According to the attentional resources account, mind wandering (or “task-unrelated thought”) is thought to compete with a focal task for attentional resources. Here, we tested two key predictions of this account: First, that mind wandering should not interfere with performance on a task that does not require attentional resources; second, that as task requirements become automatized, performance should improve and depth of mind wandering should increase. Here, we used a serial reaction time task with implicit- and explicit-learning groups to test (...) these predictions. Providing novel evidence for the attentional resource account’s first prediction, results indicated that depth of mind wandering was negatively associated with learning in the explicit, but not the implicit, group, indicating that mind wandering is associated with impaired explicit, but not implicit, learning. Corroborating the attention resource account’s second prediction, we also found that, overall, performance improved while at the same time depth of mind wandering increased. From an implicit learning perspective, these results are consistent with the claim that explicit learning is impaired under attentional load, but implicit learning is not. (shrink)

The review first discusses componential explanations of automaticity, which specify non/automaticity features (e.g., un/controlled, un/conscious, non/efficient, fast/slow) and their interrelations. Reframing these features as factors that influence processes (e.g., goals, attention, and time) broadens the range of factors that can be considered (e.g., adding stimulus intensity and representational quality). The evidence reviewed challenges the view of a perfect coherence among goals, attention, and consciousness, and supports the alternative view that (a) these and other factors influence the quality of representations in (...) an additive way (e.g., little time can be compensated by extra attention or extra stimulus intensity) and that (b) a first threshold of this quality is required for unconscious processing and a second threshold for conscious processing. The review closes with a discussion of causal explanations of automaticity, which specify factors involved in automatization such as repetition and complexity, and a discussion of mechanistic explanations, which specify the low-level processes underlying automatization. (shrink)

The current status of Beilock and Carr's "execution focus" theory of choking under pressure in performance of a sensorimotor skill is reviewed and assessed, mainly from the perspective of cognitive psychology, and put into the context of a wider range of issues, attempting to take philosophical analysis into account. These issues include other kinds of skills, pre-performance practice, post-performance evaluation and repair, and integrating new and creative achievements into repertoires of heavily practiced routines. The focus is on variation in the (...) demand for reflection versus automaticity across the full gamut of learning and experience, not just game-time performance. Though automaticity remains important and there are many circumstances in which being "in the zone" is good whereas “execution focus” can do harm, it appears that reflective action deserves just as much a place at the performance table as does unreflective action. (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)

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)

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)

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)

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)

Explicit and implicit learning have been attributed to different learning processes that create different types of knowledge structures. Consistent with that claim, our study provides evidence that people integrate stimulus events differently when consciously aware versus unaware of the relationship between the events. In a first, acquisition phase participants sorted words into two categories , which were fully predicted by task-irrelevant primes—the labels of two other, semantically unrelated categories . In a second, test phase participants performed a lexical decision task, (...) in which all word stimuli stemmed from the previous prime categories and the primes were the labels of the previous target categories . Reliable priming effects in the second phase demonstrated that bidirectional associations between the respective categories had been formed in the acquisition phase , but these effects were found only in participants that were unaware of the relationship between the categories! We suggest that unconscious, implicit learning of event relationships results in the rather unsophisticated integration of the underlying event representations, whereas explicit learning takes the meaning of the order of the events into account, and thus creates unidirectional associations. (shrink)

Mental imagery (varieties of which are sometimes colloquially refered to as “visualizing,” “seeing in the mind's eye,” “hearing in the head,” “imagining the feel of,” etc.) is quasi-perceptual experience; it resembles perceptual experience, but occurs in the absence of the appropriate external stimuli. It is also generally understood to bear intentionality (i.e., mental images are always images of something or other), and thereby to function as a form of mental representation. Traditionally, visual mental imagery, the most discussed variety, was thought (...) to be caused by the presence of picturelike representations (mental images) in the mind, soul, or brain, but this is no longer universally accepted. (shrink)

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)

What is Consciousness For? Lee Pierson and Monroe Trout Copyright © 2005 Abstract: The answer to the title question is, in a word, volition. Our hypothesis is that the ultimate adaptive function of consciousness is to make volitional movement possible. All conscious processes exist to subserve that ultimate function. Thus, we believe that all conscious organisms possess at least some volitional capability. Consciousness makes volitional attention possible; volitional attention, in turn, makes volitional movement possible. There is, as far as we (...) know, no valid theoretical argument that consciousness is needed for any function other than volitional movement and no convincing empirical evidence that consciousness performs any other ultimate function. Consciousness, via volitional action, increases the likelihood that an organism will direct its attention, and ultimately its movements, to whatever is most important for its survival and reproduction. (shrink)

This compilation of references includes all references for the knowledge-how chapters included in Bengson & Moffett's edited volume. The volume and the compilation of references may serve as a good starting point for people who are unfamiliar with the philosophical literature on knowledge-how.

Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task,m×ntask) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative ofexternally-specifiedsequencing—motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks (...) that involveinternally-guidedsequencing—where the sequence of motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task (GST), which required navigating (by executing sequential keypresses) a 5 × 5 grid from start to goal (SG) position while using a particular key-mapping (KM) among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments—Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning. (shrink)

Usage-based linguists and psychologists have produced a large body of empirical results suggesting that linguistic structure is derived from language use. However, while researchers agree that these results characterize grammar as an emergent phenomenon, there is no consensus among usage-based scholars as to how the various results can be explained and integrated into an explicit theory or model. Building on network theory, the current paper outlines a structured network approach to the study of grammar in which the core concepts of (...) syntax are analyzed by a set of relations that specify associations between different aspects of a speaker’s linguistic knowledge. These associations are shaped by domain-general processes that can give rise to new structures and meanings in language acquisition and language change. Combining research from linguistics and psychology, the paper proposes specific network analyses for the following phenomena: argument structure, word classes, constituent structure, constructions and construction families, and grammatical categories such as voice, case and number. The article builds on data and analyses presented inDiessel (2019;The Grammar Network. How Linguistic Structure is Shaped by Language Use) but approaches the topic from a different perspective. (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)

Attention is often dichotomized into controlled vs. automatic processing, where controlled processing is slow, flexible, and intentional, and automatic processing is fast, inflexible, and unintentional. In contrast to this strict dichotomy, there is mounting evidence for context-specific processes that are engaged rapidly yet are also flexible. In the present study we extend this idea to the domain of implicit learning to examine whether flexibility in automatic processes can be implemented through the reliance on contextual features. Across three experiments we show (...) that participants can learn implicitly two complementary sequences that are associated with distinct contexts, and that transfer of learning when the two contexts are randomly intermixed depends on the distinctiveness of the two contexts. Our results point to the role of context-specific processes in the acquisition and expression of implicit sequence knowledge, and also suggest that episodic details can be represented in sequence knowledge. (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)

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)

Prominent models of attentional control assert a dichotomy between top-down and bottom-up control, with the former determined by current selection goals and the latter determined by physical salience. This theoretical dichotomy, however, fails to explain a growing number of cases in which neither current goals nor physical salience can account for strong selection biases. For example, equally salient stimuli associated with reward can capture attention, even when this contradicts current selection goals. Thus, although 'top-down' sources of bias are sometimes defined (...) as those that are not due to physical salience, this conception conflates distinct - and sometimes contradictory - sources of selection bias. We describe an alternative framework, in which past selection history is integrated with current goals and physical salience to shape an integrated priority map. (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.

Walker's target article proposes a refinement of the well known two-stage model of memory formation to explain the positive effects of sleep on consolidation. After a first stage in which a labile memory representation is formed, a further stabilisation of the memory trace takes place in the second stage, which is dependent on (REM) sleep. Walker has refined the latter stage into a stage in which a consolidation-based enhancement occurs. It is not completely clear what consolidation-based enhancement implies and how (...) it can be dissociated from a stage for memory-stabilisation. A more serious consideration, however, is whether a second stage in memory consolidation that is solely dependent on sleep, is really necessary. The classical, passive, interference theory is able to explain adequately the findings related to the effects of sleep and memory, and can lead perhaps better to an understanding of the highly variable data in this field. (shrink)

Uncertainty and affect are fundamental and interrelated aspects of the human condition. Uncertainty is often associated with negative affect, but in some circumstances it is associated with positive affect. In this paper, we review different explanations for the varying relationship between uncertainty and affect. We identify “mental simulation” as a key process that links uncertainty to affective states. We suggest that people have a propensity to simulate negative outcomes, which results in a propensity towards negative affective responses to uncertainty. We (...) also propose the existence of several important moderators of this process, including context and individual differences such as uncertainty tolerance, as well as emotion regulation strategies. Finally, we highlight important knowledge gaps and promising areas for future research, both empirical and conceptual, to further elucidate the relationship between uncertainty and affect. (shrink)