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]
References:
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]