Neuronal coding and spiking randomness

被引:59
|
作者
Kostal, Lubomir
Lansky, Petr
Rospars, Jean-Pierre
机构
[1] Acad Sci Czech Republ, Inst Physiol, Prague 14220 4, Czech Republic
[2] INRA, UMPC, UMR 1272, INRA AgroParisTech Physiol Insecte,Signalizat & C, F-78026 Versailles, France
关键词
entropy; randomness; spike train; variability; INFORMATION-THEORETIC ANALYSIS; STATISTICAL-ANALYSIS; CORTICAL-NEURONS; ENTROPY; DISTRIBUTIONS; TRAINS; VARIABILITY; SEQUENCES; INTERVALS; LEIBLER;
D O I
10.1111/j.1460-9568.2007.05880.x
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Fast information transfer in neuronal systems rests on series of action potentials, the spike trains, conducted along axons. Methods that compare spike trains are crucial for characterizing different neuronal coding schemes. In this paper we review recent results on the notion of spiking randomness, and discuss its properties with respect to the rate and temporal coding schemes. This method is compared with other widely used characteristics of spiking activity, namely the variability of interspike intervals, and it is shown that randomness and variability provide two distinct views. We demonstrate that estimation of spiking randomness from simulated and experimental data is capable of capturing characteristics that would otherwise be difficult to obtain with conventional methods.
引用
收藏
页码:2693 / 2701
页数:9
相关论文
共 50 条
  • [1] Variability and randomness in stationary neuronal activity
    Kostal, Lubomir
    Lansky, Petr
    BIOSYSTEMS, 2007, 89 (1-3) : 44 - 49
  • [2] Randomness and variability of the neuronal activity described by the Ornstein-Uhlenbeck model
    Kostal, Lubomir
    Lansky, Petr
    Zucca, Cristina
    NETWORK-COMPUTATION IN NEURAL SYSTEMS, 2007, 18 (01) : 63 - 75
  • [3] Variability and Randomness of the Instantaneous Firing Rate
    Tomar, Rimjhim
    Kostal, Lubomir
    FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2021, 15
  • [4] Linear Response of General Observables in Spiking Neuronal Network Models
    Cessac, Bruno
    Ampuero, Ignacio
    Cofre, Rodrigo
    ENTROPY, 2021, 23 (02) : 1 - 29
  • [5] Neuronal Jitter: Can We Measure the Spike Timing Dispersion Differently?
    Kostal, Lubomir
    Marsalek, Petr
    CHINESE JOURNAL OF PHYSIOLOGY, 2010, 53 (06): : 454 - 464
  • [6] Entropy factor for randomness quantification in neuronal data
    Rajdl, K.
    Lansky, P.
    Kostal, L.
    NEURAL NETWORKS, 2017, 95 : 57 - 65
  • [7] Inhibition and modulation of rhythmic neuronal spiking by noise
    Tuckwell, Henry C.
    Jost, Juergen
    Gutkin, Boris S.
    PHYSICAL REVIEW E, 2009, 80 (03):
  • [8] Asynchronous Rate Chaos in Spiking Neuronal Circuits
    Harish, Omri
    Hansel, David
    PLOS COMPUTATIONAL BIOLOGY, 2015, 11 (07)
  • [9] Estimating Neuronal Information: Logarithmic Binning of Neuronal Inter-Spike Intervals
    Dorval, Alan D.
    ENTROPY, 2011, 13 (02) : 485 - 501
  • [10] Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State
    Lagzi, Fereshteh
    Rotter, Stefan
    PLOS ONE, 2015, 10 (09):