Characterizing the information transmission of inverse stochastic resonance and noise-induced activity amplification in neuronal systems

被引:1
作者
Martinez, Nataniel [1 ]
Deza, Roberto R. [1 ]
Montani, Fernando [2 ]
机构
[1] Univ Nacl Mar Del Plata, Fac Ciencias Exactas & Nat, IFIMAR CONICET, RA-B7602AYL Mar Del Plata, Argentina
[2] Univ Nacl La Plata, Fac Ciencias Exactas, IFLP CONICET, RA-B1900 La Plata, Argentina
关键词
WEAK-NOISE; SPIKING; NETWORKS; INHIBITION; DYNAMICS;
D O I
10.1103/PhysRevE.107.054402
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
Purkinje cells exhibit a reduction of the mean firing rate at intermediate-noise intensities, which is somewhat reminiscent of the response enhancement known as "stochastic resonance" (SR). Although the comparison with the stochastic resonance ends here, the current phenomenon has been given the name "inverse stochastic resonance" (ISR). Recent research has demonstrated that the ISR effect, like its close relative "nonstandard SR" [or, more correctly, noise-induced activity amplification (NIAA)], has been shown to stem from the weak-noise quenching of the initial distribution, in bistable regimes where the metastable state has a larger attraction basin than the global minimum. To understand the underlying mechanism of the ISR and NIAA phenomena, we study the probability distribution function of a one-dimensional system subjected to a bistable potential that has the property of symmetry, i.e., if we change the sign of one of its parameters, we can obtain both phenomena with the same properties in the depth of the wells and the width of their basins of attraction subjected to Gaussian white noise with variable intensity. Previous work has shown that one can theoretically determine the probability distribution function using the convex sum between the behavior at small and high noise intensities. To determine the probability distribution function more precisely, we resort to the "weighted ensemble Brownian dynamics simulation" model, which provides an accurate estimate of the probability distribution function for both low and high noise intensities and, most importantly, for the transition of both behaviors. In this way, on the one hand, we show that both phenomena emerge from a metastable system where, in the case of ISR, the global minimum of the system is in a state of lower activity, while in the case of NIAA, the global minimum is in a state of increased activity, the importance of which does not depend on the width of the basins of attraction. On the other hand, we see that quantifiers such as Fisher information, statistical complexity, and especially Shannon entropy fail to distinguish them, but they show the existence of the mentioned phenomena. Thus, noise management may well be a mechanism by which Purkinje cells find an efficient way to transmit information in the cerebral cortex.
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页数:12
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共 61 条
  • [1] Alberts B., 2002, Mol. Biol. Cell
  • [2] Two paradigmatic scenarios for inverse stochastic resonance
    Bacic, Iva
    Franovic, Igor
    [J]. CHAOS, 2020, 30 (03)
  • [3] Inverse stochastic resonance in a system of excitable active rotators with adaptive coupling
    Bacic, Iva
    Klinshov, Vladimir
    Nekorkin, Vladimir
    Perc, Matjaz
    Franovic, Igor
    [J]. EPL, 2018, 124 (04)
  • [4] Excitable dynamics in neural and cardiac systems
    Barrio, Roberto
    Coombes, Stephen
    Desroches, Mathieu
    Fenton, Flavio
    Luther, Stefan
    Pueyo, Esther
    [J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2020, 86 (86):
  • [5] Positive feedback in eukaryotic gene networks:: cell differentiation by graded to binary response conversion
    Becskei, A
    Séraphin, B
    Serrano, L
    [J]. EMBO JOURNAL, 2001, 20 (10) : 2528 - 2535
  • [6] An adaptive weighted ensemble procedure for efficient computation of free energies and first passage rates
    Bhatt, Divesh
    Bahar, Ivet
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2012, 137 (10)
  • [7] First-passage times in integrate-and-fire neurons with stochastic thresholds
    Braun, Wilhelm
    Matthews, Paul C.
    Thul, Ruediger
    [J]. PHYSICAL REVIEW E, 2015, 91 (05):
  • [8] Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons
    Brunel, N
    [J]. JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2000, 8 (03) : 183 - 208
  • [9] Inverse Stochastic Resonance in Cerebellar Purkinje Cells
    Buchin, Anatoly
    Rieubland, Sarah
    Hausser, Michael
    Gutkin, Boris S.
    Roth, Arnd
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2016, 12 (08)
  • [10] A Nonequilibrium-Potential Approach to Competition in Neural Populations
    Deza, Roberto R.
    Deza, Ignacio
    Martinez, Nataniel
    Mejias, Jorge F.
    Wio, Horacio S.
    [J]. FRONTIERS IN PHYSICS, 2019, 6 (JAN)