Neural Codes Formed by Small and Temporally Precise Populations in Auditory Cortex
Neural Codes Formed by Small and Temporally Precise Populations in Auditory Cortex
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DOI：
10.1523/jneurosci.2631-13.2013
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发表时间：
2013-11-13
影响因子：
5.3
通讯作者：
Kayser, Christoph
中科院分区：
文献类型：
--
作者：
Ince, Robin A. A.;Panzeri, Stefano;Kayser, Christoph
皮层神经元群对感觉信息的编码构成了感知的基础，但人们对此仍然知之甚少。为了了解皮质群体编码的限制，我们分析了灵长类动物（猕猴）听觉皮层中记录的自然声音的神经反应。我们在改变所考虑人口的组成和规模的同时估计了刺激信息。与之前的报告一致，我们发现，当从记录的集合中随机选择子种群时，平均种群信息随着种群大小的增加而稳定增加。这种缩放是通过一个模型来解释的，该模型假设每个神经元携带等量的信息，并且每个神经元携带的信息之间的任何重叠纯粹来自刺激空间内的随机采样。然而，当研究为每个给定群体规模优化信息而选择的亚群体时，信息的缩放比例却截然不同：一小部分时间精确的细胞携带了绝大多数信息。这种缩放可以通过扩展模型来解释，假设单个神经元携带的信息量高度不均匀，很少有神经元携带大量信息。重要的是，这些最佳群体可以通过单个生物物理标记（神经元的编码时间尺度）来确定，从而可以在生物真实电路中检测和读出它们。这些结果表明，基于随机集合的群体信息外推可能会高估刺激编码所需的群体规模，并且感觉皮层电路可能使用小型但信息丰富的集合来处理信息。
The encoding of sensory information by populations of cortical neurons forms the basis for perception but remains poorly understood. To understand the constraints of cortical population coding we analyzed neural responses to natural sounds recorded in auditory cortex of primates (Macaca mulatta). We estimated stimulus information while varying the composition and size of the considered population. Consistent with previous reports we found that when choosing subpopulations randomly from the recorded ensemble, the average population information increases steadily with population size. This scaling was explained by a model assuming that each neuron carried equal amounts of information, and that any overlap between the information carried by each neuron arises purely from random sampling within the stimulus space. However, when studying subpopulations selected to optimize information for each given population size, the scaling of information was strikingly different: a small fraction of temporally precise cells carried the vast majority of information. This scaling could be explained by an extended model, assuming that the amount of information carried by individual neurons was highly nonuniform, with few neurons carrying large amounts of information. Importantly, these optimal populations can be determined by a single biophysical marker-the neuron's encoding time scale-allowing their detection and readout within biologically realistic circuits. These results show that extrapolations of population information based on random ensembles may overestimate the population size required for stimulus encoding, and that sensory cortical circuits may process information using small but highly informative ensembles.