Citizen Science Games Speeding Up Alzheimer’s Research

Image credit: EyesOnALZ
Together with collaborators at Cornell, Berkeley, and Princeton, and with support from the BrightFocus Foundation, the Human Computation Institute (HCI) has created the first citizen science project to fight Alzheimer’s – EyesOnALZ. This project enables everyone to contribute to Alzheimer’s disease research and speed up drug discovery by playing Citizen Science Games – games that let players contribute to real scientific research.

Their first game, Stall Catchers, is celebrating 1 year birthday in October. The team is cooking up some graphics to illustrate its main milestones & the achievements of its community during the last 12 months. But for now, they would like to acknowledge the Catchers of the year at

Stall Catchers is a “Serious Game” designed to help researchers at Cornell University to search the brain for stalled blood vessels that may contribute to Alzheimer’s disease.
The Science

It has long been known that reduced blood flow in the brain is associated with Alzheimer’s disease and other forms of dementia. However, new imaging techniques have only recently enabled project collaborators at the Schaffer-Nishimura Lab (Cornell University) to make important discoveries about the mechanisms that underlie this reduced blood flow.

For instance, one such cause seems to be capillaries becoming clogged by white blood cells. By sticking to the inside walls of blood vessels, white blood cells cause “stalls” – instances where blood is no longer flowing. It seems that around 2% of the tiniest blood vessels in the brain can become stalled in Alzheimer’s, causing up to 30% reduction in overall blood flow. This is likely to contribute to further disease progression and typical Alzheimer’s symptoms.

In fact, the researchers at the Schaffer-Nishimura Lab have recently demonstrated that reversing stalls in mice also reduces Alzheimer’s symptoms, such as cognitive decline and mood changes. But to get to the bottom of this process & discover functional treatment target for humans there is a lot more work to be done.

The Citizen Science

While the research at the Schaffer-Nishimura Lab is promising, it is also incredibly time-consuming. In fact, the data that takes about one hour to collect, takes about a week for a trained scientist to analyze. At this rate, it could take decades to find functional Alzheimer’s treatment candidates.

Fortunately, the data curation step, though still too complicated for machines, involves perceptual tasks that are very easy for humans. Stall Catchers crowdsources the data analysis to the general public through a game-like activity, to drastically speed up the research.

While playing the game, you’ll be looking at real movies of live mouse brain. You will be given one vessel to annotate per movie, and will do so by searching for signs of blood flow or stalls. “Vessel movies” here are played back using a special tool – the Virtual Microscope (VM).

Screenshots from the Stall Catchers game
In Stall Catchers, the Virtual Microscope allows participants to look into successive layers of brain tissue, where different blood vessels come in and out of view, and search for “stalls” – clogged capillaries where blood is no longer flowing. By “catching stalls,” players build up their score, level up, and compete in the game leaderboard, as well as receive digital badges for their various achievements in the game.

Stall Catchers reduces the time needed for each of these studies from years to weeks by enabling everyone – regardless of their background or age – to contribute to the data analysis.

The Growing Field Of Citizen Science and PPSR
Source: Cornell University

The growing field of Public Participation in Scientific Research (PPSR) includes Citizen Science, volunteer monitoring, and other forms of organized research in which members of the public engage in the process of scientific investigations:  asking questions, collecting data, and/or interpreting results.

PPSR collaborations yield new knowledge by providing access to more and different observations and data than traditional science research. PPSR often focuses on a question or issue that requires data to be gathered or processed over long periods of time and/or wide geographic areas. Although projects vary in the degree of collaboration between science researchers and volunteers, in most projects volunteers receive some degree of training in project procedures to ensure consistency in data collection and accuracy in data analysis.

Over the past few years several models for PPSR have been developed to meet varied goals. All models share the same basic strategy, however, in which volunteers collect and share data that can be analyzed by scientists, project participants, or both.

PPSR projects have achieved notable outcomes for both science and education. In recent years over one hundred articles have been published, in peer-reviewed scientific literature that analyze and draw significant conclusions from volunteer-collected data. Many articles and book chapters describing learning outcomes for participants also have been published. Numerous publications document action outcomes as well, and offer strategies for linking research findings with management and decision making in different contexts.

Designing PPSR projects to achieve specific goals is not a simple process. Ensuring that projects will be meaningful to all participants, that project data will be collected accurately, that data will be analyzed with rigor, and that project results will be communicated to participants and to the greater scientific community all take careful planning and “intentional design.”

Author: Eliane Alhadeff

Written By juliooliveira

I’m from Sao Paulo / Brazil, married with a incredible woman called Francine and I have two lovely children: Sarah (8 years old) and Nicolas (2 years old). Currently enrolled at the master degree program (MSc) in Information Systems Management at the University of Liverpool (UK). Holder of the credentials PMP and PMI-ACP of the Project Management Institute (PMI).

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