ArticlePLoS computational biology2020
Efficient sensory coding of multidimensional stimuli.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A unifying theory of receptive field heterogeneity predicts hippocampal spatial tuning.bioRxiv : the preprint server for biology · 2025Article
- Weight illusions explained by efficient coding based on correlated natural statistics.Communications psychology · 2024Article
- Jointly efficient encoding and decoding in neural populations.PLoS computational biology · 2024Article
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- Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
According to the efficient coding hypothesis, sensory systems are adapted to maximize their ability to encode information about the environment. Sensory neurons play a key role in encoding by selectively modulating their firing rate for a subset of all possible stimuli. This pattern of modulation is often summarized via a tuning curve. The optimally efficient distribution of tuning curves has been calculated in variety of ways for one-dimensional (1-D) stimuli. However, many sensory neurons encode multiple stimulus dimensions simultaneously. It remains unclear how applicable existing models of 1-D tuning curves are for neurons tuned across multiple dimensions. We describe a mathematical generalization that builds on prior work in 1-D to predict optimally efficient multidimensional tuning curves. Our results have implications for interpreting observed properties of neuronal populations. For example, our results suggest that not all tuning curve attributes (such as gain and bandwidth) are equally useful for evaluating the encoding efficiency of a population.
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