Preparing words in speech production is normally a fast and accurate process. We generate them two or three per second in fluent conversation; and overtly naming a clear picture of an object can easily be initiated within 600 msec after picture onset. The underlying process, however, is exceedingly complex. The theory reviewed in this target article analyzes this process as staged and feedforward. After a first stage of conceptual preparation, word generation proceeds through lexical selection, morphological and phonological encoding, phonetic (...) encoding, and articulation itself. In addition, the speaker exerts some degree of output control, by monitoring of self-produced internal and overt speech. The core of the theory, ranging from lexical selection to the initiation of phonetic encoding, is captured in a computational model, called WEAVER++. Both the theory and the computational model have been developed in interaction with reaction time experiments, particularly in picture naming or related word production paradigms, with the aim of accounting for the real-time processing in normal word production. A comprehensive review of theory, model, and experiments is presented. The model can handle some of the main observations in the domain of speech errors (the major empirical domain for most other theories of lexical access), and the theory opens new ways of approaching the cerebral organization of speech production by way of high-temporal-resolution imaging. (shrink)

We sometimes fail unwittingly to do things that we ought to do. And we are, from time to time, culpable for these unwitting omissions. We provide an outline of a theory of responsibility for unwitting omissions. We emphasize two distinctive ideas: (i) many unwitting omissions can be understood as failures of appropriate vigilance, and; (ii) the sort of self-control implicated in these failures of appropriate vigilance is valuable. We argue that the norms that govern vigilance and the value of self-control (...) explain culpability for unwitting omissions. (shrink)

How might attention intersect with normative issues and the psychology surrounding them? I provide an empirically grounded framework integrating three attentional phenomena: salience, vigilance (or broadly attunement) and attentional character. Using this frame, I review recent philosophical work on attention and norms. -/- Section 1 establishes a common ground conception of attention no more controversial than the established experimental paradigms for attention. This conception explicates the concept of a bias, which explains core features of action and attention, one that intersects (...) biological, psychological and philosophical concerns. I emphasize historical biases associated with learning and experience. Section 2 presents an analysis of automaticity and control, concepts needed to fully characterize action. Historical biases are revealed as automatic. Specifically, the automatization of attention is central to acquiring skills and excellence in light of normative standards for a practice. Section 3 argues that salience involves the deployment of attention, while Section 4 characterizes vigilance not merely as a disposition but as an active orientation to attend. Vigilance is one type of attunement, and the set of attunements constitutes the agent’s varied orientations to deploy attention, part of their attentional character. As discussed in Section 5, shaping this character is a goal of a normatively sensitive upbringing where appropriate attention is automatized through proper practice. Section 6 examines a common epistemic bias in academia and subsequent attempts to debias. I conclude with an example of acquired epistemic skill to give hope that attentional excellence is achievable. (shrink)

What is the primary function of consciousness in the nervous system? The answer to this question remains enigmatic, not so much because of a lack of relevant data, but because of the lack of a conceptual framework with which to interpret the data. To this end, we have developed Passive Frame Theory, an internally coherent framework that, from an action-based perspective, synthesizes empirically supported hypotheses from diverse fields of investigation. The theory proposes that the primary function of consciousness is well-circumscribed, (...) serving the 'somatic nervous system[. For this system, consciousness serves as a frame that constrains and directs skeletal muscle output, thereby yielding adaptive behavior. The mechanism by which consciousness achieves this is more counterintuitive, passive, and “low level” than the kinds of functions that theorists have previously attributed to consciousness. Passive frame theory begins to illuminate (a) what consciousness contributes to nervous function, (b) how consciousness achieves this function, and (c) the neuroanatomical substrates of conscious processes. Our untraditional, action-based perspective focuses on olfaction instead of on vision and is 'descriptive' (describing the products of nature as they evolved to be) rather than 'normative' (construing processes in terms of how they should function). Passive frame theory begins to isolate the neuroanatomical, cognitive-mechanistic, and representational (e.g., conscious contents) processes associated with consciousness. (shrink)

Complete URL to this document: http://srsc.ulb.ac.be/axcWWW/93-Principles.html.

Topics in Cognitive Science, Volume 13, Issue 1, Page 63-78, January 2021.

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)

Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on cognitive control with new energy and new ideas. On the occasion of the books' anniversary, we review computational modeling in the study of cognitive (...) control, with a focus on the influence that the PDP approach has brought to bear in this area. Rather than providing a comprehensive review, we offer a framework for thinking about past and future modeling efforts in this domain. We define control in terms of the optimal parameterization of task processing. From this vantage point, the development of control systems in the brain can be seen as responding to the structure of naturalistic tasks, through the filter of the brain systems with which control directly interfaces. This perspective lays open a set of fascinating but difficult research questions, which together define an important frontier for future computational research. (shrink)

We propose the Selfish Goal model, which holds that a person's behavior is driven by psychological processes called goals that guide his or her behavior, at times in contradictory directions. Goals can operate both consciously and unconsciously, and when activated they can trigger downstream effects on a person's information processing and behavioral possibilities that promote only the attainment of goal end-states (and not necessarily the overall interests of the individual). Hence, goals influence a person as if the goals themselves were (...) selfish and interested only in their own completion. We argue that there is an evolutionary basis to believe that conscious goals evolved from unconscious and selfish forms of pursuit. This theoretical framework predicts the existence of unconscious goal processes capable of guiding behavior in the absence of conscious awareness and control (theautomaticity principle), the ability of the most motivating or active goal to constrain a person's information processing and behavior toward successful completion of that goal (thereconfiguration principle), structural similarities between conscious and unconscious goal pursuit (thesimilarity principle), and goal influences that produce apparent inconsistencies or counterintuitive behaviors in a person's behavior extended over time (theinconsistency principle). Thus, we argue that a person's behaviors are indirectly selected at the goal level but expressed (and comprehended) at the individual level. (shrink)

Resource rationality may explain suboptimal patterns of reasoning; but what of “anti-Bayesian” effects where the mind updates in a direction opposite the one it should? We present two phenomena — belief polarization and the size-weight illusion — that are not obviously explained by performance- or resource-based constraints, nor by the authors’ brief discussion of reference repulsion. Can resource rationality accommodate them?

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary (...) developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called “deep networks”—systems that build on key ideas presented in the PDP volumes. (shrink)

The contents of our conscious mind can seem unpredictable, whimsical, and free from external control. When instructed to attend to a stimulus in a work setting, for example, one might find oneself thinking about household chores. Conscious content thus appears different in nature from reflex action. Under the appropriate conditions, reflexes occur predictably, reliably, and via external control. Despite these intuitions, theorists have proposed that, under certain conditions, conscious content resembles reflexes and arises reliably via external control. We introduce the (...) Reflexive Imagery Task, a paradigm in which, as a function of external control, conscious content is triggered reliably and unintentionally: When instructed to not subvocalize the name of a stimulus object, participants reliably failed to suppress the set-related imagery. This stimulus-elicited content is considered ‘high-level’ content and, in terms of stages of processing, occurs late in the processing stream. We discuss the implications of this paradigm for consciousness research. (shrink)

The medial prefrontal cortex (mPFC) has been the subject of intense interest as a locus of cognitive control. Several computational models have been proposed to account for a range of effects, including error detection, conflict monitoring, error likelihood prediction, and numerous other effects observed with single-unit neurophysiology, fMRI, and lesion studies. Here, we review the state of computational models of cognitive control and offer a new theoretical synthesis of the mPFC as signaling response–outcome predictions. This new synthesis has two interacting (...) components. The first component learns to predict the various possible outcomes of a planned action, and the second component detects discrepancies between the actual and intended responses; the detected discrepancies in turn update the outcome predictions. This single construct is consistent with a wide array of performance monitoring effects in mPFC and suggests a unifying account of the cognitive role of medial PFC in performance monitoring. (shrink)

Theories of language production propose that utterances are constructed by a mechanism that separates linguistic content from linguistic structure, Linguistic content is retrieved from the mental lexicon, and is then inserted into slots in linguistic structures or frames. Support for this kind of model at the phonological level comes from patterns of phonological speech errors. W present an alternative account of these patterns using a connectionist or parallel distributed proceesing (PDP) model that learns to produce sequences of phonological features. The (...) model's errors exhibit some of the properties of human speech errors, specifically, properties that have been attributed to the action of phonological rules, frames, or other structural generalizations. (shrink)

In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...) (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed-forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. (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)

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)

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

When we read a list of words, are we doing something, or is it something that just happens to us? On the one hand, according to intention-for-action theories, reading can be active only if we do it intentionally, meaning that the action is caused and sustained by the agent’s intention. Many cases of reading seem to be intentional: consider, for instance, when a person is reading a novel, a newspaper article, or an academic paper. Yet, reading often seems to be (...) something that passively happens to us. It is sufficient that a word appears in front of us to make us read it. Numerous studies on the Stroop task – a well-known experimental set-up in the cognitive sciences – make clear that reading is unavoidable, suggesting that reading takes place regardless of the agent’s intention. This tension constitutes the reading puzzle. I argue that if intention is necessary for a process to be active, then intention-for-action theories fail to account for such a distinctive human activity as reading. I conclude that reading represents a real challenge to the intention-for-action theories and shows that what an agent can actively do should not be limited to behaviors that involve intentions. (shrink)