Your browser doesn't support javascript.
loading
In silico assessment of electrophysiological neuronal recordings mediated by magnetoelectric nanoparticles.
Bok, Ilhan; Haber, Ido; Qu, Xiaofei; Hai, Aviad.
Afiliação
  • Bok I; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA.
  • Haber I; Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA.
  • Qu X; Wisconsin Institute for Translational Neuroengineering (WITNe), Madison, WI, USA.
  • Hai A; Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA.
Sci Rep ; 12(1): 8386, 2022 05 19.
Article em En | MEDLINE | ID: mdl-35589877
Magnetoelectric materials hold untapped potential to revolutionize biomedical technologies. Sensing of biophysical processes in the brain is a particularly attractive application, with the prospect of using magnetoelectric nanoparticles (MENPs) as injectable agents for rapid brain-wide modulation and recording. Recent studies have demonstrated wireless brain stimulation in vivo using MENPs synthesized from cobalt ferrite (CFO) cores coated with piezoelectric barium titanate (BTO) shells. CFO-BTO core-shell MENPs have a relatively high magnetoelectric coefficient and have been proposed for direct magnetic particle imaging (MPI) of brain electrophysiology. However, the feasibility of acquiring such readouts has not been demonstrated or methodically quantified. Here we present the results of implementing a strain-based finite element magnetoelectric model of CFO-BTO core-shell MENPs and apply the model to quantify magnetization in response to neural electric fields. We use the model to determine optimal MENPs-mediated electrophysiological readouts both at the single neuron level and for MENPs diffusing in bulk neural tissue for in vivo scenarios. Our results lay the groundwork for MENP recording of electrophysiological signals and provide a broad analytical infrastructure to validate MENPs for biomedical applications.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nanopartículas Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nanopartículas Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos