How Games Can Create Citizen Neuroscientists
Over the last few years, a number of fascinating games have emerged whereby the players become active participants in scientific research.
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Over the last few years, I’ve covered a number of fascinating games whereby the players become active participants in scientific research.
For instance, Phylo was produced by McGill in a bid to increase the understanding of genetic research. Eyewire is a similar effort, this time produced by MIT, that aims to further understanding of neuroscience.
Charities have also gotten involved. Reverse the Odds is a game created by Cancer Research UK to help with the fight against the disease.
You also have Nanocrafter, which has been created by researchers at the University of Washington to help further understanding of synthetic biology.
The latest game of this ilk is Mozak, a new game that aims to recruit players to tackle neuroscience challenges. The game asks players to examine images of neurons in the hope that a complete 3D image of the neuron will eventually be created, with players eventually classifying those neurons and potentially even creating a model of the brain.
The game was covered in a recent paper published in Cell. I’ve mentioned a few times recently that healthcare is increasingly a big data challenge, and that is certainly the case with neuroscience. Machine learning is one way of tackling this, but so too is citizen science. The game helps to cross the gap between those creating the data, and those capable of analyzing it.
The game, which was developed by the Center for Game Science at the University of Washington, and which takes it’s name from the Slavic word for brain, aims to fill a gap in the ability of algorithms to characterize neurons fully, due in large part to the less than perfect images available.
Inside the Mozak
The game provides a platform to provide players with the opportunity to develop their skills in the understanding of neuronal diversity. The makers believe this first step of skills development is crucial before players can be valuable members of the community.
So the first levels of the game take 3D neuronal images and gradually trains the players so that they can be expert neuron reconstructors. The game is designed to be accessible by players of any age, nationality, or vocation.
The game has already proven successful in this regard, with teams of middle schoolers already successfully reconstructing neurons without any prior expertise. What’s more, the game is also useful for those at the other end of the spectrum, with scientists increasing their own reconstruction speeds by up to 10 times after playing the game.
This interaction between expert and layperson is a nice feature of the game, and the makers hope it allows the transfer of knowledge to the community, and vice versa. What’s more, the game will also enable a transfer of expertise to the algorithms that usually do this work. Once a consensus has been reached on an image, it will be fed to the labs to help guide the work conducted there, with the algorithms automatically incorporating aspects of the reconstruction process so that future analysis can take advantage of this crowd-based input.
To add to the game based aspect of the process, the team also hope to develop a World Cup of neuroscience, with international teams competing to analyze complex neuroscience data faster than professional scientists can produce it. The ultimate aim is to help develop a new generation of expert citizen neuroscientists and further our understanding of this most complex of organs.
Check out the video below for an overview of the game, or click the link above to participate yourself.
Published at DZone with permission of Adi Gaskell, DZone MVB. See the original article here.
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