The activity of each neuron in a 350 × 300 × 60 μm3 portion of a retina was determined by
two-photon microscopy. Using
serial block-face scanning electron microscopy, the same volume was
stained to bring out the contrast of the
plasma membranes, sliced into layers by a
microtome, and imaged using an
electron microscope. A number of in-progress neurons are selected by the researchers for tracing. After the player chooses which neuron to work on, the program chooses a cubic volume associated with that neuron for the player
. This volume is first segmented into a number of (invisible to the player)
supervoxels before an artificial intelligence performs a conservative best guess for tracing the neuron through the two-dimensional images. The artificial intelligence used is a
convolutional deep learning neural network, a type of artificial intelligence often used for feature detectors. Multiple players will independently finish the reconstruction of the cube, creating a community consensus that is then submitted. These submitted consensuses are then checked by more experienced players. ==Publications==