Zhu Fengyun, Wang Rubin, Pan Xiaochuan, Zhu Zhenyu
2Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, 200237 China.
1School of Computer Science, Hangzhou Dianzi University, Hangzhou, China.
Cogn Neurodyn. 2019 Feb;13(1):75-87. doi: 10.1007/s11571-018-9503-3. Epub 2018 Sep 3.
Brief bursts of high-frequency spikes are a common firing pattern of neurons. The cellular mechanisms of bursting and its biological significance remain a matter of debate. Focusing on the energy aspect, this paper proposes a neural energy calculation method based on the Chay model of bursting. The flow of ions across the membrane of the bursting neuron with or without current stimulation and its power which contributes to the change of the transmembrane electrical potential energy are analyzed here in detail. We find that during the depolarization of spikes in bursting this power becomes negative, which was also discovered in previous research with another energy model. We also find that the neuron's energy consumption during bursting is minimal. Especially in the spontaneous state without stimulation, the total energy consumption (2.152 × 10 J) during 30 s of bursting is very similar to the biological energy consumption (2.468 × 10 J) during the generation of a single action potential, as shown in Wang et al. (Neural Plast 2017, 2017a). Our results suggest that this property of low energy consumption could simply be the consequence of the biophysics of generating bursts, which is consistent with the principle of energy minimization. Our results also imply that neural energy plays a critical role in neural coding, which opens a new avenue for research of a central challenge facing neuroscience today.
高频尖峰的短暂爆发是神经元常见的放电模式。爆发的细胞机制及其生物学意义仍存在争议。本文从能量角度出发,提出了一种基于爆发的Chay模型的神经能量计算方法。详细分析了有或无电流刺激时爆发神经元跨膜的离子流及其对跨膜电位能变化的贡献功率。我们发现,在爆发尖峰的去极化过程中,这种功率变为负值,这在先前使用另一种能量模型的研究中也有发现。我们还发现,爆发期间神经元的能量消耗最小。特别是在无刺激的自发状态下,30秒爆发期间的总能量消耗(2.152×10焦耳)与产生单个动作电位期间的生物能量消耗(2.468×10焦耳)非常相似,如Wang等人(《神经可塑性》2017年,2017a)所示。我们的结果表明,这种低能量消耗特性可能仅仅是产生爆发的生物物理学结果,这与能量最小化原则一致。我们的结果还意味着神经能量在神经编码中起关键作用,这为当今神经科学面临的一个核心挑战的研究开辟了一条新途径。