Volume 10 Supplement 1
Is the Langevin phase equation an efficient model for stochastic limit cycle oscillators in real neurons?
© Ota et al; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
The Langevin phase equation dϕ/dt = 1 + Z(ϕ)(G(t) + σs(t)), where ϕ is the phase, which is disturbed by a perturbation G and Langevin force s of intensity σ, and Z is the phase response curve (PRC), has been deemed to be a good model for stochastic limit cycle oscillators , and it has been extensively used in theoretical neuroscience as a model neural oscillator . Inspired by the theoretical research, experimental researchers have measured PRCs, but none of them have identified the Langevin phase equation for real neurons directly. In fact, biological experiments have yet to show whether this equation is a good model for neural oscillators.
Results and discussion
- Nakao H, Teramae J, Ermentrout GB: Comment on "phase reduction of stochastic limit cycle oscillators". [http://arxiv.org/abs/0812.3205]
- Ermentrout GB, Galan RF, Urban NN: Relating neural dynamics to neural coding. Phys Rev Lett. 2007, 99: 248103-10.1103/PhysRevLett.99.248103.PubMed CentralPubMedView ArticleGoogle Scholar
- Ota K, Omori T, Aonishi T: MAP estimation algorithm for phase reponse curves based on analysis of the observation process. J Comput Neurosci.
This article is published under license to BioMed Central Ltd.