title: Silicon modeling of the Mihalaş-Niebur neuron.
abstract: There are a number of spiking and bursting neuron models with varying levels of complexity, ranging from the simple integrate-and-fire model to the more complex Hodgkin-Huxley model. The simpler models tend to be easily implemented in silicon but yet not biologically plausible. Conversely, the more complex models tend to occupy a large area although they are more biologically plausible. In this paper, we present the 0.5 μm complementary metal-oxide-semiconductor (CMOS) implementation of the Mihalaş-Niebur neuron model--a generalized model of the leaky integrate-and-fire neuron with adaptive threshold--that is able to produce most of the known spiking and bursting patterns that have been observed in biology. Our implementation modifies the original proposed model, making it more amenable to CMOS implementation and more biologically plausible. All but one of the spiking properties--tonic spiking, class 1 spiking, phasic spiking, hyperpolarized spiking, rebound spiking, spike frequency adaptation, accommodation, threshold variability, integrator and input bistability--are demonstrated in this model.
authors: Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. fope@jhu.edu
authors: Fopefolu
authors: F
authors: Folowosele
authors: Tara Julia
authors: TJ
authors: Hamilton
authors: Ralph
authors: R
authors: Etienne-Cummings
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D032701:Biomimetics / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*