On Complexity and Phase Effects in Reconstructing the Directionality of Coupling in Non-linear Systems

Vakorin, Vasily A.; Krakovska, Olga; McIntosh, Anthony R.

doi:10.1007/978-3-642-54474-3_6

Cited by 3 publications

(3 citation statements)

References 35 publications

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“…This study was partly inspired by the work of Vasily A. Vakorin on the interplay of complexity and information transfer in [74]. The authors thank Saskia Helbling for fruitful discussions on data analysis and for making the permutation ANOVA code available.…”

Section: Acknowledgementsmentioning

confidence: 99%

Breakdown of local information processing may underlie isoflurane anesthesia effects

et al. 2017

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The disruption of coupling between brain areas has been suggested as the mechanism underlying loss of consciousness in anesthesia. This hypothesis has been tested previously by measuring the information transfer between brain areas, and by taking reduced information transfer as a proxy for decoupling. Yet, information transfer is a function of the amount of information available in the information source—such that transfer decreases even for unchanged coupling when less source information is available. Therefore, we reconsidered past interpretations of reduced information transfer as a sign of decoupling, and asked whether impaired local information processing leads to a loss of information transfer. An important prediction of this alternative hypothesis is that changes in locally available information (signal entropy) should be at least as pronounced as changes in information transfer. We tested this prediction by recording local field potentials in two ferrets after administration of isoflurane in concentrations of 0.0%, 0.5%, and 1.0%. We found strong decreases in the source entropy under isoflurane in area V1 and the prefrontal cortex (PFC)—as predicted by our alternative hypothesis. The decrease in source entropy was stronger in PFC compared to V1. Information transfer between V1 and PFC was reduced bidirectionally, but with a stronger decrease from PFC to V1. This links the stronger decrease in information transfer to the stronger decrease in source entropy—suggesting reduced source entropy reduces information transfer. This conclusion fits the observation that the synaptic targets of isoflurane are located in local cortical circuits rather than on the synapses formed by interareal axonal projections. Thus, changes in information transfer under isoflurane seem to be a consequence of changes in local processing more than of decoupling between brain areas. We suggest that source entropy changes must be considered whenever interpreting changes in information transfer as decoupling.

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Section: Acknowledgementsmentioning

confidence: 99%

Breakdown of local information processing may underlie isoflurane anesthesia effects

et al. 2017

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“…but the researches on indirect coupling are few when the interdependence between two variables under the influences of other variables, namely confounding variables. Considering the influences of confounding variables, partial transfer entropy(PTE) is multivariate extension of TE [35,36]. Also partial symbolic transfer entropy(PSTE) performs well with the non-stationarity time series but not effective with only linear couplings [37].…”

Section: Introductionmentioning

confidence: 99%

Risk spillover networks in financial system based on information theory

Liu

et al. 2021

PLoS ONE

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Since the financial system has illustrated an increasingly prominent characteristic of inextricable connections, information theory is gradually utilized to study the financial system. By collecting the daily data of industry index (2005-2020) and region index (2012-2020) listed in China as samples, this paper applies an innovative measure named partial mutual information on mixed embedding to generate directed networks. Based on the analysis of nonlinear relationships among sectors, this paper realizes the accurate construction of “time-varying” financial network from the perspective of risk spillover. The results are presented as follow: (1) interactions can be better understood through the nonlinear networks among distinct sectors, and sectors in the networks could be classified into different types according to their topological properties connected to risk spillover; (2) in the rising stage, information is transmitted rapidly in the network, so the risk is fast diffused and absorbed; (3) in the declining stage, the network topology is more complex and panic sentiments have long term impact leading to more connections; (4) The US market, Japan market and Hongkong market have significant affect on China’s market. The results suggest that this nonlinear measure is an effective approach to develop financial networks and explore the mechanism of risk spillover.

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“…Understanding how information is processed in the brain is one of the key areas in neuroscience research.Different tools have been employed to reconstruct directional influence and to infer the effective connectivity between distinct brain regions. Particularly, it has been shown [ 1 ] that in non-linear delay-coupled oscillating systems exhibiting a negative phase lag, Granger causality (GC) might not provide the correct direction of information flow (from the driver to the receiver). Such systems have been studied before in the theoretical framework of Anticipated Synchronization (AS) developed in the field of dynamical systems [ 2 ].…”

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confidence: 99%

Reconstructing the directionality of coupling between cortical populations with negative phase lag

et al. 2015

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On Complexity and Phase Effects in Reconstructing the Directionality of Coupling in Non-linear Systems

Cited by 3 publications

References 35 publications

Breakdown of local information processing may underlie isoflurane anesthesia effects

Breakdown of local information processing may underlie isoflurane anesthesia effects

Risk spillover networks in financial system based on information theory

Reconstructing the directionality of coupling between cortical populations with negative phase lag

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