Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve (...) complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. (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, (1) between learning that takes place with versus without concurrent awareness, and (2) between learning that involves the encoding of instances (or fragments) 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 (e.g., artificial grammar learning) is predominantly based on rule abstraction is questionable. When subjects cannot report the 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)

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)

The study aims to help characterize the sort of structures about which people can acquire unconscious knowledge. It is already well established that people can implicitly learn n-grams and also repetition patterns. We explore the acquisition of unconscious structural knowledge of symmetry. Chinese Tang poetry uses a specific sort of mirror symmetry, an inversion rule with respect to the tones of characters in successive lines of verse. We show, using artificial poetry to control both n-gram structure and repetition patterns, that (...) people can implicitly learn to discriminate inversions from non-inversions, presenting a challenge to existing models of implicit learning. (shrink)

The dominant theory of what people can learn implicitly is that they learn chunks of adjacent elements in sequences. A type of musical grammar that goes beyond specifying allowable chunks is provided by serialist or 12‐tone music. The rules constitute operations over variables and could not be appreciated as such by a system that can only chunk elements together. A series of studies investigated the extent to which people could implicitly (or explicitly) learn the structures of serialist music. We found (...) that people who had no background in atonal music did not learn the structures, but highly selected participants with an interest in atonal music could implicitly learn to detect melodies instantiating the structures. The results have implications for both theorists of implicit learning and composers who may wish to know which structures they put into a piece of music can be appreciated. (shrink)

We investigated the implicit learning of a linguistically relevant variable in a natural language context . Trial by trial subjective measures indicated that exposure to a form–animacy regularity led to unconscious knowledge of that regularity. Under the same conditions, people did not learn about another form–meaning regularity when a linguistically arbitrary variable was used instead of animacy . Implicit learning is constrained to acquire unconscious knowledge about features with high prior probabilities of being relevant in that domain.

An experiment explored the acquisition of conscious and unconscious knowledge of semantic prosody in a second language under incidental and intentional learning conditions. Semantic prosody is the conotational coloring of the semantics of a word, largely uncaptured by dictionary definitions. Contrary to some claims in the literature, we revealed that both conscious and unconscious knowledge were involved in the acquisition of semantic prosody. Intentional learning resulted in similar unconscious but more conscious knowledge than incidental learning. The results are discussed in (...) terms of second language learning and the nature of unconscious knowledge. (shrink)

This paper investigates the time it takes unconscious vs. conscious knowledge to form by using an improved “no-loss gambling” method to measure awareness of knowing. Subjects could either bet on a transparently random process or on their grammaticality judgment in an artificial grammar learning task. A conflict in the literature is resolved concerning whether unconscious rather than conscious knowledge is especially fast or slow to form. When guessing , accuracy was above chance and RTs were longer than when feeling confident (...) . In a second experiment, short response deadlines only interfered with the quality of confident decisions . When people are unaware of their knowledge, externally enforced decisions can be made rapidly with little decline in quality; but if given ample time, they await a metacognitive process to complete. The dissociation validates no-loss gambling as a measure of conscious awareness. (shrink)

referred to as implicit learning (Reber, 1989). Implicit learning contrasts with explicit learning (exhibited for.

How people learn chunks or associations between adjacent items in sequences was modelled. Two previously successful models of how people learn artificial grammars were contrasted: the CCN, a network version of the competitive chunker of Servan‐Schreiber and Anderson [J. Exp. Psychol.: Learn. Mem. Cogn. 16 (1990) 592], which produces local and compositionally‐structured chunk representations acquired incrementally; and the simple recurrent network (SRN) of Elman [Cogn. Sci. 14 (1990) 179], which acquires distributed representations through error correction. The models' susceptibility to two (...) types of interference was determined: prediction conflicts, in which a given letter can predict two other letters that appear next with an unequal frequency; and retroactive interference, in which the prediction made by a letter changes in the second half of training. The predictions of the models were determined by exploring parameter space and seeing howdensely different regions of the space of possible experimental outcomes were populated by model outcomes. For both types of interference, human data fell squarely in regions characteristic of CCN performance but not characteristic of SRN performance. (shrink)

The time course of different metacognitive experiences of knowledge was investigated using artificial grammar learning. Experiment 1 revealed that when participants are aware of the basis of their judgments decisions are made most rapidly, followed by decisions made with conscious judgment but without conscious knowledge of underlying structure , and guess responses were made most slowly, even when controlling for differences in confidence and accuracy. In experiment 2, short response deadlines decreased the accuracy of unconscious but not conscious structural knowledge. (...) Conversely, the deadline decreased the proportion of conscious structural knowledge in favour of guessing. Unconscious structural knowledge can be applied rapidly but becomes more reliable with additional metacognitive processing time whereas conscious structural knowledge is an all-or-nothing response that cannot always be applied rapidly. These dissociations corroborate quite separate theories of recognition and metacognition. (shrink)

Previous research has established that people can implicitly learn chunks, which do not require a memory buffer to process. The present study explores the implicit learning of nonlocal dependencies generated by higher than finite-state grammars, specifically, Chinese tonal retrogrades and inversions , which do require buffers . People were asked to listen to and memorize artificial poetry instantiating one of the two grammars; after this training phase, people were informed of the existence of rules and asked to classify new poems, (...) while providing attributions of the basis of their judgments. People acquired unconscious structural knowledge of both tonal retrogrades and inversions. Moreover, inversions were implicitly learnt more easily than retrogrades constraining the nature of the memory buffer in computational models of implicit learning. (shrink)

Most would agree that attention and consciousness are related to one another; however, this is not to say that everything being attended to is available to consciousness, or vice versa. In fact, some researchers argue that information being attended to is not always under the control of top-down attentional processes, and attention can often be directed towards input that remains outside of consciousness . For example, the attentional system could become oriented to a familiar smell entering the environment. Attending to (...) this sensory input could even bring on sadness without awareness of the culprit behind this sudden onset of emotion. Further examination could be facilitated by selecting the input being received by the olfactory system, leading to the conscious realization that the floral aroma filling the room reminds one of a recently-attended funeral. The foregoing example raises several issues that speak to the connection between attention and consciousness. First, a person is not always consciously aware of what he or she is attending to, which suggests attention and consciousness are separate, albeit related, constructs. Attentional orienting is one example of how attention can be shifted in response to changing states in the environment, without the voluntary control of the organism . Second, the contents of the unconscious mind can influence ongoing cognitive operations in a variety of ways that are not yet fully understood. Third, attention can be used to draw important information into conscious awareness, making the study of attentional processes useful as a tool to explore the nature of consciousness. The relationship between attention and consciousness, and the utility of this relationship for understanding these complex constructs, will be discussed, followed by a consideration of the remaining issues and the tools that may be used to address them. (shrink)