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Relevance-based selectivity: the case of implicit learning
Baruch Eitam1, Arit Glicksohn, Roy Shoval
1Psychology Department, University of Haifa.
Abstract:
Learning the structure of the environment (e.g., what usually follows what) enables animals to behave in an effective manner and prepare for future events. Unintentional learning is capable of efficiently producing such knowledge as has been demonstrated with the Artificial Grammar Learning paradigm (AGL), among others. It has been argued that selective attention is a necessary and sufficient condition for visual implicit learning. Experiment 1 shows that spatial attention is not sufficient for implicit learning. Learning does not occur if the stimuli instantiating the structure are task irrelevant. In a second experiment, we demonstrate that this holds even with abundance of available attentional resources. Together, these results challenge the current view of the relations between attention, resources, and implicit learning.
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