### Abstract

Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.

Original language | English (US) |
---|---|

Pages (from-to) | 299-320 |

Number of pages | 22 |

Journal | Network: Computation in Neural Systems |

Volume | 11 |

Issue number | 4 |

State | Published - Nov 2000 |

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### ASJC Scopus subject areas

- Neuroscience(all)

### Cite this

*Network: Computation in Neural Systems*,

*11*(4), 299-320.

**Self-organized synchronous oscillations in a network of excitable cells coupled by gap junctions.** / Lewis, T. J.; Rinzel, J.

Research output: Contribution to journal › Article

*Network: Computation in Neural Systems*, vol. 11, no. 4, pp. 299-320.

}

TY - JOUR

T1 - Self-organized synchronous oscillations in a network of excitable cells coupled by gap junctions.

AU - Lewis, T. J.

AU - Rinzel, J.

PY - 2000/11

Y1 - 2000/11

N2 - Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.

AB - Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.

UR - http://www.scopus.com/inward/record.url?scp=0034321837&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034321837&partnerID=8YFLogxK

M3 - Article

C2 - 11128169

AN - SCOPUS:0010198648

VL - 11

SP - 299

EP - 320

JO - Network: Computation in Neural Systems

JF - Network: Computation in Neural Systems

SN - 0954-898X

IS - 4

ER -