大脑血液动力学现象中的能量编码

彭俊; 王如彬; 王毅泓

doi:10.6052/0459-1879-19-010

大脑血液动力学现象中的能量编码

华东理工大学理学院认知神经动力学研究所, 上海 200237

基金项目: 1) 国家自然科学基金资助项目(11232005);国家自然科学基金资助项目(11472104);国家自然科学基金资助项目(11872180)

详细信息

通讯作者:
王如彬

中图分类号: Q189
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出版历程
- 收稿日期: 2019-01-06
- 刊出日期: 2019-07-17

ENERGY CODING OF HEMODYNAMIC PHENOMENA IN THE BRAIN

The Institute for Cognitive Neurodynamics,School of Science,East China University of Science and Technology,Shanghai 200237, China

摘要

摘要: 神经信息的编码与解码是神经科学中的核心研究内容,同时又极具挑战性.传统的编码理论都具有各自的局限性,很难从脑的全局运行方式上给出有效的理论.而由于能量是一个标量具有可叠加性,因此能量编码理论可以从神经元活动的能量特征出发来研究脑功能的全局神经编码问题,取得了一系列的研究成果.本研究以王-张神经元能量计算模型为基础,构建了一个多层次结构的神经网络,通过计算机数值模拟得到了神经网络的能量消耗和血液中葡萄糖供能的变化情况.计算结果显示,和网络的神经活动达到峰值的时间相比,血液中葡萄糖的供能达到峰值的时间延迟了约5.6s.从定量的角度再现了功能性核磁共振(fMRI)中的血液动力学现象：大脑某个脑区的神经元集群被激活以后经过5~7 s的延迟,脑血流的变化才会大幅增加.模拟结果表明先前发表的由王-张神经元模型所揭示的负能量机制在控制大脑的血液动力学现象中起着核心的作用,预测了刺激条件下大脑的能量代谢与血流之间变化的本质是由神经元在发放动作电位过程中正、负能量之间的非平衡、不匹配性质所决定的.本文的研究结果为今后进一步探究血液动力学现象的生理学机制提供了新的研究方向,在神经网络的建模与计算方面给出了一个新的视角和研究方法.
- 负能量 /
- 能量编码 /
- 血液动力学 /
- 多层次神经网络
Abstract: The coding and decoding of neural information is the core research content in neuroscience, and it is also very challenging. The traditional neural coding theories have their own limitations, and they are difficult to provide effective theory from the global operation mode of the brain. Since energy is a scalar and has superposition, the theory of energy coding can study the global neural coding problem of the brain function from the prospective of energy characteristics of neuron activities, and has achieved a series of research results. Based on the Wang-Zhang neuron energy calculation model, this paper constructed a multi-level neural network, and we obtained the changes of the energy consumption of the neural network and energy supply of glucose in the blood by numerical simulation. The calculation results showed that the time of peak supply of glucose in the blood is delayed about 5.6 seconds compared to the time when the neural activity of the network reaches its peak, which reproduced hemodynamic phenomena in functional nuclear magnetic resonance (fMRI) from a quantitative perspective: after a five to seven seconds delay in the activation of a brain region, the change in cerebral blood flow increases dramatically. The simulation results showed that negative energy mechanism, which was previously reported by our group using Wang-Zhang neuronal model, played a central role in controlling the hemodynamics of the brain. Also, it predicted the neural coupling mechanism between the energy metabolism and blood flow changes in the brain under the condition of stimulation, which was determined by imbalance and mismatch between the positive and negative energy during the spike of neuronal action potentials. The research results in this paper provided a new research direction for further exploring the physiological mechanism of hemodynamic phenomena in the future, and gave a new perspective and research method in the modeling and calculation of neural networks.
- negative energy /
- energetics coding /
- hemodynamics /
- multi-level neural network

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