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Published on: May 25, 2013
Noise shaping in populations of coupled model neurons
D J Mar1, C C Chow, W Gerstner
1Center for BioDynamics and Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA. djmar@bu.edu
Abstract:
Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.
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