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Washington: How on
earth do busy nerve cells pick and respond to relevant signals
amid the relentless bombardment of information?
Somehow neurons (nerve cells) do manage to accomplish the daunting
task, and they do it with more finesse than anyone ever realized,
as new research by University of Michigan shows.
The findings of mathematician Daniel Forger and co-authors add to
basic knowledge about how neurons work.
It also suggests ways of better designing the brain implants, used
to treat diseases such as Parkinson's, the journal Public Library
of Science Computational Biology reports.
Forger and co-authors David Paydarfar at the University of
Massachusetts Medical School and John Clay at the National
Institute of Neurological Disorders and Stroke studied neuronal
responses, according to a Michigan statement.
Among the key findings are that neurons are adept at their job.
"They can pick out a signal from hundreds of other similar
signals," said Forger, research assistant professor of
computational medicine and bioinformatics.
Neurons discriminate among signals based on the signals' "shape,"
(how a signal changes over time), and the authors found that,
contrary to prior belief, a neuron's preference depends on
context.
"We found that neurons 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 said.
This is true even when signal A and signal B are not at all alike.
"We found that the optimal stimulus is context-dependent. So the
best signal will differ, depending on the part of the brain where
the implant is placed," he said.
"Our results determine the optimal signals to stimulate a neuron,"
Forger said.
"These signals are much more effective and require less battery
power than what is currently used," he added.
Such efficiency would translate into less frequent surgery to
replace batteries in patients with brain implants, according to
Forger.
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