Study shows that artificial neural networks can be used to drive brain activity.
Anne Trafton | MIT News Office
MIT neuroscientists have performed the most rigorous testing yet of computational models that mimic the brain’s visual cortex.
Using their current best model of the brain’s visual neural network, the researchers designed a new way to precisely control individual neurons and populations of neurons in the middle of that network. In an animal study, the team then showed that the information gained from the computational model enabled them to create images that strongly activated specific brain neurons of their choosing.
The findings suggest that the current versions of these models are similar enough to the brain that they could be used to control brain states in animals. The study also helps to establish the usefulness of these vision models, which have generated vigorous debate over whether they accurately mimic how the visual cortex works, says James DiCarlo, the head of MIT’s Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute for Brain Research and the Center for Brains, Minds, and Machines, and the senior author of the study.
“People have questioned whether these models provide understanding of the visual system,” he says. “Rather than debate that in an academic sense, we showed that these models are already powerful enough to enable an important new application. Whether you understand how the model works or not, it’s already useful in that sense.”
MIT postdocs Pouya Bashivan and Kohitij Kar are the lead authors of the paper, which appears in the May 2 online edition of Science...
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