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视网膜神经节细胞中适应和预测性敏感的空间分离。

Spatial segregation of adaptation and predictive sensitization in retinal ganglion cells.

机构信息

Neuroscience Program, Stanford University School of Medicine, 299 Campus Drive West, Stanford, CA, USA.

出版信息

Neuron. 2013 Aug 7;79(3):541-54. doi: 10.1016/j.neuron.2013.06.011.

Abstract

Sensory systems change their sensitivity based on recent stimuli to adjust their response range to the range of inputs and to predict future sensory input. Here, we report the presence of retinal ganglion cells that have antagonistic plasticity, showing central adaptation and peripheral sensitization. Ganglion cell responses were captured by a spatiotemporal model with independently adapting excitatory and inhibitory subunits, and sensitization requires GABAergic inhibition. Using a simple theory of signal detection, we show that the sensitizing surround conforms to an optimal inference model that continually updates the prior signal probability. This indicates that small receptive field regions have dual functionality--to adapt to the local range of signals but sensitize based upon the probability of the presence of that signal. Within this framework, we show that sensitization predicts the location of a nearby object, revealing prediction as a functional role for adapting inhibition in the nervous system.

摘要

感觉系统会根据最近的刺激改变其敏感度,以调整其响应范围,使其适应输入范围,并预测未来的感觉输入。在这里,我们报告了存在拮抗可塑性的视网膜神经节细胞,其表现为中枢适应和外周致敏。通过具有独立适应的兴奋性和抑制性亚基的时空模型捕获神经节细胞的反应,并且致敏需要 GABA 能抑制。使用信号检测的简单理论,我们表明致敏的周围环境符合不断更新先前信号概率的最优推理模型。这表明小的感受野区域具有双重功能——适应局部信号范围,但根据该信号存在的概率进行敏化。在这个框架内,我们表明敏化预测了附近物体的位置,揭示了适应抑制在神经系统中的预测功能。

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