Neural image processing by dendritic networks
Neural image processing by dendritic networks
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DOI：
10.1073/pnas.1830705100
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发表时间：
2003-09-16
影响因子：
11.1
通讯作者：
Borst, A
中科院分区：
文献类型：
--
作者：
Cuntz, H;Haag, J;Borst, A
卷积是图像处理中最常用的运算之一。基于对苍蝇运动敏感的视觉中间神经元的实验结果，我们通过真实的隔室建模表明树枝状网络可以实现这一操作。在第一步骤中，两个细胞之间的树突电耦合在空间上模糊了原始运动输入。然后，模糊的运动图像通过抑制性树突突触传递到第三个细胞，从而使信号变得清晰。这种运动对比度的增强可能是基于飞行中的相对运动的图形-背景辨别的中心要素。
Convolution is one of the most common operations in image processing. Based on experimental findings on motion-sensitive visual interneurons of the fly, we show by realistic compartmental modeling that a dendritic network can implement this operation. in a first step, dendritic electrical coupling between two cells spatially blurs the original motion input. The blurred motion image is then passed onto a third cell via inhibitory dendritic synapses resulting in a sharpening of the signal. This enhancement of motion contrast may be the central element of figure-ground discrimination based on relative motion in the fly.