U. MICHIGAN (US) — Neurons are very good at what they do, picking out signals from a flood of information with more finesse than anyone ever realized, new research shows.
The findings, published in the journal PLoS Computational Biology, add to the basic knowledge of how neurons work and could lead to better ways to design brain implants used to treat neurological diseases such as Parkinson’s disease.
Researchers examined neuronal excitation using mathematical models and experiments using the squid giant axon—a long arm of a nerve cell that controls part of the water jet propulsion system in squid.
Neurons “can pick out a signal from hundreds of other, similar signals,” says Daniel Forger, associate professor of mathematics and a research assistant professor of computational medicine and bioinformatics at the University of Michigan.
Researchers discovered that neurons discriminate among signals based on the signals’ “shape” (how a signal changes over time) and, contrary to prior belief, their preference depends on context.
Often compared to transistors on a computer that search for and respond to one specific pattern, neurons are more complex—and are able to search for more than one signal at the same time. Their choice depends on what else is competing for their attention.
“We found that a neuron can prefer one signal—call it signal A—when compared with a certain group of signals, and a different signal—call it signal B—when compared with another group of signals,” Forger says. This is true even when signal A and signal B aren’t at all alike.
The findings could contribute in two specific ways to the design and use of brain implants in treating neurological disorders.
“First, our results determine the optimal signals to stimulate a neuron,” Forger says. “These signals are much more effective and require less battery power than what is currently used.” Such efficiency would translate into less frequent surgery to replace batteries in patients with brain implants.
“Second, we found that the optimal stimulus is context-dependent,” he says, “so the best signal will differ, depending on the part of the brain where the implant is placed.”
The research was funded by the Air Force Office of Scientific Research and the National Institutes of Health.
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