Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap

Area of Science:

• Neuroscience
• Analytical Chemistry
• Molecular Biology

Background:

• Understanding brain function and diagnosing neurological disorders like Parkinson's disease relies on analyzing neurotransmitters.
• Current methods such as pharmacological inhibition, electrophysiology, and mass spectrometry lack the spatiotemporal resolution for direct, nanoscale neurotransmitter detection.

Purpose of the Study:

• To develop a novel technique for direct observation of single neurotransmitter molecules.
• To achieve high temporal resolution (millisecond scale) and spatial resolution (nanometer scale) in neurotransmitter detection.

Main Methods:

• Utilized nanogap electrodes with a gap width of ≤1 nm to measure quantum tunneling current through single molecules.
• Integrated machine learning algorithms for accurate identification and analysis of neurotransmitter signals.

Main Results:

• Successfully identified dopamine, serotonin, and norepinephrine at the single-molecule level with high accuracy.
• Determined the relative concentrations of these three neurotransmitters in mouse striatum and cerebral cortex samples.
• Demonstrated the capability for neurotransmitter detection on a millisecond timescale.

Conclusions:

• The developed method enables direct, high-temporal-resolution observation of single neurotransmitter molecules.
• This technique offers a significant advancement over existing methods for brain neurotransmitter analysis.
• Future applications include detailed investigation of neurotransmitter distribution and dynamics in the brain.