Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, VIC, Australia.
Department of Optometry and Vision Sciences, The University of Melbourne, Parkville, VIC, Australia.
Front Neural Circuits. 2023 Apr 17;17:1138774. doi: 10.3389/fncir.2023.1138774. eCollection 2023.
Widely used in neuroscience the averaging of event related potentials is based on the assumption that small responses to the investigated events are present in every trial but can be hidden under the random noise. This situation often takes place, especially in experiments performed at hierarchically lower levels of sensory systems. However, in the studies of higher order complex neuronal networks evoked responses might appear only under particular conditions and be absent otherwise. We encountered this problem studying a propagation of interoceptive information to the cortical areas in the sleep-wake cycle. Cortical responses to various visceral events were present during some periods of sleep, then disappeared for a while and restored again after a period of absence. Further investigation of the viscero-cortical communication required a method that would allow labeling the trials contributing to the averaged event related responses-"efficient trials," and separating them from the trials without any response. Here we describe a heuristic approach to solving this problem in the context of viscero-cortical interactions occurring during sleep. However, we think that the proposed technique can be applicable to any situation where neuronal processing of the same events is expected to be variable due to internal or external factors modulating neuronal activity. The method was first implemented as a script for Spike 2 program version 6.16 (CED). However, at present a functionally equivalent version of this algorithm is also available as Matlab code at https://github.com/george-fedorov/erp-correlations.
事件相关电位的平均被广泛应用于神经科学,其基于这样一种假设,即对所研究事件的小反应存在于每个试验中,但可能被随机噪声所掩盖。这种情况经常发生,特别是在感官系统的较低层次进行的实验中。然而,在对高阶复杂神经网络的研究中,诱发反应可能仅在特定条件下出现,否则则不存在。我们在研究睡眠-觉醒周期中内脏感觉信息向皮质区域的传播时遇到了这个问题。在睡眠的某些时期,皮质对各种内脏事件有反应,然后暂时消失,在一段时间没有反应后又恢复。为了进一步研究内脏-皮质的通讯,需要一种方法来标记有助于平均事件相关反应的试验——“有效试验”,并将其与没有任何反应的试验区分开来。在这里,我们描述了一种在睡眠过程中发生的内脏-皮质相互作用的背景下解决这个问题的启发式方法。然而,我们认为,所提出的技术可以适用于任何情况下,由于内部或外部因素调节神经元活动,对相同事件的神经元处理预计是可变的。该方法最初是作为 Spike 2 程序版本 6.16(CED)的脚本实现的。然而,目前,该算法的功能等效版本也可以在 https://github.com/george-fedorov/erp-correlations 上以 Matlab 代码的形式获得。