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This book illustrates the thrust of the scientific community to use machine learning concepts for tackling a complex problem: given time series of neuronal spontaneous activity, which is the underlying connectivity between the neurons in the network? The contributing authors also develop tools for the advancement of neuroscience through machine learning techniques, with a focus on the major open problems in neuroscience. While the techniques have been developed for a specific application, they address the more general problem of network reconstruction from observational time series, a problem of interest in a wide variety of domains, including econometrics, epidemiology, and climatology, to cite only a few. divThe book is designed for the mathematics, physics and computer science communities that carry out research in neuroscience problems. The content is also suitable for the machine learning community because it exemplifies how to approach the same problem from different perspectives./divdivbr/divdivbr
Adiabatic quantum computation (AQC) is an alternative to the better-known gate model of quantum computation. The two models are polynomially equivalent, but otherwise quite dissimilar: one property that distinguishes AQC from the gate model is its analog nature. Quantum annealing (QA) describes a type of heuristic search algorithm that can be implemented to run in the ``native instruction set'' of an AQC platform. D-Wave Systems Inc. manufactures {quantum annealing processor chips} that exploit quantum properties to realize QA computations in hardware. The chips form the centerpiece of a novel computing platform designed to solve NP-hard optimization problems. Starting with a 16-qubit protot...
Closed-loop neurophysiology has been accelerated by recent software and hardware developments and by the emergence of novel tools to control neuronal activity with spatial and temporal precision, in which stimuli are delivered in real time based on recordings or behavior. Real-time stimulation feedback enables a wide range of innovative studies of information processing and plasticity in neuronal networks. This Research Topic e-Book comprises 16 Original Research Articles, seven Methods Articles, and seven Reviews, Mini- Reviews, and Perspectives, all peer-reviewed and published in Frontiers in Neural Circuits. The contributions deal with closed loop neurophysiology experiments at a variety of levels of neural circuit complexity. Some include modeling and theoretical analyses. New enabling technologies and techniques are described. Novel work is presented from experiments in vitro, in vivo, and in humans, along with their clinical and technological implications for improving the human condition.
The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion. Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables. In the last years...
Analysis of information transfer has found rapid adoption in neuroscience, where a highly dynamic transfer of information continuously runs on top of the brain's slowly-changing anatomical connectivity. Measuring such transfer is crucial to understanding how flexible information routing and processing give rise to higher cognitive function. Directed Information Measures in Neuroscience reviews recent developments of concepts and tools for measuring information transfer, their application to neurophysiological recordings and analysis of interactions. Written by the most active researchers in the field the book discusses the state of the art, future prospects and challenges on the way to an ef...
The two-volume set LNCS 3561 and LNCS 3562 constitute the refereed proceedings of the First International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2005, held in Las Palmas, Canary Islands, Spain in June 2005. The 118 revised papers presented are thematically divided into two volumes; the first includes all the contributions mainly related with the methodological, conceptual, formal, and experimental developments in the fields of Neurophysiology and cognitive science. The second volume collects the papers related with bioinspired programming strategies and all the contributions related with the computational solutions to engineering problems in different application domains.
Figures of Chance II: Chance in Theory and Practice proposes a multidisciplinary analysis of cultural phenomena related to notions of chance and contingency. Alongside its transhistorical companion volume (Figures of Chance I), it considers how the projective and predictive capacity of societies is shaped by representations and cultural models of a reality that is understood, by varying degrees, to be contingent, unpredictable, or chaotic. This volume reevaluates the role played by figurative representations of chance in contemporary discourses about chance and contingency. Written by seven interdisciplinary teams, and encompassing philosophy, literature, history of science, sociology, mathematics, cognitive science, information science, and art history, this text puts scientific conceptions of chance into dialogue with their contemporary literary and artistic representations. It thus brings out the central role played by art in the human perception of chance, and in our methods for projecting the future, in order to better understand contemporary human attitudes in the face of risk.
An exhilarating, genre-bending exploration of curiosity’s powerful capacity to connect ideas and people. Curious about something? Google it. Look at it. Ask a question. But is curiosity simply information seeking? According to this exhilarating, genre-bending book, what’s left out of the conventional understanding of curiosity are the wandering tracks, the weaving concepts, the knitting of ideas, and the thatching of knowledge systems—the networks, the relations between ideas and between people. Curiosity, say Perry Zurn and Dani Bassett, is a practice of connection: it connects ideas into networks of knowledge, and it connects knowers themselves, both to the knowledge they seek and to...
The two-volume set LNCS 5601 and LNCS 5602 constitutes the refereed proceedings of the Third International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2009, held in Santiago de Compostela, Spain, in June 2009. The 108 revised papers presented are thematically divided into two volumes. The first volume includes papers relating the most recent collaborations with Professor Mira and contributions mainly related with theoretical, conceptual and methodological aspects linking AI and knowledge engineering with neurophysiology, clinics and cognition. The second volume contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.