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 examines the possibility that the components of an informationprocessing system all operate continuously, passing information from one to the next as it becomes available. A model called the cascade model is presented and it is shown to be compatible with the general form of the relation between time and accuracy in speed-accuracy trade-off experiments. In the model, ex--perimentlLlmanipulations may have either or both of two effects on a processing level: They may alter the rate of response or the asymptotic quality pf the output. The effects of such manipulations on the output of a system of proessesare described. The model is then used to reexamine, the subtraction and additive factors methods for analyzing the composition of systems of processes. The examination of the additive factors method yields particularly interesting results. Among them is the finding that factors that affect the rates of two different processes would be expected to have additive effects on reaction times under the cascade model, whereas factors that both affect the rate of the same process would tend to interact, just as in the case in which the manipulations

Two connectionist frameworks, GRAIN (McClelland, 1993) and BSB (Anderson, 1991), and the diffusion model (Ratcliff, 1978) were evaluated using data from a signal detection task. Subjects were asked to choose one of two possible responses to a stimulus and were provided feedback about whether the choice was correct. The dependent variables included response probabilities, reaction times for correct and error responses, and reaction time distributions, and the independent variables were stimulus value, stimulus probability, and lag from an abrupt switch in stimulus probability. The diffusion model accounted for all aspects of the asymptotic data, including error reaction times, which had previously been a problem. The connectionist models accounted for many aspects of the data adequately, but each failed to a greater or lesser degree in important ways except for one model very similar to the diffusion model. The connectionist learning mechanisms were unable to account for initial learning or abrupt changes in stimulus probability. The results provide an advance in the development of the diffusion model and show that the long tradition of reaction time research and theory is a fertile domain for development and testing of connectionist assumptions about how decisions are generated over time.

this article are also gratefully acknowledged

This article defends the claim that a significant part of visual perception (called "early vision") is impervious to the influence of beliefs, expectations or knowledge. We examine a wide range of empirical evidence that has been cited in support of the continuity of vision and cognition and argue that the evidence either shows withinvision top-down effects, or else the extra-visual effects that are demonstrated occur before the operation of the autonomous early vision system (through the allocation of focal attention) or after the visual system has produced its 3D shape-description (through the intervention of post-visual decision processes).

It has generally been assumed that rapid visual search is based on simple features and that spatial relations between features are irrelevant for this task. Seven experiments involving search for line drawings contradict this assumption; a major determinant of search is the presence of line junctions. Arrow- and Y-junctions were detected rapidly in isolation and when they were embedded in drawings of rectangular polyhedra. Search for T-junctions was considerably slower. Drawings containing T-junctions often gave rise to very slow search even when distinguishing arrow- or Y-junctions were present. This sensitivity to line relations suggests that preattentive processes can extract 3-dimensional orientation from line drawings. A computational model is outlined for how this may be accomplished in early human vision. Although we are still a long way from a complete understanding of visual perception, considerable progress has been made in our understanding of its earliest stages (see Zucker, 1987). These stages are concerned with the extrac-tion of information from the retinal image, and as such are generally assumed to be carried out by processes operating in parallel across the visual field. They are also generally assumed to be

Summary. The Simon effect indicates that choice reac-tions can be performed more quickly if the response corre-sponds spatially to the stimulus- even when stimulus location is irrelevant to the task. Two experiments tested an intentional approach to the Simon effect that assigns a critical role to the cognitively represented action goal (i. e., the intended action effect). It was assumed that the direc-tion of the Simon effect depends on stimulus-goal corre-spondence, that is, that responses are faster with spatial correspondence of stimulus and intended action effect. Ex-periment 1 confirmed that the direction of the Simon effect was determined by spatial correspondence of stimulus and intended action effect, the latter having been manipulated by different instructions. Experiment 2 indicated that ef-fects of correspondences unrelated to the action goal (i. e., stimulus to hand location or to anatomical mapping of the hand), contributed additively to the resulting Simon effect. It is discussed how current approaches to the Simon effect can be elaborated to account for these results.

the properties of distributed network models, and support this account by demonstrating that an implemented simulation closely approximates the empirical findings despite the absence of expectancy-based processes and postlexical semantic matching. The results suggest that distributed network models can provide a viable single-mechanism account of lexical processing. Introduction It is well-established that people are faster and more accurate to read a word (e.g., BUTTER) when it is preceded by a related word (e.g., BREAD) compared with when it is preceded by an unrelated word (e.g., DOCTOR; The research was supported by an NIMH FIRST award (MH55628) to the first author and by NIMH Training Grant 5T32MH19102 and NICHD Grant 80258. The computational simulation was run using customized software written within the Xerion simulator (version 3.1) developed by Drew van Camp, Tony Plate, and Geoff Hinton at the Univers

INTRODUCTION How do we go from seeing a word to accessing its meaning? Classical models of word processing postulate that words are initially recognized in modalityspecific input lexicons before contacting a common semantic representation (Caramazza, 1996; Morton, 1979). This predicts that areas which are engaged in semantic-level processing should activate in direct correlation with the amount of semantic manipulation required by the task and do so independent of the modality of presentation of the concept (Chao et al., 2000; Perani et al., 1999; Vandenberghe et al., 1996). Here, we attempt to identify the cerebral areas engaged in the coding and internal manipulation of an abstract semantic content, the meaning of number words. Although numbers can be written in multiple notations, such as words or digits, the parietal lobes are thought to comprise a notation-independent representation of their semantic content as quantities. According to the "triple-code model" of number process

Background noise is the irregular variation across repeated measurements of human performance. Background noise remains after task and treatment effects are minimized. Background noise refers to intrinsic sources of variability, the intrinsic dynamics of mind and body, and the internal workings of a living being. Two experiments demonstrate 1/f scaling (pink noise) in simple reaction times and speeded word naming times, which round out a catalog of laboratory task demonstrations that background noise is pink noise. Ubiquitous pink noise suggests processes of mind and body that change each other’s dynamics. Such interaction-dominant dynamics are found in systems that self-organize their behavior. Self-organization provides an unconventional perspective on cognition, but this perspective closely parallels a contemporary interdisciplinary view of living systems. Psychological science usually ignores the background noise in behavioral data. Background noise is what is left over when task demands, experimental manipulations, and other external sources of variability have been eliminated or minimized. What we call background noise is treated as random variability in most research, the nuisance factor in factorial experiments. We argue, to the