Dvir Hila, Guo Shu, Kang Rui, Li Daqing, Havlin Shlomo
Department of Physics, Bar-Ilan University, Ramat Gan, Israel.
Research Institute of Science and Technology Innovation, Civil Aviation University of China, Tianjin, China.
Commun Biol. 2025 Aug 26;8(1):1281. doi: 10.1038/s42003-025-08667-8.
Even without external stimuli, neurons produce spontaneous bursts of activities. Theoretical and practical clinical considerations, suggest the importance of determining the in-vivo statistical profile of those spontaneous spikes bursts, however this task has not been accomplished yet. Currently, it is only accepted that the in-vivo value of the mean firing rate (λ) of those spontaneous bursts is below 0.1Hz, without knowing its specific value and its population distribution. Here we propose a framework to evaluate the neurons' λ during rest of a given subject, using stochastic signal processing analysis of in-vivo brain fMRI and EEG. Our main hypothesis is that during rest the input to the neurons is mostly formed by a random neuronal noise, and although it fluctuates with zero mean, it affects the neurons' signal output characteristics. Our results based on in-vivo human fMRI and EEG databases, suggest that different people have different and stable characteristic λ values, and that λ of different functional systems of the same subject correlate in their values. Moreover, we find here that the λ values of subjects correlate with their brain task performances, in particular for tasks which are known to be affected by changes in neuronal noise or neuronal excitability threshold.
即使没有外部刺激，神经元也会产生自发的活动爆发。理论和实际临床考量表明，确定这些自发尖峰爆发的体内统计特征很重要，然而这项任务尚未完成。目前，仅知道这些自发爆发的平均放电率（λ）的体内值低于0.1Hz，但其具体值及其总体分布尚不清楚。在此，我们提出一个框架，利用体内脑功能磁共振成像（fMRI）和脑电图（EEG）的随机信号处理分析来评估给定受试者休息时神经元的λ。我们的主要假设是，在休息期间，神经元的输入主要由随机神经元噪声构成，尽管其均值为零而波动，但它会影响神经元的信号输出特征。我们基于体内人类fMRI和EEG数据库的结果表明，不同的人具有不同且稳定的特征λ值，并且同一受试者不同功能系统的λ值在数值上相互关联。此外，我们在此发现，受试者的λ值与其脑任务表现相关，特别是对于已知受神经元噪声或神经元兴奋性阈值变化影响的任务。
