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When neurons fire up: Study sheds light on rhythms of the brain
August 06, 2008
BLOOMINGTON, Ind. -- In our brains, groups of neurons fire up simultaneously for just milliseconds at a time, in random rhythms, similar to twinkling lightning bugs in our backyards. New research from neuroscientists at Indiana University and the University of Montreal provides a model -- a rhyme and reason -- for this random synchronization. The findings, both of which appear in the Journal of Neuroscience this week, draw on the variability and creative nature of neurons -- no two are exactly the same, providing for a rich and ever-changing repertoire of brain activity. The findings expand scientists' understanding of brain rhythms, both reoccurring and random, and shed light on the decades-old mystery of how the brain learns temporal patterns. "Our model is proposing a way that the brain processes temporal information and how this can vary over time" said Jean-Philippe Thivierge, a post-doctorate researcher in IU Bloomington's Department of Psychological and Brain Sciences. A better understanding of rhythms in the brain -- how to create them or stop them -- would help researchers studying such neural diseases as epilepsy, which involves seizures or uncontrollable rhythms in the brain. Thivierge and co-author Paul Cisek, an assistant professor at the University of Montreal, created a mathematical model for how hundreds of neurons interact after being stimulated by an electric current. They propose that the random synchronization, which occurs in large populations of neurons, results from "positive excitatory feedback originating from recurrent connections between the cells." The synchronization involves most of the cells in the group but begins with a preferred small group of cells -- like "elite" cells -- that tend to become active just before all the others do. When enough cells in the group become active, a threshold, or "point of no return" is reached where all the cells become active and their activity spikes. The study also demonstrates how neural activity can spike periodically or rhythmically. When researchers introduced a specific rhythm to the model, they discovered that the model could learn and repeat the rhythm. Scientists have known for 50 years that the brain could do this, but the mechanism was unknown until now. Thivierge said the mechanism is based on how the neurons come together to motivate each other to fire in a specific, periodic way, following the rhythmic stimuli. The spontaneous neural activity modeled in this study has been detected in several regions of the brain as well as in other species. The authors conjecture that the benefits of such spontaneity come in the brain's ability to be more flexible and responsive to external events, that the random synchronization can prevent the brain from remaining "stuck" in a particular state. "It seems like when you're in a more flexible brain state, it's easier for you to redirect your attention to new and important things," Thivierge said. Indiana University

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Synchronization: From Simple to Complex (Springer Series in Synergetics)
by Alexander Balanov (Author), Natalia Janson (Author), Dmitry Postnov (Author), Olga Sosnovtseva (Author)
This fascinating work is devoted to the fundamental phenomenon in physics – synchronization that occurs in coupled non-linear dissipative oscillators. Examples of such systems range from mechanical clocks to population dynamics, from the human heart to neural networks. The main purpose of this book is to demonstrate that the complexity of synchronous patterns of real oscillating systems can be described in the framework of the general approach, and the authors study this phenomenon as applied to oscillations of different types, such as those with periodic, chaotic, noisy and noise-induced nature.
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Computer Network Time Synchronization: The Network Time Protocol
by David L. Mills (Author)
What started with the sundial has, thus far, been refined to a level of precision based on atomic resonance: Time. Our obsession with time is evident in this continued scaling down to nanosecond resolution and beyond. But this obsession is not without warrant. Precision and time synchronization are critical in many applications, such as air traffic control and stock trading, and pose complex and important challenges in modern information networks.
Penned by David L. Mills, the original developer of the Network Time Protocol (NTP), Computer Network Time Synchronization: The Network Time Protocol takes a broad look at the architecture, protocols, and algorithms involved in time dissemination, distribution, and synchronization. Focused on the fourth generation of NTP, Mills' magnum...
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Digital Communication Receivers, Synchronization, Channel Estimation, and Signal Processing
by Heinrich Meyr (Author), Marc Moeneclaey (Author), Stefan A. Fechtel (Author)
Digital Communication Receivers Synchronization, Channel Estimation, and Signal Processing Digital Communication Receivers offers a complete treatment on the theoretical and practical aspects of synchronization and channel estimation from the standpoint of digital signal processing. The focus on these increasingly important topics, the systematic approach to algorithm development, and the linked algorithm-architecture methodology in digital receiver design are unique features of this book. The material is structured according to different classes of transmission channels. In Part C, baseband transmission over wire or optical fiber is addressed. Part D covers passband transmission over satellite or terrestrial wireless channels. Part E deals with transmission over fading channels. Designed...
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Synchronization in Complex Networks of Nonlinear Dynamical Systems
by Chai Wah Wu (Author)
This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ideas from systems theory, linear algebra and graph theory and the synergy between them that are necessary to derive synchronization conditions. Many of the results, which have been obtained fairly...
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Synchronization in Coupled Chaotic Circuits & System (World Scientific Series on Nonlinear Science, Series a)
by Chai Wah Wu (Author)
[World Scientific Series on Nonlinear Science, Series A, Volume 41> Invaluable study of synchronization of coupled chaotic circuits and systems, as well as its applications. Shows how one can use stability results in nonlinear control to derive synchronization criteria for coupled chaotic circuits and systems.
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Chaos: Concepts, Control and Constructive Use (Understanding Complex Systems)
by Yurii Bolotin (Author), Anatoli Tur (Author), Vladimir Yanovsky (Author)
The study of chaotic behaviour in nonlinear, dynamical systems is now a well established research domain with ramifications into all fields of sciences, spanning a vast range of applications, from celestial mechanics, via climate change, to the functioning of brownian motors in cells. A more recent discovery is that chaos can be controlled and, under appropriate conditions, can actually be constructive in the sense of becoming a control parameter itself for the system under investigation, stochastic resonance being a prime example. The present work is putting emphasis on the latter aspects, and after recalling the paradigm changes introduced by the concept of chaos, leads the reader skillfully through the basics of chaos control by detailing relevant algorithms for both Hamiltonian...
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Common-bandwidth transmission of data signals: And wide-band pseudonoise synchronization waveforms (Philips research reports. Supplements)
by L. E Zegers (Author)
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Networks of the Brain
by Olaf Sporns (Author)
Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. Modern network approaches are beginning to reveal fundamental principles of brain architecture and function, and in Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those...
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Adaptive Networks: Theory, Models and Applications (Understanding Complex Systems)
by Thilo Gross (Editor), Hiroki Sayama (Editor)
With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of...
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Network Science: Theory and Applications
by Ted G. Lewis (Author)
A comprehensive look at the emerging science of networksNetwork science helps you design faster, more resilient communication networks; revise infrastructure systems such as electrical power grids, telecommunications networks, and airline routes; model market dynamics; understand synchronization in biological systems; and analyze social interactions among people.This is the first book to take a comprehensive look at this emerging science. It examines the various kinds of networks (regular, random, small-world, influence, scale-free, and social) and applies network processes and behaviors to emergence, epidemics, synchrony, and risk. The book's uniqueness lies in its integration of concepts across computer science, biology, physics, social network analysis, economics, and marketing.The...
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