Plasticity in NEUral Memristive Architectures

神经忆阻架构中的可塑性

基本信息

批准号：
EP/J00801X/2
负责人：
Themis Prodromakis
金额：
$ 27.81万
依托单位：
University of Southampton
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
起止时间：
2013 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FJ00801X%2F2
关键词：
Plasticity NEUral Memristive Architectures

项目摘要

During the past two decades, philosophers, psychologists, cognitive scientists, clinicians and neuroscientists strived to provide authoritative definitions of consciousness within a neurobiological framework. Engineers have more recently joined this quest by developing neuromorphic VLSI circuits for emulating biological functions. Yet, to date artificial systems have not been able to faithfully recreate natural attributes such as true processing locality (memory and computation) and complexity (10^10 synapses per cm2), preventing the achievement of a long-term goal: the creation of autonomous cognitive systems.This project aspires to develop experimental platforms capable of perceiving, learning and adapting to stimuli by leveraging on the latest developments of five leading European institutions in neuroscience, nanotechnology, modeling and circuit design. The non-linear dynamics as well as the plasticity of the newly discovered memristor are shown to support Spike-based- and Spike-Timing-Dependent-Plasticity (STDP), making this extremely compact device an excellent candidate for realizing large-scale self-adaptive circuits; a step towards "autonomous cognitive systems". The intrinsic properties of real neurons and synapses as well as their organization in forming neural circuits will be exploited for optimising CMOS-based neurons, memristive grids and the integration of the two into realtime biophysically realistic neuromorphic systems. Finally, the platforms would be tested with conventional as well as abstract methods to evaluate the technology and its autonomous capacity.

在过去的二十年中，哲学家，心理学家，认知科学家，临床医生和神经科学家致力于在神经生物学框架内提供意识的权威定义。工程师最近通过开发神经形态VLSI电路来模仿生物学功能，从而加入了这一追求。然而，迄今为止，人造系统无法忠实地重现自然属性（记忆和计算）和复杂性（10^10^10的突触），从而阻止实现长期目标的实现：创建自主性认知系统的创建，使这些项目渴望开发五个能够启发的实验平台，以刺激欧洲，以刺激并适应能力，以适应能够启用，并能够适应能够启用，并能够适应能够启用，并能够适应能够启用的实验平台，从而能够为自己进行调整，从而能够适应自主性系统。神经科学，纳米技术，建模和电路设计。事实证明，非线性动力学以及新发现的备忘录的可塑性支持基于尖峰的基于尖峰和尖峰依赖性塑性性（STDP），这使得这款极其紧凑的装置是实现大型自动自动电路的绝佳候选者；朝着“自主认知系统”迈出的一步。实际神经元和突触的内在特性及其在形成神经回路中的组织将被利用，以优化基于CMO的神经元，回忆网格以及将两者整合到实时具有生物物理现实的神经形态系统中。最后，将使用常规和抽象方法对这些平台进行测试，以评估技术及其自动驾驶能力。