Redundant Input Cancellation by a Bursting Neural Network

Redundant Input Cancellation by a Bursting Neural Network

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One of the most powerful and important applications that the brain accomplishes is solving the sensory "cocktail party problem:" to adaptively suppress extraneous signals in an environment. Theoretical studies suggest that the solution to the problem involves an adaptive filter, which lear...

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Bibliographic Details
Main Author: Bol, Kieran G.
Language:en
Published: 2011
Subjects:
neural computation
neural learning
plasticity
adaptive filter
noise cancellation
LIF
neural modeling
neural network
burst learning
neuroscience
neurophysics
weakly electric fish
neural circuits
sensory processing
feedback
spike-timing dependent plasticity
burst induced depression
leaky integrate-and-fire model
stochastic modeling
Online Access:http://hdl.handle.net/10393/20061

Internet

http://hdl.handle.net/10393/20061

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