During learning, neurons deep in brain engage in a surprising level of activity -- ScienceDaily
"People used to think that the cerebellum's input layer of neurons was only sparsely active, and encoded only information collected from the external world," said Sam Wang, professor of molecular biology and the Princeton Neuroscience Institute, and a senior co-author on the study. "It turns out that they light up like a Christmas tree, and they convey information both from outside the body and from other areas within the brain."
The study is the first to look at the activity of these neurons, known as granule cells, in the brains of living animals while they are learning a task, said Javier Medina, associate professor and the Vivian L. Smith Endowed Chair in Neuroscience at Baylor College of Medicine, and a senior co-author with Wang. "We knew very little about how these neurons in the cerebellum were firing when the brain is engaged in behavior," he said.
The cells are packed into a dense knot deep in the brain, making them difficult to study. Through advances in brain imaging techniques and computer algorithms that detangle the signals, the team was able to explore in detail the firing patterns of these neurons while mice were learning a behavior.
The researchers expected to see only a few granule cells fire at any given time, consistent with ideas that date back to the 1960s. The commonly held theory stated that the sparse firing patterns created a sort of neural code whereby each firing pattern represented a different sensory input or stimulus. The theory helped explain why there are so many granule cells: Distinct firing patterns involving just a few of the millions of granule cells would enable the brain to assign a different firing pattern to each stimulus -- for example, a different firing pattern for the touch of the fingers versus the touch of a feather duster.