Abstract Title
Determining Electrical Signal Integrity of Passive Microelectrode Arrays
Abstract
Neural prosthetics, neuroscience, brain-machine interfaces, and medical research/diagnostics could be substantially innovated by the ability to measure in situ neuronal action potentials spatially, temporally, and over a large area. Current measuring techniques lack in one or more of those qualities. Mechanically flexible microelectrode arrays (MEAs) offer a solution to obtaining this type of data. Additionally, MEAs can electrically stimulate neurons without the insertion of a probe into the cell membrane. One factor affecting measurements of electromagnetic signal that poses problematic is noise. Noise is the unpredictable signal fluctuation that influences measurements on a microscopic scale. Neurons conduct electrical signals via ion channels in the cell membrane and the extracellular environment can be particularly noisy because of the thermal motion of charged salt ions. While noise cannot be entirely eliminated, emerging nanomaterials with unique properties can lessen the effects of noise in MEAs. Examples include large-area CVD graphene, inkjet-printed graphene or carbon nanotubes, etc. Therefore, our experiment is to test the signal integrity of different nanomaterials integrated into passive microelectrode arrays using custom electrophysiology equipment and methods.
Determining Electrical Signal Integrity of Passive Microelectrode Arrays
Neural prosthetics, neuroscience, brain-machine interfaces, and medical research/diagnostics could be substantially innovated by the ability to measure in situ neuronal action potentials spatially, temporally, and over a large area. Current measuring techniques lack in one or more of those qualities. Mechanically flexible microelectrode arrays (MEAs) offer a solution to obtaining this type of data. Additionally, MEAs can electrically stimulate neurons without the insertion of a probe into the cell membrane. One factor affecting measurements of electromagnetic signal that poses problematic is noise. Noise is the unpredictable signal fluctuation that influences measurements on a microscopic scale. Neurons conduct electrical signals via ion channels in the cell membrane and the extracellular environment can be particularly noisy because of the thermal motion of charged salt ions. While noise cannot be entirely eliminated, emerging nanomaterials with unique properties can lessen the effects of noise in MEAs. Examples include large-area CVD graphene, inkjet-printed graphene or carbon nanotubes, etc. Therefore, our experiment is to test the signal integrity of different nanomaterials integrated into passive microelectrode arrays using custom electrophysiology equipment and methods.