Anesthesia-related changes in information transfer may be caused by reduction in local information generation

In anesthesia research it is an open question how general anesthetics lead to loss of consciousness (LOC). It has been proposed that LOC may be caused by the disruption of cortical information processing, preventing information integration. Therefore, recent studies investigating information processing under anesthesia focused on changes in information transfer, measured by transfer entropy (TE). However, often this complex technique was not applied rigorously, using time series in symbolic representation, or using TE differences without accounting for neural conduction delays, or without accounting for signal history.

[1]  Albert Y. Zomaya,et al.  The local information dynamics of distributed computation in complex systems , 2012 .

[2]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[3]  Raymond W. Yeung,et al.  A First Course in Information Theory , 2002 .

[4]  Kristin K Sellers,et al.  Awake vs. anesthetized: layer-specific sensory processing in visual cortex and functional connectivity between cortical areas. , 2015, Journal of neurophysiology.

[5]  M. R. Titchener,et al.  How well do practical information measures estimate the Shannon entropy , 2006 .

[6]  A. Kraskov,et al.  Estimating mutual information. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Bernhard Hemmer,et al.  Simultaneous Electroencephalographic and Functional Magnetic Resonance Imaging Indicate Impaired Cortical Top–Down Processing in Association with Anesthetic-induced Unconsciousness , 2013, Anesthesiology.

[8]  Gordon Pipa,et al.  Transfer entropy—a model-free measure of effective connectivity for the neurosciences , 2010, Journal of Computational Neuroscience.

[9]  José María Amigó,et al.  Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity , 2004, Neural Computation.

[10]  Anthony G. Hudetz,et al.  Volatile anesthetics disrupt frontal-posterior recurrent information transfer at gamma frequencies in rat , 2005, Neuroscience Letters.

[11]  Roberto Hornero,et al.  Interpretation of the Lempel-Ziv Complexity Measure in the Context of Biomedical Signal Analysis , 2006, IEEE Transactions on Biomedical Engineering.

[12]  Anthony G. Hudetz,et al.  Suppressing consciousness: Mechanisms of general anesthesia , 2006 .

[13]  UnCheol Lee,et al.  Preferential Inhibition of Frontal-to-Parietal Feedback Connectivity Is a Neurophysiologic Correlate of General Anesthesia in Surgical Patients , 2011, PloS one.

[14]  UnCheol Lee,et al.  Disruption of Frontal–Parietal Communication by Ketamine, Propofol, and Sevoflurane , 2013, Anesthesiology.

[15]  E. Bullmore,et al.  Permutation tests for factorially designed neuroimaging experiments , 2004, Human brain mapping.

[16]  Albert Y. Zomaya,et al.  Local measures of information storage in complex distributed computation , 2012, Inf. Sci..

[17]  Joseph T. Lizier,et al.  JIDT: An Information-Theoretic Toolkit for Studying the Dynamics of Complex Systems , 2014, Front. Robot. AI.

[18]  Abraham Lempel,et al.  On the Complexity of Finite Sequences , 1976, IEEE Trans. Inf. Theory.

[19]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[20]  Marti J. Anderson,et al.  Permutation tests for multi-factorial analysis of variance , 2003 .

[21]  Gerhard Schneider,et al.  Fronto-Parietal Connectivity Is a Non-Static Phenomenon with Characteristic Changes during Unconsciousness , 2014, PloS one.

[22]  Luca Faes,et al.  Conditional Entropy-Based Evaluation of Information Dynamics in Physiological Systems , 2014 .

[23]  Jonathan W. Pillow,et al.  Bayesian entropy estimation for countable discrete distributions , 2013, J. Mach. Learn. Res..

[24]  Viola Priesemann,et al.  TRENTOOL: A Matlab open source toolbox to analyse information flow in time series data with transfer entropy , 2011, BMC Neuroscience.

[25]  Schreiber,et al.  Measuring information transfer , 2000, Physical review letters.

[26]  Viola Priesemann,et al.  Measuring Information-Transfer Delays , 2013, PloS one.

[27]  Mario Ragwitz,et al.  Markov models from data by simple nonlinear time series predictors in delay embedding spaces. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  George A. Mashour,et al.  Assessing levels of consciousness with symbolic analysis , 2015, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[29]  G. Tononi,et al.  Consciousness and Anesthesia , 2008, Science.