title: A network model of catecholamine effects: gain, signal-to-noise ratio, and behavior.
abstract: At the level of individual neurons, catecholamine release increases the responsivity of cells to excitatory and inhibitory inputs. A model of catecholamine effects in a network of neural-like elements is presented, which shows that (i) changes in the responsivity of individual elements do not affect their ability to detect a signal and ignore noise but (ii) the same changes in cell responsivity in a network of such elements do improve the signal detection performance of the network as a whole. The second result is used in a computer simulation based on principles of parallel distributed processing to account for the effect of central nervous system stimulants on the signal detection performance of human subjects.
authors.affiliation: School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213.
authors.forename: D
authors.initials: D
authors.lastname: Servan-Schreiber
authors.forename: H
authors.initials: H
authors.lastname: Printz
authors.forename: J D
authors.initials: JD
authors.lastname: Cohen
mesh_terms: D001519:Behavior; D002395:Catecholamines / Q000502:physiology*; D002490:Central Nervous System / Q000187:drug effects / Q000502:physiology; D004298:Dopamine / Q000502:physiology; D006801:Humans; D008774:Methylphenidate / Q000494:pharmacology; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009638:Norepinephrine / Q000502:physiology
chemical_list: D002395:Catecholamines; D008774:Methylphenidate; D004298:Dopamine; D009638:Norepinephrine