Well, soon enough at least. 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 filter through 663 GB of images of a zebra finch’s brain and construct a 3D model of every neuron and synapse.
“The real impact of this is the amount of neuroscience that can be done,” Viren Jain, a Google co-author on the pape who has been researching this automated neuronal structure problem for 12 years, told Quartz. “One thing that historically neuroscientists haven’t had access to is being able to study the actual patterns of neurons in the brain in a comprehensive way.”
The Max Planck Institute, the German research center, collaborated with Google on the project and provided the data, which it’s had since 2012.
It’s easiest to think of the data as thousands of 2D images showing a slice of the brain. When stacked on top of each other, they make a 3D image.
Google’s algorithm took this process and automated it. Though Google wasn’t the first to attempt this automated process, its algorithm is ten times more accurate than previous automated approaches.
Next, the researchers at Google and Max Planck will take this data from the bird, and try to determine how they learn to sing.