Xu Jia-Min, Wang Ce-Qun, Lin Long-Nian
Key Laboratory of Brain Functional Genomics (Ministry of Education and Shanghai Municipality), East China Normal University, Shanghai 200062, China.
Sheng Li Xue Bao. 2014 Jun 25;66(3):349-57.
Multi-channel in vivo recording techniques are used to record ensemble neuronal activity and local field potentials (LFP) simultaneously. One of the key points for the technique is how to process these two sets of recorded neural signals properly so that data accuracy can be assured. We intend to introduce data processing approaches for action potentials and LFP based on the original data collected through multi-channel recording system. Action potential signals are high-frequency signals, hence high sampling rate of 40 kHz is normally chosen for recording. Based on waveforms of extracellularly recorded action potentials, tetrode technology combining principal component analysis can be used to discriminate neuronal spiking signals from differently spatially distributed neurons, in order to obtain accurate single neuron spiking activity. LFPs are low-frequency signals (lower than 300 Hz), hence the sampling rate of 1 kHz is used for LFPs. Digital filtering is required for LFP analysis to isolate different frequency oscillations including theta oscillation (4-12 Hz), which is dominant in active exploration and rapid-eye-movement (REM) sleep, gamma oscillation (30-80 Hz), which is accompanied by theta oscillation during cognitive processing, and high frequency ripple oscillation (100-250 Hz) in awake immobility and slow wave sleep (SWS) state in rodent hippocampus. For the obtained signals, common data post-processing methods include inter-spike interval analysis, spike auto-correlation analysis, spike cross-correlation analysis, power spectral density analysis, and spectrogram analysis.
多通道体内记录技术用于同时记录神经元集群活动和局部场电位(LFP)。该技术的关键要点之一是如何正确处理这两组记录的神经信号,以确保数据准确性。我们打算基于通过多通道记录系统收集的原始数据,介绍动作电位和LFP的数据处理方法。动作电位信号是高频信号,因此通常选择40kHz的高采样率进行记录。基于细胞外记录的动作电位波形,结合主成分分析的四极管技术可用于区分来自不同空间分布神经元的神经元放电信号,以获得准确的单神经元放电活动。LFP是低频信号(低于300Hz),因此LFP的采样率为1kHz。LFP分析需要进行数字滤波,以分离不同频率的振荡,包括在主动探索和快速眼动(REM)睡眠中占主导地位的theta振荡(4-12Hz)、在认知处理过程中伴随theta振荡的gamma振荡(30-80Hz),以及啮齿动物海马体在清醒不动和慢波睡眠(SWS)状态下的高频涟漪振荡(100-250Hz)。对于获得的信号,常见的数据后处理方法包括峰峰间隔分析、尖峰自相关分析、尖峰互相关分析、功率谱密度分析和频谱图分析。