title: A parametric examination of VLSI-based neuronal models of cyclic and reciprocal inhibition.
abstract: As a prelude to a silicon implementation of a live locomotory network, the phenomena of tonic excitation in single cells, reciprocal inhibition in pairs of cells, and recurrent cyclic inhibition in rings of five cells were recreated and subjected to parametric tests of oscillatory range and stability. Various networks were constructed from comprehensive very large scale integration (VLSI)-based artificial neurons and their parametric stability with respect to cellular threshold, refraction, and synaptic weight observed. Circuit tests demonstrated that all three oscillator topologies operated over a broad range of cellular and network frequencies. It was also noted that cells of reciprocal oscillators must possess some measure of short-term synaptic plasticity while those in the cyclically inhibited networks did not. This suggests that the two oscillator types utilize different temporal mechanisms. In parametric tests, tonic cells were sensitive to threshold, refraction, and synaptic weight. Cyclic networks were found to be sensitive to cell threshold, yet less so to refraction. Conversely, the reciprocal circuits were found to be sensitive to refraction, yet less so to cell threshold. This complementary relationship suggests a stability advantage for biological oscillatory networks that incorporate both types.
authors.affiliation: School of Science, Engineering, and Technology, Pennsylvania State University, Middletown 17057-4898, USA. sxw33@psuvm.psu.edu
authors.forename: S
authors.initials: S
authors.lastname: Wolpert
mesh_terms: D016014:Linear Models; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net; D009474:Neurons / Q000502:physiology*; D010507:Periodicity; D013569:Synapses / Q000502:physiology