New project at the junction of neuroscience and memristor electronics supported by the Russian Foundation for Basic Research
A research team from Lobachevsky University became a winner in the competition for the best interdisciplinary basic research projects on the topic “Fundamentals of nature-like technologies for energy generation and consumption”. The expected funding for the project is 18 million roubles for three years.
According to the project manager, head of the PTRI laboratory Alexey Mikhaylov, the project aims to address the fundamental scientific problems related to the development of energy-efficient brain-like electronic systems and the implementation of hardware models of biomorphic neural networks for modeling brain architecture, for creating adaptive robotic systems, and for applications in neuroprosthetics and neuroimplantation.
In modern interdisciplinary science, research in the field of nature-like technologies aimed at studying and applying the principles of energy-efficient functioning and information processing in the brain neural networks is one of the most rapidly expanding areas. The demand for such research stems from a wide range of relevant applications: information technology and big data processing, designing neuromorphic computing systems, creating autonomous adaptive control systems, basic research in medicine and biology, including such breakthrough areas as neuroprosthetics and neuroimplantation. Along with a large number of theoretical studies aimed at identifying the fundamental principles of brain functioning, there is a growing interest in new experimental approaches for creating artificial analogs of brain neural networks based on electronic neurons and synapses. Currently, there exist some electronic models of neurons of varying degrees of detail (both analog and digital), but the hardware simulation of synaptic connections with the reproduction of plasticity effects is only at the initial stage of research.
The new project will focus on theoretical and experimental research with the aim to determine the possibility of constructing electronic models of synaptic connections between artificial neurons on the basis of memristive devices capable of adaptively changing their resistance. The collective dynamics of a biomorphic neural network based on self-organizing memoristive connections will be also studied. To achieve biological plausibility, the architecture and dynamics of the developed neural networks with memristive connections will be for the first time directly compared with the results of an experimental study of the wave and vibrational activity of the brain hippocampal networks in vitro and/or in vivo. The proposed project provides for complex modeling and hardware implementation of biomorphic neural networks based on memristive devices possessing the properties of synaptic plasticity, including the plasticity stimulated by living neurons of the brain. The project is based on an interdisciplinary approach and will involve the participation of experts who have significant expertise in the fields of electronics, nanotechnology, nonlinear dynamics, mathematical and physical modeling, and neuroscience, which ensures that the objectives of the project will be achieved.