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NSAI: Neuroprosthesis to prevent epilepsy attacks

Product
Developers: NNSU - National Research Nizhny Novgorod State University named after N.I. Lobachevsky
Date of the premiere of the system: February 2025
Branches: Pharmaceuticals, Medicine, Healthcare

Content

History

2025: Product Announcement

On February 17, 2025, it became known that scientists at Nizhny Novgorod State University named after N.I. Lobachevsky created the world's first artificial memristor-based synapse capable of processing hippocampal cell signals and preventing epilepsy attacks.

According to the press service of Lobachevsky University, in vitro experiments confirmed the ability of the memristor to interact with neural signals as part of a living system and recognize epileptic signals.

In Russia,
developed neuroprosthesis to prevent seizures of epilepsy

Maria Koryazhkina, a researcher at the Laboratory of Stochastic Multi-Stable Systems at NNSU, noted that the device allows you to smoothly adjust the conductivity of the memristor to transmit a normal neural signal and suppress outbreaks of epilepsy.

Key benefits of memristors:

  • Ability to generate, process and store information.
  • High performance and accuracy.
  • Compact dimensions.
  • Low power consumption.
  • Versatility

A senior researcher at the Research Institute of Neurosciences of the University of Lobachevsky Albina Lebedeva emphasized that the development of an electronic component base based on new physical principles contributes to the development of a new generation of neuroprosthetic devices.

The development is based on memristors based on stabilized zirconium dioxide created in the laboratory of memristor nanoelectronics of NNGU. The project was implemented by scientists of the memristor nanoelectronics laboratory of the Scientific and Educational Center "Physics of Solid-State Nanostructures" and the Research Institute of Neurosciences of the National Research University of Economics with the support of the Russian National Research Institute.

Traditional microelectronic systems for modeling neural signals require the use of transistors and amplifiers, which leads to large device sizes and high power consumption. The new memristor-based technology allows for more efficient and miniaturized neuroprostheses.[1]

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