Critical slowing down governs the transition to neuron spiking.

Many complex systems have been found to exhibit critical transitions, or so-called tipping points, which are sudden changes to a qualitatively different system state. These changes can profoundly impact the functioning of a system ranging from controlled state switching to a catastrophic break-down;...

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Main Authors: Christian Meisel, Andreas Klaus, Christian Kuehn, Dietmar Plenz
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-02-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC4338190?pdf=render
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author Christian Meisel
Andreas Klaus
Christian Kuehn
Dietmar Plenz
author_facet Christian Meisel
Andreas Klaus
Christian Kuehn
Dietmar Plenz
author_sort Christian Meisel
collection DOAJ
description Many complex systems have been found to exhibit critical transitions, or so-called tipping points, which are sudden changes to a qualitatively different system state. These changes can profoundly impact the functioning of a system ranging from controlled state switching to a catastrophic break-down; signals that predict critical transitions are therefore highly desirable. To this end, research efforts have focused on utilizing qualitative changes in markers related to a system's tendency to recover more slowly from a perturbation the closer it gets to the transition--a phenomenon called critical slowing down. The recently studied scaling of critical slowing down offers a refined path to understand critical transitions: to identify the transition mechanism and improve transition prediction using scaling laws. Here, we outline and apply this strategy for the first time in a real-world system by studying the transition to spiking in neurons of the mammalian cortex. The dynamical system approach has identified two robust mechanisms for the transition from subthreshold activity to spiking, saddle-node and Hopf bifurcation. Although theory provides precise predictions on signatures of critical slowing down near the bifurcation to spiking, quantitative experimental evidence has been lacking. Using whole-cell patch-clamp recordings from pyramidal neurons and fast-spiking interneurons, we show that 1) the transition to spiking dynamically corresponds to a critical transition exhibiting slowing down, 2) the scaling laws suggest a saddle-node bifurcation governing slowing down, and 3) these precise scaling laws can be used to predict the bifurcation point from a limited window of observation. To our knowledge this is the first report of scaling laws of critical slowing down in an experiment. They present a missing link for a broad class of neuroscience modeling and suggest improved estimation of tipping points by incorporating scaling laws of critical slowing down as a strategy applicable to other complex systems.
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spelling doaj.art-42c74ca091e841c2a26969a3d30d1f7e2022-12-21T19:04:44ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-02-01112e100409710.1371/journal.pcbi.1004097Critical slowing down governs the transition to neuron spiking.Christian MeiselAndreas KlausChristian KuehnDietmar PlenzMany complex systems have been found to exhibit critical transitions, or so-called tipping points, which are sudden changes to a qualitatively different system state. These changes can profoundly impact the functioning of a system ranging from controlled state switching to a catastrophic break-down; signals that predict critical transitions are therefore highly desirable. To this end, research efforts have focused on utilizing qualitative changes in markers related to a system's tendency to recover more slowly from a perturbation the closer it gets to the transition--a phenomenon called critical slowing down. The recently studied scaling of critical slowing down offers a refined path to understand critical transitions: to identify the transition mechanism and improve transition prediction using scaling laws. Here, we outline and apply this strategy for the first time in a real-world system by studying the transition to spiking in neurons of the mammalian cortex. The dynamical system approach has identified two robust mechanisms for the transition from subthreshold activity to spiking, saddle-node and Hopf bifurcation. Although theory provides precise predictions on signatures of critical slowing down near the bifurcation to spiking, quantitative experimental evidence has been lacking. Using whole-cell patch-clamp recordings from pyramidal neurons and fast-spiking interneurons, we show that 1) the transition to spiking dynamically corresponds to a critical transition exhibiting slowing down, 2) the scaling laws suggest a saddle-node bifurcation governing slowing down, and 3) these precise scaling laws can be used to predict the bifurcation point from a limited window of observation. To our knowledge this is the first report of scaling laws of critical slowing down in an experiment. They present a missing link for a broad class of neuroscience modeling and suggest improved estimation of tipping points by incorporating scaling laws of critical slowing down as a strategy applicable to other complex systems.http://europepmc.org/articles/PMC4338190?pdf=render
spellingShingle Christian Meisel
Andreas Klaus
Christian Kuehn
Dietmar Plenz
Critical slowing down governs the transition to neuron spiking.
PLoS Computational Biology
title Critical slowing down governs the transition to neuron spiking.
title_full Critical slowing down governs the transition to neuron spiking.
title_fullStr Critical slowing down governs the transition to neuron spiking.
title_full_unstemmed Critical slowing down governs the transition to neuron spiking.
title_short Critical slowing down governs the transition to neuron spiking.
title_sort critical slowing down governs the transition to neuron spiking
url http://europepmc.org/articles/PMC4338190?pdf=render
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