Dynamic properties of compass neurons in the bee brain

许多动物表现出的卓越的定向技能的一个基本要求是它们将自己的前进方向与外部参考框架联系起来的能力。大脑中完成这一壮举的神经元被称为头向细胞（在哺乳动物中）或罗盘神经元（在昆虫中）。每一个罗盘神经元都发出动物和外部参照系之间的特定角度的信号，对昆虫来说，外部参照系是天空的偏振模式、太阳的方位角或类似地标的线索。神经元的偏好方向，即动物与刺激之间引发最高活动的角度，通常通过缓慢旋转昆虫头部上方的偏光片或模拟太阳来评估。这是为了模仿动物在自然天空下的旋转。然而，这种刺激忽略了自然运动的动态特征。飞行和行走的昆虫都不是连续地改变它们的方向，而是在所谓的扫视过程中以高角速度突然改变它们的方向，这种速度与纯粹的向前运动交替进行。到目前为止，我们还不知道昆虫的罗盘神经元是如何在自然发生的运动动态下编码天空罗盘信号的。利用大黄蜂中央复合体罗盘神经元的细胞内记录，我们可以表明，导致最强激发的偏振角（首选偏振角）不是神经元的静态特性，而是受到三个参数的强烈影响：1。偏振光的旋转方向，2。偏振光的角速度3。神经元先前的活动状态（兴奋或抑制）。这些参数的变化导致首选偏振角的偏移高达60°。这就提出了一个问题，这样的系统如何能够可靠地告知动物当前的航向。为了回答这个问题，我们需要深入了解神经元反应的动力学。因此，这个项目的目标是描述天空罗盘刺激的速度动力学如何塑造大黄蜂中央复合体中罗盘神经元的反应特性。我们将使用天空罗盘刺激，如偏振光（代表天空）和非偏振光绿斑（代表太阳），具有广泛的速度范围，包括公布的大黄蜂飞行的自然速度曲线。我们将具体描述大黄蜂中枢-复杂网络不同阶段的罗盘神经元的调谐特性，作为旋转方向和旋转速度的函数，以及神经元活动历史的影响。这项研究的结果将有助于理解罗盘网络如何在输入信号高度可变的情况下产生一致的航向信号。

A fundamental requirement for the remarkable orientation skills, that many animals show is their ability to relate their heading direction to an external frame of reference. Neurons in the brain that accomplish this feat are called head-direction cells (in mammals) or compass neurons (in insects). Each compass neuron signals a specific angle between the animal and an external frame of reference, which in insects is the sky polarization pattern, the azimuth of the sun, or landmark-like cues. The preference direction of the neuron, i.e. the angle between the animal and the stimulus eliciting the highest activity, is usually assessed by slowly rotating a polarizer above, or a simulated sun around, the insect’s head. This is supposed to mimic a rotation of the animal underneath a natural sky. However, such stimuli neglect the dynamic features of natural movement. Both flying and walking insects change their heading not continuously, but abruptly at high angular velocities during so-called saccades, which alternate with segments of pure forward motion. It so far unknown, how insect compass neurons code sky-compass cues under naturally occurring dynamics of movement.Using intracellular recordings from compass neurons in the central complex of bumblebees, we could show that the angle of polarization that leads to the strongest excitation (preferred angle of polarization) is not a static property of the neurons but is strongly influenced by three parameters: 1. The direction of rotation of the polarized light, 2. The angular velocity of the polarized light 3. The previous activity state of the neuron (excited or inhibited). Changes in these parameters lead to shifts of the preferred angle of polarization of up to 60°. This raises the question, how such a system can reliably inform the animal about its current heading. To answer this question, we need to understand the dynamics of the neuronal responses in depth.The goal of this project is therefore to characterize how the velocity dynamics of sky-compass stimuli shape the response properties of compass neurons in the central-complex of bumblebees. We will use sky-compass stimuli such as polarized light (representing the sky) and an unpolarized green light spot (representing the sun) with a broad range of velocities, including naturalistic velocity profiles from published bumblebee flights. We will specifically characterize the tuning properties of compass neurons at different stages of the bumblebee central-complex network as a function of rotation direction and rotation velocity as well as the effects of the history of neuronal activity. The results of this study will help to understand how compass networks can generate consistent heading signals despite highly variable dynamics of their input signal.