Switchable slow cellular conductances determine robustness and tunability of network states.
PLoS Comput Biol
Public Library of Science (PLoS)
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Drion, G., Dethier, J., Franci, A., & Sepulchre, R. (2018). Switchable slow cellular conductances determine robustness and tunability of network states.. PLoS Comput Biol, 14 (4), e1006125. https://doi.org/10.1371/journal.pcbi.1006125
Neuronal information processing is regulated by fast and localized fluctuations of brain states. Brain states reliably switch between distinct spatiotemporal signatures at a network scale even though they are composed of heterogeneous and variable rhythms at a cellular scale. We investigated the mechanisms of this network control in a conductance-based population model that reliably switches between active and oscillatory mean-fields. Robust control of the mean-field properties relies critically on a switchable negative intrinsic conductance at the cellular level. This conductance endows circuits with a shared cellular positive feedback that can switch population rhythms on and off at a cellular resolution. The switch is largely independent from other intrinsic neuronal properties, network size and synaptic connectivity. It is therefore compatible with the temporal variability and spatial heterogeneity induced by slower regulatory functions such as neuromodulation, synaptic plasticity and homeostasis. Strikingly, the required cellular mechanism is available in all cell types that possess T-type calcium channels but unavailable in computational models that neglect the slow kinetics of their activation.
Action Potentials, Animals, Brain, Calcium Channels, T-Type, Computational Biology, Computer Simulation, Electrophysiological Phenomena, Humans, Kinetics, Models, Neurological, Nerve Net, Neural Networks, Computer, Neuronal Plasticity, Neurons
European Research Council (670645)
External DOI: https://doi.org/10.1371/journal.pcbi.1006125
This record's URL: https://www.repository.cam.ac.uk/handle/1810/283435
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/
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