientists now routinely record simultaneously from hundreds of different neurons and from different brain areas, and then attempt to evaluate the network activities by computing various interdependence measures, including cross correlation, phase synchronization and spectral coherence. This book examines neuronal variability from theoretical, experimental and clinical perspectives.

Memory itself is inseparable from all other brain functions and involves distributed dynamic neural processes. A wealth of publications in neuroscience literature report that the concerted action of distributed multiple oscillatory processes (EEG oscillations) play a major role in brain functioning. The analysis of function-related brain oscillatio

It is easy to imagine the excitement that pervaded the neurological world in the late 1920's and early 1930's when Berger's first descriptions of the electro encephalogram appeared. Berger was not the first to discover that changes in electric potential can be recorded from the surface of the head, but it was he who first systematized the method, and it was he who first proposed that explanatory correlations might be found between the electroencephalogram, brain processes, and behavioral states. An explosion of activity quickly fol lowed: studies were made of the brain waves in virtually every conceivable behavioral state, ranging from normal human subjects to those with major psychoses or with epilepsy, to state changes such as the sleep-wakefulness transition. There evolved from this the discipline of Clinical Electroencepha lography which rapidly took a valued place in clinical neurology and neuro surgery. Moreover, use of the method in experimental animals led to a further understanding of such state changes as attention-inattention, arousal, and sleep and wakefulness. The evoked potential method, derived from electro encephalography, was used in neurophysiological research to construct pre cise maps of the projection of sensory systems upon the neocortex. These maps still form the initial guides to studies of the cortical mechanisms in sensation and perception. The use of the event-related potential paradigm has proved useful in studies of the brain mechanisms of some cognitive functions of the brain.