Submitted:
29 May 2024
Posted:
30 May 2024
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Electromagnetic Simulation
2.1.1. MENPs Model
2.1.2. Nerve Model
2.1.3. Stimulation Settings
2.2. Modeling of the Neuronal Dynamics
2.3. Configurations and Data Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Bavishi, S.; Rosenthal, J.; Bockbrader, M. ; Chapter, in Rehabilitation After Traumatic Brain Injury, B. C. Eapen and D. X. Cifu, Eds., Elsevier, 2019, pp. 241–253. [CrossRef]
- Yu, B.M.; Santhanam, G.; Sahani, M.; Shenoy, K.V. , ‘Chapter 7 - Neural Decoding for Motor and Communication Prostheses’, in Statistical Signal Processing for Neuroscience and Neurotechnology, K. G. Oweiss, Ed., Oxford: Academic Press, 2010, pp. 219–263. [CrossRef]
- Russell, C.; Roche, A.D.; Chakrabarty, S. , ‘Peripheral nerve bionic interface: a review of electrodes’, Int. J. Intell. Robot. Appl., vol. 3, no. 1, pp. 11–18, Mar. 2019. [CrossRef]
- Lee, S.; Lee, C. , ‘Toward advanced neural interfaces for the peripheral nervous system (PNS) and their future applications’, Curr. Opin. Biomed. Eng., vol. 6, pp. 130–137, Jun. 2018. [CrossRef]
- Günter, C.; Delbeke, J.; Ortiz-Catalan, M. , ‘Safety of long-term electrical peripheral nerve stimulation: review of the state of the art’, J. NeuroEngineering Rehabil., vol. 16, no. 1, p. 13, Jan. 2019. [CrossRef]
- Kargol, A.; Malkinski, L.; Caruntu, G.; Kargol, A.; Malkinski, L.; Caruntu, G. , ‘Biomedical Applications of Multiferroic Nanoparticles’, in Advanced Magnetic Materials, IntechOpen, 2012. [CrossRef]
- Kozielski, K.L. , et al.,‘Nonresonant powering of injectable nanoelectrodes enables wireless deep brain stimulation in freely moving mice’, Sci. Adv., vol. 7, no. 3, p. eabc4189, Jan. 2021. [CrossRef]
- Apu, E.H. , et al.,‘Biomedical applications of multifunctional magnetoelectric nanoparticles’, Mater. Chem. Front., vol. 6, no. 11, pp. 1368–1390, 2022. [CrossRef]
- Khizroev, S.; Enabler, T. Technobiology’s Enabler: The Magnetoelectric Nanoparticle’, Cold Spring Harb. Perspect. Med.; vol.; no.; p. a034207, Aug. 2019. [CrossRef]
- Kopyl, S.; Surmenev, R.; Surmeneva, M.; Fetisov, Y.; Kholkin, A. , ‘Magnetoelectric effect: principles and applications in biology and medicine– a review’, Mater. Today Bio, vol. 12, p. 100149, Sep. 2021. [CrossRef]
- Kaushik, A. , et al.,‘Magnetically guided central nervous system delivery and toxicity evaluation of magneto-electric nanocarriers’, Sci. Rep., vol. 6, no. 1, Art. no. 1, 16. 20 May. [CrossRef]
- Rodzinski, A. , et al.,‘Targeted and controlled anticancer drug delivery and release with magnetoelectric nanoparticles’, Sci. Rep., vol. 6, no. 1, Art. no. 1, Feb. 2016. [CrossRef]
- Guduru, R. , et al.,‘Magnetoelectric “spin” on stimulating the brain’, Nanomed., vol. 10, no. 13, pp. 2051–2061, Jul. 2015. [CrossRef]
- Nguyen, T. , et al.,‘In Vivo Wireless Brain Stimulation via Non-invasive and Targeted Delivery of Magnetoelectric Nanoparticles’, Neurother. J. Am. Soc. Exp. Neurother., vol. 18, no. 3, pp. 2091–2106, Jul. 2021. [CrossRef]
- Pardo, M. , et al.,‘Size-dependent intranasal administration of magnetoelectric nanoparticles for targeted brain localization’, Nanomedicine Nanotechnol. Biol. Med., vol. 32, p. 102337, Feb. 2021. [CrossRef]
- Hadjikhani, A. , et al.,‘Biodistribution and clearance of magnetoelectric nanoparticles for nanomedical applications using energy dispersive spectroscopy’, Nanomed., vol. 12, no. 15, pp. 1801–1822, Aug. 2017. [CrossRef]
- Stefano, M.; Cordella, F.; Loppini, A.; Filippi, S.; Zollo, L. , ‘A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review’, IEEE Trans. Neural Syst. Rehabil. Eng., vol. 29, pp. 397–407, 2021. [CrossRef]
- Stefano, M.; Cordella, F.; Gioi, S.M.L.; Zollo, L. , ‘Electrical stimulation of the human median nerve: A comparison between anatomical and simplified simulation models’, in 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER), 21, pp. 769–772. 20 May. [CrossRef]
- Chiaramello, E. , et al.,‘Magnetoelectric Nanoparticles: Evaluating Stimulation Feasibility of the Possible Next Generation Approach for Deep Brain Stimulation’, IEEE Access, vol. 10, pp. 124884–124893, 2022. [CrossRef]
- Marrella, A. , et al.,‘Magnetoelectric nanoparticles shape modulates their electrical output’, Front. Bioeng. Biotechnol., vol. 11, Aug. 2023. [CrossRef]
- Fiocchi, S.; Chiaramello, E.; Marrella, A.; Bonato, M.; Parazzini, M.; Ravazzani, P. , ‘Modelling of magnetoelectric nanoparticles for non-invasive brain stimulation: a computational study’, J. Neural Eng., vol. 19, no. 5, Sep. 2022. [CrossRef]
- Romeni, S.; Valle, G.; Mazzoni, A.; Micera, S. , ‘Tutorial: a computational framework for the design and optimization of peripheral neural interfaces’, Nat. Protoc., vol. 15, no. 10, pp. 3129–3153, Oct. 2020. [CrossRef]
- Hasgall, P. , et al.,‘IT’IS Database for thermal and electromagnetic parameters of biological tissues’, vol. Version 4.1, Feb. 2022. [CrossRef]
- McIntyre, C.C.; Richardson, A.G.; Grill, W.M. , ‘Modeling the Excitability of Mammalian Nerve Fibers: Influence of Afterpotentials on the Recovery Cycle’, J. Neurophysiol., vol. 87, no. 2, pp. 995–1006, Feb. 2002. [CrossRef]
- Pardo, M.; Khizroev, S. , ‘Where do we stand now regarding treatment of psychiatric and neurodegenerative disorders? Considerations in using magnetoelectric nanoparticles as an innovative approach’, WIREs Nanomedicine Nanobiotechnology, vol. 14, no. 3, p. e1781, 2022. [CrossRef]
- Warman, E.; Grill, W.; Durand, D. , ‘Modeling the effects of electric fields on nerve fibers: Determination of excitation thresholds’, IEEE Trans. Biomed. Eng., vol. 39, pp. 1244–54, Jan. 1993. [CrossRef]
- Richardson, A.G.; McIntyre, C.C.; Grill, W.M. , ‘Modelling the effects of electric fields on nerve fibres: Influence of the myelin sheath’, Med. Biol. Eng. Comput., vol. 38, no. 4, pp. 438–446, Jul. 2000. [CrossRef]
- Grinberg, Y.; Schiefer, M.A.; Tyler, D.J.; Gustafson, K.J.; Thickness, F.P. ; Size, and Position Affect Model Predictions of Neural Excitation’, IEEE Trans. Neural Syst. Rehabil. Eng. Publ. IEEE Eng. Med. Biol. Soc., vol. 16, no. 6, pp. 572–581, Dec. 2008. [CrossRef]
- Adewole, D.O. , et al.,‘The Evolution of Neuroprosthetic Interfaces’, Crit. Rev. Biomed. Eng., vol. 44, no. 1–2, pp. 123–152, 2016. [CrossRef]
- Winkler, T.; Stålberg, E. , ‘Surface anodal stimulation of human peripheral nerves’, Exp. Brain Res., vol. 73, no. 3, pp. 481–488, Dec. 1988. [CrossRef]
- Paffi, A. , et al.,‘A numerical study to compare stimulations by intraoperative microelectrodes and chronic macroelectrodes in the DBS technique’, BioMed Res. Int., vol. 2013, p. 262739, 2013. [CrossRef]
- McIntyre, C.C.; Mori, S.; Sherman, D.L.; Thakor, N.V.; Vitek, J.L. , ‘Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus’, Clin. Neurophysiol. Off. J. Int. Fed. Clin. Neurophysiol., vol. 115, no. 3, pp. 589–595, Mar. 2004. [CrossRef]
- Fiocchi, S. , et al.,‘Modeling of core-shell magneto-electric nanoparticles for biomedical applications: Effect of composition, dimension, and magnetic field features on magnetoelectric response’, PLOS ONE, vol. 17, no. 9, p. e0274676, Sep. 2022. [CrossRef]
- Devan, R.S.; Chougule, B.K. , ‘Effect of composition on coupled electric, magnetic, and dielectric properties of two phase particulate magnetoelectric composite’, J. Appl. Phys., vol. 101, no. 1, p. 014109, Jan. 2007. [CrossRef]
- Zhang, E. , et al.,‘Magnetic-field-synchronized wireless modulation of neural activity by magnetoelectric nanoparticles’, Brain Stimulat., vol. 15, no. 6, pp. 1451–1462, Nov. 2022. [CrossRef]






| Dipole diameter | Parallel orientation | Perpendicular orientation |
|---|---|---|
| MENP – fiber distance | MENP – fiber distance | |
| 80 nm | 1R | 1R, 2R, 3R |
| 80 m | 1R, 2R, 3R | 1R, 2R, 3R |
| 250 m | 1R, 2R, 3R | 1R, 2R, 3R |
| 500 m | 1R, 2R, 3R | 1R, 2R, 3R |
| MENPs – fiber distance | Perpendicular orientation | Parallel orientation | |
|---|---|---|---|
| MENP 80 nm | 1R | 4.8 | 4.7 |
| 2R | 13.7 | ||
| 3R | 31.1 | ||
| Cluster 80 m | 1R | 5.8 | 7.9 |
| 2R | 16.7 | 67.9 | |
| 3R | 34.2 | 85.8 | |
| Cluster 250 m | 1R | 5.7 | 6.3 |
| 2R | 13.2 | 22 | |
| 3R | 21.9 | 45 | |
| Cluster 500 m | 1R | 2.9 | 3.9 |
| 2R | 7.4 | 23.5 | |
| 3R | 27.8 | 17.2 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).