Literature DB >> 18002478

Effects of an exogenous noise on a realistic network model: encoding of an EM signal.

A Paffi1, M Gianni, F Maggio, M Liberti, F Apollonio, G D'Inzeo.   

Abstract

Endogenous noise has been shown to play a central role in the detection of an electromagnetic signal in the nervous system. In this work, following a biomedical perspective, an exogenous noise applied to a realistic feedforward network model has been considered. It will be shown that, if the exogenous noise is properly filtered and its level is adjusted, a clear optimization of network encoding of an electromagnetic signal, representative of an external stimulation, is obtained through the stochastic resonance paradigm.

Mesh:

Year:  2007        PMID: 18002478     DOI: 10.1109/IEMBS.2007.4352812

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  2 in total

1.  The CNP signal is able to silence a supra threshold neuronal model.

Authors:  Francesca Camera; Alessandra Paffi; Alex W Thomas; Francesca Apollonio; Guglielmo D'Inzeo; Frank S Prato; Micaela Liberti
Journal:  Front Comput Neurosci       Date:  2015-04-28       Impact factor: 2.380

2.  Restoring the encoding properties of a stochastic neuron model by an exogenous noise.

Authors:  Alessandra Paffi; Francesca Camera; Francesca Apollonio; Guglielmo d'Inzeo; Micaela Liberti
Journal:  Front Comput Neurosci       Date:  2015-05-06       Impact factor: 2.380

  2 in total

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