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Schematic diagram showing how neural gain parameters (e.g. under modulation by noradrenaline) may potentially affect the information processing structure of the brain.

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posted on 2019-10-15, 17:24 authored by Mike Li, Yinuo Han, Matthew J. Aburn, Michael Breakspear, Russell A. Poldrack, James M. Shine, Joseph T. Lizier

(a) The effect of neural gain (σ) and excitability (γ), the two tuning parameters being varied in our neural mass model (see Methods), on the response of individual neurons to stimuli are shown schematically. Each input stimulus to a target region in the model contributes an effect to the rate of change of the target via a sigmoid function. Arrows in the figures indicate how the sigmoid function defining these effects changes with increases in these gain parameters (with σ increasing nonlinearity of response and γ increase amplification). (b) Previous results from [7] (adapted under Creative Commons Attribution License CC BY 4.0) showing that varying neural gain and excitability may cause abrupt changes in the mean phase synchrony of the brain from modelled fMRI BOLD recordings, implying the existence of a critical boundary between a segregated phase (“S”, low phase synchrony) and an integrated phase (“I”, high phase synchrony) in the brain. (c) Schematic diagram of functional brain networks in the segregated and integrated phases, and how changing neural gain and excitability may lead to transitions between the two. (d) Schematic diagram of the concept of active information storage and transfer entropy, and how they may be affected by phase transitions. Qualitatively, active information storage (green arrow) describes information on the next instance Xn+1 (blue sample) of a time series X provided by its own history (, green samples), whereas transfer entropy (orange arrow) describes that provided by the past (, orange samples) of another time series Y in the context of the target’s history. See further details on these measures in Methods.