Creation of brain-machine interfaces is the next frontier, said Unnikrishnan. Recording from a large number of neurons and deciphering the underlying neuronal network might enable interfaces with prosthetic devices, such as the creation of an artificial retina. Giving senses to people who have lost them vision, touch, hearing, and motor - would be a contribution to humanity. An even more ambitious goal would be to discover the neural code leading to fundamental insights about information processing, memory, and higher-level functions.
Virginia Techs focus on nanofabrication through ICTAS provides the potential for an extended partnership to realize this application, Unnikrishnan said.
In addition to applications, asking basic science questions is also important motivation for the research, he said. How do we learn" That is the mechanics of learning. How do we store memories" asked Unnikrishnan. We will be able to study networks and patterns of neuronal activity so we can ask these questions. They are fundamental scientific questions, and this pursuit connects back bioinformatics and the analysis of essential data.
What brought GM to Virginia Tech is, first, the core group of data mining expertise; second, capabilities such as the System X supercomputer put Virginia Tech in a different league in terms of computational resources, said Unnikrishnan.
The third reason GM decided to partner with Virginia Tech is the universitys commitment to interdisciplinary research, such as through ICTAS and the centralized support of advanced research computing resources, including System X, for the entire university.
"In addition to research activities, new interdisciplinary courses at the meeting point of data mining and neuroscience can be proposed and offered," said Don Leo, associate dean of engineering for research and graduate studies at Virginia Tech.
|Contact: Christina Daniilidi|