Tested the 2-process theory of detection, search, and attention presented by the current authors in a series of experiments. The studies demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; trace the course of the learning of automatic detection, of categories, and of automatic-attention responses; and 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. (shrink)

The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of (...) activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed. (shrink)

If we are eventually to understand the capability of higher organisms for perceptual recognition, generalization, recall, and thinking, we must first have answers to three fundamental questions: 1. How is information about the physical world sensed, or detected, by the biological system? 2. In what form is information stored, or remembered? 3. How does information contained in storage, or in memory, influence recognition and behavior? The first of these questions is in the.

One hypothesis concerning the human dorsal anterior cingulate cortex (ACC) is that it functions, in part, to signal the occurrence of conflicts in information processing, thereby triggering compensatory adjustments in cognitive control. Since this idea was first proposed, a great deal of relevant empirical evidence has accrued. This evidence has largely corroborated the conflict-monitoring hypothesis, and some very recent work has provided striking new support for the theory. At the same time, other findings have posed specific challenges, especially concerning the (...) way the theory addresses the processing of errors. Recent research has also begun to shed light on the larger function of the ACC, suggesting some new possibilities concerning how conflict monitoring might fit into the cingulate's overall role in cognition and action. (shrink)

This paper offers a conceptual framework which (re)integrates goal-directed control, motivational processes, and executive functions, and suggests a developmentalpathway from situated action to higher level cognition. We first illustrate a basic computational (control-theoretic) model of goal-directed action that makes use of internalmodeling. We then show that by adding the problem of selection among multiple actionalternatives motivation enters the scene, and that the basic mechanisms of executivefunctions such as inhibition, the monitoring of progresses, and working memory, arerequired for this system to (...) work. Further, we elaborate on the idea that the off-line re-enactment of anticipatory mechanisms used for action control gives rise to (embodied)mental simulations, and propose that thinking consists essentially in controlling mental simulations rather than directly controlling behavior and perceptions. We concludeby sketching an evolutionary perspective of this process, proposing that anticipationleveraged cognition, and by highlighting specific predictions of our model. (shrink)

The past 25 years have witnessed an increasing awareness of the importance of cognitive control in the regulation of complex behavior. It now sits alongside attention, memory, language, and thinking as a distinct domain within cognitive psychology. At the same time it permeates each of these sibling domains. This introduction reviews recent work on cognitive control in an attempt to provide a context for the fundamental question addressed within this topic: Is cognitive control to be understood as resulting from the (...) interaction of multiple distinct control processes, or are the phenomena of cognitive control emergent? (shrink)

This article investigates the potential of fMRI to test assumptions about different components in models of complex cognitive tasks. If the components of a model can be associated with specific brain regions, one can make predictions for the temporal course of the BOLD response in these regions. An event‐locked procedure is described for dealing with temporal variability and bringing model runs and individual data trials into alignment. Statistical methods for testing the model are described that deal with the scan‐to‐scan correlations (...) in the errors of measurement of the BOLD signal. This approach is illustrated using a “sacrificial” ACT‐R model that involves mapping 6 modules onto 6 brain regions in an experiment from concerned with equation solving. The model's visual encoding predicted the BOLD response in the fusiform gyrus, its controlled retrieval predicted the BOLD response in the lateral inferior prefrontal cortex, and its subgoal setting predicted the BOLD response in the anterior cingulate cortex. On the other hand, its motor programming failed to predict anticipatory activation in the motor cortex, its representational changes failed to predicted the pattern of activity in the posterior parietal cortex, and its procedural component failed to predict an initial spike in caudate. The results illustrate the power of such data to direct the development of a theory of complex problem solving, both at the level of a specific task model as well as at the level of the cognitive architecture. (shrink)

Page's proposal to stipulate representations in which individual units correspond to meaningful entities is too unconstrained to support effective theorizing. An approach combining general computational principles with domain-specific assumptions, in which learning is used to discover representations that are effective in solving tasks, provides more insight into why cognitive and neural systems are organized the way they are.