Diffusive homeostasis in a spiking network model (Sweeney et al. 2015)

In this paper we propose a new mechanism, diffusive homeostasis, in which neural excitability is modulated by nitric oxide, a gas which can flow freely across cell membranes. Our model simulates the activity-dependent synthesis and diffusion of nitric oxide in a recurrent network model of integrate-and-fire neurons. The concentration of nitric oxide is then used as homeostatic readout which modulates the firing threshold of each neuron.

Model Type: Realistic Network

Cell Type(s): Abstract integrate-and-fire leaky neuron

Receptors: NO

Transmitters: NO

Model Concept(s): Synaptic Plasticity; Intrinsic plasticity; STDP; Homeostasis; Volume transmission

Simulation Environment: Brian; Python

Implementer(s): Sweeney, Yann [yann.sweeney at ed.ac.uk]


Sweeney Y, Hellgren Kotaleski J, Hennig MH. (2015). A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks. PLoS computational biology. 11 [PubMed]

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