Consciousness: converging insights from connectionist modeling and neuroscience

Over the past decade, many findings in cognitive neuroscience have resulted in the view that selective attention, working memory and cognitive control involve competition between widely distributed representations. This competition is biased by top-down projections (notably from prefrontal cortex), which can selectively enhance some representations over others. This view has now been implemented in several connectionist models. In this review, we emphasize the relevance of these models to understanding consciousness. Interestingly, the models we review have striking similarities to others directly aimed at implementing 'global workspace theory'. All of these models embody a fundamental principle that has been used in many connectionist models over the past twenty years: global constraint satisfaction.     

Contribution of lexico-semantic processes to verbal short-term memory tasks: a PET activation study

Recent studies have demonstrated the intervention of long-term memory processes in verbal STM tasks and several cognitive models have been proposed to explain these effects. A PET study was performed in order to determine whether supplementary cerebral areas are involved when subjects have to execute short-term memory tasks for items having representations in long-term memory (in comparison to items without such representations: words vs non-words). Results indicate that verbal STM for words specifically involves the left middle temporal gyrus (BA 21) and temporo-parietal junction (BA 39). These areas can be associated with lexical and semantic processes. These results are in agreement with cognitive models that postulate the simultaneous influence of lexical and semantic long-term representations on verbal STM processes and/or a lexico-semantic buffer.     

Feature importance in feature generation and typicality rating

Many theoretical models of cognition are based on the assumption that cognitive processes and representations are hierarchically structured. The issue of whether these hierarchies are mere constructs or conceptual tools, or whether they have psychological and neurological reality, is addressed. Theories across a range of cognitive domains are reviewed and four kinds of evidence are considered: behavioural, neuropsychological, ontogenetic, and logical. Logical constraints are identified in relation to operating principles of control, access, economy and analogy. The general characteristics of hierarchical structures and their advantages and disadvantages are discussed.     

Cognitive Biases in Visual Pilots' Weather‐Related Decision Making

Flights into deteriorating weather conditions are a significant cause of fatalities in general aviation accidents. This study investigated whether three common cognitive heuristics (anchoring and adjustment, confirmation, outcome) could lead to cognitive biases that might adversely affect pilots' weather‐related decision making. Study 1 found that weather reports obtained before a flight affected how pilots interpreted weather cues during flights (anchoring and adjustment). Study 2 found no evidence that pilots favoured disconfirmatory evidence over confirmatory evidence when deciding which environmental cues were most useful in deciding whether to continue a flight (confirmation). Study 3 found that pilots interpreted the decisions of pilots who flew into deteriorating weather conditions more favourably when the outcome was positive than when it was negative (outcome). These findings suggest that use of these three cognitive heuristics may lead to pilots continuing to fly into deteriorating weather conditions when the safer option is to divert or turn back. Copyright © 2016 John Wiley & Sons, Ltd.     

Mental models of line drawings.

Mental models are internal representations of world structure, used to accomplish cognitive tasks. I postulate specific representations (of objects and images) and associated context (of world and view) for mental models of line drawings. I then analyze the representations and context to predict specific perceptual modes, including the relative strengths of these modes. The predicted modes are supported by a well-known example [from Rock, 1983 The Logic of Perception (Cambridge, MA: MIT Press)] where object perception changes with image orientation.     

Representations and Cognitive Explanations: Assessing the Dynamicist's Challenge in Cognitive Science

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations.     

In defense of representation

The computational paradigm, which has dominated psychology and artificial intelligence since the cognitive revolution, has been a source of intense debate. Recently, several cognitive scientists have argued against this paradigm, not by objecting to computation, but rather by objecting to the notion of representation. Our analysis of these objections reveals that it is not the notion of representation per se that is causing the problem, but rather specific properties of representations as they are used in various psychological theories. Our analysis suggests that all theorists accept the idea that cognitive processing involves internal information-carrying states that mediate cognitive processing. These mediating states are a superordinate category of representations. We discuss five properties that can be added to mediating states and examine their importance in various cognitive models. Finally, three methodological lessons are drawn from our analysis and discussion.     

Representations gone mental

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation.     

Extensions of the Johnson-Neyman Technique to Linear Models With Curvilinear Effects: Derivations and Analytical Tools

The past decade has witnessed renewed interest in the use of the Johnson-Neyman (J-N) technique for calculating the regions of significance for the simple slope of a focal predictor on an outcome variable across the range of a second, continuous independent variable. Although tools have been developed to apply this technique to probe 2- and 3-way interactions in several types of linear models, this method has not been extended to include quadratic terms or more complicated models involving quadratic terms and interactions. Curvilinear relations of this type are incorporated in several theories in the social sciences. This article extends the J-N method to such linear models along with presenting freely available online tools that implement this technique as well as the traditional pick-a-point approach. Algebraic and graphical representations of the proposed J-N extension are provided. An example is presented to illustrate the use of these tools and the interpretation of findings. Issues of reliability as well as “spurious moderator” effects are discussed along with recommendations for future research.     

Getting from neuron to checkmark: models and methods in cognitive survey research

Since the 1980s much work has been done in the field of Cognitive Survey Research. In an interdisciplinary endeavour, survey methodologists and cognitive psychologists (as well as social psychologists and linguists) have worked to unravel the cognitive processes underlying survey responses: to improve survey measurement, but also to obtain fundamental insight into the process of question answering, the nature of attitudes, the functioning of human memory, etc. Yet, despite the amount of work that has been done, less progress has been made than was deemed possible. This paper suggests ways in which to develop cognitive theories that may help to obtain an integrated understanding of question answering in surveys. One way to build better theories is to focus on model construction. Different types of cognitive models are discussed that can be used to model question answering. Second, a larger variety of methods from the cognitive toolbox can be used to further develop and test these models. An overview is given of the various tools available to researchers of cognitive aspects of survey research, with a special focus on newer methods from cognitive neuroscience. To connect different tools and methods into an integrative theory of question answering, the idea of hierarchical modelling is proposed. Copyright © 2007 John Wiley & Sons, Ltd.     

Implicit Representations of Political Leaders: A Multidimensional Analysis

Implicit cognitive representations of 20 salient political personalities (10 domestic, 10 foreign) were studied in two samples (N₁= 121; N₂= 129) over a 1-year interval. The aim of the study was to elaborate multidimensional models of voting preference by (a) representing the cognitive dimensions used by subjects in perceiving politicians, (b) contrasting perceptions of domestic and foreign leaders, (c) evaluating the effects of time, and (d) assessing individual differences between subjects on political perception. Judgments were analyzed by Carroll and Chang's (1970) Individual Differences Multidimensional Scaling (INDSCAL) procedure. Results showed that three implicit dimensions, evaluation, ideology , and leadership qualities, underlied perceptions of both domestic and foreign politicians. There were greater changes in perceptions of foreign and left-of-center leaders over the year than in judgments of domestic and right-of-center leaders; and individual differences such as attitudes, personality, and cognitive style were also significantly related to cognitive representations of politicians. Results were discussed in terms of their implications for predictive models of voting behavior, and the use of these methods in large-scale political surveys and polls is suggested.     

Theories of spatial representations and reference frames: What can configuration errors tell us?

The issue of reference frame is central to theories of spatial representations. Various classifications have been made for different types of reference frames, along with prototypical research paradigms to distinguish between them. This article focuses on the configuration error paradigm proposed by Wang and Spelke (Cognition 77:215-250, 2000) that has been used to examine the nature of the spatial representations underlying object localization during self-movement. Three basic models of spatial memory and spatial updating are discussed, as well as the assumptions behind the configuration error paradigm, to distinguish between static representations, such as the traditional allocentric cognitive map and the egocentric snapshots, and dynamic representations, such as the egocentric updating system. Recent experimental findings are reexamined and shown to be consistent with multiple models, among which the egocentric-updating-and-reload model with an enduring egocentric component provides the simplest interpretations.     

Why ‘scaffolding’ is the wrong metaphor: the cognitive usefulness of mathematical representations

The metaphor of scaffolding has become current in discussions of the cognitive help we get from artefacts, environmental affordances and each other. Consideration of mathematical tools and representations indicates that in these cases at least (and plausibly for others), scaffolding is the wrong picture, because scaffolding in good order is immobile, temporary and crude. Mathematical representations can be manipulated, are not temporary structures to aid development, and are refined. Reflection on examples from elementary algebra indicates that Menary is on the right track with his ‘enculturation’ view of mathematical cognition. Moreover, these examples allow us to elaborate his remarks on the uniqueness of mathematical representations and their role in the emergence of new thoughts.

     

Beyond the exclusively propositional era

Contemporary epistemology has assumed that knowledge is represented in sentences or propositions. However, a variety of extensions and alternatives to this view have been proposed in other areas of investigation. We review some of these proposals, focusing on (1) Ryle's notion of knowing how and Hanson's and Kuhn's accounts of theory-laden perception in science; (2) extensions of simple propositional representations in cognitive models and artificial intelligence; (3) the debate concerning imagistic versus propositional representations in cognitive psychology; (4) recent treatments of concepts and categorization which reject the notion of necessary and sufficient conditions; and (5) parallel distributed processing (connectionist) models of cognition. This last development is especially promising in providing a flexible, powerful means of representing information nonpropositionally, and carrying out at least simple forms of inference without rules. Central to several of the proposals is the notion that much of human cognition might consist in pattern recognition rather than manipulation of rules and propositions.The preparation of this article was supported in part by National Institutes of Health Grants No. NICHD-19265 and NICHD-06016. We would like to thank Rita Anderson, David Blumenfeld, Robert McCauley, and Patricia Siple for helpful discussions on points in this paper.     

Processes of similarity judgment

Similarity underlies fundamental cognitive capabilities such as memory, categorization, decision making, problem solving, and reasoning. Although recent approaches to similarity appreciate the structure of mental representations, they differ in the processes posited to operate over these representations. We present an experiment that differentiates among extant structural accounts of similarity in their ability to account for patterns of similarity ratings. These data pose a challenge for transformation-based models and all but one mapping-based model, the Similarity as Interactive Activation and Mapping (SIAM) model of similarity.     

Evaluating the random representation assumption of lexical semantics in cognitive models

A common assumption implicit in cognitive models is that lexical semantics can be approximated by using randomly generated representations to stand in for word meaning. However, the use of random representations contains the hidden assumption that semantic similarity is symmetrically distributed across randomly selected words or between instances within a semantic category. We evaluated this assumption by computing similarity distributions for randomly selected words from a number of well-known semantic measures and comparing them with the distributions from random representations commonly used in cognitive models. The similarity distributions from all semantic measures were positively skewed compared with the symmetric normal distributions assumed by random representations. We discuss potential consequences that this false assumption may have for conclusions drawn from process models that use random representations.     

Building Cognition: The Construction of Computational Representations for Scientific Discovery

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model‐building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account.     

Body representations and cognitive ontology: Drawing the boundaries of the body image

The distinction between body image and body schema has been incredibly influential in cognitive neuroscience. Recently, researchers have begun to speculate about the relationship between these representations (Gadsby, 2017, 2018; Pitron & de Vignemont, 2017; Pitron et al., 2018). Within this emerging literature, Pitron et al. (2018) proposed that the long-term body image and long-term body schema co-construct one another, through a process of reciprocal interaction. In proposing this model, they make two assumptions: that the long-term body image incorporates the spatial characteristics of tools, and that it is distorted in the case of Alice in wonderland syndrome. Here, I challenge these assumptions, with a closer examination of what the term “long-term body image” refers to. In doing so, I draw out some important taxonomic principles for research into body representation.     

Very short-term conceptual memory

Short-term memory for conceptual information is largely missing from current models of short-term memory. Several phenomena are discussed that give evidence for very brief conceptual representations of stimuli. Although these fleeting representations do not surface readily with many of the standard methods for studying and testing short-term memory, I argue that they are fundamental to cognitive processing and to the form that long-term memory takes.     

Animal Cognition: The Bridge BetweenAnimal Learning and Human Cognition

Carefully controlled research with animals has demonstrated cognitive capacities for which traditional theories of associative learning cannot account. One example is the symbolic representation of stimuli. If two arbitrary stimuli are associated with a third event, an emergent relation can be shown to develop. A second example is the ability of animals to plan ahead, and to choose whether to plan ahead or not. Although animals have often been used to model drug effects in humans, these models have rarely been used to examine the effects of drugs on cognitive functioning. Furthermore, examination of the effects of drugs on the cognitive behavior of animals may help to identify the nature of the representations underlying the cognition.