Inhibition enhances the coherence in the Jacobi neuronal model

0517542 - FGÚ 2020 RIV GB eng J - Journal Article
D´Onofrio, G. - Lánský, Petr - Tamborrino, M.
Inhibition enhances the coherence in the Jacobi neuronal model.
Chaos Solitons & Fractals. Roč. 128, Nov (2019), s. 108-113. ISSN 0960-0779. E-ISSN 1873-2887
R&D Projects: GA ČR(CZ) GA17-06943S; GA MŠMT(CZ) 7AMB17AT048
Institutional support: RVO:67985823
Keywords : coherence resonance * signal-to-noise ratio * leaky integrate-and-fire neuron model * multiplicative noise
OECD category: Statistics and probability
Impact factor: 3.764, year: 2019
Method of publishing: Limited access
https://doi.org/10.1016/j.chaos.2019.07.040

The output signal is examined for the Jacobi neuronal model which is characterized by input-dependent multiplicative noise. The dependence of the noise on the rate of inhibition turns out to be of primary importance to observe maxima both in the output firing rate and in the diffusion coefficient of the spike count and, simultaneously, a minimum in the coefficient of variation (Fano factor). Moreover, we observe that an increment of the rate of inhibition can increase the degree of coherence computed from the power spectrum. This means that inhibition can enhance the coherence and thus the information transmission between the input and the output in this neuronal model. Finally, we stress that the firing rate, the coefficient of variation and the diffusion coefficient of the spike count cannot be used as the only indicator of coherence resonance without considering the power spectrum.
Permanent Link: http://hdl.handle.net/11104/0302881