Recent data indicate that under a specific posthypnotic suggestion to circumvent reading, highly suggestible subjects successfully eliminated the Stroop interference effect. The present study examined whether an optical explanation could account for this finding. Using cyclopentolate hydrochloride eye drops to pharmacologically prevent visual accommodation in all subjects, behavioral Stroop data were collected from six highly hypnotizables and six less suggestibles using an optical setup that guaranteed either sharply focused or blurred vision. The highly suggestibles performed the Stroop task when naturally (...) vigilant, under posthypnotic suggestion not to read, and while visually blurred; the less suggestibles ran naturally vigilant, while looking away, and while visually blurred. Although visual accommodation was precluded for all subjects, posthypnotic suggestion effectively eliminated Stroop interference and was comparable to looking away in controls. These data strengthen the view that Stroop interference is neither robust nor inevitable and support the hypothesis that posthypnotic suggestion may exert a top-down influence on neural processing. (shrink)

The relations between automatic processing and consciousness are discussed in this paper. It is argued that automatic processing should not be identified with the absence of consciousness. The organism has access to representations resulting from automatic processing, but these representations, in contrast to the representations resulting from nonautomatic processing, are not propositional. Therefore monitoring of the process, the defining feature of nonautomatic processing, is not possible.

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

In a previous study we examined reading, spelling, and maths skills in an unselected group of 129 Italian children attending fifth grade by testing various cognitive predictors; results showed a high degree of predictors’ selectivity for each of these three behaviors. In the present study, we focused on the specificity of the predictors by performing cross-analyses on the same dataset; i.e., we predicted spelling and maths skills based on reading predictors, reading based on maths predictors and so on. Results indicated (...) that some predictors, such as the Orthographic Decision and the Arithmetic Facts tests, predicted reading, spelling and maths skills in similar ways, while others predicted different behaviors but only for a specific parameter, such as fluency but not accuracy, and still others were specific for a single behavior. To interpret these results, we propose a novel model of learning skills separately considering factors in terms of competence, performance and acquisition. Reading, spelling and calculation skills would depend on the development of discrete and different abstract competences. By contrast, overlap among behaviors would be accounted for by defective acquisition in automatized responses to individual “instances”; this latter skill is item specific but domain independent. Finally, performance factors implied in task’s characteristics may contribute to the partial association among learning skills. It is proposed that this new model may provide a useful base for interpreting the diffuse presence of comorbidities among learning disorders. (shrink)

Research in the neurosciences continues to provide evidence that sleep plays a role in the processes of learning and memory. There is less of a consensus, however, regarding the precise stages of memory development during which sleep is considered a requirement, simply favorable, or not important. This article begins with an overview of recent studies regarding sleep and learning, predominantly in the procedural memory domain, and is measured against our current understanding of the mechanisms that govern memory formation. Based on (...) these considerations, I offer a new neurocognitive framework of procedural learning, consisting first of acquisition, followed by two specific stages of consolidation, one involving a process of stabilization, the other involving enhancement, whereby delayed learning occurs. Psychophysiological evidence indicates that initial acquisition does not rely fundamentally on sleep. This also appears to be true for the stabilization phase of consolidation, with durable representations, resistant to interference, clearly developing in a successful manner during time awake (or just time, per se). In contrast, the consolidation stage, resulting in additional/enhanced learning in the absence of further rehearsal, does appear to rely on the process of sleep, with evidence for specific sleep-stage dependencies across the procedural domain. Evaluations at a molecular, cellular, and systems level currently offer several sleep specific candidates that could play a role in sleep-dependent learning. These include the upregulation of select plasticity-associated genes, increased protein synthesis, changes in neurotransmitter concentration, and specific electrical events in neuronal networks that modulate synaptic potentiation. Key Words: consolidation; enhancement; learning; memory; plasticity; sleep; stabilization. (shrink)

Glenberg's account falls short in several respects. Besides requiring clearer explication of basic concepts, his account fails to recognize the autonomous nature of perception. His account of what is remembered, and its description, is too static. His strictures against connectionist modeling might be overcome by combining the notions of psychological space and principled learning in an embodied and situated network.

: This article describes a psychological test of Hull's (1988) theory of science as an evolutionary process by seeing if it can account for how scientists sometimes remember and cite the scientific literature. The conceptual adequacy of Hull's theory was evaluated by comparing it to Bartlett's (1932) seminal theory of human remembering. Bartlett found that remembering is an active, reconstructive process driven by a schema that biases recall in the direction of proto- typicality and personal involvement. This account supports Hull's (...) theory of science because it shows that the characteristics of reconstructive remembering are consistent with the generic properties of an evolutionary process. The empirical adequacy of Hull's theory was evaluated by comparing the predictions made from this evolutionary viewpoint against evidence from the history of science. Six cases studies of well-known psychological experiments that had been subject to repeated miscitation errors were collected and reviewed. All six case studies revealed a systematic pattern of distortions that is consistent with the schema-induced biases of reconstructive remembering. These findings support Hull's claim that science is an evolutionary process with scientists as interactors, scientific beliefs as replicators, and schemata as means for that replication. (shrink)

Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the most prominent criteria by which architectures are designed and evaluated, but they are not the only ones. This paper considers three additional criteria that have been comparatively undertheorized. (a) Successful architectures possess subjective and intersubjective meaning, making cognition comprehensible to individual cognitive (...) scientists and organizing groups of like-minded cognitive scientists into genuine communities. (b) Successful architectures provide idioms that structure the design and interpretation of computational models. (c) Successful architectures are strange: They make provocative, often disturbing, and ultimately compelling claims about human information processing that demand evaluation. (shrink)

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture–word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential sampling and long-term (...) declarative learning, and between sequential sampling and task control. In a traditional sequential sampling model, the onset of the process within the task is unclear, as is the number of sampling processes. RACE/A provides a theoretical basis for estimating the onset of sequential sampling processes during task execution and allows for easy modeling of multiple sequential sampling processes within a task. (shrink)

In the current paper, we articulate a theory to explain the phenomenology of mental effort. The theory provides a working definition of mental effort, explains in what sense mental effort is a limited resource, and specifies the factors that determine whether or not mental effort is experienced as aversive. The core of our theory is the conjecture that the sense of effort is the output of a cost-benefit analysis. This cost-benefit analysis employs heuristics to weigh the current and anticipated costs (...) of mental effort for a particular activity against the anticipated benefits. This provides a basis for spelling out testable predictions to structure future research on the phenomenology of mental effort. (shrink)

This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A variety of qualitative data (...) can be accounted for by the approach. A computational model, CLARION, is then used to simulate a range of quantitative data. The results demonstrate the plausibility of the model, which provides a new perspective on skill learning. (PsycINFO Database Record (c) 2012 APA, all rights reserved). (shrink)

This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...) tasks, (c) the redundant representation of explicit and implicit knowledge, (d) the integration of the results of explicit and implicit processing, and (e) the iterative (and possibly bidirectional) processing. A computational implementation of the theory is developed based on the CLARION cognitive architecture and applied to the simulation of relevant human data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related.. (shrink)

The brain networks underlying human multiple-cue judgment, the judgment of a continuous criterion based on multiple cues, have been examined in a few recent studies, and the ventral precuneus has been found to be a key region. Specifically, activation differences in ventral precuneus (as measured with functional magnetic resonance imaging, fMRI) has been linked to an exemplar-based judgment process, where judgments are based on memory for previous similar cases. What aspects of exemplar-based judgment ventral precuneus supports is however poorly understood. (...) Ventral precuneus is a brain region important for various episodic memory processes, where increased engagement of this region together with the ventromedial prefrontal cortex (vmPFC) and the medial temporal lobes (MTL) during learning have been linked to retrieval success. Several alternatives are plausible, for example that reduced brain activity in ventral precuneus during learning to make exemplar-based judgments could reflect reduced needs for visuo-spatial attention as a function of learning to master the task. The present study used fMRI during a multiple-cue judgment task to gain novel neurocognitive evidence informative for the link between learning-related activity changes in ventral precuneus and exemplar-based judgment. Participants (N = 27) spontaneously learned to make judgments during fMRI, in a multiple-cue judgment task specifically designed to induce exemplar-based processing. Contrasting brain activity during late learning to early learning indeed revealed higher activity in ventral precuneus, the bilateral MTL and the vmPFC. Activity in the ventral precuneus and the vmPFC was found to parametrically increase between each judgment event, and activity levels in the ventral precuneus predicted performance after learning. These results are interpreted such that the ventral precuneus supports the aspects of exemplar-based processes that are related to episodic memory, tentatively by building and retrieving memory representations for judgment. (shrink)

In three experiments, each of a set colour-unrelated distracting words was presented most often in a particular target print colour . In Experiment 1, half of the participants were told the word-colour contingencies in advance and half were not . The instructed group showed a larger learning effect. This instruction effect was fully explained by increases in subjective awareness with instruction. In Experiment 2, contingency instructions were again given, but no contingencies were actually present. Although many participants claimed to be (...) aware of these contingencies, they did not produce an instructed contingency effect. In Experiment 3, half of the participants were given contingency instructions that did not correspond to the correct contingencies. Participants with these false instructions learned the actual contingencies worse than controls. Collectively, our results suggest that conscious contingency knowledge might play a moderating role in the strength of implicit learning. (shrink)

Recent studies show that when words are correlated with the colours they are printed in , colour identification is faster when the word is presented in its correlated colour than in an uncorrelated colour . The present series of experiments explored the possible mechanisms involved in this colour-word contingency learning effect. Experiment 1 demonstrated that the effect is already present after 18 learning trials. During subsequent unlearning, the effect extinguished equally rapidly. Two reanalyses of data from Schmidt, Crump, Cheesman, and (...) Besner ruled out an account of the effect in terms of stimulus repetitions. Experiment 2 demonstrated that participants who carry a memory load do not show a contingency effect, supporting the hypothesis that limited-capacity resources are required for learning. Experiment 3 demonstrated that memory resources are required for both storage and retrieval processes. (shrink)

Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to mechanisms that proceduralize knowledge into more efficient forms, skill acquisition requires tight integration of newly acquired knowledge and previously learned knowledge. Skill acquisition also benefits from reuse of existing knowledge across disparate (...) task domains, relying on indexicals to reference and share necessary information across knowledge components. To demonstrate these ideas, the article proposes a computational model of skill acquisition from instructions focused on integration and reuse, and applies this model to account for behavior across seven task domains. (shrink)

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations (...) of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

The ability to imagine objects undergoing rotation (mental rotation) improves markedly with practice, but an explanation of this plasticity remains controversial. Some researchers propose that practice speeds up the rate of a general-purpose rotation algorithm. Others maintain that performance improvements arise through the adoption of a new cognitive strategy—repeated exposure leads to rapid retrieval from memory of the required response to familiar mental rotation stimuli. In two experiments we provide support for an integrated explanation of practice effects in mental rotation (...) by combining behavioral and EEG measures in a way that provides more rigorous inference than is available from either measure alone. Before practice, participants displayed two well-established signatures of mental rotation: Both response time and EEG negativity increased linearly with rotation angle. After extensive practice with a small set of stimuli, both signatures of mental rotation had all but disappeared. In contrast, after the same amount of practice with a much larger set both signatures remained, even though performance improved markedly. Taken together, these results constitute a reversed association, which cannot arise from variation in a single cause, and so they provide compelling evidence for the existence of two routes to expertise in mental rotation. We also found novel evidence that practice with the large but not the small stimulus set increased the magnitude of an early visual evoked potential, suggesting increased rotation speed is enabled by improved efficiency in extracting three-dimensional information from two-dimensional stimuli. (shrink)

A computational modeling approach was used to test one possible explanation for the limited capacity of the subitizing phenomenon. Most existing models of this phenomenon associate the subitizing span with an assumed structural limitation of the human information processing system. In contrast, we show how this limit might emerge as the combinatorics of the space of enumeration problems interacts with the human cognitive architecture in the context of an enumeration task. Subitizing‐like behavior was generated in two different models of enumeration, (...) one based on the ACT‐R cognitive architecture and the other based on the principles of parallel distributed processing (PDP). Our results provide good qualitative fits to results obtained in a variety of empirical studies. (shrink)