Alzheimer's research has received a boost through an online game that invites the public to look under a virtual microscope. The Human Computation Institute has launched Stall Catchers as part of EyesOnALZ, a citizen science project.
Funded by the BrightFocus Foundation, the game's participants can watch videos of real blood vessels in the brain of a mouse. The challenge is to point out "stalls" or clogged capillaries where blood does not flow. Successful participants will be awarded points and earn digital badges depending on their scores.
Indirectly, the participants will be contributing to Alzheimer's research at the Schaffer-Nishimura Laboratory, which is led by Chris Schaffer and Nozomi Nishimura of Meinig School of Biomedical Engineering at Cornell. Their laboratory also supplied the black and white videos used in the game.
Their hypothesis is that blood flow deficit is responsible for many of the symptoms of Alzheimer's including memory loss.
"Today, we have a handful of lab experts putting their eyes on the research data," said Pietro Michelucci, director of HCI. "If we can enlist thousands of people to do that same analysis by playing an online game, then we have created a huge force multiplier in our fight against this dreadful disease." He added that the game can be played by people of all ages.
He wanted thousands of people to play the online game and be a huge force multiplier in fighting the dreadful disease.
For the citizen science game to fight Alzheimer's disease, the HCI collaborated with the Cornell University, Princeton University, University of California-Berkeley and SciStarter.com.
Mitigating Blood Reduction in Brain
Schaffer is jubilant that his team could find out the mechanism responsible for the significant blood flow reduction in Alzheimer's.
He also claimed that the success in reversing some of the cognitive symptoms of the disease was brought on by administering a drug that improves blood flow.
For the researchers, the challenge has been in finding stalled blood vessels, because automating the detection has not been successful and the manual process has to continue.
Under the new method, a researcher can acquire image data within two hours, which otherwise would have taken at least a week under the manual image analysis.
The developers of Stall Catchers have a reason to be optimistic because they are building up the project on the edifice of the highly successful citizen science project Stardust@home run by Professor Andrew Westfall of UC Berkeley.
For those who are interested in playing the game and fighting Alzheimer's disease, just visit and register at StallCatchers.com.