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分离的多单位活动和局部场电位:对一个运动决策任务的理论启发分析。

Dissociated multi-unit activity and local field potentials: a theory inspired analysis of a motor decision task.

机构信息

Department of Technologies and Health, Istituto Superiore di Sanità, I-00161 Roma, Italy.

出版信息

Neuroimage. 2010 Sep;52(3):812-23. doi: 10.1016/j.neuroimage.2010.01.063. Epub 2010 Jan 25.

Abstract

Local field potentials (LFP) and multi-unit activity (MUA) recorded in vivo are known to convey different information about the underlying neural activity. Here we extend and support the idea that single-electrode LFP-MUA task-related modulations can shed light on the involved large-scale, multi-modular neural dynamics. We first illustrate a theoretical scheme and associated simulation evidence, proposing that in a multi-modular neural architecture local and distributed dynamic properties can be extracted from the local spiking activity of one pool of neurons in the network. From this new perspective, the spectral features of the field potentials reflect the time structure of the ongoing fluctuations of the probed local neuronal pool on a wide frequency range. We then report results obtained recording from the dorsal premotor (PMd) cortex of monkeys performing a countermanding task, in which a reaching movement is performed, unless a visual stop signal is presented. We find that the LFP and MUA spectral components on a wide frequency band (3-2000 Hz) are very differently modulated in time for successful reaching, successful and wrong stop trials, suggesting an interplay of local and distributed components of the underlying neural activity in different periods of the trials and for different behavioural outcomes. Besides, the MUA spectral power is shown to possess a time-dependent structure, which we suggest could help in understanding the successive involvement of different local neuronal populations. Finally, we compare signals recorded from PMd and dorso-lateral prefrontal (PFCd) cortex in the same experiment, and speculate that the comparative time-dependent spectral analysis of LFP and MUA can help reveal patterns of functional connectivity in the brain.

摘要

在体记录的局部场电位 (LFP) 和多单位活动 (MUA) 被认为传递了关于潜在神经活动的不同信息。在这里,我们扩展并支持这样一种观点,即单电极 LFP-MUA 任务相关的调制可以揭示涉及的大规模、多模块神经动力学。我们首先说明一个理论方案和相关的模拟证据,提出在多模块神经结构中,可以从网络中一个神经元池中局部的尖峰活动中提取局部和分布式动态特性。从这个新的角度来看,场电位的频谱特征反映了在广泛的频率范围内探测到的局部神经元池的持续波动的时间结构。然后,我们报告了在猴子执行反命令任务时从背侧运动前皮层 (PMd) 记录的结果,在该任务中,除非出现视觉停止信号,否则会进行伸手运动。我们发现,在成功的伸手、成功和错误的停止试验中,宽频带(3-2000 Hz)的 LFP 和 MUA 频谱成分在时间上的调制非常不同,这表明在试验的不同时期和不同行为结果下,潜在神经活动的局部和分布式成分之间存在相互作用。此外,MUA 频谱功率显示出时间依赖性结构,我们认为这有助于理解不同局部神经元群体的相继参与。最后,我们比较了在相同实验中从 PMd 和背外侧前额叶 (PFCd) 皮层记录的信号,并推测 LFP 和 MUA 的比较时频谱分析可以帮助揭示大脑中的功能连接模式。

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