How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

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 efficie...

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Bibliographic Details
Published in:PLoS computational biology 2016-10, Vol.12 (10), p.e1005150-e1005150
Main Authors: Brinkman, Braden A W, Weber, Alison I, Rieke, Fred, Shea-Brown, Eric
Format: Article
Language:English
Subjects:
Animals
Applied mathematics
Binomial distribution
Biology and Life Sciences
Biophysics
Coding theory
Computer and Information Sciences
Computer Simulation
Engineering and Technology
Humans
Hypotheses
Information Storage and Retrieval - methods
Mathematics
Medicine and Health Sciences
Models, Neurological
Models, Statistical
Nerve Net - physiology
Nervous system
Neural circuitry
Neurosciences
Noise
Physical Sciences
Physiological aspects
Physiology
Sensory Receptor Cells - physiology
Signal-To-Noise Ratio
Simulation
Studies
Synaptic Transmission - physiology
Trends
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Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1005150