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网络可塑性在自适应滤波和行为习惯化中的作用。

Network plasticity in adaptive filtering and behavioral habituation.

机构信息

Trinity College Institute of Neuroscience, Smurfit Institute of Genetics, School of Genetics and Microbiology and School of Natural Sciences, Trinity College Dublin, Dublin-2, Ireland; National Centre for Biological Sciences, TIFR Centre, Bangalore 560065, India.

出版信息

Neuron. 2014 Jun 18;82(6):1216-29. doi: 10.1016/j.neuron.2014.04.035.

Abstract

The ability of organisms to seamlessly ignore familiar, inconsequential stimuli improves their selective attention and response to salient features of the environment. Here, I propose that this fundamental but unexplained phenomenon substantially derives from the ability of any pattern of neural excitation to create an enhanced inhibitory (or "negative") image of itself through target-specific scaling of inhibitory inputs onto active excitatory neurons. Familiar stimuli encounter strong negative images and are therefore less likely to be transmitted to higher brain centers. Integrating historical and recent observations, the negative-image model described here provides a mechanistic framework for understanding habituation, which is connected to ideas on dynamic predictive coding. In addition, it suggests insights for understanding autism spectrum disorders.

摘要

生物体能够无缝地忽略熟悉的、无关紧要的刺激,从而提高其对环境显著特征的选择性注意和反应能力。在这里,我提出一个假设,即这种基本但尚未得到解释的现象主要源自于任何模式的神经兴奋通过对活跃兴奋神经元的抑制性输入进行目标特异性缩放,从而产生自身增强的抑制(或“负”)图像的能力。熟悉的刺激会遇到强烈的负像,因此不太可能被传送到大脑高级中枢。结合历史和近期的观察结果,这里描述的负像模型为理解习惯化提供了一个机制框架,习惯化与动态预测编码的思想有关。此外,它还为理解自闭症谱系障碍提供了一些见解。

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