Green Brain: Computational Modelling of the Honeybee Brain
Green Brain: Computational Modelling of the Honeybee Brain
批准号:
EP/J019534/1
负责人:
James Marshall
金额:
$84.17万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --
中文摘要
构建能够执行复杂认知任务的智能机器以及或优于人类大脑是现代科学的长期挑战。1997年,IBM的深蓝国际象棋计算机击败了世界冠军卡斯帕罗夫,这是这一探索的亮点之一。尽管它在国际象棋中的表现上级,但这个系统却与大脑完全不同,也没有大脑那么强大和多才多艺。最近,蓝脑计划(Blue Brain initiative)也得到了IBM的部分资助,开始着手构建一个真实规模的人脑皮质柱模型,使我们更接近最终构建一个像生物大脑一样工作的人工大脑的目标。在“绿色大脑”项目中,我们打算建造这样一个人工大脑,但它是蜜蜂的小大脑。我们将与图卢兹的Martin Giurfa教授的世界领先的研究小组合作,他们是蜜蜂大脑解剖学,生理学以及蜜蜂认知和行为各个方面的专家。蜜蜂具有惊人的大认知能力,包括跨感官模式的学习关联的转移,例如从气味到颜色,以及学习抽象概念,例如“相同”和“不同”的类别。与此同时,他们的大脑比复杂的人类大脑小得多,结构化得多,而且(按比例)研究得更好。在绿色脑项目中,我们将建立蜜蜂两个最重要的感觉系统的详细计算机模型,即嗅觉(嗅觉系统)和视觉(视觉系统)。在此过程中,我们将整合现有的数据、模型和原则,并进一步确定它们如何产生所观察到的令人印象深刻的认知能力。然后,我们将联合收割机与Giurfa实验室的专家密切合作,将感觉系统与学习模型和感觉整合模型结合起来,最终建立一个完整的蜜蜂大脑模型。该模型将在最先进的基于大规模并行图形处理单元(GPU)的超级计算机上实现,这是由NVIDIA公司率先推出的一项新技术,该公司正在通过GPU硬件捐赠支持该项目。使用GPU计算将使我们能够真实的模拟我们的绿色大脑模型,这对于项目的最后阶段至关重要,届时我们将把绿色大脑作为自主飞行机器人的大脑。这是对目前大脑模型工作的一个重要的进一步进展,因为越来越清楚的是,大脑功能的一个重要方面是大脑不是孤立地起作用,而是与身体和环境不断相互作用。“具身”的概念及其对认知的影响是现代认知科学的重要见解,对现代神经科学也同样重要。“绿色大脑”项目的产出将在若干学术领域产生影响。在神经科学中,它将推进大规模大脑模型领域,以及我们对蜜蜂感觉系统中信息处理方式的理解。我们还将贡献新的工具,用于将现代GPU技术用于人工大脑,并将其用于仿生机器人。对于认知科学,我们将有助于理解在生物现实模型系统中的体现。在学术界之外,自主飞行机器人的发展可能会在环境勘探,搜索和救援以及人工授粉中应用。更好地理解认知的潜在机制可能最终转化为对人类认知和认知障碍的更深入了解。最后,更好地了解蜜蜂本身可能很重要,因为蜜蜂是大多数生态系统中的关键授粉者,因此是“关键物种”,对粮食安全至关重要。
英文摘要
Building intelligent machines that can perform complex cognitive tasks as well as or better than the human brain is a long-standing challenge of modern science. This quest has seen one of its highlights when IBM's Deep Blue chess computer beat the world champion Kasparov in 1997. Despite its superior performance in chess, this system was however in no way similar to or as powerful and versatile as a brain. More recently the Blue Brain initiative, also partially funded by IBM, set out to build a real-scale model of a cortical column of the human brain, moving us closer to the goal of eventually building an artificial brain that works like its biological counterpart. In the Green Brain project we propose to build such an artificial brain, but of the smaller brain of the honeybee. We will work with the world-leading research group of Prof. Martin Giurfa in Toulouse, who are experts in all aspects of bee brain anatomy, physiology and bee cognition and behavior. Bees have a surprisingly large cognitive capacity including transfer of learned associations across sensory modalities, e.g. from smells to colors, and learning abstract concepts such as the categories of "the same" and "different". At the same time their brains are much smaller, structured and (proportionally) much better researched than the complex human brain. It is also much easier to perform invasive manipulations to dissect how different parts of the bee brain function.In the Green Brain project we will build detailed computer models of the two most important sensory systems of the bee, the senses of smell (olfactory system) and of sight (visual system). In doing so, we will incorporate existing data, models and principles and identify further how they give rise to the observed impressive cognitive abilities. We will then combine the sensory systems with learning models and models of sensory integration in close collaboration with the experts in the Giurfa lab to eventually build a full-scale model of the bee brain. This model will be implemented on state-of-the-art massively parallel graphical processing unit (GPU) based super-computers, a new technology spearheaded by NVIDIA Corporation who is supporting this project with GPU hardware donations. Using GPU computing will allow us to simulate our Green Brain model in real time, which will be essential for the final phase of the project when we will put the Green Brain to work as the brain of an autonomous flying robot. This is an important further advance over current work on brain models because it is becoming more and more clear that an essential aspect of brain function is that the brain is not acting in isolation but in constant interaction with the body and the environment. This concept of "embodiment" and its consequences for cognition are important insights of modern cognitive science and will become equally important for modern neuroscience. The outputs from the Green Brain project will have impacts in several academic areas. In the neurosciences it will advance the field of large scale brain models and our understanding of how information is processed in the sensory systems of bees. We will also contribute new tools for the use of modern GPU technology for artificial brains and employing them in bio-mimetic robotics. For the cognitive sciences we will contribute to the understanding of embodiment in biologically realistic model systems.Beyond academia, the development of autonomous flying robots may have applications in environmental exploration, search and rescue and artificial pollination. Developing a better understanding of the mechanisms underlying cognition may ultimately translate into greater insights into human cognition and cognitive disorders. Finally, developing a better understanding of the honeybee may prove to be important in its own right as bees are a key pollinator in most ecologies and hence a 'keystone species' and vital for food security.
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DOI:
10.1371/journal.pcbi.1006435
发表时间:
2018-09
期刊:
PLoS computational biology
影响因子:
4.3
作者:
[Cope AJ, Vasilaki E, Minors D, Sabo C, Marshall JAR, Barron AB]
通讯作者:
Barron AB
Abstract concept learning in a simple neural network inspired by the insect brain
受昆虫大脑启发的简单神经网络中的抽象概念学习
DOI:
10.1101/268375
发表时间:
2018
期刊:
影响因子:
--
作者:
[Cope A]
通讯作者:
Cope A
DOI:
10.1371/journal.pcbi.1004887
发表时间:
2016-05
期刊:
PLoS computational biology
影响因子:
4.3
作者:
[Cope AJ, Sabo C, Gurney K, Vasilaki E, Marshall JA]
通讯作者:
Marshall JA
DOI:
10.1371/journal.pone.0172325
发表时间:
2017
期刊:
PloS one
影响因子:
3.7
作者:
[Cope AJ, Sabo C, Vasilaki E, Barron AB, Marshall JA]
通讯作者:
Marshall JA
DOI:
10.1186/1471-2202-16-s1-p159
发表时间:
2015-12-18
期刊:
BMC Neuroscience
影响因子:
2.4
作者:
[Cope A, Sabo C, Vasilaki E, Gurney K, Marshall JA]
通讯作者:
Marshall JA
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