• Open Access

Homeostatic Plasticity and External Input Shape Neural Network Dynamics

Johannes Zierenberg, Jens Wilting, and Viola Priesemann
Phys. Rev. X 8, 031018 – Published 20 July 2018

Abstract

In vitro and in vivo spiking activity clearly differ. Whereas networks in vitro develop strong bursts separated by periods of very little spiking activity, in vivo cortical networks show continuous activity. This is puzzling considering that both networks presumably share similar single-neuron dynamics and plasticity rules. We propose that the defining difference between in vitro and in vivo dynamics is the strength of external input. In vitro, networks are virtually isolated, whereas in vivo every brain area receives continuous input. We analyze a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state. In more detail, our analytical and numerical results on various network topologies show consistently that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating, and irregular states. This implies that the dynamic state of a neural network is not fixed but can readily adapt to the input strengths. Indeed, our results match experimental spike recordings in vitro and in vivo: The in vitro bursting behavior is consistent with a state generated by very low network input (<0.1%), whereas in vivo activity suggests that on the order of 1% recorded spikes are input driven, resulting in reverberating dynamics. Importantly, this predicts that one can abolish the ubiquitous bursts of in vitro preparations, and instead impose dynamics comparable to in vivo activity by exposing the system to weak long-term stimulation, thereby opening new paths to establish an in vivo-like assay in vitro for basic as well as neurological studies.

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  • Received 3 August 2017
  • Revised 8 June 2018

DOI:https://doi.org/10.1103/PhysRevX.8.031018

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsNonlinear Dynamics

Authors & Affiliations

Johannes Zierenberg1,2,*, Jens Wilting1,*, and Viola Priesemann1,2

  • 1Max Planck Institute for Dynamics and Self-Organization, Am Fassberg 17, 37077 Göttingen, Germany,
  • 2Bernstein Center for Computational Neuroscience, Am Fassberg 17, 37077 Göttingen, Germany,

  • *J. Z., and J. W. contributed equally to this work.

Popular Summary

When cultured in a dish, neurons self-organize into a network that often shows strong bursts of activity separated by pauses of several seconds. However, such system-wide pauses are not observed in the cortex of mammalian brains, which instead exhibit continuous fluctuating spiking activity. This difference is puzzling, given that the two systems are presumably governed by similar underlying single-neuron dynamics. We propose that the disparity can be explained by the difference in external input. Cortical networks receive continuous input from other brain areas and sensory modalities. In isolated cultured networks, however, all activity has to be generated from within; if spiking dies out, it has to be spontaneously reignited.

Using a generic model of spiking neurons, we show analytically and numerically that homeostatic plasticity (the ability of neurons to regulate their own excitability) is a sufficient mechanism to generate continuous dynamics under intermediate and weak input (such as in a cortical network) as well as intermittent bursts under very weak input (such as in a cultured network). The external input strength becomes a control parameter that generates these different behaviors, highlighting the importance of the input strength on shaping collective network dynamics.

We predict that homeostatic plasticity can be harnessed to tune the collective dynamics of a neuronal network by altering the strength of its input. Most importantly, weak long-term stochastic stimulation could allow one to abolish bursts in neuronal cultures and render their dynamics cortical-like instead, a key prerequisite for sensitive studies of neurological and psychiatric disorders in the lab.

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Vol. 8, Iss. 3 — July - September 2018

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