NDLI: Mapped Clock Oscillators as Ring Devices and Their Application to Neuronal Electrical Rhythms

Content Provider	IEEE Xplore Digital Library
Author	Zalay, O.C. Bardakjian, B.L.
Copyright Year	2001
Abstract	The mapped clock oscillator (MCO) is a second-order, Winfree-type oscillator generating two instantaneous clock variables (amplitude and phase) that are mapped to an observable output variable (voltage) via a static nonlinearity. Two fundamental classes of ring devices are presented. Their respective dynamics give rise to two oscillator forms-the labile clock and the clock-which can be coupled together in various configurations to create higher-order systems with sufficient complexity to capture the dynamics of neuronal assemblies. To demonstrate the applicability of MCOs in modelling neuronal rhythms, a hippocampal network model of four coupled oscillators was constructed and shown to exhibit rhythmic activity of varying complexity, depending on model parameters. The dynamics of the network were quantified through estimation of the maximum lyapunov exponent and the correlation dimension. Synthesis of complex neuronal rhythms may have therapeutic implications. The modular and efficient design of the MCO should facilitate the process of implementing coupled MCO networks in electronic hardware as potential neural prostheses for treating dynamic diseases such as epilepsy.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	12
File Size	1022008
Starting Page	233
Ending Page	244
File Format	PDF
ISSN	15344320
Volume Number	16
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clocks Ring oscillators Rhythm Voltage-controlled oscillators Assembly systems Network synthesis Neural network hardware Prosthetics Diseases Epilepsy nonlinear dynamics Complexity coupled oscillators electroencephalogram (EEG) neuronal assemblies neuronal rhythms EEG Neuronal rhythms complexity
Content Type	Text
Resource Type	Article
Subject	Neuroscience Rehabilitation Internal Medicine Biomedical Engineering Computer Science Applications

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