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通过间隙连接耦合的可兴奋细胞网络中的自组织同步振荡。

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

作者信息

Lewis T J, Rinzel J

机构信息

Center for Neural Science and Courant Institute for Mathematical Sciences, New York University, NY 10003, USA.

出版信息

Network. 2000 Nov;11(4):299-320.

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.

摘要

最近的证据表明,电耦合在神经元网络振荡行为的产生中发挥作用;然而,其潜在机制尚未明确。利用Traub等人提出的细胞自动机模型(Traub R D, Schmitz D, Jefferys J G和Draguhn A 1999通过轴-轴突缝隙连接相互连接的海马锥体神经网络中预测会出现高频群体振荡《神经科学》92 407 - 26),我们描述了一种在通过缝隙连接具有强、稀疏随机电耦合的网络中自组织振荡的新机制。网络活动由随机自发活动产生,该活动通过网络传播被塑造成规则的群体振荡。我们解释了这种活动如何导致平均振荡频率对网络连接参数和自发活动速率的特定依赖性,并推导了近似振荡平均频率和方差的解析表达式。在此过程中,我们深入了解了神经元网络中频率控制和调制的可能机制。

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