Dendritic Computation and the Neural Code

树突计算和神经代码

• 批准号: RGPIN-2017-06872
• 负责人: Naud, Richard
• 金额: $ 1.89万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=628811
• 关键词: Dendritic; Computation; Neural; Code

If one connects loudspeakers to an electrode implanted in brain cells, one would hear a rough, crackling and apparently unstructured sound. Is this noise a reflection of intrinsic imprecisions of an organic form of information processing or, rather, is it the result of an unknown and perhaps highly optimized way of encoding information? At the center of neuroscience research lies this problem of neural coding. It has become clear that peripheral nerves code information streaming from the senses in their spiking rate. Neurons within the hierarchical structure of the neocortex, however, constantly combine information of two different natures: bottom-up information coming more directly from the senses and top-down information coming from internal sources. Therefore, we propose a simple reformulation of the neural coding problem and ask the general question: How can a single population of neurons encode two streams of information simultaneously? Recent experimental evidence point to a pivotal role of dendrites in answering this question.

如果将扬声器连接到植入脑细胞的电极上，人们会听到一种粗糙的、噼啪作响的、明显无结构的声音。这种噪音是反映了信息处理的有机形式的内在不精确性，还是一种未知的，也许是高度优化的信息编码方式的结果？神经科学研究的中心是神经编码问题。很明显，周围神经以其尖峰速率编码来自感官的信息流。然而，在新皮层的层级结构中，神经元不断地将两种不同性质的信息联合收割机结合起来：自下而上的信息更直接地来自感官，而自上而下的信息来自内部来源。因此，我们提出了一个简单的神经编码问题的重新表述，并提出了一个普遍的问题：一个单一的神经元群体如何同时编码两个信息流？最近的实验证据指出树突在回答这个问题中的关键作用。