As academic studies go the findings were not all that surprising or noteworthy — something about the impact that lifestyle choices and sleep, aging, and alcohol consumption have on health and well being. What is notable, however, is how the findings in these two studies were arrived at.
Last week Lumosity, a Bay Area startup that creates and sells brain training and mind exercise games, released a paper in conjunction with Duke University as part of its Human Cognition Project. This is an initiative that offers researchers access to its data for purposes of scientific research. Lumosity, it must be said, has captured a whole lot of data, or as Mashable put it, a “continuously growing data mass of human cognitive performance.”
This heap of information is growing every day as Lumosity adds 100,000 new users each day with seventeen million Americans accessing the site each month. Since launching in 2007, Lumosity’s 36 million users have played more than 609 million cognitive games. In the process, they’ve shared a lot about themselves.
“New technologies and research platforms have the potential to transform the speed, scale, efficiency and range of topics in which neuroscience research is conducted,” said P. Murali Doraiswamy, Professor of Psychiatry at Duke University Medical Center and member of the Duke Institute for Brain Sciences, and co-author of the study, in a press release. “This study is interesting because it brings to light the possibilities of what we can uncover by taking a big data approach to cognitive performance research.”
Lumosity’s dataset was mined for patterns in the effects of sleep and alcohol on three cognitive abilities: speed, memory, and flexibility. After poring through the data the researchers found that cognitive performance was most efficient for users who slept seven hours a night. Meanwhile, those with a low to moderate alcohol intake (one or two drinks per day) performed better on all three tasks, while brain performance scores decreased with each additional drink.
Troves of information like this represent a shifting tide for neuroscience, which has never performed experiments at such massive scale before. Usually they take place in labs with maybe 100 participants. But the sheer size and scale of some datasets opens up intriguing possibilities. What’s implicit in this Big Data fascination is a new emphasis on different, broader ways of analysis.
In an article for Associate for Psychological Research’s Observer, Professor Rich Ivry looks at the new studies using Big Data as “shifts in the knowledge domains that inform their work, as well as forming affiliations to maximize resource utilization.” In other words, when Big Data is introduced it means a shift toward more interdisciplinary analysis. This is because the questions this data can answer are generally borrowed from other fields, as well as the tools for analyzing these numbers.
This paper by Lumosity is a good example. Its research question spans various subject matters and mines a new scope of data analysis previously foreign to cognitive neuroscience. Dr. Ivry asks, in a slightly polemical fashion, if, in the face of these new methods, psychology departments will exist 50 years down the road? Or, will they become part of some other, more generalized field of study?
While it’s doubtful Ivry actually believes this to be a bellwether of what’s to come, he is highlighting what these new methods mean. They are forcing reevaluations of method as well as new lines of reasoning within and across academic fields. He concludes that scientists, “should also be prepared to find that the kinds of theories that emerge from such enterprises [as Big Data] may not have the same form as those that have framed our field in its first 100 plus years.”
In other words, everything is about to change and cause a shift in what we thought we knew. And it’s all in the game. You just have to now where to look.