ArticlePLoS computational biology2016
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- When noncanonical olfaction is optimal.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A universal power law optimizes energy and representation fidelity in visual adaptation.bioRxiv : the preprint server for biology · 2025Article
- Low-dimensional controllability of brain networks.PLoS computational biology · 2025Article
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- The geometry of correlated variability leads to highly suboptimal discriminative sensory coding.Journal of neurophysiology · 2025Article
- Stochastic resonance in sparse neuronal network: functional role of ongoing activity to detect weak sensory input in awake auditory cortex of rat.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Spatiotemporal visual statistics of aquatic environments in the natural habitats of zebrafish.Scientific reports · 2023Article
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- Efficient and adaptive sensory codes.Nature neuroscience · 2021Article
- How inhibitory neurons increase information transmission under threshold modulation.Cell reports · 2021Article
- Efficient population coding depends on stimulus convergence and source of noise.PLoS computational biology · 2021Article
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- Nonlinear convergence boosts information coding in circuits with parallel outputs.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Ignoring correlated activity causes a failure of retinal population codes.Nature communications · 2020Article
- A practical guide to methodological considerations in the controllability of structural brain networks.Journal of neural engineering · 2020Article
- Functional diversity among sensory neurons from efficient coding principles.PLoS computational biology · 2019Article
- Linking neural responses to behavior with information-preserving population vectors.Current opinion in behavioral sciences · 2019Article
- Stimulus- and goal-oriented frameworks for understanding natural vision.Nature neuroscience · 2019Review
- Pathway-Specific Asymmetries between ON and OFF Visual Signals.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- Adaptive coding for dynamic sensory inference.eLife · 2018Article
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4 authors.
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Abstract
Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.
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