Rössert Christian, Pfanzelt Sandra, Straka Hans, Glasauer Stefan
Department of Neurology, BCCN, Ludwig-Maximilians-Universität München, München, Germany.
Ann N Y Acad Sci. 2009 May;1164:451-4. doi: 10.1111/j.1749-6632.2009.03766.x.
Computational modeling of cellular and network properties of central vestibular neurons is necessary for understanding the mechanisms of sensory-motor transformation for gaze stabilization. As a first step to mathematically describe vestibular signal processing, the available physiological data of the synaptic and intrinsic properties of frog second-order vestibular neurons (2 degrees VN) were used to create a model that combines cellular and network parameters. With this approach it is now possible to reveal the particular contributions of intrinsic membrane versus emerging network properties in shaping labyrinthine afferent-evoked synaptic responses in 2 degrees VN, to simulate perturbations, and to generate hypotheses that are testable in empiric experiments.
对中枢前庭神经元的细胞和网络特性进行计算建模，对于理解注视稳定的感觉运动转换机制至关重要。作为从数学上描述前庭信号处理的第一步，利用青蛙二阶前庭神经元（2°VN）突触和内在特性的现有生理数据，创建了一个结合细胞和网络参数的模型。通过这种方法，现在有可能揭示内在膜特性与新兴网络特性在塑造2°VN中迷路传入诱发的突触反应方面的特定贡献，模拟扰动，并生成可在实证实验中进行测试的假设。
