The Dynamics of Perceptual Learning: An Incremental Reweighting Model

Autor/inn/en	Petrov, Alexander A.; Dosher, Barbara Anne; Lu, Zhong-Lin
Titel	The Dynamics of Perceptual Learning: An Incremental Reweighting Model
Quelle	In: Psychological Review, 112 (2005) 4, S.715-743 (29 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-295X
Schlagwörter	Cognitive Style; Hypothesis Testing; Discriminant Analysis; Computer Simulation; Computer Assisted Instruction; Perceptual Motor Learning; Evaluation Research; Weighted Scores; Mathematical Models; Predictor Variables + Suchen Sie Ihr Suchwort? Cognitive styles; Kognitiver Stil; Hypothesenprüfung; Hypothesentest; Diskriminanzanalyse; Computergrafik; Computersimulation; Computer based training; Computerunterstützter Unterricht; Perceptual-motor learning; Sensumotorisches Lernen; Wahrnehmungsschulung; Evaluationsforschung; Mathematical model; Mathematisches Modell; Prädiktor
Abstract	The mechanisms of perceptual learning are analyzed theoretically, probed in an orientation-discrimination experiment involving a novel nonstationary context manipulation, and instantiated in a detailed computational model. Two hypotheses are examined: modification of early cortical representations versus task-specific selective reweighting. Representation modification seems neither functionally necessary nor implied by the available psychophysical and physiological evidence. Computer simulations and mathematical analyses demonstrate the functional and empirical adequacy of selective reweighting as a perceptual learning mechanism. The stimulus images are processed by standard orientation- and frequency-tuned representational units, divisively normalized. Learning occurs only in the "read-out" connections to a decision unit; the stimulus representations never change. An incremental Hebbian rule tracks the task-dependent predictive value of each unit, thereby improving the signal-to-noise ratio of their weighted combination. Each abrupt change in the environmental statistics induces a switch cost in the learning curves as the system temporarily works with suboptimal weights. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10