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Invariant visual representation by single neurons in the human brain.人类大脑中单个神经元的不变视觉表征。
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Neuronal variability: noise or part of the signal?神经元变异性:噪声还是信号的一部分?
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Neural population code for fine perceptual decisions in area MT.大脑中颞叶视觉区(MT)精细感知决策的神经群体编码
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Appraising the brain's energy budget.评估大脑的能量预算。
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Energy-efficient neuronal computation via quantal synaptic failures.通过量子突触故障实现高效能神经元计算。
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生物神经网络中的能量编码。

Energy coding in biological neural networks.

机构信息

Institute for Brain Information Processing and Cognitive Neurodynamics, School of Information Science and Engineering, East China University of Science and Technology, Meilong Road 130, Shanghai, 200237, P.R. China,

出版信息

Cogn Neurodyn. 2007 Sep;1(3):203-12. doi: 10.1007/s11571-007-9015-z. Epub 2007 Apr 12.

DOI:10.1007/s11571-007-9015-z
PMID:19003513
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2267673/
Abstract

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model's ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function.

摘要

根据信号传输和神经元能量需求与大脑皮层信息编码紧密耦合的实验结果,我们提出了一个全新的科学理论,为大脑信息处理提供了独特的机制。我们证明,大脑活动产生的神经编码可以很好地用我们的能量编码理论来描述。由于能量编码模型能够根据已知的生物物理特性揭示大脑信息处理的机制,我们不仅可以再现神经电生理学的各种实验结果,还可以通过能量编码原理定量解释耶鲁大学神经科学家的最新实验结果。由于能量编码理论弥合了生物神经网络内部的功能连接和能量消耗之间的差距,我们估计该理论对认知功能的定量研究具有非常重要的意义。