Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Cell Rep. 2023 Apr 25;42(4):112254. doi: 10.1016/j.celrep.2023.112254. Epub 2023 Mar 24.
Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.
系统神经科学的大部分内容假定大脑活动模式具有重要的功能,而这些模式缺乏自然的大小、持续时间或频率尺度。该领域已经提出了一些突出的、有时甚至相互竞争的解释,来阐述这种无标度活动的本质。在这里,我们在跨物种和模态的范围内协调这些解释。首先,我们将兴奋-抑制(E-I)平衡的估计与分布式大脑活动的时间分辨相关性联系起来。其次,我们开发了一种无偏的方法来对受这种时间分辨相关性约束的时间序列进行抽样。第三,我们使用这种方法表明,E-I 平衡的估计可以解释各种无标度现象,而无需为这些现象赋予额外的功能或重要性。总的来说,我们的结果简化了现有对无标度大脑活动的解释,并对试图超越这些解释的未来理论提供了严格的检验。