CCNR, University of Sussex, Falmer, Brighton, United Kingdom.
Phys Rev Lett. 2011 Jun 10;106(23):238109. doi: 10.1103/PhysRevLett.106.238109.
We present a systematic multiscale reduction of a biologically plausible model of the inhibitory neuronal network of the pheromone system of the moth. Starting from a Hodgkin-Huxley conductance based model we adiabatically eliminate fast variables and quantitatively reduce the model to mean field equations. We then prove analytically that the network's ability to operate on signal amplitudes across several orders of magnitude is optimal when a disinhibitory mode is close to losing stability and the network dynamics are close to bifurcation. This has the potential to extend the idea that optimal dynamic range in the brain arises as a critical phenomenon of phase transitions in excitable media to brain regions that are dominated by inhibition or have slow dynamics.
我们提出了一种系统的多尺度方法，用于简化飞蛾信息素系统抑制性神经元网络的一种合理生物模型。从基于 Hodgkin-Huxley 电导率的模型开始，我们绝热地消除快速变量，并将模型定量简化为平均场方程。然后我们从理论上证明，当去抑制模式接近失稳且网络动力学接近分岔时，网络在跨越多个数量级的信号幅度上进行操作的能力是最优的。这有可能将大脑中最优动态范围产生的想法扩展到兴奋介质相变的临界现象，使其适用于主要由抑制作用或具有缓慢动力学的脑区。
