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Bayesian Spiking Neurons I: Inference
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.
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“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”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Deneve, 2008
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“The firing of a single neuron (or a small population of neurons) represents the presence or absence of some feature at a moment in time (Deneve, 2008; Deneve and Jardri, 2016).”
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Metadata
- 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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