Emergent representations, interaction theory and the cognitive force of metaphor

We focus here on the problem of how new representations emerge through a cognitive agent's interaction with the environment. We address this problem within a framework where representation-building mechanisms operate to create new representations against a backdrop of existing representations, and argue that novel and creative metaphors in any language provide a prime example of this phenomenon. Our approach to modeling the emergence of representation integrates ideas from three different streams of research: (1) the interaction theory of metaphor proposed by Black and others to account for the creativity of metaphors; (2) gestalt theories of perception; and (3) contemporary research supporting a constructivist and action-oriented view of perception and cognition. Combining these insights together, we outline our Gestalt projection model, and discuss three different ways in which new representations might emerge through metaphors. Finally, we propose that metaphor may be viewed as a cognitive force through which a cognitive agent asserts its creative spirit onto the environment.     

Cognition in rapists Theoretical patterns by typological breakdown

Cognitive processing has been implicated in sexual offending in a number of recent theoretical and empirical papers. Clinicians have emphasized the need to challenge the cognitive distortions that are often exhibited by sexual offenders, and they have incorporated cognitive restructuring components into treatment programs. However, until recently, the literature has lacked an integrative theoretical approach to cognition in sexual offenders. In addition, the use of generic classifications (i.e., rapist, child molester) in both theoretical and empirical work has obscured understanding of the role played by a number of etiological factors, including cognition. In this paper, we present a multifaceted approach to cognition in rapists. We begin with a brief overview of a conceptual framework of cognitive dimensions. Next, we consider the heterogeneity that characterizes rapists as a group and the problems this presents for research. We suggest that Knight and Prentky's typology may prove useful for dealing with these problems and, in the final section, we provide our conceptualization of the potential distorted cognitions for each of the subtypes within the typology.     

A computational cognitive framework of spatial memory in brains and robots

Computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. Here, we describe a computational framework for robotic architectures aiming to function in realistic environments, as well as to be cognitively plausible.We motivate and describe several mechanisms towards achieving this despite the sensory noise and spatial complexity inherent in the physical world. We tackle error accumulation during path integration by means of Bayesian localization, and loop closing with sequential gradient descent. Finally, we outline a method for structuring spatial representations using metric learning and clustering. Crucially, unlike the algorithms of traditional robotics, we show that these mechanisms can be implemented in neuronal or cognitive models.We briefly outline a concrete implementation of the proposed framework as part of the LIDA cognitive architecture, and argue that this kind of probabilistic framework is well-suited for use in cognitive robotic architectures aiming to combine spatial functionality and psychological plausibility.     

Rationality,perception, and the all-seeing eye

Seeing—perception and vision—is implicitly the fundamental building block of the literature on rationality and cognition. Herbert Simon and Daniel Kahneman’s arguments against the omniscience of economic agents—and the concept of bounded rationality—depend critically on a particular view of the nature of perception and vision. We propose that this framework of rationality merely replaces economic omniscience with perceptual omniscience. We show how the cognitive and social sciences feature a pervasive but problematic meta-assumption that is characterized by an “all-seeing eye.” We raise concerns about this assumption and discuss different ways in which the all-seeing eye manifests itself in existing research on (bounded) rationality. We first consider the centrality of vision and perception in Simon’s pioneering work. We then point to Kahneman’s work—particularly his article “Maps of Bounded Rationality”—to illustrate the pervasiveness of an all-seeing view of perception, as manifested in the extensive use of visual examples and illusions. Similar assumptions about perception can be found across a large literature in the cognitive sciences. The central problem is the present emphasis on inverse optics—the objective nature of objects and environments, e.g., size, contrast, and color. This framework ignores the nature of the organism and perceiver. We argue instead that reality is constructed and expressed, and we discuss the species-specificity of perception, as well as perception as a user interface. We draw on vision science as well as the arts to develop an alternative understanding of rationality in the cognitive and social sciences. We conclude with a discussion of the implications of our arguments for the rationality and decision-making literature in cognitive psychology and behavioral economics, along with suggesting some ways forward.     

生成认知：理论基础与实践走向

生成认知是具身认知思潮中的一个新取向。它主张认知是通过身体活动“生成的” (enacted)。认知的起点不是一个怎样精确表征世界的信息加工问题, 而是行动者在情境中怎样利用知觉来指导自己的行动。认知不是通过精确的心理表征“恢复”世界, 而是通过知觉引导的行动“生成”或“造就”一个自己的世界。认知是具身的行动, 认知结构形成于经常和反复出现的感觉运动模式, 与身体构造和身体活动具有深刻连续性。梅洛·庞蒂的身体现象学对生成认知具有深刻影响。同时, 詹姆斯、杜威等人的实用主义哲学对于实践行动的强调也深刻影响了生成认知。这种认知观强调了“行动”对心智的意义, 引发许多争议, 也促进了心理学研究范式的转变。     

Cognitive Evaluation of Machine Learning Agents

Advances in applying statistical Machine Learning (ML) led to several claims of human-level or near-human performance in tasks such as image classification & speech recognition. Such claims are unscientific primarily for two reasons, (1) They incorrectly enforce the notion that task-specific performance can be treated as manifestation of General Intelligence and (2) They are not verifiable as currently there is no set benchmark for measuring human-like cognition in a machine learning agent. Moreover, ML agent’s performance is influenced by knowledge ingested in it by its human designers. Therefore, agent’s performance may not necessarily reflect its true cognition. In this paper, we propose a framework that draws parallels from human cognition to measure machine’s cognition. Human cognitive learning is quite well studied in developmental psychology with frameworks and metrics in place to measure actual learning. To either believe or refute the claims of human-level performance of machine learning agent, we need scientific methodology to measure its cognition. Our framework formalizes incremental implementation of human-like cognitive processes in ML agents with an implicit goal to measure it. The framework offers guiding principles for measuring, (1) Task-specific machine cognition and (2) General machine cognition that spans across tasks. The framework also provides guidelines for building domain-specific task taxonomies to cognitively profile tasks. We demonstrate application of the framework with a case study where two ML agents that perform Vision and NLP tasks are cognitively evaluated.     

Visible embodiment: Gestures as simulated action

Spontaneous gestures that accompany speech are related to both verbal and spatial processes. We argue that gestures emerge from perceptual and motor simulations that underlie embodied language and mental imagery. We first review current thinking about embodied cognition, embodied language, and embodied mental imagery. We then provide evidence that gestures stem from spatial representations and mental images. We then propose the gestures-as-simulated-action framework to explain how gestures might arise from an embodied cognitive system. Finally, we compare this framework with other current models of gesture production, and we briefly outline predictions that derive from the framework.     

The role of robotic modelling in cognitive science

From the perspective of cognitive robotics, this paper presents a modern interpretation of Newell’s (1973) reasoning and suggestions for why and how cognitive psychologists should develop models of cognitive phenomena. We argue that the shortcomings of current cognitive modelling approaches are due in significant part to a lack of exactly the kind of integration required for the development of embodied autonomous robotics. Moreover we suggest that considerations of embodiment, situatedness, and autonomy, intrinsic to cognitive robotics, provide an appropriate basis for the integration and theoretic cumulation that Newell argued was necessary for psychology to mature. From this perspective we analyse the role of embodiment and modes of situatedness in terms of integration, cognition, emotion, and autonomy. Four complementary perspectives on embodied and situated cognitive science are considered in terms of their potential to contribute to cognitive robotics, cognitive science, and psychological theorizing: minimal cognition and organization, enactive perception and sensorimotor contingency, homeostasis and emotion, and social embedding. In combination these perspectives provide a framework for cognitive robotics, not only wholly compatible with the original aims of cognitive modelling, but as a more appropriate methodology than those currently in common use within psychology.     

How much “effort” should be devoted to memory?

We focus on the issue of whether cognitive effort is causally related to memory. We begin with a discussion of the concept of cognitive effort as derived from capacity models of attention. We then suggest that the theoretical analysis of memory may involve concepts from different levels of psychological analysis, and we draw a distinction between concepts that represent boundary conditions and sufficient cause. When applied to memory phenomena, attentional concepts serve only as a boundary--or limiting--function in memory theory. In contrast, concepts that represent memorial processes serve as a sufficient cause function. In some instances, cognitive effort appears to have been used as a sufficient cause concept, resulting in some confusion. A review of the literature reveals a haphazard correlation between indexes of cognitive effort and of memory performance. Alternatively, the application of cognitive effort or capacity to the memory performance of certain populations (clinical, children, and elderly) illustrates a potentially more appropriate use of the concept.     

Neuropsychological Contributions to the Early Identification of Alzheimer’s Disease

A wealth of evidence demonstrates that a prodromal period of Alzheimer’s disease (AD) exists for some years prior to the appearance of significant cognitive and functional declines required for the clinical diagnosis. This prodromal period of decline is characterized by a number of different neuropsychological and brain changes, and reliable identification of individuals prior to the development of significant clinical symptoms remains a top priority of research. In this review we provide an overview of those neuropsychological changes. In particular, we examine specific domains of cognition that appear to be negatively affected during the prodromal period of AD, and we review newer analytic strategies designed to examine cognitive asymmetries or discrepancies between higher-order cognitive functions versus fundamental skills. Finally, we provide a critical examination of the clinical concept of Mild Cognitive Impairment and offer suggestions for an increased focus on the impact of cerebrovascular disease (CVD) and CVD risk during the prodromal period of AD.     

The Notion of Dynamic Unit: Conceptual Developments in Cognitive Science

We suggest a common ground for alternative proposals In different domains of cognitive science which have previously seemed to have little in common. The underlying common theme is associated with a redefinition of the basic unit of analysis in each domain of thought. Our framework suggests a definition of unity which is based not on inherent properties of the elements constituting the unit, but rather on dynamic patterns of correlation across the elements. We introduce a set of features that characterize the new dynamic units, and distinguish them from traditional units of analysis. A conceptual connection is made with the identification of elementary units in modern physics theories, as well as with concepts and structures in the study of complex dynamical systems and connectionism. The paper analyses the evolution of the concept of unit in different domains of thought in cognitive science, and examines the proposed framework of “dynamic unity” with regard to various theoretical problems within each domain. The particular cognitive science issues discussed in the paper include: (1) the binding problem in the brain; (2) the mental unit of conceptual organization; (3) defining ‘wordhood’ in linguistics; and (4) identifying the unit of cognition in the natural environment.     

Cognitive externalism meets bounded rationality

When proponents of cognitive externalism (CE) turn to empirical studies in cognitive science to put the framework to use and to assess its explanatory success, they typically refer to perception, memory, or motor coordination. In contrast, not much has been said about reasoning. One promising avenue to explore in this respect is the theory of bounded rationality (BR). To clarify the relationship between CE and BR, we criticize Andy Clark's understanding of BR, as well as his claim that BR does not fit his version of CE. We then propose and defend a version of CE—“scaffolded cognition”—that is not committed to constitutive claims about the mind, but still differs from mainstream internalism. Finally, we analyze BR from our own CE perspective, thereby clarifying its vague appeals to the environment, and argue that cognitive internalism cannot explain important aspects of the BR program.     

Can language restructure cognition? The case for space

Frames of reference are coordinate systems used to compute and specify the location of objects with respect to other objects. These have long been thought of as innate concepts, built into our neurocognition. However, recent work shows that the use of such frames in language, cognition and gesture varies cross-culturally, and that children can acquire different systems with comparable ease. We argue that language can play a significant role in structuring, or restructuring, a domain as fundamental as spatial cognition. This suggests we need to rethink the relation between the neurocognitive underpinnings of spatial cognition and the concepts we use in everyday thinking, and, more generally, to work out how to account for cross-cultural cognitive diversity in core cognitive domains.     

How Do Artificial Neural Networks Classify Musical Triads? A Case Study in Eluding Bonini's Paradox

How might artificial neural networks (ANNs) inform cognitive science? Often cognitive scientists use ANNs but do not examine their internal structures. In this paper, we use ANNs to explore how cognition might represent musical properties. We train ANNs to classify musical chords, and we interpret network structure to determine what representations ANNs discover and use. We find connection weights between input units and hidden units can be described using Fourier phase spaces, a representation studied in musical set theory. We find the total signal coming through these weighted connection weights is a measure of the similarity between two Fourier structures: the structure of the hidden unit's weights and the structure of the stimulus. This is surprising because neither of these Fourier structures is computed by the hidden unit. We then show how output units use such similarity measures to classify chords. However, we also find different types of units—units that use different activation functions—use this similarity measure very differently. This result, combined with other findings, indicates that while our networks are related to the Fourier analysis of musical sets, they do not perform Fourier analyses of the kind usually described in musical set theory. Our results show Fourier representations of music are not limited to musical set theory. Our results also suggest how cognitive psychologists might explore Fourier representations in musical cognition. Critically, such theoretical and empirical implications require researchers to understand how network structure converts stimuli into responses.     

A framework for local cortical oscillation patterns

Oscillations are a pervasive feature of neuronal activity in the cerebral cortex. Here, we propose a framework for understanding local cortical oscillation patterns in cognition: two classes of network interactions underlying two classes of cognitive functions produce different local oscillation patterns. Local excitatory-inhibitory interactions shape neuronal representations of sensory, motor and cognitive variables, and produce local gamma-band oscillations. By contrast, the linkage of such representations by integrative functions such as decision-making is mediated by long-range cortical interactions, which yield more diverse local oscillation patterns often involving the beta range. This framework reconciles different cortical oscillation patterns observed in recent studies and helps to understand the link between cortical oscillations and the fMRI signal. Our framework highlights the notion that cortical oscillations index the specific circuit-level mechanisms of cognition.     

Distributed learning: Educating and assessing extended cognitive systems

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualizing how we learn to assemble extended cognitive systems by internalizing cultural norms and practices. Having a better grip on how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organize (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the internet during exams.     

Analogical modification in the creation of contemporary art

The goal of this study was to propose a framework to describe the analogical process in the context of creation. We conducted retrospective interviews with two contemporary artists in their forties using portfolios of their past works so that they could recall their creation processes in detail. We found that the artists often use analogical modification to produce new series of artwork. Analogical modification is a cognitive process used to generate a new target, in the context of creation, by changing values of a source to make differences during analogical mapping. We found three types of analogical modification, namely, subject modification, structure modification, and concept modification. Creative vision, which is formed through many years of creative activity and consists of long-term intentions or goals for creation, plays an important role in guiding the use of analogical modification. The process of artistic creation can be better understood using the framework of the interaction between activities in different time spans, such as analogical modification and creative vision.     

Dissociable learning processes in comparative psychology

Comparative and cognitive psychologists interpret performance in different ways. Animal researchers invoke a dominant construct of associative learning. Human researchers acknowledge humans’ capacity for explicit-declarative cognition. This article offers a way to bridge a divide that defeats productive cross-talk. We show that animals often challenge the associative-learning construct, and that it does not work to try to stretch the associative-learning construct to encompass these performances. This approach thins and impoverishes that important construct. We describe an alternative approach that restrains the construct of associative learning by giving it a clear operational definition. We apply this approach in several comparative domains to show that different task variants change—in concert—the level of awareness, the declarative nature of knowledge, the dimensional breadth of knowledge, and the brain systems that organize learning. These changes reveal dissociable learning processes that a unitary associative construct cannot explain but a neural-systems framework can explain. These changes define the limit of associative learning and the threshold of explicit cognition. The neural-systems framework can broaden empirical horizons in comparative psychology. It can offer animal models of explicit cognition to cognitive researchers and neuroscientists. It can offer simple behavioral paradigms for exploring explicit cognition to developmental researchers. It can enliven the synergy between human and animal research, promising a productive future for both.