Neural bases of honeybee visual information processing and locomotion control

光感受器通过它们的突触传递来代表光的变化。然后，突触后神经元将这些信息编码成反应，以一致地代表现实世界对象的相似和不同。当世界看起来嘈杂时(在昏暗的光线下)，最好通过缓慢地总结它的事件来捕捉它，因为这增加了视觉的可靠性。但当世界(在明亮的光线下)是明确的时，重要的是迅速增强其差异，因为这最好地利用了神经元有限的通道容量。因此，为了最大化信息流，世界的神经表征应该适应其不断变化的统计数据。尽管光感受器突触被暗示遵循这些编码规则，但支撑其适应性信息处理的机制仍然是一个谜。这个P.D.项目的目的是量化和模拟蜜蜂光感受器突触中的量子突触信息传递如何适应不断变化的光条件。通过使用电生理学方法监测新型虚拟现实系统和数学模型中的行为，学生将研究突触前机制和突触后机制如何协调在一起，以最大限度地提高突触信息传输，以及这些信息是如何表现和分配给蜜蜂的视觉感知的。我们预计，这些知识将对指导未来神经植入物、其他仿生装置和机器人视觉的设计产生直接影响。

Photoreceptors represent light changes through their synaptic transmission. Postsynaptic interneurones then encode these messages into responses that represent similarities and differences of real-world objects consistently. When the world seems noisy (in dim light), it is best captured by summing up its events slowly, as this increases the reliability of vision. But when the world is unambiguous (in bright light), it is important to enhance its differences fast, as this best utilises the neurones' limited channel capacity. Thus, to maximise information flow, neural representations of the world should adapt to its changing statistics. Although photoreceptor synapses have been implied to follow these coding rules, the mechanisms underpinning their adaptive information processing remain a mystery. The aim of this P.D.-project is to quantify and model how quantal synaptic information transfer in honeybee photoreceptor synapses adapts to changing light conditions. By using electrophysiological approaches while monitoring behavior in novel virtual reality systems and mathematical modelling, the student will investigate how pre- and postsynaptic mechanisms are tuned together to maximise synaptic information transfer and how this information is represented and distributed for the bee visual perception. We anticipate that such knowledge would have direct impact in guiding the design of future neural implants, other biomimetic devises and robotic vision.