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Modelling of magnetoelectric nanoparticles for non-invasive brain stimulation: a computational study

Academic Article
Publication Date:
2022
abstract:
Objective. Recently developed magnetoelectric nanoparticles (MENPs) provide a potential tool to enable different biomedical applications. They could be used to overcome the intrinsic constraints posed by traditional neurostimulation techniques, namely the invasiveness of electrodes-based techniques, the limited spatial resolution, and the scarce efficiency of magnetic stimulation. Approach. By using computational electromagnetic techniques, we modelled the behaviour of recently designed biocompatible MENPs injected, in the shape of clusters, in specific cortical targets of a highly detailed anatomical head model. The distributions and the tissue penetration of the electric fields induced by MENPs clusters in each tissue will be compared to the distributions induced by traditional transcranial magnetic stimulation (TMS) coils for non-invasive brain stimulation positioned on the left prefrontal cortex (PFC) of a highly detailed anatomical head model. Main results. MENPs clusters can induce highly focused electric fields with amplitude close to the neural activation threshold in all the brain tissues of interest for the treatment of most neuropsychiatric disorders. Conversely, TMS coils can induce electric fields of several tens of V m(-1) over a broad volume of the PFC, but they are unlikely able to efficiently stimulate even small volumes of subcortical and deep tissues. Significance. Our numerical results suggest that the use of MENPs for brain stimulation may potentially led to a future pinpoint treatment of neuropshychiatric disorders, in which an impairment of electric activity of specific cortical and subcortical tissues and networks has been assumed to play a crucial role.
Iris type:
01.01 Articolo in rivista
Keywords:
magnetoelectric nanoparticles; brain stimulation; computational modelling
List of contributors:
Bonato, Marta; Ravazzani, PAOLO GIUSEPPE; Parazzini, Marta; Fiocchi, Serena; Marrella, Alessandra; Chiaramello, Emma
Authors of the University:
BONATO MARTA
CHIARAMELLO EMMA
FIOCCHI SERENA
MARRELLA ALESSANDRA
PARAZZINI MARTA
RAVAZZANI PAOLO GIUSEPPE
Handle:
https://iris.cnr.it/handle/20.500.14243/463368
Published in:
JOURNAL OF NEURAL ENGINEERING (PRINT)
Journal
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