Literature DB >> 15447561

Encoding via conjugate symmetries of slow oscillations for globally coupled oscillators.

Peter Ashwin1, Jon Borresen.   

Abstract

We study properties of the dynamics underlying slow cluster oscillations in two systems of five globally coupled oscillators. These slow oscillations are due to the appearance of structurally stable heteroclinic connections between cluster states in the noise-free dynamics. In the presence of low levels of noise they give rise to long periods of residence near cluster states interspersed with sudden transitions between them. Moreover, these transitions may occur between cluster states of the same symmetry, or between cluster states with conjugate symmetries given by some rearrangement of the oscillators. We consider the system of coupled phase oscillators studied by Hansel et al. [Phys. Rev. E 48, 3470 (1993)] in which one can observe slow, noise-driven oscillations that occur between two families of two cluster periodic states; in the noise-free case there is a robust attracting heteroclinic cycle connecting these families. The two families consist of symmetric images of two inequivalent periodic orbits that have the same symmetry. For N=5 oscillators, one of the periodic orbits has one unstable direction and the other has two unstable directions. Examining the behavior on the unstable manifold for the two unstable directions, we observe that the dimensionality of the manifold can give rise to switching between conjugate symmetry orbits. By applying small perturbations to the system we can easily steer it between a number of different marginally stable attractors. Finally, we show that similar behavior occurs in a system of phase-energy oscillators that are a natural extension of the phase model to two dimensional oscillators. We suggest that switching between conjugate symmetries is a very efficient method of encoding information into a globally coupled system of oscillators and may therefore be a good and simple model for the neural encoding of information.

Year:  2004        PMID: 15447561     DOI: 10.1103/PhysRevE.70.026203

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  8 in total

1.  Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience.

Authors:  Peter Ashwin; Stephen Coombes; Rachel Nicks
Journal:  J Math Neurosci       Date:  2016-01-06       Impact factor: 1.300

2.  Reducing Neuronal Networks to Discrete Dynamics.

Authors:  David Terman; Sungwoo Ahn; Xueying Wang; Winfried Just
Journal:  Physica D       Date:  2008-03       Impact factor: 2.300

3.  A Framework for Engineering the Collective Behavior of Complex Rhythmic Systems.

Authors:  Craig G Rusin; István Z Kiss; Hiroshi Kori; John L Hudson
Journal:  Ind Eng Chem Res       Date:  2009-03-16       Impact factor: 3.720

4.  Criteria for robustness of heteroclinic cycles in neural microcircuits.

Authors:  Peter Ashwin; Ozkan Karabacak; Thomas Nowotny
Journal:  J Math Neurosci       Date:  2011-11-28       Impact factor: 1.300

Review 5.  Neuronal Sequence Models for Bayesian Online Inference.

Authors:  Sascha Frölich; Dimitrije Marković; Stefan J Kiebel
Journal:  Front Artif Intell       Date:  2021-05-21

6.  Oscillatory threshold logic.

Authors:  Jon Borresen; Stephen Lynch
Journal:  PLoS One       Date:  2012-11-16       Impact factor: 3.240

7.  Transient cognitive dynamics, metastability, and decision making.

Authors:  Mikhail I Rabinovich; Ramón Huerta; Pablo Varona; Valentin S Afraimovich
Journal:  PLoS Comput Biol       Date:  2008-05-02       Impact factor: 4.475

8.  Community structure and multi-modal oscillations in complex networks.

Authors:  Henry Dorrian; Jon Borresen; Martyn Amos
Journal:  PLoS One       Date:  2013-10-10       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.