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Artificial transneurons emulate neuronal activity in different areas of brain cortex

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posted on 2025-09-12, 10:24 authored by Rivu Midya, Ambarish S. Pawar, Debi P. Pattanaik, Eric Mooshagian, Pavel BorisovPavel Borisov, Thomas D. Albright, Lawrence H. Snyder, R. Stanley Williams, J. Joshua Yang, Alexander BalanovAlexander Balanov, Sergei Gepshtein, Sergey SavelievSergey Saveliev
Rapid development of memristive elements emulating biological neurons creates new opportunities for brain-like computation at low energy consumption. A first step toward mimicking complex neural computations is the analysis of single neurons and their characteristics. Here we measure and model spiking activity in artificial neurons built using diffusive memristors. We compare activity of these artificial neurons with the spiking activity of biological neurons measured in sensory, pre-motor, and motor cortical areas of the monkey (male) brain. We find that artificial neurons can operate in diverse self-sustained and noise-induced spiking regimes that correspond to the activity of different types of cortical neurons with distinct functions. We demonstrate that artificial neurons can function as trans-functional devices (transneurons) that reconfigure their behaviour to attain instantaneous computational needs, each capable of emulating several biological neurons.<p></p>

Funding

Neuromorphic memristive circuits to simulate inhibitory and excitatory dynamics of neuron networks: from physiological similarities to deep learning

Engineering and Physical Sciences Research Council

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National Eye Institute (NEI) Core Grant for Vision Research P30 EY019005

NIBIB + NIMH grant 1R01EB028154

NINDS R01 NS123435

X-Grants Program of the President’s Excellence Fund at Texas A&M University, and Air Force Office of Scientific Research grant under contract no. FA9550-19-1-0213

NEI grants 5R01EY012135, R01 EY018613, R01EY029117

History

School

  • Science

Published in

Nature Communications

Volume

16

Issue

1

Article number

7289

Publisher

Nature Portfolio

Rights holder

© The Author(s)

Publisher statement

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Acceptance date

2025-07-11

Publication date

2025-08-07

Copyright date

2025

ISSN

2041-1723

eISSN

2041-1723

Language

  • en

Depositor

Prof Sergey Saveliev. Deposit date: 11 September 2025

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