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

BioComp：将果蝇的新颖性识别机制转化为计算设备

• 批准号: 0523216
• 负责人: Ralph Greenspan
• 金额: $ 50万
• 依托单位: Neurosciences Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0523216&HistoricalAwards=false
• 关键词: BioComp; Translating; Mechanisms; Novelty; Recognition

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.

果蝇表现出多才多艺和复杂的刺激辨别能力和类似“注意力”的行为。他们尤其习惯于识别新奇事物。这项提议勾勒出一项计划，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。这个多步骤的计划将从定义果蝇中为其识别、选择性注意和新奇反应服务的回路开始，分析这些回路元素在行为和生理上的构成、联系和相互作用，然后在基于大脑的设备中引入这种神经结构作为计算机模拟大脑的基础，该装置能够显示新奇识别。我们将使用我们以前开发的基因打靶技术来识别大脑中有助于识别、选择性注意和新奇反应的部分。我们将绘制神经系统中的位置图，通过操纵神经活动来调节效果。这将通过两种相反的方式实现：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系列基因工程苍蝇品系来针对大脑的不同受限部分。目标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。目标2：绘制20-30赫兹LFP反应在不同脑区的分布，以及这些脑区之间的一致性在果蝇新奇反应产生中的作用。基于大脑的设备为智能机器的开发奠定了基础，这种机器在结构上遵循神经生物学而不是计算原理。与动物的情况一样，大脑设备的行为完全是神经系统内部活动的结果，而不是对计算机软件的任何程序指令的反应。在原理上不可能进行计算的新颖情况下，或者在编程证明不可行的情况下，这种装置特别有用。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，使用神经科学研究所开发的现有基于大脑的设备作为我们的平台。目标3：将基于AIMS 1和2中定义的新奇检测功能网络的模拟神经架构引入基于大脑的设备。这项工作的长期目标是了解果蝇的神经系统作为神经生物启发计算设备的基础运行的原理。神经系统功能的基本原理有望开发出比当前系统更能适应行为的新一代设备。无论是生物制剂还是人工制剂中最复杂的行为，都是由神经系统引导行为的有机体表现出来的。果蝇提供了必要的复杂性，在这一努力中具有价值，同时足够简单(即，神经元数量足够小)，可以进行分析。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施。