Spontaneous Fluctuations in Visual Cortical Responses Influence Population Coding Accuracy
Spontaneous Fluctuations in Visual Cortical Responses Influence Population Coding Accuracy
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DOI：
10.1093/cercor/bhv312
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发表时间：
2017-02-01
期刊：
影响因子：
3.7
通讯作者：
Dragoi, Valentin
中科院分区：
文献类型：
--
作者：
Gutnisky, Diego A.;Beaman, Charles B.;Dragoi, Valentin
大脑皮层的信息处理不仅取决于传入刺激的性质，还取决于刺激时神经元网络的状态。也就是说，同样的刺激会根据接收到的神经元环境而被不同地处理。可能影响神经元环境的一个主要因素是背景，或刺激前正在进行的神经元活动。在视觉皮层中，持续的活动已知在局部回路的发育中起关键作用，但它是否影响成人皮层中视觉特征的编码尚不清楚。在这里，我们研究了初级视觉皮层（V1）中单个神经元和群体编码的信息是否以及如何依赖于刺激呈现前正在进行的活动。我们报告说，当单个神经元处于“低”刺激前状态时，尽管它们的诱发反应减少，但它们具有更高的识别刺激特征（如方向）的能力。通过测量刺激前活动在神经元群中的分布，我们发现在低刺激状态下，网络识别的准确性得到了提高。因此，正在进行的活动状态在网络上的分布创造了一个“内部环境”，它动态地过滤传入的刺激，以调节感觉编码的准确性。持续活动状态对刺激编码的调节与循环网络模型一致，在循环网络模型中，持续活动动态控制单个神经元的平衡背景兴奋和抑制。
Information processing in the cerebral cortex depends not only on the nature of incoming stimuli, but also on the state of neuronal networks at the time of stimulation. That is, the same stimulus will be processed differently depending on the neuronal context in which it is received. A major factor that could influence neuronal context is the background, or ongoing neuronal activity before stimulation. In visual cortex, ongoing activity is known to play a critical role in the development of local circuits, yet whether it influences the coding of visual features in adult cortex is unclear. Here, we investigate whether and how the information encoded by individual neurons and populations in primary visual cortex (V1) depends on the ongoing activity before stimulus presentation. We report that when individual neurons are in a "low" prestimulus state, they have a higher capacity to discriminate stimulus features, such as orientation, despite their reduction in evoked responses. By measuring the distribution of prestimulus activity across a population of neurons, we found that network discrimination accuracy is improved in the low prestimulus state. Thus, the distribution of ongoing activity states across the network creates an "internal context" that dynamically filters incoming stimuli to modulate the accuracy of sensory coding. The modulation of stimulus coding by ongoing activity state is consistent with recurrent network models in which ongoing activity dynamically controls the balanced background excitation and inhibition to individual neurons.