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迈向大脑动力学的整合连续体模型:脑节律、同步振荡与皮质稳定性。

Toward an integrated continuum model of cerebral dynamics: the cerebral rhythms, synchronous oscillation and cortical stability.

作者信息

Wright J J, Robinson P A, Rennie C J, Gordon E, Bourke P D, Chapman C L, Hawthorn N, Lees G J, Alexander D

机构信息

Brain Dynamics Laboratory, Mental Health Research Institute of Victoria, Melbourne, Australia.

出版信息

Biosystems. 2001 Nov-Dec;63(1-3):71-88. doi: 10.1016/s0303-2647(01)00148-4.

Abstract

Continuum models of cerebral cortex with parameters derived from physiological data, provide explanations of the cerebral rhythms, synchronous oscillation, and autonomous cortical activity in the gamma frequency range, and suggest possible mechanisms for dynamic self-organization in the brain. Dispersion relations and derivations of power spectral response for the models, show that a low frequency resonant mode and associated travelling wave solutions of the models' equations of state can account for the predominant 1/f spectral content of the electroencephalogram (EEG). Large scale activity in the alpha, beta, and gamma bands, is accounted for by thalamocortical interaction, under regulation by diffuse cortical excitation. System impulse responses can be used to model Event-Related Potentials. Further classes of local resonance may be generated by rapid negative feedbacks at active synapses. Activity in the gamma band around 40 Hz, associated with large amplitude oscillations of pulse density, appears at higher levels of cortical activation, and is unstable unless compensated by synaptic feedbacks. Control of cortical stability by synaptic feedbacks offers a partial account of the regulation of autonomous activity within the cortex. Synchronous oscillation occurs between concurrently excited cortical sites, and can be explained by analysis of wave motion radiating from each of the co-active sites. These models are suitable for the introduction of learning rules-most notably the coherent infomax rule.

摘要

具有从生理数据得出的参数的大脑皮质连续体模型,解释了大脑节律、同步振荡以及伽马频率范围内的自主皮质活动,并提出了大脑中动态自组织的可能机制。模型的色散关系和功率谱响应推导表明,模型状态方程的低频共振模式及相关行波解可以解释脑电图(EEG)主要的1/f频谱成分。在弥散性皮质兴奋的调节下,丘脑皮质相互作用解释了α、β和伽马波段的大规模活动。系统脉冲响应可用于对事件相关电位进行建模。活跃突触处的快速负反馈可能会产生更多类别的局部共振。与脉冲密度的大幅度振荡相关的40赫兹左右伽马波段的活动,出现在较高水平的皮质激活状态下,并且除非由突触反馈进行补偿否则是不稳定的。突触反馈对皮质稳定性的控制部分解释了皮质内自主活动的调节。同步振荡发生在同时被激发的皮质位点之间,并且可以通过分析从每个共同活跃位点辐射出的波动来解释。这些模型适用于引入学习规则——最显著的是相干信息最大化规则。

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