Cymbalyuk G S, Patel G N, Calabrese R L, DeWeerth S P, Cohen A H
Institute of Mathematical Problems in Biology, Russian Academy of Sciences, Pushchino, Moscow region.
Neural Comput. 2000 Oct;12(10):2259-78. doi: 10.1162/089976600300014926.
We developed an analog very large-scale integrated system of two mutually inhibitory silicon neurons that display several different stable oscillations. For example, oscillations can be synchronous with weak inhibitory coupling and alternating with relatively strong inhibitory coupling. All oscillations observed experimentally were predicted by bifurcation analysis of a corresponding mathematical model. The synchronous oscillations do not require special synaptic properties and are apparently robust enough to survive the variability and constraints inherent in this physical system. In biological experiments with oscillatory neuronal networks, blockade of inhibitory synaptic coupling can sometimes lead to synchronous oscillations. An example of this phenomenon is the transition from alternating to synchronous bursting in the swimming central pattern generator of lamprey when synaptic inhibition is blocked by strychnine. Our results suggest a simple explanation for the observed oscillatory transitions in the lamprey central pattern generator network: that inhibitory connectivity alone is sufficient to produce the observed transition.
我们开发了一个由两个相互抑制的硅神经元组成的模拟超大规模集成系统,该系统呈现出几种不同的稳定振荡。例如,振荡可以在弱抑制耦合下同步,在相对强的抑制耦合下交替。实验观察到的所有振荡都通过相应数学模型的分岔分析得到了预测。同步振荡不需要特殊的突触特性,而且显然足够稳健,能够在这个物理系统固有的变异性和约束条件下存活。在振荡神经网络的生物学实验中,抑制性突触耦合的阻断有时会导致同步振荡。这种现象的一个例子是,当用士的宁阻断突触抑制时,七鳃鳗游泳中枢模式发生器中从交替爆发到同步爆发的转变。我们的结果为七鳃鳗中枢模式发生器网络中观察到的振荡转变提供了一个简单的解释:仅抑制性连接就足以产生观察到的转变。