Machine learning platform identifies activated neurons in re

Machine learning platform identifies activated neurons in real-time


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IMAGE: The video shows the results of the SUNS online technique without the "tracking " option enabled (left) and with the "tracking " option enabled (right). The green contours in the right panels...
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Credit: Yiyang Gong, Duke University
DURHAM, N.C. -- Biomedical engineers at Duke University have developed an automatic process that uses streamlined artificial intelligence (AI) to identify active neurons in videos faster and more accurately than current techniques.
The technology should allow researchers to watch an animal's brain activity in real time, as they are behaving.
The work appears May 20 in
Nature Machine Intelligence.
One of the ways researchers study the activity of neurons in living animals is through a process known as two-photon calcium imaging, which makes active neurons appear as flashes of light. Analyzing these videos, however, typically requires a human circling every burst of intensity they see in a process called segmentation. While this may seem straightforward, these bursts often overlap in spaces where thousands of neurons are imaged simultaneously. Analyzing just a five-minute video this way could take weeks or even months.

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