Enhanced magnetic transduction of neuronal activity by nanofabricated inductors quantified via finite element analysis

Abstract

Objective. Methods for the detection of neural signals involve a compromise between invasiveness, spatiotemporal resolution, and the number of neurons or brain regions recorded. Electrode-based probes provide excellent response but usually require transcranial wiring and capture activity from limited neuronal populations. Noninvasive methods such as electroencephalography (EEG) and magnetoencephalography (MEG) offer fast readouts of field potentials or biomagnetic signals, respectively, but have spatial constraints that prohibit recording from single neurons. A cell-sized device that enhances neurogenic magnetic fields can be used as an in situ sensor for magnetic-based modalities and increase the ability to detect diverse signals across multiple brain regions. Approach. We designed a device capable of forming a tight electromagnetic junction with single neurons, thereby transducing changes in cellular potential to magnetic field perturbations by driving current through a nanofabricated inductor element. Main results. We present detailed quantification of the device performance using realistic finite element simulations with signals and geometries acquired from patch-clamped neurons in vitro, and demonstrate the capability of the device to produce magnetic signals readable via existing modalities. We compare the magnetic output of the device to intrinsic neuronal magnetic fields and show that the transduced magnetic field intensity from a single neuron is more than three-fold higher at its peak (1.619 nT vs 0.506 nT). Importantly, we report on a large spatial enhancement of the transduced magnetic field output within a typical voxel (40x40x10 microns) over 250 times higher than the intrinsic neuronal magnetic field strength (0.64 nT vs 2.5 pT). We use this framework to perform optimizations of device performance based on nanofabrication constraints and material choices. Significance. Our quantifications institute a foundation for synthesizing and applying electromagnetic sensors for detecting brain activity and can serve as a general method for quantifying recording devices at the single cell level.

Wirelessin vivoRecording of Cortical Activity by an Ion-Sensitive Field Effect Transistor

“…Most wireless electrophysiology systems are reliant on an on-board battery for data transmission or include circuitry for power harvesting, employing either head-mounted replaceable power cells [7,6,12] or advanced transcutaneous inductive links for periodical charging and continuous operation [5,8]. More minimalistic circuits that interact with outside detectors such as ultrasound transducers [13,14] magnetic resonance imaging (MRI) hardware [15][16][17][18] and optoelectronic interfaces [19][20][21][22] present new possibilities for backscatter power harvesting, simplified device delivery and localization, and detection across multiple regions in the nervous system. Radio frequency (RF) sensors in particular, have traditionally benefitted from high signal penetration through the skull and other tissue types compared with optical and ultrasonic modalities [23,24], and new designs enable improved deep tissue sensing, micro-scale device localization, and controlled drug delivery [25][26][27][28].…”

Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles

“…[17][18][19] Examples include SPIONs conjugated with calmodulin and its target peptides 20,21 or C2 domains of synaptotagmin 22 as calcium-responsive MRI contrast agents; engineered monoaminergic binding peptide domains for sensing neurotransmitters 23 ; and more. [24][25][26][27] Moreover, other types of injectable nanoparticles, nanostructures, and molecular probes offer aggregation-based sensing and modulation of electric fields [28][29][30][31][32] and biochemical processes [33][34][35] with particular uses in neuroscience and neurology. 36 The spatial distribution and related aggregation attributes of magnetic particles are important to both static and dynamic contrast enhancement, as the final 3D scaling factor, arrangement, and distribution of tracers can affect image quality, contrast, SNR, and sensitivity to analytes.…”

Application of finite element analysis in structural analysis and computer simulation

“…Finite element analysis is a scientific method that uses mathematical methods to simulate real physical systems, based on mechanics theory, which is a combination of mechanics, mathematics, and computers, and with the development of computer technology, from its initial application in the aerospace field, it has been developed to the vast majority of scientific fields such as automotive industry, ship industry, unmanned aircraft, etc., and is widely used in electromagnetic fields, fluid fields, stress fields, etc. [5][6][7][8].…”