@inbook{d2073ff197c24598b872018c62e6e84c,
title = "Stimulus-response reliability of biological networks",
abstract = "If a network of cells is repeatedly driven by the same sustained, complex signal, will it give the same response each time? A system whose response is reproducible across repeated trials is said to be reliable. reliability Reliability is of interest in, e.g., computational neuroscience because the degree to which a neuronal network is reliable constrains its ability to encode information via precise temporal patterns of spikes. This chapter reviews a body of work aimed at discovering network conditions and dynamical mechanisms that can affect the reliability of a network. A number of results are surveyed here, including a general condition for reliability and studies of specific mechanisms for reliable and unreliable behavior in concrete models. This work relies on qualitative arguments using random dynamical systems theory, in combination with systematic numerical simulations.",
keywords = "Coupled oscillators, Lyapunov exponents, Neuronal networks, Random dynamical systems, Reliability, SRB measures, Spike-time precision",
author = "Lin, {Kevin K.}",
note = "Funding Information: The work described in this review were supported in part by the Burroughs-Wellcome Fund (Eric Shea-Brown) and the NSF (Lai-Sang Young and Kevin K Lin). ",
year = "2013",
doi = "10.1007/978-3-319-03080-7_4",
language = "English (US)",
isbn = "9783319030791",
series = "Lecture Notes in Mathematics",
publisher = "Springer-Verlag",
pages = "135--161",
booktitle = "Nonautonomous Dynamical Systems in the Life Sciences",
}