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A network model of catecholamine effects: gain, signal-to-noise ratio, and behavior.

作者信息

Servan-Schreiber D, Printz H, Cohen J D

机构信息

School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213.

出版信息

Science. 1990 Aug 24;249(4971):892-5. doi: 10.1126/science.2392679.

DOI:10.1126/science.2392679
PMID:2392679
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.

摘要

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