Bayesian spiking neurons I: Inference

被引：188

作者：

Deneve, Sophie ^{[1
]}

机构：

[1] Ecole Normale Super, Coll France, Dept Detudes Cognit, Grp Neural Theory, F-75005 Paris, France

来源：

NEURAL COMPUTATION | 2008年 / 20卷 / 01期

关键词：

D O I：

10.1162/neco.2008.20.1.91

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We show that the dynamics of spiking neurons can be interpreted as a form of Bayesian inference in time. Neurons that optimally integrate evidence about events in the external world exhibit properties similar to leaky integrate-and-fire neurons with spike-dependent adaptation and maximally respond to fluctuations of their input. Spikes signal the occurrence of new information-what cannot be predicted from the past activity. As a result, firing statistics are close to Poisson, albeit providing a deterministic representation of probabilities.

引用

页码：91 / 117

页数：27

共 50 条

[21] Simulation of Bayesian Learning and Inference on Distributed Stochastic Spiking Neural Networks
Ahmed, Khadeer
Shrestha, Amar
Qiu, Qinru
[J]. 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 1044 - 1051
[22] BayesianSpikeFusion: accelerating spiking neural network inference via Bayesian fusion of early prediction
Habara, Takehiro
Sato, Takashi
Awano, Hiromitsu
[J]. FRONTIERS IN NEUROSCIENCE, 2024, 18
[23] Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons
Pecevski, Dejan
Buesing, Lars
Maass, Wolfgang
[J]. PLOS COMPUTATIONAL BIOLOGY, 2011, 7 (12)
[24] Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment
Legenstein, Robert
Maass, Wolfgang
[J]. PLOS COMPUTATIONAL BIOLOGY, 2014, 10 (10)
[25] Fast inference of couplings between integrate-and-fire neurons from their spiking activity
Simona Cocco
Stanislas Leibler
Rémi Monasson
[J]. BMC Neuroscience, 10 (Suppl 1)
[26] Nonlinear point-process estimation of neural spiking activity based on variational Bayesian inference
Xiao, Ping
Liu, Xinsheng
[J]. JOURNAL OF NEURAL ENGINEERING, 2022, 19 (04)
[27] A simulation of spiking neurons by sigmoid neurons
Kvasnicka, V
[J]. ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS, 2001, : 31 - 34
[28] Ferroelectric spiking neurons
Thomas, Stuart
[J]. NATURE ELECTRONICS, 2019, 2 (01) : 10 - 10
[29] Ferroelectric spiking neurons
Stuart Thomas
[J]. Nature Electronics, 2019, 2 : 10 - 10
[30] Clustering with spiking neurons
Opher, I
Horn, D
Quenet, B
[J]. NINTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS (ICANN99), VOLS 1 AND 2, 1999, (470): : 485 - 490

← 1 2 3 4 5 →