Dyakova Olga, Lee Yu-Jen, Longden Kit D, Kiselev Valerij G, Nordström Karin
Department of Neuroscience, Uppsala University, Box 593, 75124 Uppsala, Sweden.
HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20176, USA.
Nat Commun. 2015 Oct 6;6:8522. doi: 10.1038/ncomms9522.
Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons with limited bandwidth to encode challengingly large input ranges. Natural scenes are not random, and peripheral visual systems in vertebrates and insects have evolved to respond efficiently to their typical spatial statistics. The mammalian visual cortex is also tuned to natural spatial statistics, but less is known about coding in higher order neurons in insects. To redress this we here record intracellularly from a higher order visual neuron in the hoverfly. We show that the cSIFE neuron, which is inhibited by stationary images, is maximally inhibited when the slope constant of the amplitude spectrum is close to the mean in natural scenes. The behavioural optomotor response is also strongest to images with naturalistic image statistics. Our results thus reveal a close coupling between the inherent statistics of natural scenes and higher order visual processing in insects.
动物的感觉系统能最佳地适应自然环境中通常遇到的那些特征，从而使带宽有限的神经元能够编码具有挑战性的大范围输入。自然场景并非随机的，脊椎动物和昆虫的外周视觉系统已经进化到能够有效地响应其典型的空间统计特征。哺乳动物的视觉皮层也能适应自然空间统计特征，但对于昆虫高阶神经元中的编码情况了解较少。为了纠正这一点，我们在这里对食蚜蝇的一个高阶视觉神经元进行细胞内记录。我们发现，被静止图像抑制的cSIFE神经元，在幅度谱的斜率常数接近自然场景中的平均值时受到最大抑制。行为上的视动反应对具有自然图像统计特征的图像也最为强烈。因此，我们的结果揭示了自然场景的固有统计特征与昆虫高阶视觉处理之间的紧密联系。
