Roberts P D
Neurological Sciences Institute, OHSU, Portland, Oregon 97209, USA.
J Neurophysiol. 2000 Oct;84(4):2035-47. doi: 10.1152/jn.2000.84.4.2035.
Mathematical analyses and computer simulations are used to study the adaptation induced by plasticity at inhibitory synapses in a cerebellum-like structure, the electrosensory lateral line lobe (ELL) of mormyrid electric fish. Single-cell model results are compared with results obtained at the system level in vivo. The model of system level adaptation uses detailed temporal learning rules of plasticity at excitatory and inhibitory synapses onto Purkinje-like neurons. Synaptic plasticity in this system depends on the time difference between pre- and postsynaptic spikes. Adaptation is measured by the ability of the system to cancel a reafferent electrosensory signal by generating a negative image of the predicted signal. The effects of plasticity are tested for the relative temporal correlation between the inhibitory input and the sensory input, the gain of the sensory signal, and the presence of shunting inhibition. The model suggests that the presence of plasticity at inhibitory synapses improves the function of the system if the inhibitory inputs are temporally correlated with a predictable electrosensory signal. The functional improvements include an increased range of adaptability and a higher rate of system level adaptation. However, the presence of shunting inhibition has little effect on the dynamics of the model. The model quantifies the rate of system level adaptation and the accuracy of the negative image. We find that adaptation proceeds at a rate comparable to results obtained from experiments in vivo if the inhibitory input is correlated with electrosensory input. The mathematical analysis and computer simulations support the hypothesis that inhibitory synapses in the molecular layer of the ELL change their efficacy in response to the timing of pre- and postsynaptic spikes. Predictions include the rate of adaptation to sensory stimuli, the range of stimulus amplitudes for which adaptation is possible, the stability of stored negative images, and the timing relations of a temporal learning rule governing the inhibitory synapses. These results may be generalized to other adaptive systems in which plasticity at inhibitory synapses obeys similar learning rules.
数学分析和计算机模拟被用于研究在象小脑的结构——电鱼的电感觉侧线叶（ELL）中，抑制性突触可塑性所诱导的适应性。将单细胞模型结果与体内系统水平获得的结果进行比较。系统水平适应性模型使用了兴奋性和抑制性突触到浦肯野样神经元上的详细时间学习可塑性规则。该系统中的突触可塑性取决于突触前和突触后尖峰之间的时间差。适应性通过系统通过生成预测信号的负像来消除再传入电感觉信号的能力来衡量。针对抑制性输入与感觉输入之间的相对时间相关性、感觉信号的增益以及分流抑制的存在，测试了可塑性的影响。该模型表明，如果抑制性输入与可预测的电感觉信号在时间上相关，那么抑制性突触处可塑性的存在会改善系统功能。功能上的改进包括适应性范围的增加和系统水平适应性的更高速率。然而，分流抑制的存在对模型的动力学影响很小。该模型量化了系统水平适应性的速率和负像的准确性。我们发现，如果抑制性输入与电感觉输入相关，适应性的进行速率与体内实验获得的结果相当。数学分析和计算机模拟支持这样的假设，即ELL分子层中的抑制性突触会根据突触前和突触后尖峰的时间改变其效能。预测包括对感觉刺激的适应速率、可能进行适应的刺激幅度范围、存储负像的稳定性以及支配抑制性突触的时间学习规则的时间关系。这些结果可能推广到其他适应性系统，其中抑制性突触的可塑性遵循类似的学习规则。
