NEMO: Neural Electro-Mechano-Optic Sensors for Multiplexed Neural Interfaces
Andrew Cochran (1), Harshvardhan Gupta (1), Vishal Jain (1,2), Maysamreza Chamanzar (1,2), Gianluca Piazza (1) ((1) Department of Electrical, Computer Engineering, Carnegie Mellon University, Pittsburgh, USA. (2) Carnegie Mellon Neuroscience Institute, Pittsburgh, USA.)

TL;DR
The paper presents a new ultra-compact electro-optomechanical neural sensor that enables high-resolution, multiplexed neural recordings with minimal artifacts, suitable for use in freely moving subjects.
Contribution
Introduction of a miniaturized electro-optomechanical sensor using NEMS technology for improved neural signal detection and multiplexing capabilities.
Findings
Achieved a detection limit of 110 microvolts.
Demonstrated successful benchtop and ex-vivo neural recordings.
Eliminated the need for bulky headstage equipment.
Abstract
We introduce a novel electro-optomechanic neural sensor for realizing ultra-compact neural recording probes that can detect and relay electrophysiology signals from within neural tissue. This technology addresses outstanding challenges faced by existing neural recording technologies, including the resolution trade-off with signal-to-noise-ratio (SNR) due to the high impedances of small electrodes, and lingering stimulation artifacts. The sensor employs a highly miniaturized NEMS (nano-electromechanical systems) electrostatic transducer that modulates a silicon photonic microdisk resonator to convert electrical signals to an optical signal modulation. We have been able to achieve a limit of detection down to 110 microvolts, making the sensor sensitive enough to detect neural signals. This sensitive electro-optomechanic sensor directly detects electrophysiology signals and converts them…
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