The two-process theory of detection, search, and attention presented by Schneider and Shiffrin is tested and extended in a series of experiments. The studies demonstrate the qualitative difference between two modes of information processing: automatic detection and controlled search. They trace the course of the learning of automatic detection, of categories, and of automaticattention responses. They show the dependence of automatic detection on attending responses and demonstrate how such responses interrupt controlled processing and interfere with the focusing of attention. The learning of categories is shown to improve controlled search performance. A general framework for human information processing is proposed; the framework emphasizes the roles of automatic and controlled processing. The theory is compared to and contrasted with extant models of search and attention.

This article indicates how competition between afferent data and learned feedback expectancies can stabilize a developing code by buffering committed populations of detectors against continual erosion by new environmental demands. Tille gating phenomena that result lead to dynamically maintained critical peri(Jlds, and to attentional phenomena such as overshadowing in the adult. The fuillctional unit of cognitive coding is suggested to be an adaptive resonance, or amplification and,prolongation of neural activity, that occurs when afferent data and efferent expectancies reach consensus through a matching process. The resonant state embodies the perceptual event, or attentional focus, and its amplified and sustained activities are capable of driving slow changes of long-term memor:r"' Mismatch between afferent data and efferent expectancies yields a global sulppression of activity and triggers a reset of short-term memory, as well as raJ~id parallel search and hypothesis testing for uncommitted cells. These mechanisms help to explain and predict, as manifestations of the unified theme of stable code development, positive and negative aftereffects, the McCollough effect, spatial frequency adaptation, monocular rivalry, binocular rivalry and hysteresis, pattern completion, and Gestalt switching; analgesia, partial reinforcement acquisition effect, conditioned reinforcers, underaroused versus overaroused depression; the contingent negative variation, P300, and pontoge]lliculo-occipital waves; olfactory coding, corticogeniculate feedback, matching of proprioceptive and terminal motor maps, and cerebral dominance. The psychophysiological mechanisms that unify these effects are inherently nonlinear and parallel and are inequivalent to the computer, probabilistic, and linear models currently in use.

This paper presents a skill learning model CLARION. Different from existing models of mostly high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge through practice), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. Our model is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line reactive learning. It adopts a two-level dual-representation framework (Sun, 1995), with a combination of localist and distributed representation. We compare the model with human data in a minefield navigation task, demonstrating some match between the model and human data in several respects.

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Data and models about recognition and recall of words and non words are unified using a real-time network processing theory. Lexical decision and word frequency effect data are analyzed in terms of theoretical concepts that have unified data about development of circular reactions, imitation of novel sounds, the matching of phonetic to articulatory requirements, serial and paired associate verbal learning, free recall, unitization, categorical perception, selective adaptation, auditory contrast, and word superiority effects. The theory, called adaptive resonance theory, arose from an analysis of how a language system self-organizes in real time in response to its complex input environment. Such an approach emphasizes the moment-by-moment dynamical interactions that control language development, learning, and stability. Properties of language performance emerge from an analysis of the system constraints that govern stable language learning. Concepts such as logogens, verification, automatic activation, interactive activation, limited-capacity processing, conscious attention, serial search, processing stages, speed-accuracy trade-off, situational frequency, familiarity, and encoding specificity are revised and developed using this analysis. Concepts such as adaptive resonance, resonant equilibration of short-term memory, bottom-up adaptive filtering, tQp-down adaptiveteml'late matching, competitive masking field, unitized list representation, temporal order information over item representations,

A theory of perception and attention that emphasizes the relational nature o { perceptual invariants is developed within the context of auditory pattern research. The theory is divided into two parts. The first part, addresses world pattern structure; the second describes interaction of organisms with pattern structure. Tn the former, world patterns arc subjectively represented as nested relations within a multidimensional space defined by pilch, loudncss, and time. But dependency of these defining dimensions means that a pattern's lime scale determines the serial integrity of its pitch/loudness structure. Second, the theory proposes a time scale for living things that is manifest in graded perceptual rhythms. These rhythms can be synchronized to corresponding nested time zones within world pattern structure. Related assumptions about the deployment of physical energy across time zones and cognitive locations of perceptual rhythms lead to a simple, but general, attentional theory. Theoretical support, found in research with tone patterns, speech, and sequences of noise is died in a final section. Beyond this focal research, the theory offers a general framework for understanding diverse phenomena thai range from speech perception and aphasia to sleep, growth, and time eslimation. The ideas presented in this paper are the foundation for a new way to understand human perception and memory. They are developed within the context of research with auditory patterns, but the general approach has implications for man} ' other areas of inquiry. Nevertheless, their most immediate relevance is to research and theory in speech and auditory pattern perception. The specific problems which give rise to this theory arc briefly outlined in the next section. This article was prepared with the support of National Science Foundation Grant UMS74-21492.

Short-term memory for conceptual information is largelymissing from current models of shortterm memory. Several phenomena are discussed that give evidence for very briefconceptual representations of stimuli. Altho~sghthese fleeting representations do not surface readily with-many of the standard methods for studying and testing short-term memory, I argue that they are fundamental to cognitive processing and to the form that long-term memory takes.

Scientific knowledge is dynamic in two senses: it changes and increases extremely rapidly, and it is thrust from the lab into the wider world and public forum almost as rapidly. This implies increasing demands on secondary school science education. Besides knowing key facts, concepts, and procedures, it is important for today’s students to understand the process by which the claims of science are generated, evaluated, and revised – an interplay between theoretical and empirical work (Dunbar & Klahr, 1989). The educational goals behind the work reported in this chapter are to improve students ’ understanding of this process and to facilitate students ’ acquisition of critical inquiry skills, while also meeting conventional subject matter learning objectives. In addition to the need to change what is taught, there are grounds to change how it is taught. Research shows that students learn better when they actively pursue understanding rather than passively

Abstract: The importance of collaborative and social learning processes is well established, as is the utility of external representations in supporting learners ' active expression, examination and manipulation of their own emerging knowledge. However, research on how computerbased representational tools may support collaborative learning is in its infancy. This paper motivates such a line of research, sketches a theoretical analysis of the roles of constraint and salience in the representational guidance of collaborative learning discourse, and reports on an initial study that compared textual, graphical, and matrix representations. Differences in the predicted direction were observed in the amount of talk about evidential relations and the use of epistemological categories.

Neuroimaging studies have suggested the involvement of ventrolateral, dorsolateral, and frontopolar prefrontal cortex (PFC) regions in both working (WM) and long-term memory (LTM). The current study used functional magnetic resonance imaging (fMRI) to directly compare whether these PFC regions show selective activation associated with one memory domain. In a within-subjects design, subjects performed the n-back WM task (two-back condition) as well as LTM encoding (intentional memorization) and retrieval (yes–no recognition) tasks. Additionally, each task was performed with two different types of stimulus materials (familiar words, unfamiliar faces) in order to determine the influence of material-type vs task-type. A bilateral region of dorsolateral PFC (DL-PFC; BA 46/9)