Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
PLoS Comput Biol. 2010 Nov 4;6(11):e1000977. doi: 10.1371/journal.pcbi.1000977.
Traditionally, the information content of the neural response is quantified using statistics of the responses relative to stimulus onset time with the assumption that the brain uses onset time to infer stimulus identity. However, stimulus onset time must also be estimated by the brain, making the utility of such an approach questionable. How can stimulus onset be estimated from the neural responses with sufficient accuracy to ensure reliable stimulus identification? We address this question using the framework of colour coding by the archer fish retinal ganglion cell. We found that stimulus identity, "what", can be estimated from the responses of best single cells with an accuracy comparable to that of the animal's psychophysical estimation. However, to extract this information, an accurate estimation of stimulus onset is essential. We show that stimulus onset time, "when", can be estimated using a linear-nonlinear readout mechanism that requires the response of a population of 100 cells. Thus, stimulus onset time can be estimated using a relatively simple readout. However, large nerve cell populations are required to achieve sufficient accuracy.
传统上,神经反应的信息含量是使用相对于刺激起始时间的反应统计数据来量化的,假设大脑使用起始时间来推断刺激的身份。然而,刺激起始时间也必须由大脑来估计,这使得这种方法的实用性值得怀疑。那么,大脑如何才能以足够的精度从神经反应中估计刺激起始时间,以确保可靠的刺激识别呢?我们使用箭鱼视网膜神经节细胞的颜色编码框架来解决这个问题。我们发现,刺激的身份“是什么”可以从最佳单个细胞的反应中以与动物的心理物理估计相当的精度来估计。然而,要提取这些信息,刺激起始时间的准确估计是必不可少的。我们表明,刺激起始时间“何时”可以使用线性-非线性读出机制来估计,该机制需要 100 个细胞的反应。因此,刺激起始时间可以使用相对简单的读出机制来估计。然而,需要大量的神经细胞群体才能达到足够的精度。