Adaptive coding of visual information in neural populations
Adaptive coding of visual information in neural populations
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DOI：
10.1038/nature06563
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发表时间：
2008-03-13
期刊：
影响因子：
64.8
通讯作者：
Dragoi, Valentin
中科院分区：
文献类型：
--
作者：
Gutnisky, Diego A.;Dragoi, Valentin
我们对环境的看法取决于神经网络迅速适应传入刺激的能力（1-4）。越来越多地意识到神经代码是自适应的（5），也就是说，感觉神经元以动态方式改变其反应和选择性，以匹配输入刺激的变化（1,2,5）。了解对固定结构变化的刺激刺激皮质网络的刺激的迅速暴露或适应性对于理解感觉编码与行为之间的关系至关重要（5-8）。适应的生理研究极大地有助于我们对个人感觉神经元如何改变其对影响刺激编码的反应的理解（2,9-12）（2,9-12），但是适应是否会影响神经种群中的信息编码。在这里，我们研究了短暂的适应性（关于视觉固定的时间尺度）（2,9,10）如何影响猕猴（Macaca Mulatta）初级视觉皮层（V1）中的神经元相关性结构和人口编码的准确性。我们发现，对固定结构的刺激的简要适应通过选择性降低其平均值和可变性，可以重新组织整个网络的相关性分布。神经元相关性的自适应变化与特定的刺激依赖性效率变化有关，并且与适应后感知性能的变化一致（2,13,14）。我们的结果超出了当前感觉编码理论的预测，这表明简短的适应性提高了人口编码的准确性，以优化自然观看过程中的神经元性能。
Our perception of the environment relies on the capacity of neural networks to adapt rapidly to changes in incoming stimuli(1-4). It is increasingly being realized that the neural code is adaptive(5), that is, sensory neurons change their responses and selectivity in a dynamic manner to match the changes in input stimuli(1,2,5). Understanding how rapid exposure, or adaptation, to a stimulus of fixed structure changes information processing by cortical networks is essential for understanding the relationship between sensory coding and behaviour(5-8). Physiological investigations of adaptation have contributed greatly to our understanding of how individual sensory neurons change their responses to influence stimulus coding(2,9-12), yet whether and how adaptation affects information coding in neural populations is unknown. Here we examine how brief adaptation ( on the timescale of visual fixation)(2,9,10) influences the structure of interneuronal correlations and the accuracy of population coding in the macaque ( Macaca mulatta) primary visual cortex ( V1). We find that brief adaptation to a stimulus of fixed structure reorganizes the distribution of correlations across the entire network by selectively reducing their mean and variability. The post- adaptation changes in neuronal correlations are associated with specific, stimulus- dependent changes in the efficiency of the population code, and are consistent with changes in perceptual performance after adaptation(2,13,14). Our results have implications beyond the predictions of current theories of sensory coding, suggesting that brief adaptation improves the accuracy of population coding to optimize neuronal performance during natural viewing.