From neurons to circuits: linear estimation of local field potentials.
From neurons to circuits: linear estimation of local field potentials.
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DOI：
10.1523/jneurosci.2390-09.2009
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发表时间：
2009-11-04
期刊：
影响因子：
--
通讯作者：
Kreiman G
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文献类型：
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作者：
Rasch M;Logothetis NK;Kreiman G
细胞外生理记录通常分为两个频带：局部场电位（LFP，一种电路特性）和尖峰多单位活动（MUA）。由于LFPs与功能磁共振成像测量的相关性以及研究局部加工和神经元同步性的可能性，人们对LFPs的兴趣越来越大。为了进一步了解LFP的生物物理起源，我们询问是否可以基于来自相同或附近电极的尖峰活动来估计它们的时间过程。我们使用信号估计理论表明，对一个/几个神经元的活动进行线性滤波操作可以解释猕猴初级视觉皮层中LFP时间过程的显著部分。用于估计LFP的线性滤波器具有刻板的形状，其特征在于在负时间滞后处的急剧下降和在正时间滞后处的较慢的正上升。该过滤器在新皮层区域和行为条件（包括自发活动和视觉刺激）之间是相似的。的估计有一个空间分辨率为~1毫米和时间分辨率为~200毫秒。通过考虑一个因果过滤器，我们观察到一个时间不对称，使过滤器中的正时间滞后的贡献更多的LFP估计比负时间滞后。此外，我们发现，尖峰发生在约10毫秒的尖峰从附近的神经元产生更好的估计精度比非同步尖峰。总之，我们的研究结果表明，至少有一些电路级的局部属性的场电位可以预测从一个或几个神经元的活动。
Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons.