“In our in vitro experiments, we have shown that the memristor responds to neurosignals as part of a living system. Tests on healthy and epileptic brain cells have proven that the device can recognise epileptic signals and potentially block them. We can gradually adjust the conductivity of the memristor to transmit normal neurosignals and suppress epileptic outbreaks,“ said Maria Koryazhkina, researcher at the UNN Laboratory for Stochastic Multistable Systems.
“The development of electronic components based on new physical principles contributes to the advancement of a new generation of neuroprosthetic and neuromodulatory devices. In this project, we demonstrated a novel approach to modelling epileptic activity in in vitro experiments and showed the basic principles of memristive neuroprostheses at the cell-network level,” said study co-author Albina Lebedeva, senior researcher at the Neuroscience Research Institute of Lobachevsky University.
Memristors can perform the functions of both neurons and synapses: they can generate, process and store information. New microelectronic elements will make it possible to improve known neuroprostheses, making them cheaper, faster and more energy-efficient. Memristor-based neuroprostheses will also be miniaturised, which is important for medical applications.
“Neurons exchange analog signals. In traditional microelectronics, they can be modelled with transistors, amplifiers, and other standard components. The resulting systems are bulky, slow and have high power consumption. Memristors, due to their versatility, will make neuroprosthesis circuits much more efficient, accurate and simple,” commented Maria Koryazhkina.
The study used stabilised zirconium dioxide-based memristors developed at the UNN Laboratory for Stochastic Multistable Systems.
Image by Lobachevsky University
The project was implemented by researchers of the Laboratory for Memristor Nanoelectronics of the Research and Education Centre “Physics of Solid-State Nanostructures” and the UNN Nanoscience Research Institute with the support of the Russian Science Foundation.
The results were published in the high-rated journal Chaos, Solitons & Fractals in 2025. Research is supported by Russian Science Foundation (Grant No 24-21-00440).
