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ORIGINAL RESEARCH article
Front. Neurosci.
Sec. Neural Technology
Volume 19 - 2025 | doi: 10.3389/fnins.2025.1583152
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This study investigates the potential of magnetoelectric nanoparticles (MENPs) as a novel tool for localized electric stimulation of the central nervous system at single-neuron level, addressing the need for precise and minimally invasive neural modulation. Using a computational framework based on finite element methods coupled with neuronal dynamics simulations on a realistic model of a hippocampal CA1 pyramidal neuron, the study evaluates how MENPs' stimulation parameters influence neural activation. Analyses included electric potential distributions, the activating function along the axon, amplification coefficients required for action potential generation, spike propagation, and membrane potential. The study initially focused on highly localized stimulation using a nanometric MENP close to the axon and then demonstrated the feasibility of a more realistic framework involving a micrometric cluster of MENPs. To emulate physiological signal convergence, the summation effects of multiple MENPs strategically positioned across the basal dendritic tree near the axon were explored. The findings revealed the critical role of MENPs' configuration, location, and modulating stimuli in shaping neuronal responses, highlighting the feasibility of MENPs as a cutting-edge approach for precise neural stimulation. This work provides a foundation for integrating MENPs into therapeutic strategies for neurodegenerative diseases.
Keywords: magnetoelectric nanoparticles, Neural Stimulation, Numerical methods, computational neuroscience, neuroengineering
Received: 03 Mar 2025; Accepted: 07 Apr 2025.
Copyright: © 2025 Vezzoni, Chiaramello, Galletta, Bonato, Parazzini and Fiocchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Emma Chiaramello, Institute of Electronics, Computer and Telecommunication Engineering, National Research Council (CNR), Roma, 00185, Lazio, Italy
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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