Collaboration with Prof. Jeff Lichtman's laboratory at Harvard University, leveraged innovative automated tissue preparation and new machine learning reconstruction algorithms. This cutting-edge technology enabled the cutting and sorting of ultra-thin sections, each a mere 30 millionths of a millimeter thick, constructing a three-dimensional representation of the structural elements comprising the network.
"We meticulously charted the connectivity of the vertical lobe using the precision of an electron microscope, achieving a resolution on the order of about 4 millionths of a millimeter. Together with Prof. Jeff Lichtman's team at Harvard University, we engineered a robotic system alongside a sophisticated computational algorithm, uniquely capable of organizing hundreds of ultra-thin sections into a comprehensive 3D structure.
This challenged established notions of neural network functionality in the context of learning and memory. Unlike typical models, the vertical lobe's network operates in a feed-forward configuration, like a one-way street, with information only from the input neurons to output neurons that control octopus behavior.
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