Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
Proc Natl Acad Sci U S A. 2013 Jan 8;110(2):696-701. doi: 10.1073/pnas.1210489109. Epub 2012 Dec 3.
Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair with a 95% success rate. In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not. Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this information is relayed from the brain to the wing motor centers in population vector form.
拦截移动物体需要预测其未来位置。蜻蜓通过 95%的成功率在空中拦截猎物,解决了这一复杂任务。在这项研究中,我们表明,一组 16 个神经元,称为目标选择性下行神经元(TSDN),以高准确性和可靠性编码了一个群体矢量,该矢量反映了 360°范围内目标的方向。TSDN 的空间(感受野)和时间(潜伏期)特性分别与捕食飞行过程中猎物集中的视网膜区域和反应时间相匹配。在动物之间,每种 TSDN 类型的定向调谐曲线和形态特征(3D 轨迹)都是一致的,但尖峰率则不然。我们的研究结果强调,使用少量神经元就可以实现用于目标跟踪和拦截的成功神经回路,并且在蜻蜓中,这些信息以群体矢量的形式从大脑传递到翅膀运动中心。