Eyewire gameplay is used for neuroscience research by enabling the reconstruction of morphological neuron data, which helps researchers model information-processing circuits.[3][4] It is also used to generate a training dataset to further improve the artificial intelligence that assists the player through the gameplay.[5][6]
A later project spawned from Eyewire is the Flywire project, which used a similar but more selective citizen science system for its tracing and annotation. Flywire builds on Eyewire and used AIs trained on the dataset produced by Eyewire players.[5][7]Flywire would go on to complete and publish the first connectome of an adult fruit fly, a structure with about 140,000 neurons.[8]
A sequel project to Eyewire, Eyewire II, was announced on March 31, 2025. It is of a similar scale to Flywire, intending to trace over 100,000 new neurons. Eyewire II is open in its alpha stages to Eyewire players ranked Scythe or higher.[9]
Gameplay
The player is given a cube with a partially reconstructed neuron branch stretching through it. The player completes the reconstruction by coloring a 2D image with a 3D image generated simultaneously. Reconstructions are compared across players as each cube is submitted, with points yielded to the players based on the agreement of their reconstruction with the developed consensus. Players are ranked on a leaderboard based on their point contributions.
Goal
Eyewire is used to advance the use of artificial intelligence in neuronal reconstruction by providing a dataset from which to train and test new models. It is also hoped that the neuronal reconstruction data from Eyewire and other similar projects will result a 'virtuous cycle,' where the neuroscience discoveries achieved from analyzing real neural networks could result in improvements to artificial intelligence, and that this newer artificial intelligence could then speed up further connectomic work.[10][11]
The project is also used in research determining how mammals see directional motion.[12][13]
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.[15] The artificial intelligence used is a convolutionaldeep learning neural network,[16][17][18] 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.[13]
↑ Sebastian Seung (March 18, 2012). "Very small sections of neuron". Archived from the original on April 19, 2014. Retrieved March 27, 2012. A few more words of explanation for the curious...you color neurons on Eyewire by guiding an artificial intelligence (AI). The AI was trained to color the branches of neurons.
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