Most of us are familiar with the phenomenology of mental effort accompanying cognitively demanding tasks, like focusing on the next chess move or performing lengthy mental arithmetic. In this paper, I argue that phenomenology of mental effort poses a novel counterexample to tracking intentionalism, the view that phenomenal consciousness is a matter of tracking features of one’s environment in a certain way. I argue that an increase in the phenomenology of mental effort does not accompany a change in any of (...) the following candidate representational contents: representation of externally presented features, e.g. brightness, contrast, and so on representation of task difficulty, representation of the possibility of error, representation of trying to achieve some state of affairs, representation of bodily changes like muscle tension, or representation of change in cognitive resource availability and lost opportunity cost. While tracking intentionalism about some phenomenal experiences like pains might obtain, it does not seem to obtain for all phenomenal experiences. This puts the intentionalist into an uncomfortable position of trying to explain why some phenomenal experiences have representational content and not others. Since many believe that tracking intentionalism or something like it provides the best chance of naturalizing consciousness, these arguments deserve detailed consideration. (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 commentary, I focus on the difference between processes and representations and how this distinction relates to the question of what is controlled. Despite some views that task switching is a prototypical control process, the analysis concludes that task switching depends on the task goal representation and that control processes are there to prevent goal representations from disintegrating. Over time, these processes become obsolete, leaving behind a representation that automatically controls task performance. The distinction between processes and representations relates (...) to practice effects and automaticity and sheds light on what is meant by the phrase “automatic control.”. (shrink)

A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together (...) with a range of empirical phenomena related to human sequential behaviour. It is argued that the empirical phenomena pose difficulties for most sequencing mechanisms, but that converging evidence from behavioural flexibility, error data arising from when the system is stressed or when it is damaged following brain injury, and between-trial effects in reaction time tasks, point to a hybrid symbolic activation-based mechanism for the generation and regulation of sequential behaviour. Some implications of this view for the nature of mental computation are highlighted. (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)

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

Automatic imitation or “imitative compatibility” is thought to be mediated by the mirror neuron system and to be a laboratory model of the motor mimicry that occurs spontaneously in naturalistic social interaction. Imitative compatibility and spatial compatibility effects are known to depend on different stimulus dimensions—body movement topography and relative spatial position. However, it is not yet clear whether these two types of stimulus–response compatibility effect are mediated by the same or different cognitive processes. We present an interactive activation model (...) of imitative and spatial compatibility, based on a dual-route architecture, which substantiates the view they are mediated by processes of the same kind. The model, which is in many ways a standard application of the interactive activation approach, simulates all key results of a recent study by Catmur and Heyes (2011). Specifically, it captures the difference in the relative size of imitative and spatial compatibility effects; the lack of interaction when the imperative and irrelevant stimuli are presented simultaneously; the relative speed of responses in a quintile analysis when the imperative and irrelevant stimuli are presented simultaneously; and the different time courses of the compatibility effects when the imperative and irrelevant stimuli are presented asynchronously. (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)

The Stroop effect is a well-documented phenomenon, demonstrating both interference and facilitation effects. Many versions of the Stroop task were created, according to the purposes of its applications, varying in numerous aspects. While many versions are developed to investigate the mechanisms of the effect itself, the Stroop effect is also considered a general measure of attention, inhibitory control, and executive functions. In this paper, we implement “eStroop”: a new digital version based on verbal responses, measuring the main processes involved in (...) the traditional effect. eStroop features four categories of stimuli in four different colors: geometrical shapes, neutral words, congruent words, and incongruent words. The results of the administration to 307 University students confirm the Stroop effect and offer baseline data for future research and clinical testing. Direct comparisons with other recent versions of the task are discussed, offering insights into differences and similarities between different task variables. (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)

Cognitive control is not only componential, but those components may interact in complicated ways in the service of cognitive control tasks. This complexity poses a challenge for developing an ontological description, because the mapping may not be direct between our task descriptions and true component differences reflected in indicators. To illustrate this point, I discuss two examples: (a) the relationship between adaptive gating and working memory and (b) the recent evidence for a control hierarchy. From these examples, I argue that (...) an ontological program must simultaneously seek to identify component processes and their interactions within a broader processing architecture. (shrink)

Explicatures are not cancellable. Theoretical considerations.

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

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 thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed control (...) with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)