Frontiers in Neurorobotics

Frontiers in Neurorobotics publishes rigorously peer-reviewed research in the science and technology of embodied autonomous neural systems. Specialty Chief Editors Alois C. Knoll and Florian R?hrbein at the Technische Universit?t München are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide.Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural nets, large-scale simulations of neural microcircuits) and actual biological systems (e.g. in vivo and in vitro neural nets). The focus of the journal is the embodiment of such neural systems in artificial software and hardware devices, machines, robots or any other form of physical actuation. This also includes prosthetic devices, brain machine interfaces, wearable systems, micro-machines, furniture, home appliances, as well as systems for managing micro and macro infrastructures. Frontiers in Neurorobotics also aims to publish radically new tools and methods to study plasticity and development of autonomous self-learning systems that are capable of acquiring knowledge in an open-ended manner. Models complemented with experimental studies revealing self-organizing principles of embodied neural systems are welcome. Our journal also publishes on the micro and macro engineering and mechatronics of robotic devices driven by neural systems, as well as studies on the impact that such systems will have on our daily life.

Frontiers in Neurorobotics期刊中文简介

《神经机器人学前沿》发表了关于体现自主神经系统科学和技术的同行评审研究。理工大学的专业首席编辑阿洛伊斯·C·诺尔和Florian R_hrbein得到了国际专家优秀编辑委员会的支持。这本多学科开放获取期刊处于向研究人员、学者和全世界公众传播和交流科学知识和有影响力的发现的前沿。神经系统包括受大脑启发的算法（例如，连接主义网络）、生物神经网络的计算模型（例如，人工阻挠神经网络、神经微电路的大规模模拟）和实际生物系统（例如，体内和体外神经网络）。期刊的重点是将这种神经系统应用于人工软硬件设备、机器、机器人或任何其他形式的物理驱动中。这还包括假肢设备、脑机接口、可穿戴系统、微型机械、家具、家用电器以及管理微观和宏观基础设施的系统。神经机器人领域的前沿也旨在发布全新的工具和方法，研究能够以开放式方式获取知识的自主学习系统的可塑性和发展。模型与实验研究相补充，揭示了具体神经系统的自组织原理是受欢迎的。我们的期刊还发表在由神经系统驱动的机器人装置的微观和宏观工程和机电一体化，以及这些系统对我们日常生活的影响的研究上。