哺乳动物视网膜的运动检测过去一直被认为在很大程度上依靠“ 星爆无长突细胞”(SACs)的树突的内在生物物理。现在，Sebastian Seung及同事通过EyeWire 脑绘图游戏(brain-mapping game)将新的机器学习方法与“众包”(crowd sourcing)方法相结合来重绘无长突细胞和双极细 胞的连线图。他们的结果表明，方向选择性是在突触前层面上、在无长突细胞的时空输入信号中就确定了的，这说明神经回路而非SACs的内在性质才是方向选择性的关键。这一新方法在某些方面使小鼠视网膜与作为昆虫视觉特征的Reichardt运动检测器更接近了.
How does the mammalian retina detect motion? This classic problem in visual neuroscience has remained unsolved for 50 years. In search of clues, here we reconstruct Off-type starburst amacrine cells (SACs) and bipolar cells (BCs) in serial electron microscopic images with help from EyeWire, an online community of ‘citizen neuroscientists’. On the basis of quantitative analyses of contact area and branch depth in the retina, we find evidence that one BC type prefers to wire with a SAC dendrite near the SAC soma, whereas another BC type prefers to wire far from the soma. The near type is known to lag the far type in time of visual response. A mathematical model shows how such ‘space–time wiring specificity’ could endow SAC dendrites with receptive fields that are oriented in space–time and therefore respond selectively to stimuli that move in the outward direction from the soma.