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本文引用的文献

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Irregular dynamics in up and down cortical states.上下皮质状态的不规则动力学。
PLoS One. 2010 Nov 8;5(11):e13651. doi: 10.1371/journal.pone.0013651.
2
How do neurons work together? Lessons from auditory cortex.神经元如何协同工作?来自听觉皮层的启示。
Hear Res. 2011 Jan;271(1-2):37-53. doi: 10.1016/j.heares.2010.06.006. Epub 2010 Jul 11.
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Inhibitory modulation of cortical up states.皮层上状态的抑制性调制。
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Attractors and noise: twin drivers of decisions and multistability.吸引子和噪声:决策和多稳定性的双驱动因素。
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Temperature modulation of slow and fast cortical rhythms.温度调节慢波和快波皮质节律。
J Neurophysiol. 2010 Mar;103(3):1253-61. doi: 10.1152/jn.00890.2009. Epub 2009 Dec 23.
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Effective reduced diffusion-models: a data driven approach to the analysis of neuronal dynamics.有效的简化扩散模型:一种基于数据驱动的神经元动力学分析方法。
PLoS Comput Biol. 2009 Dec;5(12):e1000587. doi: 10.1371/journal.pcbi.1000587. Epub 2009 Dec 4.
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A simple model of cortical dynamics explains variability and state dependence of sensory responses in urethane-anesthetized auditory cortex.一个简单的皮质动力学模型解释了乌拉坦麻醉的听觉皮质中感觉反应的变异性和状态依赖性。
J Neurosci. 2009 Aug 26;29(34):10600-12. doi: 10.1523/JNEUROSCI.2053-09.2009.
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Spontaneous events outline the realm of possible sensory responses in neocortical populations.自发事件勾勒出新皮层群体中可能的感觉反应范围。
Neuron. 2009 May 14;62(3):413-25. doi: 10.1016/j.neuron.2009.03.014.
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The response of cortical neurons to in vivo-like input current: theory and experiment : I. Noisy inputs with stationary statistics.皮层神经元对类体内输入电流的反应:理论与实验:I. 具有平稳统计特性的噪声输入
Biol Cybern. 2008 Nov;99(4-5):279-301. doi: 10.1007/s00422-008-0272-7. Epub 2008 Nov 5.
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A fluctuation-driven mechanism for slow decision processes in reverberant networks.一种用于回响网络中缓慢决策过程的波动驱动机制。
PLoS One. 2008 Jul 2;3(7):e2534. doi: 10.1371/journal.pone.0002534.

探索自发皮层活动中动力学状态和时间尺度的范围。

Exploring the spectrum of dynamical regimes and timescales in spontaneous cortical activity.

机构信息

Istituto Superiore di Sanità, viale Regina Elena 299, 00161 Rome, Italy ; Istituto Superiore di Sanità, viale Regina Elena 299, 00133 Rome, Italy.

出版信息

Cogn Neurodyn. 2012 Jun;6(3):239-50. doi: 10.1007/s11571-011-9179-4. Epub 2011 Nov 1.

DOI:10.1007/s11571-011-9179-4
PMID:23730355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3368061/
Abstract

Rhythms at slow (<1 Hz) frequency of alternating Up and Down states occur during slow-wave sleep states, under deep anaesthesia and in cortical slices of mammals maintained in vitro. Such spontaneous oscillations result from the interplay between network reverberations nonlinearly sustained by a strong synaptic coupling and a fatigue mechanism inhibiting the neurons firing in an activity-dependent manner. Varying pharmacologically the excitability level of brain slices we exploit the network dynamics underlying slow rhythms, uncovering an intrinsic anticorrelation between Up and Down state durations. Besides, a non-monotonic change of Down state duration is also observed, which shrinks the distribution of the accessible frequencies of the slow rhythms. Attractor dynamics with activity-dependent self-inhibition predicts a similar trend even when the system excitability is reduced, because of a stability loss of Up and Down states. Hence, such cortical rhythms tend to display a maximal size of the distribution of Up/Down frequencies, envisaging the location of the system dynamics on a critical boundary of the parameter space. This would be an optimal solution for the system in order to display a wide spectrum of dynamical regimes and timescales.

摘要

在慢波睡眠状态、深度麻醉和体外培养的哺乳动物皮质切片中,会出现慢频率(<1 Hz)的上下状态交替的节律。这种自发振荡是由网络的相互作用产生的,网络的非线性维持着强烈的突触耦合,而疲劳机制则以活动依赖的方式抑制神经元的发射。通过药理学改变脑片的兴奋性水平,我们可以利用慢节律的网络动力学,揭示上下状态持续时间之间的固有反相关性。此外,还观察到下状态持续时间的非单调变化,这缩小了慢节律的可及频率分布。具有活动依赖性自抑制的吸引子动力学即使在系统兴奋性降低时也预测了类似的趋势,这是由于上下状态的稳定性丧失。因此,这种皮质节律往往会显示出最大的上下频率分布大小,预示着系统动力学在参数空间的临界边界上的位置。对于系统来说,这是一个最佳解决方案,以便显示广泛的动力学状态和时间尺度。