Agmon-Snir H, Carr C E, Rinzel J
Mathematical Research Branch, NIDDK, National Institutes of Health, Bethesda, Maryland 20892, USA.
Nature. 1998 May 21;393(6682):268-72. doi: 10.1038/30505.
Coincidence-detector neurons in the auditory brainstem of mammals and birds use interaural time differences to localize sounds. Each neuron receives many narrow-band inputs from both ears and compares the time of arrival of the inputs with an accuracy of 10-100 micros. Neurons that receive low-frequency auditory inputs (up to about 2 kHz) have bipolar dendrites, and each dendrite receives inputs from only one ear. Using a simple model that mimics the essence of the known electrophysiology and geometry of these cells, we show here that dendrites improve the coincidence-detection properties of the cells. The biophysical mechanism for this improvement is based on the nonlinear summation of excitatory inputs in each of the dendrites and the use of each dendrite as a current sink for inputs to the other dendrite. This is a rare case in which the contribution of dendrites to the known computation of a neuron may be understood. Our results show that, in these neurons, the cell morphology and the spatial distribution of the inputs enrich the computational power of these neurons beyond that expected from 'point neurons' (model neurons lacking dendrites).
哺乳动物和鸟类听觉脑干中的重合检测神经元利用双耳时间差来定位声音。每个神经元从双耳接收许多窄带输入,并以10 - 100微秒的精度比较输入的到达时间。接收低频听觉输入(高达约2千赫)的神经元具有双极树突,并且每个树突仅从一只耳朵接收输入。通过使用一个模拟这些细胞已知电生理学和几何结构本质的简单模型,我们在此表明树突改善了细胞的重合检测特性。这种改善的生物物理机制基于每个树突中兴奋性输入的非线性总和以及每个树突作为另一个树突输入的电流汇集器的作用。这是一种罕见的情况,其中树突对神经元已知计算的贡献可以被理解。我们的结果表明,在这些神经元中,细胞形态和输入的空间分布丰富了这些神经元的计算能力,超出了“点神经元”(缺乏树突的模型神经元)的预期。