Cited by 314Neural dynamics and brain functionstochastic dynamics and bifurcationAdvanced Memory and Neural Computing

Bayesian Spiking Neurons I: Inference

Deneve, Sophie·2008·Neural Computation

Abstract

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.

Integrity signals

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Crossref · 10.1162/neco.2008.20.1.91

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  • Using Bayesian logic, a brain uses pattern completion to decide among simulations and implement one based on predicted maintenance of physiological efficiency across multiple body systems.

    “Using Bayesian logic (Deneve, 2008; Bastos et al., 2012), a brain uses pattern completion to decide among simulations and implement one of them (Gallivan et al., 2016), based on predicted maintenance of physiological efficiency across multiple body systems”

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Authors
Deneve, S.
Affiliations
Group for Neural Theory, Département d'Etudes Cognitives, Ecole Normale Supérieure, Collège de France, 75005 Paris, France
Venue
Neural Computation
Publisher
MIT Press
Published
2008-01
Volume
20
Issue
1
Pages
91-117
ISSN
  • 0899-7667 (ISSN-L)
  • 1530-888X
OpenAlex
W2139295975
Cited by
313
References
50
Citations by year
2026: 3 · 2025: 14 · 2024: 12 · 2023: 16 · 2022: 9 · 2021: 15 · 2020: 10 · 2019: 13 · 2018: 14 · 2017: 14 · 2016: 29 · 2015: 26 · 2014: 24 · 2013: 22 · 2012: 29
FWCI
7.66
Type
journal article
Language
en
Open access
closed
Locations
  • Neural Computation (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Gatsby Charitable Foundation
  • Ministry of Education, Culture, Sports, Science and Technology
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
Keywords
spiking neurons, Bayesian inference, leaky integrate-and-fire neurons, evidence integration, neural coding
MeSH terms
Action Potentials, Adaptation, Physiological, Algorithms, Animals, Bayes Theorem, Central Nervous System, Computer Simulation, Humans, Markov Chains, Movement, Nerve Net, Synaptic Transmission, Neurons, Perception, Models, Statistical, Neural Networks, Computer

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