Neural Circuits Underlying Adaptive Behavior and Addiction

描述（由申请人提供）：学习需要根据经验更新预测，这一过程被认为是由多巴胺能神经元携带的错误信号驱动的。许多滥用药物使这一过程短路是成瘾的一个重要因素。尽管如此，计算预期变化并对调节多巴胺信号起作用的神经回路在很大程度上仍然未知。在哺乳动物中，多巴胺在果蝇的适应行为中起着指导作用。我们以前已经确定了一个子集的多巴胺能神经元足以提供条件反射错误信号在嗅觉学习过程中，并已解剖映射的来源强化到一个单一的集群的12个细胞，PPL 1神经元。该项目将利用果蝇大脑的数字简单性和遗传易处理性，并使用PPL 1簇作为进入适应行为背后的保守机制的切入点。使用遗传学、神经解剖学和光遗传学方法的组合，沿着功能光学成像、电生理学和行为分析，我们将解决四个具体目标：1）我们将光遗传学工具靶向PPL 1神经元的有限子集，并确定哪些细胞是必要的，哪些细胞是足够的，以驱动学习。2)我们将使用光学和电生理记录来监测PPL 1神经元在学习之前，期间和之后的活动，使我们能够测试PPL 1输出代表预测误差信号的假设。可卡因，哌醋甲酯和安非他明对这个学习过程的影响将被确定，揭示这些药物滥用对确定的学习回路的影响。3)我们将追踪PPL 1投射到联想记忆的存储位点，分析记忆形成背后的生物物理变化，并识别将记忆内容传递到下游决策中心的电路组件。4)我们将识别和操纵PPL 1神经元的突触输入，以努力剖析调节多巴胺释放的生物算法。因此，该项目在一个非常容易处理的实验系统中使用强大的新技术，解决了关于支持适应行为和成瘾的神经原则的基本问题。

DESCRIPTION (provided by applicant): Learning requires the updating of predictions based on experience, a process thought to be driven by error signals carried by dopaminergic neurons. The short-circuiting of this process by many drugs of abuse is an important factor in addiction. Despite this, the neural circuits that calculate changes in expectation and act upon conditioning dopamine signals remain largely unknown. As in mammals, dopamine plays an instructive role in the adaptive behavior of the fly, Drosophila melanogaster. We have previously identified a subset of dopaminergic neurons sufficient to provide conditioning error signals during olfactory learning, and have anatomically mapped the source of reinforcement to a single cluster of 12 cells, the PPL1 neurons. This project will take advantage of the numerical simplicity and genetic tractability of the fly brain and use the PPL1 cluster as the point of entry into the conserved mechanisms underlying adaptive behavior. Using a combination of genetic, neuroanatomical and optogenetic approaches along with functional optical imaging, electrophysiology and behavioral analysis, we will address four Specific Aims: 1) We will target optogenetic tools to restricted subsets of PPL1 neurons and establish which cells are necessary, and which sufficient, to drive learning. 2) We will use optical and electrophysiological recordings to monitor the activity of PPL1 neurons before, during, and after learning, allowing us to test the hypothesis that PPL1 output represents a prediction error signal. The effect of cocaine, methylphenidate, and amphetamine on this learning process will be determined, revealing the effects of these drugs of abuse on an identified learning circuit. 3) We will trace PPL1 projections to the storage sites of associative memories, analyze the biophysical changes underlying memory formation, and identify the circuit components that relay the contents of memory to downstream decision-making centers. 4) We will identify and manipulate synaptic inputs to PPL1 neurons in an effort to dissect the biological algorithm that regulates dopamine release. The project thus addresses fundamental questions about the neural principles underpinning adaptive behavior and addiction, using powerful new technologies in an eminently tractable experimental system.