When the stored representation of the meaning of a stimulus is accessed through the processing of a sensory input it is maintained in an activated state for a certain amount of time that allows for further processing. This semantic activation is generally accompanied by conscious identification, which can be demonstrated by the ability of a person to perform discriminations on the basis of the meaning of the stimulus. The idea that a sensory input can give rise to semantic activation without (...) concomitant conscious identification was the central thesis of the controversial research in subliminal perception. Recently, new claims for the existence of such phenomena have arisen from studies in dichotic listening, parafoveal vision, and visual pattern masking. Because of the fundamental role played by these types of experiments in cognitive psychology, the new assertions have raised widespread interest. (shrink)

A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, between learning that takes place with versus without concurrent awareness, and between learning that involves the encoding of instances versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning derived from subliminal learning, (...) conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks is predominantly based on rule abstraction is questionable. When subjects cannot report the “implicitly learned” rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning. (shrink)