BioComp: Translating Mechanisms of Novelty Recognition in Drosophila into a Computational Device

果蝇表现出多样化和复杂的刺激识别能力和“注意力”样行为。他们特别善于识别新奇事物。这个提议概述了一个计划，描述果蝇执行这些信息处理功能的能力背后的网络和神经原理，然后将它们用作计算设备的基础。这个多步骤的程序将开始定义的电路在果蝇subserving其识别，选择性注意，和新奇的反应，分析thecontributions，连接，和相互作用的这些电路元素的行为和生理，and then introducing介绍this neural神经architecture架构as the basis基础for the computer-simulated计算机-simulated模拟brain脑in a brain脑-我们将使用我们以前开发的基因靶向技术来识别大脑中负责识别、选择性注意和新奇反应的部分。我们将通过操纵神经活动来绘制神经系统中调节这种效应的部位，这将通过两种相反的方式来实现：一种是通过阻断活动，另一种是通过增加活动。这些干扰将通过我们多年来开发和使用的一套基因工程果蝇品系针对大脑的不同限制部位。通过这种方式，我们将通过增加或减少有限脑区的兴奋性来绘制介导果蝇新奇反应的功能回路。目的1：分析果蝇神经系统在行为上实现新奇识别的复杂组织结构。目的2：绘制20-30 Hz LFP反应在不同脑区的分布图，以及这些大脑区域在果蝇产生新奇反应中的一致性作用。的设备为智能机器的发展提供了基础，这些智能机器在其构造中遵循神经生物学而不是计算原理。与动物的情况一样，基于大脑的设备的行为仅仅是神经系统内部产生的活动的结果，而不是对计算机软件的任何程序指令的反应。这种设备是特别有用的情况下的noveltywhere计算是不可能的原则上或在案件的巨大的本地复杂性wherprogramming证明是不可行的。这样的设备必须面对新的情况和复杂的参数集，必须迅速处理。我们的目标是将果蝇系统的原理应用到这样的设备中，使用TheNeurosciences Institute开发的现有基于脑的设备作为我们的平台。目标3：将基于目标1和2中定义的新颖性检测功能网络的模拟神经架构&引入基于脑的设备中。这项工作的长期目标是了解果蝇神经系统作为神经生物学启发的计算设备的基础的运作原理。神经系统功能的基本原理有望开发新一代的设备，这些设备比当前的系统更有能力进行自适应行为。在生物或人工媒介中看到的最复杂的行为是由神经系统指导行为的生物体所表现出来的。果蝇提供了必要的复杂性，在这奋进是有价值的，而足够简单（即，神经元数目足够小）以使能波束化以进行分析。最重要的是，它提供了由多学科实验方法（遗传学，解剖学，生理学和行为学）提供的复杂性，随后是计算机模拟和设备实现。

Fruit flies exhibit versatile and sophisticated capabilities of stimulus discrimination and"attention"-like behavior. They are particularly attuned to recognizing novelty. This proposaloutlines a plan to delineate the network and neural principles underlying the fruit fly's ability toperform these information-processing functions, and then to employ them as the basis for acomputational device. This multi-step program will be begun by defining the circuitry in the fruitfly subserving its recognition, selective attention, and novelty responses, analyzing thecontributions, connections, and interactions of these circuit elements both behaviorally andphysiogically, and then introducing this neural architecture as the basis for the computer-simulatedbrain in a brain-based device capable of displaying novelty recognition.We will use techniques of gene targeting that we have developed previously to identifythe parts of the brain contributing to recognition, selective attention, and novelty responses. Wewill map the sites in the nervous system mediating the effect by manipulating neural activity.This will be achieved in two opposing ways: one way by blocking activity and the other byincreasing activity. These perturbations will be targeted to different, restricted parts of the brainby means of a set of genetically engineered fly strains we have developed and used over theyears. In this manner, we will map the funcitonal circuitry mediating a fruit fly's noveltyresponse by increasing or decreasing excitability in restricted brain regions.Aim 1: Analyze the complex, organizational architecture by which the fruit fly's nervous systemachieves behaviorally the recognition of novelty.Aim 2: Map the distribution of the 20-30 Hz LFP response in various brain regions, and the roleof coherence between these brain regions in the generation of the fruit fly's novelty response.Brain-based devices provide the groundwork for the development of intelligent machinesthat follow neurobiological rather than computational principles in their construction. As is thecase with animals, the behaviors of brain-based devices emerge solely as a result of internallygenerated activity of their nervous systems rather than of responses to any programmedinstructions from computer software. Such devices are particularly useful in situations of noveltywhere computation is not possible in principle or in cases of great local complexity whereprogramming proves infeasible. Such a device must confront novel situations and complex sets ofparameters that must be dealt with rapidly. Our goal is to implement principles from the fruit flysystem into such a device, using as our platform an existing brain-based device developed at TheNeurosciences Institute.Aim 3: Introduce a simulated neural architecture based on the functional network for noveltydetection defined in Aims 1 & 2 into a brain-based device.The long-term goal of this work is to understand the principles upon which the nervoussystem of the fruit fly operates as the basis for neurobiologically inspired computational devices.The principles underlying nervous system function hold promise for developing a new generationof devices that would be more capable of adaptive behavior than current systems. The mostsophisticated behavior seen in either biological or artificial agents is shown by organisms whosebehavior is guided by a nervous system. The fruit fly offers the requisite complexity to be ofvalue in this endeavor, while being simple enough (i.e., small enough in neuron number) to beamenable to analysis. Most importantly, it offers sophistication afforded by a multi-disciplinaryexperimental approach (genetics, anatomy, physiology and behavior) to be followed by computersimulation and device implementation.