HONG KONG, April 9 (Xinhua) -- A research team from the University of Hong Kong (HKU) announced on Tuesday that it has successfully developed an ultra-high-speed microscope capable of capturing brainwave signals, offering new clues for the study of brain diseases such as neurodegeneration.
Developed in collaboration with a team from the University of California, Berkeley, the "two-photon fluorescence microscope" can capture electrical signals and chemical substance transmission between neurons. In experiments, the team successfully recorded millisecond-scale electrical pulse signals generated by neurons in the brain of a living mouse.
The microscope employs an ultra-fast laser scanning technology developed by the HKU team, using a pair of parallel mirrors to generate a train of laser pulses at a speed at least 1,000 times faster than current laser scanning techniques. In experiments, the researchers used the high-speed microscope to project scanning laser beams onto a mouse's brain, capturing two-dimensional scan images of the mouse cerebral cortex at a rate of 1,000 to 3,000 times per second.
Sherman Cheung, Associate Professor in the Department of Electrical and Electronic Engineering and Director of the Biomedical Engineering Programme, who led the research team, explained that various existing technologies can capture brainwave signals, including implanting electrodes directly into the brain to measure voltage, but such methods are highly invasive, while magnetic resonance imaging (MRI) and conventional optical microscopes are relatively slow. The advantage of HKU's new technology lies in its low invasiveness and its ability to precisely locate individual neurons and track their firing pathways on a millisecond timescale.
Cheung noted that the new technology can detect millisecond-scale changes in the activity of single neurons in a living brain. The team aims to further improve the technology over the next one to two years to explore deeper brain structures and gain a more comprehensive understanding of brain functions.
The research findings have been published in the academic journal Nature Methods.
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