- Open Science Grid targets the mysteries of the mind
- Over 2 million CPU hours used in study of memory and decision making
- Insights into knowledge construction will aid understanding of cognitive decline
Here's a brain teaser for you: What weighs three pounds, contains 86 billion cells, and can move information at up to 268 miles per hour?
Give up? It's the human brain, but don't be fooled — there's more going on up there than you imagine.
This exceptional organ allows us to compose symphonies, recognize our loved ones, and remember where we left our keys. But scientists still struggle to understand exactly how it works.
Chris Cox, cognitive neuroscientist from the University of Wisconsin Madison (UW-Madison), uses high-throughput computing (HTC) to study which parts of the brain support memory and decision making. He wants to know how the brain represents objects.
“Having a more accurate understanding of what it means to ‘know’ something can help us understand how fake news and misinformation take hold in individuals and spread through social networks,” says Cox.
“At the core of these issues are fundamental questions about how our brains process and assimilate information.”
Profiles in computing
Previously, Cox and his team looked for correspondence between brain activation and associated anatomical landmarks. They then asked whether those landmarks responded the same way across different people.
Recently, they refined their research to look at how multiple parts of the brain work in concert. But adding diversity to a brain activation profile increased the complexity of the computer models.
We see knowledge more like Lego blocks than a library — no single block has meaning, but a collection can express meaning when properly composed. ~Chris Cox
Cox says that it takes about two full seconds for a functional MRI to collect a single sample, yielding thousands of individual data points in the process. Cox’s research is now beginning to explore the neural dynamics involved when calling to mind a concept, with millisecond resolution.
“The problem is that lots of cognitive activity is going on in those two seconds that is being missed,” says Cox. “When you gain resolution in the time domain you have a chance to notice qualitative shifts that may delimit different neural processes.”
Each model can take 30 minutes to an hour to compute. Cox then runs hundreds of thousands of them to narrow in on the appropriate parameter values. To deal with the massive amounts of data these models were creating, Cox turned to the Open Science Grid (OSG).
In one year, Cox used 2.2 million CPU hours of HTC (around 250 years), with 1.1 million hours coming from OSG resources outside of UW-Madison.
“The OSG at UW-Madison is like flipping a switch,” says Cox. “It cut my computing time in half and was totally painless. Once we had access to the OSG, we saw a paradigm shift in the way we think about research.”
“Our research gets into the transformations that take place in the brain,” says Cox. We ask questions like ‘how is information from our senses combined to support abstract knowledge that seems to transcend our senses.' For example, we can recognize a single object from different perspectives and scales as being the same thing, and when we read a word we can call to mind all kinds of meaning that have little if anything to do with the letters on the page.”
Research by cognitive neuroscientists like Cox can offer clues to cognitive decline, which in turn could inform how we think about learning, instruction, and training. How we understand the patterns of decline can lead to better, more precise therapies, and help scientists tackle challenges like dementia.
Their research may also shine light on how false information is accepted so readily.
“We know it is hard to get someone to change their mind, so the question is what is happening in the brain. The answers depend on a better understanding of what knowledge is and how we acquire it. Our research is pointed to these higher-level questions.”