Priming effects have been used widely as a tool to study attentional processes. However, inferences regarding attention depend on how priming effects are interpreted. In the case of negative priming, an activation-based framework for interpreting priming suggests that attention inhibits the representation of prime distractors and that this inhibition is measured in performance to subsequent probes. Data summarized in this article point out that negative priming does not depend on selection of one of two primes and that attentional influences during (...) retrieval play an important role in determining negative priming. Also, two experiments are described that demonstrate a correlation between priming effects and knowledge of the relation between primes and probes. We suggest that negative priming is not determined directly by a process of ignoring, but instead occurs because a repeated probe is less temporally distinct when ignored as a prime than when attended. (shrink)

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. (shrink)

The processes mediating dynamic and flexible responding to rapidly changing task-environments are not well understood. In the present research we employ a Stroop procedure to clarify the contribution of context-sensitive control processes to online performance. In prior work Stroop interference varied as a function of probe location context, with larger Stroop interference occurring for contexts associated with a high proportion of congruent items [Crump, M. J., Gong, Z., & Milliken, B. . The context-specific proportion congruent stroop effect: location as a (...) contextual cue. Psychonomic Bulletin & Review, 13, 316–321.] Here, we demonstrate that this effect does not depend on awareness of the context manipulation, but that it can depend on attention to the predictive context dimension, and on the relative salience of the target and predictive context dimensions. We discuss the implications of our results for current theories of cognitive control. (shrink)

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic (...) transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category-exemplar, mediated and backward prime-target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model. (shrink)

Theory suggests that stimulus evaluations automatically evoke approach–avoidance behavior. However, the extent to which approach–avoidance behavior is triggered automatically is not yet clear. Furthermore, the nature of automatically triggered approach–avoidance behavior is controversial. We review research on two views on the type of approach–avoidance behavior that is triggered automatically (arm flexion/extension, distance change). Present evidence supports the distance-change view and corroborates the notion of an automatic pathway from evaluation to distance-change behavior. We discuss underlying mechanisms (direct stimulus–response links, outcome anticipations, (...) goals) as well as implications regarding the flexibility of the evaluation–behavior link. (shrink)

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the (...) analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. (shrink)

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point (...) estimates, decisions, and probability assessments by human participants. The best fit is obtained for a version that weights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implements speed and frugality in a psychologically plausible way. (shrink)

Recent research suggests that processing of irrelevant information can be modulated in a rapid online fashion by contextual information in the task environment depending on the usefulness of that information in different contexts. Congruency effects evoked by irrelevant stimulus attributes are smaller in contexts with high proportions of incongruent trials and larger in contexts with high proportions of congruent trials . The present study investigates these context-adaptation effects in a masked-priming paradigm. Context-specific adaptation effects transfer to stimulus identities that are (...) equiprobale in all contexts – an observation that renders explanations in terms of event-learning processes unlikely. Yet, context-specific effects vanished when the irrelevant information remained unconscious. The results suggest that context-specific adaptation of congruency effects reflect cognitive control operations that alter the processing of irrelevant information depending on the experienced utility of that information for action control. (shrink)

Cognitive architectures (i.e., theorized blueprints on the structure of the mind) can be used to make predictions about the effect of multiregion brain activity on the systems level. Recent work has connected one high-level cognitive architecture, known as the “Common Model of Cognition,” to task-based functional MRI data with great success. That approach, however, was limited in that it was intrinsically top-down, and could thus only be compared with alternate architectures that the experimenter could contrive. In this paper, we propose (...) a bottom-up method to infer a cognitive architecture directly from brain imaging data itself, overcoming this limitation. Specifically, Granger causality modeling was applied to the same task-based fMRI data to infer a network of causal connections between brain regions based on their functional connectivity. The resulting network shares many connections with those proposed by the Common Model of Cognition but also suggests important additions likely related to the role of episodic memory. This combined top-down and bottom-up modeling approach can be used to help formalize the computational instantiation of cognitive architectures and further refine a comprehensive theory of cognition. (shrink)

The present research investigates the role of voluntary, conscious processing in strategy change. In 2 experiments, we address whether the switch to a new strategy is the result of data - driven, automatic processes or of voluntary processes. Experiment 1 demonstrates that participants performing an alphabet verification task are able to transfer a newly adopted strategy to dissimilar information never encountered before, verbally describe the task regularity that allows for the generation and application of the new strategy immediately after the (...) strategy was adopted. Using the same experimental task, Experiment 2 shows that participants, and decide against adopting a new strategy when the available evidence suggests that the new strategy cannot be used for the entire range of problems encountered. Overall, the obtained results support the view that strategy change is mediated by voluntary controlled processing. They do not support the view that strategy change is an inevitable, automatic consequence of task practice. The present research thus highlights a potential function of conscious human processing. (shrink)

This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision‐making process: instance‐based knowledge, recognition‐based retrieval, adaptive strategies, necessity‐based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refinement of instances, containing the decision‐making situation, action, and utility of decisions. As decision makers interact with a dynamic task, they recognize a situation according to its similarity to past instances, (...) adapt their judgment strategies from heuristic‐based to instance‐based, and refine the accumulated knowledge according to feedback on the result of their actions. The IBLT's learning mechanisms have been implemented in an ACT‐R cognitive model. Through a series of experiments, this paper shows how the IBLT's learning mechanisms closely approximate the relative trend magnitude and performance of human data. Although the cognitive model is bounded within the context of a dynamic task, the IBLT is a general theory of decision making applicable to other dynamic environments. (shrink)

Corrigendum to "Exploration and exploitation during information search and consequential choice".

Cohen Kadosh & Walsh (CK&W) present convincing evidence indicating the existence of notation-specific numerical representations in parietal cortex. We suggest that the same conclusions can be drawn for a particular type of numerical representation: the representation of time. Notation-dependent representations need not be limited to number but may also be extended to other magnitude-related contents processed in parietal cortex (Walsh 2003).