Projects per year
Abstract (may include machine translation)
In 2006, Ma et al. (Nat. Neurosci. 1006;9:1432–1438) presented an elegant theory for how populations of neurons might represent uncertainty to perform Bayesian inference. Critically, according to this theory, neural variability is no longer a nuisance, but rather a vital part of how the brain encodes probability distributions and performs computations with them.
Original language | English |
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Pages (from-to) | 767-770 |
Number of pages | 4 |
Journal | Trends in Neurosciences |
Volume | 41 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2018 |
Keywords
- Bayesian inference
- cortex
- neural network
- neural variability
- perception
- uncertainty
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Dive into the research topics of 'The Redemption of Noise: Inference with Neural Populations'. Together they form a unique fingerprint.Projects
- 1 Finished
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COGTOM: Cognitive Tomography of Mental Representations
Lengyel, M. (PI)
European Commission - H2020 - European Research Council - Consolidator Grant
1/05/17 → 30/04/23
Project: Research