Integrated Information in the Spiking-Bursting Stochastic Model
Oleg Kanakov, Susanna Gordleeva, Alexey Zaikin

TL;DR
This paper analytically compares two measures of Integrated Information in a spiking-bursting stochastic neuron-astrocyte network model, revealing their similarities, differences, and the conditions under which they converge or change sign.
Contribution
It provides a detailed analytical comparison of the 'whole minus sum' and 'decoder based' Integrated Information measures in a novel neuron-astrocyte network model.
Findings
The measures show mutual asymptotic convergence with increased uncorrelated activity.
The 'whole minus sum' information can change sign, indicating net synergy or redundancy.
The model serves as a reference for applying and testing Integrated Information concepts.
Abstract
This study presents a comprehensive analytic description in terms of the empirical "whole minus sum" version of Integrated Information in comparison to the "decoder based" version for the "spiking-bursting" discrete-time, discrete-state stochastic model, which was recently introduced to describe a specific type of dynamics in a neuron-astrocyte network. The "whole minus sum" information may change sign, and an interpretation of this transition in terms of "net synergy" is available in the literature. This motivates our particular interest to the sign of the "whole minus sum" information in our analytical consideration. The behavior of the "whole minus sum" and "decoder based" information measures are found to bear a lot of similarity, showing their mutual asymptotic convergence as time-uncorrelated activity is increased, with the sign transition of the "whole minus sum" information…
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