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Relationships between spike-free local field potentials and spike timing in human temporal cortex

机译:人颞皮质无峰值局部场电势与峰值时序之间的关系

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摘要

Intracortical recordings comprise both fast events, action potentials (APs), and slower events, known as local field potentials (LFPs). Although it is believed that LFPs mostly reflect local synaptic activity, it is unclear which of their signal components are most closely related to synaptic potentials and would therefore be causally related to the occurrence of individual APs. This issue is complicated by the significant contribution from AP waveforms, especially at higher LFP frequencies. In recordings of single-cell activity and LFPs from the human temporal cortex, we computed quantitative, nonlinear, causal dynamic models for the prediction of AP timing from LFPs, at millisecond resolution, before and after removing AP contributions to the LFP. In many cases, the timing of a significant number of single APs could be predicted from spike-free LFPs at different frequencies. Not surprisingly, model performance was superior when spikes were not removed. Cells whose activity was predicted by the spike-free LFP models generally fell into one of two groups: in the first group, neuronal spike activity was associated with specific phases of low LFP frequencies, lower spike activity at high LFP frequencies, and a stronger linear component in the spike-LFP model; in the second group, neuronal spike activity was associated with larger amplitude of high LFP frequencies, less frequent phase locking, and a stronger nonlinear model component. Spike timing in the first group was better predicted by the sign and level of the LFP preceding the spike, whereas spike timing in the second group was better predicted by LFP power during a certain time window before the spike.
机译:皮层内记录既包括快速事件,动作电位(AP),也包括较慢的事件,称为局部场电位(LFP)。尽管据信LFP最能反映局部突触活动,但尚不清楚它们的哪些信号成分与突触电位最密切相关,因此与单个AP的发生有因果关系。 AP波形的重要贡献使此问题变得复杂,尤其是在较高的LFP频率下。在人类颞叶皮质的单细胞活动和LFP的记录中,我们计算了定量,非线性,因果动态模型,用于以毫秒为单位从LFP预测AP时序,并在移除AP对LFP的贡献之前和之后。在许多情况下,可以根据不同频率的无尖峰LFP预测大量单个AP的时序。毫不奇怪,当不消除尖峰时,模型性能会更好。通过无尖峰LFP模型预测其活性的细胞通常分为两组:在第一组中,神经元尖峰活性与低LFP频率的特定阶段相关,在高LFP频率下较低的尖峰活性和更强的线性峰值LFP模型中的组件;在第二组中,神经元的尖峰活动与高LFP频率的较大幅度,较低的锁相频率以及更强的非线性模型分量相关。通过峰值之前的LFP的符号和电平可以更好地预测第一组的峰值时序,而通过峰值之前的特定时间窗口内的LFP功率可以更好地预测第二组的峰值时序。

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