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在双稳态吸引子网络模型中,刺激检测率和潜伏期、放电率以及1 - 40Hz振荡功率受超慢波动调制。

Stimulus detection rate and latency, firing rates and 1-40Hz oscillatory power are modulated by infra-slow fluctuations in a bistable attractor network model.

作者信息

Lundqvist Mikael, Herman Pawel, Palva Matias, Palva Satu, Silverstein David, Lansner Anders

机构信息

Department of Computational Biology, Royal Institute of Technology (KTH), Sweden; Stockholm University, Sweden.

出版信息

Neuroimage. 2013 Dec;83:458-71. doi: 10.1016/j.neuroimage.2013.06.080. Epub 2013 Jul 10.

Abstract

Recordings of membrane and field potentials, firing rates, and oscillation amplitude dynamics show that neuronal activity levels in cortical and subcortical structures exhibit infra-slow fluctuations (ISFs) on time scales from seconds to hundreds of seconds. Similar ISFs are salient also in blood-oxygenation-level dependent (BOLD) signals as well as in psychophysical time series. Functional consequences of ISFs are not fully understood. Here, they were investigated along with dynamical implications of ISFs in large-scale simulations of cortical network activity. For this purpose, a biophysically detailed hierarchical attractor network model displaying bistability and operating in an oscillatory regime was used. ISFs were imposed as slow fluctuations in either the amplitude or frequency of fast synaptic noise. We found that both mechanisms produced an ISF component in the synthetic local field potentials (LFPs) and modulated the power of 1-40Hz oscillations. Crucially, in a simulated threshold-stimulus detection task (TSDT), these ISFs were strongly correlated with stimulus detection probabilities and latencies. The results thus show that several phenomena observed in many empirical studies emerge concurrently in the model dynamics, which yields mechanistic insight into how infra-slow excitability fluctuations in large-scale neuronal networks may modulate fast oscillations and perceptual processing. The model also makes several novel predictions that can be experimentally tested in future studies.

摘要

对膜电位和场电位、放电率以及振荡幅度动态的记录表明,皮层和皮层下结构中的神经元活动水平在从秒到数百秒的时间尺度上呈现出超慢波动(ISFs)。类似的ISFs在血氧水平依赖(BOLD)信号以及心理物理学时间序列中也很显著。ISFs的功能后果尚未完全了解。在此,我们在皮层网络活动的大规模模拟中对ISFs及其动态影响进行了研究。为此,我们使用了一个具有生物物理细节的分层吸引子网络模型,该模型表现出双稳态并在振荡状态下运行。ISFs被施加为快速突触噪声幅度或频率的缓慢波动。我们发现,这两种机制都在合成局部场电位(LFP)中产生了一个ISF成分,并调制了1-40Hz振荡的功率。至关重要的是,在模拟阈值刺激检测任务(TSDT)中,这些ISFs与刺激检测概率和潜伏期密切相关。因此,结果表明,在许多实证研究中观察到的几种现象在模型动态中同时出现,这为大规模神经元网络中的超慢兴奋性波动如何调制快速振荡和感知处理提供了机制性见解。该模型还做出了几个新的预测,可在未来的研究中进行实验验证。

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