Stationary bumps in networks of spiking neurons

被引:219
|
作者
Laing, CR [1 ]
Chow, CC [1 ]
机构
[1] Univ Pittsburgh, Dept Math, Pittsburgh, PA 15260 USA
关键词
D O I
10.1162/089976601750264974
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We examine the existence and stability of spatially localized "bumps" of neuronal activity in a network of spiking neurons. Bumps have been proposed in mechanisms of visual orientation tuning, the rat head direction system, and working memory. We show that a bump solution can exist in a spiking network provided the neurons fire asynchronously within the bump. We consider a parameter regime where the bump solution is bistable with an all-off state and can be initiated with a transient excitatory stimulus. We show that the activity profile matches that of a corresponding population rate model. The bump in a spiking network can lose stability through partial synchronization to either a traveling wave or the all-off state. This can occur if the synaptic timescale is too fast through a dynamical effect or if a transient excitatory pulse is applied to the network. A bump can thus be activated and deactivated with excitatory inputs that may have physiological relevance.
引用
收藏
页码:1473 / 1494
页数:22
相关论文
共 50 条
  • [41] Noise as a Resource for Computation and Learning in Networks of Spiking Neurons
    Maass, Wolfgang
    PROCEEDINGS OF THE IEEE, 2014, 102 (05) : 860 - 880
  • [42] Learning Temporally Encoded Patterns in Networks of Spiking Neurons
    Berthold Ruf
    Michael Schmitt
    Neural Processing Letters, 1997, 5 : 9 - 18
  • [43] A solution to the learning dilemma for recurrent networks of spiking neurons
    Guillaume Bellec
    Franz Scherr
    Anand Subramoney
    Elias Hajek
    Darjan Salaj
    Robert Legenstein
    Wolfgang Maass
    Nature Communications, 11
  • [44] Connectomic constraints on computation in feedforward networks of spiking neurons
    Venkatakrishnan Ramaswamy
    Arunava Banerjee
    Journal of Computational Neuroscience, 2014, 37 : 209 - 228
  • [45] Search for fMRI BOLD signals in networks of spiking neurons
    Amit, Daniel J.
    Romani, Sandro
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2007, 25 (06) : 1882 - 1892
  • [46] A Systematic Method for Configuring VLSI Networks of Spiking Neurons
    Neftci, Emre
    Chicca, Elisabetta
    Indiveri, Giacomo
    Douglas, Rodney
    NEURAL COMPUTATION, 2011, 23 (10) : 2457 - 2497
  • [47] A solution to the learning dilemma for recurrent networks of spiking neurons
    Bellec, Guillaume
    Scherr, Franz
    Subramoney, Anand
    Hajek, Elias
    Salaj, Darjan
    Legenstein, Robert
    Maass, Wolfgang
    NATURE COMMUNICATIONS, 2020, 11 (01)
  • [48] Emulation of Hopfield networks with spiking neurons in temporal coding
    Maass, W
    Natschlager, T
    COMPUTATIONAL NEUROSCIENCE: TRENDS IN RESEARCH, 1998, : 221 - 226
  • [49] Sequential Desynchronization in Networks of Spiking Neurons with Partial Reset
    Kirst, Christoph
    Geisel, Theo
    Timme, Marc
    PHYSICAL REVIEW LETTERS, 2009, 102 (06)
  • [50] Constructing Precisely Computing Networks with Biophysical Spiking Neurons
    Schwemmer, Michael A.
    Fairhall, Adrienne L.
    Deneve, Sophie
    Shea-Brown, Eric T.
    JOURNAL OF NEUROSCIENCE, 2015, 35 (28): : 10112 - 10134