State-dependent serotonergic long-range modulation of local interneurons in the Drosophila larval antennal lobe

寻找食物是所有动物的基本任务。嗅觉线索对于检测和评估潜在的食物来源尤为重要。嗅觉过程的调节使觅食行为和适应不断变化的需求（如饥饿）变得灵活。研究了果蝇幼虫触角叶早期嗅觉加工的调控机制。什么样的信息是通过来自大脑高级区域的远程循环连接反馈到早期嗅觉中心的？这些信息是如何整合到人工智能幼虫内部复杂的神经网络中的？我们关注的是一个复发的血清素能神经元（CSDn），它以一种状态依赖的方式调节了幼虫的AL。在食物被剥夺后，它对非食物气味的反应会增强。在这项提议中，我们首先调查这是一种跨气味的一般机制还是一种特定的气味机制。此外，在AL幼虫中，5-羟色胺能调节部分是通过激活局部AL神经元中的抑制性5-HT1A受体来实现的。在被喂食的幼虫中，这些神经元同时接受来自其他局部神经元的谷氨酸能抑制。我们将进一步研究这种双重抑制如何影响局部AL神经元的兴奋性，以及为什么单一抑制机制似乎不足以抑制神经元活动。在研究单元内，我们将比较无脊椎动物和脊椎动物模型之间的循环调节处理机制，这将使我们能够检测保守的网络原理。

Foraging for food is an essential task for all animals. Olfactory cues are especially important for the detection and evaluation of potential food sources. Modulation of olfactory processing allows flexibility in foraging behaviour and adaptation to changing needs, such as hunger. We investigate the modulatory mechanisms of early olfactory processing in the antennal lobe (AL) of Drosophila larvae in detail. What kind of information is fed back to early olfactory centres via long-range recurrent connections from higher brain regions? How is this information integrated into the complex neural network within the larval AL? We focus on a recurrent serotonergic neuron (CSDn), which modulates the larval AL in a state dependent manner. After food deprivation, its response towards a non-food odour is increased. In this proposal, we first investigate if this is a general mechanism across odours or if this is an odour-specific mechanism. Moreover, in the larval AL, serotonergic modulation partly takes place via activation of an inhibitory 5-HT1A receptor in local AL neurons. In fed larvae, these neurons simultaneously receive glutamatergic inhibition from other local neurons. We will further investigate how this double inhibition affects the excitability of local AL neurons and why a single inhibitory mechanism seems not to be sufficient to suppress neuronal activity. Within the Research Unit, we will compare recurrent modulatory processing mechanisms across invertebrate and vertebrate animal models, which will allow us to detect conserved network principles.