title: Unbiased measures of transmitted information and channel capacity from multivariate neuronal data.
abstract: Two measures from information theory, transmitted information and channel capacity, can quantify the ability of neurons to convey stimulus-dependent information. These measures are calculated using probability functions estimated from stimulus-response data. However, these estimates are biased by response quantization, noise, and small sample sizes. Improved estimators are developed in this paper that depend on both an estimate of the sample-size bias and the noise in the data.
authors.affiliation: Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, Md.
authors.forename: L M
authors.initials: LM
authors.lastname: Optican
authors.forename: T J
authors.initials: TJ
authors.lastname: Gawne
authors.forename: B J
authors.initials: BJ
authors.lastname: Richmond
authors.forename: P J
authors.initials: PJ
authors.lastname: Joseph
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D000882:Haplorhini; D007257:Information Theory; D008433:Mathematics; D008959:Models, Neurological; D015999:Multivariate Analysis; D009474:Neurons / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology