z-logo
Premium
ON THE DEVELOPMENT AND MECHANICS OF DELAYED MATCHING‐TO‐SAMPLE PERFORMANCE
Author(s) -
Kangas Brian D.,
Berry Meredith S.,
Branch Marc N.
Publication year - 2011
Publication title -
journal of the experimental analysis of behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 61
eISSN - 1938-3711
pISSN - 0022-5002
DOI - 10.1901/jeab.2011.95-221
Subject(s) - stimulus (psychology) , stimulus control , confidence interval , statistics , audiology , sample size determination , psychology , computer science , cognitive psychology , mathematics , medicine , neuroscience , nicotine
Despite its frequent use to assess effects of environmental and pharmacological variables on short‐term memory, little is known about the development of delayed matching‐to‐sample (DMTS) performance. This study was designed to examine the dimensions and dynamics of DMTS performance development over a long period of exposure to provide a more secure foundation for assessing stability in future research. Six pigeons were exposed to a DMTS task with variable delays for 300 sessions (i.e., 18,000 total trials; 3,600 trials per retention interval). Percent‐correct and log‐ d measures used to quantify the development of conditional stimulus control under the procedure generally and at each of five retention intervals (0, 2, 4, 8 and 16‐s) individually revealed that high levels of accuracy developed relatively quickly under the shorter retention intervals, but increases in accuracy under the longer retention intervals sometimes were not observed until 100–150 sessions had passed, with some still increasing at Session 300. Analyses of errors suggested that retention intervals induced biases by shifting control from the sample stimulus to control by position, something that was predicted by observed response biases during initial training. These results suggest that although it may require a great deal of exposure to DMTS prior to obtaining asymptotic steady state, quantification of model parameters may help predict trends when extended exposure is not feasible.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here