Activation of Microwave Fields in a Spin-Torque Nano-Oscillator by Neuronal Action Potentials

TL;DR

This paper demonstrates that neuronal action potentials can trigger microwave oscillations in spin-torque nano-oscillators, enabling wireless detection of neural activity with high sensitivity and temporal resolution, suitable for advanced brain-machine interfaces.

Contribution

It introduces a novel method to transduce neuronal signals into microwave fields using spin-torque nano-oscillators, advancing wireless neural sensing technology.

Findings

Action potentials activate microwave oscillations in nano-oscillators.

The amplitude of microwave signals follows neuronal action potentials.

Nano-oscillators are sensitive and fast enough to detect single-neuron activity.

Abstract

Action potentials are the basic unit of information in the nervous system and their reliable detection and decoding holds the key to understanding how the brain generates complex thought and behavior. Transducing these signals into microwave field oscillations can enable wireless sensors that report on brain activity through magnetic induction. In the present work we demonstrate that action potentials from crayfish lateral giant neuron can trigger microwave oscillations in spin-torque nano-oscillators. These nanoscale devices take as input small currents and convert them to microwave current oscillations that can wirelessly broadcast neuronal activity, opening up the possibility for compact neuro-sensors. We show that action potentials activate microwave oscillations in spin-torque nano-oscillators with an amplitude that follows the action potential signal, demonstrating that the device has both the sensitivity and temporal resolution to respond to action potentials from a single neuron. The activation of magnetic oscillations by action potentials, together with the small footprint and the high frequency tunability, makes these devices promising candidates for high resolution sensing of bioelectric signals from neural tissues. These device attributes may be useful for design of high-throughput bi-directional brain-machine interfaces.