- Reduced blood flow in brain capillaries associated with dementia
- Capillary analysis crucial to further research
- Stall Catchers video game crowdsources data curation for faster results
Citizen science. The words conjure a new era of open science, free of the trappings of rigid, inhuman, academic autocracy. Science is for the rest of us, it whispers.
Citizen science asks the unvoiced questions, bringing the fire of knowledge creation to the benighted masses.
(That’s a great story, even if it’s not true.)
Its mythical stature notwithstanding, maybe citizen science is valuable for other reasons. Maybe it helps rigid, inhuman academics™ do their science, imparting the scientific method to the uninitiated.
That’s a version of citizen science at play in the online game Stall Catchers. The brainchild of researchers in the Schaffer-Nishimura Laboratory at Cornell University and Pietro Michelucci of the Human Computation Institute, Stall Catchers is a means of annotating capillary brain blood flows.
In Stall Catchers, players review an image stack of mouse blood vessels and judge whether a capillary is stalled or not. Stall Catchers contains hundreds of thousands of these 3D stacks, comprising many terabytes of data. With each stack, a player is asked to score one identified capillary of the 500 -1,000 capillary segments in that stack as flowing or stalled.
Feeling light headed
Decades of research has taught scientists to look for interrupted blood flow as an Alzheimer’s disease marker. On average, Alzheimer’s patients experience about 30 percent less brain blood flow.
You know that light-headed feeling you get when you stand up too quickly? That’s about 30 percent less blood flow, analogous to what a person with Alzheimer’s disease experiences.
This decreased blood flow is thought to contribute to the cognitive impairments associated with the disease, explains Chris Schaffer, associate professor in the Meinig School of Biomedical Engineering at Cornell.
The mechanism behind this decreased blood flow remained unclear until Schaffer’s lab looked at the brains of genetically modified mice.
“When we looked at individual capillaries, we found that a small percent of them had stalled blood flow,” says Schaffer. “Even though just a few percent are stalled, it can add up to a significant impact on blood flow in the brain.”
Schaffer’s lab later found that these stalls were caused by white blood cells stuck to vessel walls. When they administered antibodies to the afflicted mice, the stalls disappeared, returning blood flow nearly to the level of normal mice.
The treated mice with the improved brain blood flow subsequently performed better on cognitive tasks that tested working and spatial memory.
An exciting discovery for Alzheimer’s researchers, to be sure. But the challenge with this sort of research is in identifying which capillaries are flowing and which are stalled.
To spot the stalls, Schaffer’s team views a 3D moving image of the rodent’s cerebral vasculature. The optical technique highlights the blood either moving or stalled within a capillary.
We haven't found an automated way to identify which capillaries are flowing and which are stalled. But it’s very easy to train a human. Humans are just very, very good at pattern recognition. ~Chris Schaffer
Stall Catchers harnesses this innate human skill. In Stall Catchers, citizen scientists view one of the 3D capillary movies, scanning the recorded layers of capillaries, to see if they can identify which capillaries have flowing blood, and which capillaries are experiencing stalled flow.
Each vessel is scored multiple times by different players, and calibration images are inserted from time to time. These measures generate a dynamic understanding of the performance of individual players, and provide a consensus-style answer for each segment viewed.
“This approach is essential to our research right now,” admits Schaffer. “It turns out that the process of finding which capillaries are stalled and which are flowing is the dominant bottleneck in our research.”
A single researcher needs about 40 hours of work spotting the stalls to analyze data that took only a single hour to acquire. With Stall Catchers, that data analysis is done by citizen scientists, and the researcher in the lab can focus on the thing they uniquely can do — taking more data.
Having learned about stalled blood flows, follow-on studies are called for (e.g., identifying molecular causes of the stalling phenomenon, pre-clinical trials of potential therapies humans, determining whether other cardiovascular problems contribute to the stalling).
But each of these studies require thousands of hours of capillary analysis. Analysis in the lab would necessitate a conservative approach to which questions get asked, and each would be resolved much more slowly.
By farming out the time-consuming work of recognizing patterns of blood flow and blockages in mice brains, Stall Catchers speeds up Alzheimer’s research, quickening the pace of basic exploration and hastening a cure.
Apart from the analytical aid it provides, Schaffer says one of the main reasons to develop Stall Catchers is that it provides a way a to give the public a peek behind the scientific curtain.
“My hope is that over time this imparts a sense of how science as an enterprise works, and what it means to have a scientifically validated answer to a question. Why is it that we tend to be slow, and why is it that science needs to be that way?”