首页> 外文期刊>Journal of Computational Neuroscience >A mechanism for graded, dynamically routable current propagation in pulse-gated synfire chains and implications for information coding
【24h】

A mechanism for graded, dynamically routable current propagation in pulse-gated synfire chains and implications for information coding

机译:一种在脉冲门控合成火链中分级,动态可路由电流传播的机制及其对信息编码的意义

获取原文
获取原文并翻译 | 示例

摘要

Neural oscillations can enhance feature recognition (Azouz and Gray Proceedings of the National Academy of Sciences of the United States of America, 97, 8110-8115 2000), modulate interactions between neurons (Womelsdorf et al. Science, 316, 1609-01612 2007), and improve learning and memory (Markowska et al. The Journal of Neuroscience, 15, 2063-2073 1995). Numerical studies have shown that coherent spiking can give rise to windows in time during which information transfer can be enhanced in neuronal networks (Abeles Israel Journal of Medical Sciences, 18, 83-92 1982; Lisman and Idiart Science, 267, 1512-1515 1995, Salinas and Sejnowski Nature Reviews. Neuroscience, 2, 539-550 2001). Unanswered questions are: 1) What is the transfer mechanism? And 2) how well can a transfer be executed? Here, we present a pulse-based mechanism by which a graded current amplitude may be exactly propagated from one neuronal population to another. The mechanism relies on the downstream gating of mean synaptic current amplitude from one population of neurons to another via a pulse. Because transfer is pulse-based, information may be dynamically routed through a neural circuit with fixed connectivity. We demonstrate the transfer mechanism in a realistic network of spiking neurons and show that it is robust to noise in the form of pulse timing inaccuracies, random synaptic strengths and finite size effects. We also show that the mechanism is structurally robust in that it may be implemented using biologically realistic pulses. The transfer mechanism may be used as a building block for fast, complex information processing in neural circuits. We show that the mechanism naturally leads to a framework wherein neural information coding and processing can be considered as a product of linear maps under the active control of a pulse generator. Distinct control and processing components combine to form the basis for the binding, propagation, and processing of dynamically routed information within neural pathways. Using our framework, we construct example neural circuits to 1) maintain a short-term memory, 2) compute time-windowed Fourier transforms, and 3) perform spatial rotations. We postulate that such circuits, with automatic and stereotyped control and processing of information, are the neural correlates of Crick and Koch's zombie modes.
机译:神经振荡可以增强特征识别(美国国家科学院的Azouz和Gray会议论文集,97,8110-8115 2000),调节神经元之间的相互作用(Womelsdorf等,Science,316,1609-01612 2007)。 ,并改善学习和记忆(Markowska等人,《神经科学杂志》,第15期,2063-2073 1995)。数值研究表明,相干的尖峰可以产生时间窗,在此期间可以增强神经元网络中的信息传输(Abeles以色列医学杂志,1982年第18期,第83-92页; Lisman和Idiart Science,第267期,1512-1515年) ,Salinas and Sejnowski Nature Reviews。Neuroscience,2,539-550 2001)。未解决的问题是:1)转移机制是什么? 2)转移执行得如何?在这里,我们提出了一种基于脉冲的机制,通过该机制,分级的电流幅度可能会从一个神经元群体准确地传播到另一个神经元群体。该机制依赖于平均突触电流幅度从一个神经元群体到另一个神经元脉冲的下游门控。由于传输是基于脉冲的,因此信息可以通过具有固定连接性的神经回路动态路由。我们在真实的尖峰神经元网络中演示了转移机制,并表明它以脉冲定时不准确,随机突触强度和有限大小效应的形式对噪声具有鲁棒性。我们还显示了该机制在结构上很健壮,因为它可以使用生物学上现实的脉冲来实现。传输机制可以用作神经回路中快速,复杂信息处理的基础。我们表明该机制自然导致了一个框架,其中在脉冲发生器的主动控制下,神经信息的编码和处理可以视为线性映射的产物。独特的控制和处理组件结合在一起,形成了神经通路内动态路由信息的绑定,传播和处理的基础。使用我们的框架,我们构造示例神经回路以:1)维护短期记忆,2)计算时间窗傅立叶变换,以及3)执行空间旋转。我们假设这种具有自动和定型控制和信息处理的电路是Crick和Koch的僵尸模式的神经关联。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号