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Brain dump: How publicly available fMRI can help inform neuronal network architecture

机译:人才库:公开可用的功能磁共振成像如何帮助告知神经元网络架构

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Connectomics is an emergent discipline of Neuroinformatics that studies how the brain is connected, both anatomically and functionally. A number of projects throughout the neuroscience community have tackled the problem of determining interconnectivity from the nano scale - such as those enabled by laser-scanning light microscopy and semi-automated electron microscopy - to the micro scale of neurons and neuron clusters, to the macro scale of fMRI. The amount of data required to map out the macro scale is in the manageable multi-terabyte range, and largely exists today, while gathering one milometer cubed of synaptic-level data already approaches the multi-petabyte scale and is a few years away. Between these two extremes most likely lies the fastest and most representative path to a useful map of human neuronal connectivity. Although extremely informative on may topics concerning neuronal connectivity, the of the main limitations of the smaller scale approaches are 1) the considerable amount of time and energy needed to have one sample which will likely not be widely representative of a typical human brain and 2) their highly invasive or destructive nature renders them poorly adaptable to living humans.
机译:Connectomics是神经信息学的新兴学科,它从解剖学和功能上研究大脑的连接方式。整个神经科学领域的许多项目都解决了确定从纳米尺度(例如通过激光扫描光显微镜和半自动电子显微镜实现的)到神经元和神经元簇的微观尺度以及宏观尺度之间的互连性的问题。功能磁共振成像的规模。映射宏规模所需的数据量在可管理的数TB范围内,并且如今已大量存在,而收集到的1密耳立方突触级数据已经接近数PB规模,并且距离还有数年之遥。在这两种极端之间,最有可能是最快,最有代表性的通往人类神经元连通性图的途径。尽管在涉及神经元连通性的主题方面提供的信息极为丰富,但较小规模方法的主要局限性是:1)拥有一个样本(可能无法广泛代表典型的人脑)需要大量的时间和精力; 2)它们的高度侵入性或破坏性使其难以适应活着的人类。

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