Control of automatic processes: A parallel distributed-processing model of the stroop effect. Technical report
A growing body of evidence suggests that traditional views of automaticity are in need of revision. For example, automaticity has often been treated as an all-or-none phenomenon, and traditional theories have held that automatic processes are independent of attention. Yet recent empirial data suggests that automatic processes are continuous, and furthermore are subject to attentional control. In this paper we present a model of attention which addresses these issues. Using a parallel distributed processing framework we propose that the attributes of automaticity depend upon the strength of a process and that strength increases with training. Using the Stroop effect as an example, we show how automatic processes are continuous and emerge gradually with practice. Specifically, we present a computational model of the Stroop task which simulates the time course of processing as well as the effects of learning.
- Research Organization:
- Carnegie-Mellon Univ., Pittsburgh, PA (USA). Artificial Intelligence and Psychology Project
- OSTI ID:
- 6999312
- Report Number(s):
- AD-A-218914/0/XAB; AIP-40
- Country of Publication:
- United States
- Language:
- English
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