Toward neuronal current spectroscopy at Ultra-Low field NMR

Centro Studi e Ricerche "E. Fermi", Rome, Italy. Email: [email protected] Physikalish-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587 Berlin, Germany University of Leipzig, Leipzig, Germany Neurophysics Group, Dept. of Neurology, Campus Benjamin Franklin, Charite/University Medicine, Berlin, Germany Dip. di Fisica, Universita di Roma "La Sapienza", Piazzale Aldo Moro, 5, 00185, Rome, Ital

SQUIDs in biomagnetism : A roadmap towards improved healthcare

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 686865.Peer reviewedPublisher PD

Computational and Phantom-Based Feasibility Study of 3D dcNCI With Ultra-Low-Field MRI

The possibility to directly and non-invasively localize neuronal activities in the human brain, as for instance by performing neuronal current imaging (NCI) via magnetic resonance imaging (MRI), would be a breakthrough in neuroscience. In order to assess the feasibility of 3-dimensional (3D) NCI, comprehensive computational and physical phantom experiments using low-noise ultra-low-field (ULF) MRI technology were performed using two different source models within spherical phantoms. The source models, consisting of a single dipole and an extended dipole grid, were calibrated enabling the quantitative emulation of a long-lasting neuronal activity by the application of known current waveforms. The dcNCI experiments were also simulated by solving the Bloch equations using the calculated internal magnetic field distributions of the phantoms and idealized MRI fields. The simulations were then validated by physical phantom experiments using a moderate polarization field of 17 mT. A focal activity with an equivalent current dipole of about 150 nAm and a physiologically relevant depth of 35 mm could be resolved with an isotropic voxel size of 25 mm. The simulation tool enabled the optimization of the imaging parameters for sustained neuronal activities in order to predict maximum sensitivity.ISSN:2095-0462ISSN:2095-047