Gielen Stan, Krupa Martin, Zeitler Magteld
Department of Biophysics, Donders Institute for Brain, Cognition and Information, Radboud University Nijmegen, Geert Grooteplein 21, 6525 EZ Nijmegen, The Netherlands.
Biol Cybern. 2010 Aug;103(2):151-65. doi: 10.1007/s00422-010-0390-x. Epub 2010 Apr 27.
In the past decades, many studies have focussed on the relation between the input and output of neurons with the aim to understand information processing by neurons. A particular aspect of neuronal information, which has not received much attention so far, concerns the problem of information transfer when a neuron or a population of neurons receives input from two or more (populations of) neurons, in particular when these (populations of) neurons carry different types of information. The aim of the present study is to investigate the responses of neurons to multiple inputs modulated in the gamma frequency range. By a combination of theoretical approaches and computer simulations, we test the hypothesis that enhanced modulation of synchronized excitatory neuronal activity in the gamma frequency range provides an advantage over a less synchronized input for various types of neurons. The results of this study show that the spike output of various types of neurons [i.e. the leaky integrate and fire neuron, the quadratic integrate and fire neuron and the Hodgkin-Huxley (HH) neuron] and that of excitatory-inhibitory coupled pairs of neurons, like the Pyramidal Interneuronal Network Gamma (PING) model, is highly phase-locked to the larger of two gamma-modulated input signals. This implies that the neuron selectively responds to the input with the larger gamma modulation if the amplitude of the gamma modulation exceeds that of the other signals by a certain amount. In that case, the output of the neuron is entrained by one of multiple inputs and that other inputs are not represented in the output. This mechanism for selective information transmission is enhanced for short membrane time constants of the neuron.
在过去几十年中，许多研究聚焦于神经元的输入与输出之间的关系，旨在理解神经元的信息处理过程。神经元信息的一个特定方面，即当一个神经元或一群神经元从两个或更多（群）神经元接收输入时，尤其是当这些（群）神经元携带不同类型信息时的信息传递问题，迄今尚未受到太多关注。本研究的目的是探究神经元对在伽马频率范围内调制的多个输入的反应。通过理论方法与计算机模拟相结合，我们检验了这样一个假设：在伽马频率范围内增强同步兴奋性神经元活动的调制，相较于同步性较差的输入，能为各类神经元带来优势。本研究结果表明，各类神经元 [即漏电整合发放神经元、二次整合发放神经元和霍奇金 - 赫胥黎（HH）神经元] 以及兴奋性 - 抑制性耦合神经元对（如锥体细胞间网络伽马（PING）模型）的脉冲输出与两个伽马调制输入信号中较大的那个高度锁相。这意味着，如果伽马调制的幅度超过其他信号一定量，神经元会选择性地对具有较大伽马调制的输入做出反应。在这种情况下，神经元的输出由多个输入之一带动，而其他输入在输出中未得到体现。对于神经元较短的膜时间常数，这种选择性信息传输机制会增强。
