Hooper S L
Department of Biological Sciences, Ohio University, Athens 45701, USA.
J Comput Neurosci. 1997 Jul;4(3):191-205. doi: 10.1023/a:1008822218061.
The extent to which individual neural networks can produce phase-constant motor patterns as cycle frequency is altered has not been studied extensively. I investigated this issue in the well-defined, rhythmic pyloric neural network. When pyloric cycle frequency is altered three- to fivefold, pyloric inter-neuronal delays shift by hundreds to thousands of msec, and all pyloric pattern elements show strong phase maintenance. The experimental paradigm used is unlikely to activate exogenous inputs to the network, and these delay changes are thus likely to arise from phase-compensatory mechanisms intrinsic to the network. Pyloric inter-neuronal delays depend on the time constants of the network's synapses and of the membrane properties of its neurons. The observed delay shifts thus suggest that, in response to changes in overall cycle frequency, these constants vary so as to maintain pattern phasing.
随着周期频率的改变,单个神经网络能够产生相位恒定运动模式的程度尚未得到广泛研究。我在定义明确的节律性幽门神经网络中研究了这个问题。当幽门周期频率改变三到五倍时,幽门中间神经元延迟会有数百到数千毫秒的变化,并且所有幽门模式元素都表现出很强的相位维持性。所使用的实验范式不太可能激活网络的外源输入,因此这些延迟变化可能源于网络固有的相位补偿机制。幽门中间神经元延迟取决于网络突触的时间常数及其神经元的膜特性。因此,观察到的延迟变化表明,响应于整体周期频率的变化,这些常数会发生变化以维持模式相位。