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

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

SUBMITTER: Brinkman BA 

PROVIDER: S-EPMC5065234 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature