Directed Information Measures in Neuroscience by Michael Wibral, Raul Vicente, Joseph T. Lizier

By Michael Wibral, Raul Vicente, Joseph T. Lizier

Analysis of knowledge move has discovered quick adoption in neuroscience, the place a hugely dynamic move of knowledge constantly runs on most sensible of the brain's slowly-changing anatomical connectivity. Measuring such move is essential to realizing how versatile details routing and processing supply upward push to raised cognitive functionality. Directed info Measures in Neuroscience stories contemporary advancements of ideas and instruments for measuring details move, their program to neurophysiological recordings and research of interactions. Written by means of the main lively researchers within the box the e-book discusses the state-of-the-art, destiny customers and demanding situations that allows you to an effective evaluate of neuronal info move. Highlights comprise the theoretical quantification and sensible estimation of data move, description of move in the community in area and time, multivariate directed measures, details decomposition between a suite of stimulus/responses variables and the relation among interventional and observational causality. functions to neural information units and tips that could open resource software program spotlight the usefulness of those measures in experimental neuroscience. With state of the art mathematical advancements, computational options and functions to actual info units, this publication can be of gain to all graduate scholars and researchers drawn to detecting and knowing the data move among parts of advanced systems.

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The generality of the information theory approach endows it with the ability to deal with a diversity of systems and still employ a common currency, the bit. Conceptually, information theoretic measures are very appealing because they stem from a simple and elegant set of axioms that include intuitive properties such as that the information gathered from independent sources should be additive. Also concepts like synergy and redundancy can be naturally formulated in information theoretic terms [10, 11].

The bidirectional communication theory–a generalization of information theory. IEEE Transactions on Communications 21(12), 1345–1351 (1973) 49. : Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. Henry Holt and Co. , New York (1982) 50. : Causality, feedback and directed information. In: Proc. Int. Symp. Information Theory Application (ISITA 1990), pp. 303–305 (1990) Transfer Entropy in Neuroscience 35 51. : Fast nearest-neighbor searching for nonlinear signal processing.

By highly constraining the type of interdependence evaluated, the numerical evaluation of parametric measures typically amounts to estimating a few coefficients, which in the case of linear measures can be usually obtained by matrix manipulations. Thus, parametric measures are often data-efficient, generalizable to multivariate settings, and easy to interpret. It is probably no exaggeration to say that one should always start the inspection of a new data set with linear techniques [7]. However, statistical relationships between processes are more naturally and generally formulated within the probabilistic framework, which relaxes the need to assume explicit models on how variables relate to each other [8].

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