Neuroscientists have a lot of data on the brain—we can see it, take pictures of it, study it. But for all the data, the brain’s workings are still relatively unknown.
A new paper published in Nature Methods might help neuroscientists better understand the structure of the brain and how it functions, according to research scientists from Google. A Google team trained an artificial neural network, the kind of AI perfect for automating simple human tasks, to sift through 663 GB of images of a zebra finch’s brain and construct a 3D model of every neuron and synapse.
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Manually, a neuroscientist would have to look at an image, identify the slices of neurons, and specify each one for the computer to turn into a 3D model. Google estimates it would have taken 100,000 hours to label the entire sample, which was only a 1mm cube. The AI trained for seven days to be able to accomplish the same task.
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Google’s algorithm took this process and automated it, looking slice by slice and tracing the neurons through the sample. Though Google wasn’t the first to attempt this automated process, its algorithm is ten times more accurate than previous automated approaches. Jain said that the breakthrough was teaching the AI to trace one neuron structure at a time, rather than trying to trace every neuron in the same at once.
Read full, original post: Google is using AI to see inside the brain like never before
