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Adaptive filtering enhances information transmission in visual cortex.

机译:自适应过滤可增强视觉皮层中的信息传输。

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Sensory neuroscience seeks to understand how the brain encodes natural environments. However, neural coding has largely been studied using simplified stimuli. In order to assess whether the brain's coding strategy depends on the stimulus ensemble, we apply a new information-theoretic method that allows unbiased calculation of neural filters (receptive fields) from responses to natural scenes or other complex signals with strong multipoint correlations. In the cat primary visual cortex we compare responses to natural inputs with those to noise inputs matched for luminance and contrast. We find that neural filters adaptively change with the input ensemble so as to increase the information carried by the neural response about the filtered stimulus. Adaptation affects the spatial frequency composition of the filter, enhancing sensitivity to under-represented frequencies in agreement with optimal encoding arguments. Adaptation occurs over 40 s to many minutes, longer than most previously reported forms of adaptation.
机译:感觉神经科学试图了解大脑如何编码自然环境。然而,已经使用简化刺激对神经编码进行了大量研究。为了评估大脑的编码策略是否取决于刺激集合,我们应用了一种新的信息理论方法,该方法允许根据对自然场景或具有强多点相关性的其他复杂信号的响应,对神经过滤器(接受场)进行无偏计算。在猫的主要视觉皮层中,我们将对自然输入的响应与对亮度和对比度匹配的噪声输入的响应进行比较。我们发现,神经过滤器会随着输入集合的变化而自适应地变化,从而增加神经反应所带来的关于过滤后的刺激的信息。适应会影响滤波器的空间频率组成,从而与最佳编码参数相符,从而增强了对频率不足的频率的敏感性。适应过程在40 s到数分钟内发生,比以前报道的大多数适应形式要长。

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