AMHERST — A team of scientists based at the University of Massachusetts has been awarded a four-year, $953,300 grant from the National Science Foundation to develop miniature, implantable hardware that can record complex brain activity in animals and analyze it in real-time. This new technical capability will allow the researchers to trace the origin of complex brain activity down to cellular levels, they say.
The NSF funding is part of $16 million given to 18 cross-disciplinary projects around the country to conduct innovative research on neural and cognitive systems.
The UMass team includes Guangyu Xu in electrical and computer engineering, David Moorman in psychological and brain sciences, and Geng-Lin Li in biology. They work collaboratively with Ethan Meyers in statistics, from Hampshire College.
“The toolbox we propose to establish in this project will offer high precision control over and recording from the neural activity in the brain of a rat or mouse, together with efficient algorithms that can analyze such activity in real time. Such capability will allow us to trace the origin of complex animal behaviors down to cellular levels,” Xu says.
There are multiple valuable features to this technology, they explain. First, it will be highly miniaturized — meaning that the researchers can perform powerful recording and manipulation of neurons with a minimally-invasive tool.
Second, it is highly generalizable. “We are interested in applying these tools to questions of cognition — how does the brain perform a decision (such as go left vs. go right to find a reward), or pay attention to a specific stimulus in a noisy environment with lights and sounds,” Moorman says. However, the tools the team is developing can be applied to other neuroscience questions in many different parts of the brain, meaning that they can be used to answer questions of how both normal and diseased brains function across a range of research domains.
Third, it is extremely powerful. “Our research plan provides a new way to understand brain functions at the level of cellular circuits,” they say. Ultimately, what you want to be able to do is determine which patterns of cellular activity you think are important for behavior and then “play back” these patterns of activity to verify that they actually are important.
“Not only will this provide us with an understanding of brain function that is more precise than what has previously been possible, it will allow us, and other researchers, to collect data with potential application to motor or cognitive diseases in humans,” Xu and Moorman say.