【摘要】 在利用多电极阵列(multielectrode arrays,MEA)记录离体培养海马神经元网络的电生理研究中,发现电极附近神经元群体同步放电形成了局部场电位(local field potential,LFP),同时细胞外记录信号为跨膜电压信号的微分,这些因素使检测网络发放的锋电位遇到困难。为正确检测锋电位(spike),在综合比较多种检测方法的基础上,提出一种改进的峰值检测法,以0.6ms为判决阈值,有效解决了原峰值检测法因滑动窗分界导致的重复检测。通过该方法检测发育成熟的网络发放的锋电位,虚警率和漏报率分别为:5%±1%和2%±1%,效果优于传统的阈值检测法。上述结果表明,改进的方法适合于神经元网络电活动的研究。更多还原

【Abstract】 Spike detection in the research of neural network electrophysiology with extracellular recording in vitro from Multi-microelectrode arrays(MEA) is an elementary pre-processing.Spike signals are frequently superimposed on local field potential(LFP) that reflect the activity of populations of cells near the electrode tip,moreover,the recorded extracellular signal represents a time derivative of the intracellular signal.For these reasons,the detection of spike becomes a technical challenge.After comparing varieties of detection techniques,we bring up a revised version of a peak-detection scheme.This advanced approach works out an unwanted detection problem of the previous one caused by the position of sliding window boundary.Its inclusion errors and exclusion errors are 5%±1% and 2%±1% separately.Therefore it is better than the classic threshold detection,and it will be more useful in the research of neural network.更多还原