There are several different questions associated with the study of folk psychology: what is the nature of our commonsense concepts of mental states?, how do we attribute mental states, to ourselves and to other people?, and how do we acquire our concepts and skills at mental-state attribution?Three general approaches to these questions are examined and assessed: theory theory, simulation theory, and rationality theory. A preliminary problem is to define each of these approaches. Alternative definitions are explored, centering on which questions (...) each approach tries to answer and how it answers them. For example, simulation theorists substantially agree on the answer to question but not on the answer to question. The paper then turns to some serious problems facing both rationality theory and theory theory.Rationality theory is faulted for its inadequate treatment of question and for its implausible answers to question. Theory theory is faulted for the problems it encounters in explaining first-person attribution, and for its treatment of attributed reasoning about change. Turning to simulation theory, the paper argues against Gordon’s “ascent routine” account of first-person attribution and in favor of an inner detection account. Finally, the paper addresses the question of the contents of our mental-state concepts. How do these concepts incorporate both behavioral features and inner features? A dual-representation hypothesis is advanced, and linked speculatively to mirror neurons. (shrink)

Although discriminative deep neural networks are currently dominant in cognitive modeling, we suggest that capacity-limited, generative models are a promising avenue for future work. Generative models tend to learn both local and global features of stimuli and, when properly constrained, can learn componential representations and response biases found in people's behaviors.

It is commonly supposed that perceptual representations in some way embed concepts and that this embedding accounts for the phenomenon of seeing-as. But there are good reasons, which will be reviewed here, to doubt that perceptions embed concepts. The alternative is to suppose that perceptions are marks in a perceptual similarity space that map into locations in an objective quality space. From this point of view, there are at least three sorts of seeing-as. First, in cases of ambiguity resolution, the (...) schematicity of the figure leaves us with a choice as to where in perceptual similarity space to place a mark. Second, in cases where expertise affects perception, the accumulation of perceptual landmarks permits a more precise placement of a mark in perceptual similarity space. Third, extensive experience with an object allows similarity to that object to serve as an acquired dimension in perceptual similarity space, which in turn affects the relative similarities of other objects. This is an open access publication. (shrink)

Everyday experience presents us with a world of ordinary objects, but philosophers struggle to devise a useful principle of composition that even comes close to generating just those composites we perceive the world to contain. This paper presents such a principle as a first step toward defending “object dispositionalism” as a theory of material objects. According to object dispositionalism, a plurality composes a whole just when it has the disposition to cause us to perceive a unity in the region it (...) occupies and because it possesses features that in combination realize that disposition. Sections “Object dispositionalism” and “Object dispositionalism’s color counterpart” introduce object dispositionalism and argue it satisfies plausible desiderata for a theory of material objects extant views do not. Relying on cognitive psychologists’ research on object perception, sections “The disposition to what?” through “The general mechanism” explicate the manifestation and basis of the causal power object dispositionalists propose is present wherever composition occurs. Sections “Why object perception researchers are realists” and “When we disagree” describe the perceivers with and conditions in which that causal power manifests and argues object-perception variation doesn’t undermine object dispositionalism’s status as a realist view. (shrink)

Computational modeling of sketch understanding is interesting both scientifically and for creating systems that interact with people more naturally. Scientifically, understanding sketches requires modeling aspects of visual processing, spatial representations, and conceptual knowledge in an integrated way. Software that can understand sketches is starting to be used in classrooms, and it could have a potentially revolutionary impact as the models and technologies become more advanced. This paper looks at one such effort, Sketch Worksheets, which have been used in multiple classroom (...) experiments already, with students ranging from elementary school to college. Sketch Worksheets are a software equivalent of pencil and paper worksheets commonly found in classrooms, but they provide on-the-spot feedback based on what students draw. They are built on the CogSketch platform, which provides qualitative visual and spatial representations and analogical processing based on computational models of human cognition. This paper explores three issues. First, we examine how research from cognitive science and artificial intelligence, combined with the constraints of creating new kinds of educational software, led to the representations and processing in CogSketch. Second, we examine how these capabilities have been used in Sketch Worksheets, drawing upon experiments with fifth-grade students in biology and college students in engineering design and in geoscience. Finally, we examine some open issues in sketch understanding that need to be addressed to better model high-level aspects of vision, and for sketch understanding systems to reach their full potential for supporting education. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) shared and non‐shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non‐shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non‐shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

For many centuries, philosophers and scientists have pondered the origins and nature of human intuitions about the properties of points, lines, and figures on the Euclidean plane, with most hypothesizing that a system of Euclidean concepts either is innate or is assembled by general learning processes. Recent research from cognitive and developmental psychology, cognitive anthropology, animal cognition, and cognitive neuroscience suggests a different view. Knowledge of geometry may be founded on at least two distinct, evolutionarily ancient, core cognitive systems for (...) representing the shapes of large-scale, navigable surface layouts and of small-scale, movable forms and objects. Each of these systems applies to some but not all perceptible arrays and captures some but not all of the three fundamental Euclidean relationships of distance (or length), angle, and direction (or sense). Like natural number (Carey, 2009), Euclidean geometry may be constructed through the productive combination of representations from these core systems, through the use of uniquely human symbolic systems. (shrink)

The problem of representing the spatial structure of images, which arises in visual object processing, is commonly described using terminology borrowed from propositional theories of cognition, notably, the concept of compositionality. The classical propositional stance mandates representations composed of symbols, which stand for atomic or composite entities and enter into arbitrarily nested relationships. We argue that the main desiderata of a representational system—productivity and systematicity—can (indeed, for a number of reasons, should) be achieved without recourse to the classical, proposition‐like compositionality. (...) We show how this can be done, by describing a systematic and productive model of the representation of visual structure, which relies on static rather than dynamic binding and uses coarsely coded rather than atomic shape primitives. (shrink)

More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial subset of them. In the system presented here, visual features are extracted through image processing and then translated into a symbolic visual vocabulary. We introduce a formal language (...) that allows representing compositional visual concepts based on this vocabulary. Using this language and Bayesian inference, concepts can be induced from the examples that are provided in each problem. We find a reasonable agreement between the concepts with high posterior probability and the solutions formulated by Bongard himself for a subset of 35 problems. While this approach is far from solving Bongard problems like humans, it does considerably better than previous approaches. We discuss the issues we encountered while developing this system and their continuing relevance for understanding visual cognition. For instance, contrary to other concept learning problems, the examples are not random in Bongard problems; instead they are carefully chosen to ensure that the concept can be induced, and we found it helpful to take the resulting pragmatic constraints into account. (shrink)

Deep neural networks (DNNs) provide a unique opportunity to move towards a generic modelling framework in psychology. The high representational capacity of these models combined with the possibility for further extensions has already allowed us to investigate the forest, namely the complex landscape of representations and processes that underlie human cognition, without forgetting about the trees, which include individual psychological phenomena.

Contour adaptation is a recently described paradigm that renders otherwise salient visual stimuli temporarily perceptually invisible. Here we investigate whether this illusion can be exploited to study visual awareness. We found that CA can induce seconds of sustained invisibility following similarly long periods of uninterrupted adaptation. Furthermore, even fragmented adaptors are capable of producing CA, with the strength of CA increasing monotonically as the adaptors encompass a greater fraction of the stimulus outline. However, different types of adaptor patterns, such as (...) distinctive shapes or illusory contours, produce equivalent levels of CA suggesting that the main determinants of CA are low-level stimulus characteristics, with minimal modulation by higher-order visual processes. Taken together, our results indicate that CA has desirable properties for studying visual awareness, including the production of prolonged periods of perceptual dissociation from stimulation as well as parametric dependencies of that dissociation on a host of stimulus parameters. (shrink)

Theories of the representation of specific kinetic and spatiotem-poral features of movement range from the explicit assertion that temporal aspects of movement are not represented to the idea that they are represented and that they have neurophysiological correlates. Jeannerod's thesis is that mental and visual images have common mechanisms and that there is a link between the image to move and the mechanisms involved with movement. The target article takes the position that certain parameters are coded in motor representations but (...) that the duration of an action is not one of them. This position is based on the work of Gottlieb et al. and of Decety et al.. Both these studies are worth considering in detail. In Note 1, Jeannerod suggests that: “in time-constrained tasks subjects control the amplitude parameter of force impulses, whereas in spatially constrained tasks the duration of the force impulse is affected by accuracy demands.” This is not exactly correct. Excitation pulse intensity is modulated both in tasks that require spatial and those that require temporal accuracy. Excitation pulse duration is modulated for changes in movement distance and inertial load. If subjects are required to be very accurate spatially, they will move at less than maximum speed for a given distance and this is achieved by lower levels of excitation intensity. (shrink)

A technique for the bilateral activation of neural nets that leads to a functional asymmetry of two simulated ''cerebral hemispheres'' is described. The simulation is designed to perform object recognition, while exhibiting characteristics typical of human consciousness-specifically, the unitary nature of conscious attention, together with a dual awareness corresponding to the ''nucleus'' and ''fringe'' described by William James (1890). Sensory neural nets self-organize on the basis of five sensory features. The system is then taught arbitrary symbolic labels for a small (...) number of similar stimuli. Finally, the trained network is exposed to nonverbal stimuli for object recognition, leading to Gaussian activation of the ''sensory'' maps-with a peak at the location most closely related to the features of the external stimulus. ''Verbal'' maps are activated most strongly at the labeled location that lies closest to the peak on homologous sensory maps. On the verbal maps activation is characterized by both excitatory and inhibitory Gaussians (a Mexican hat), the parameters of which are determined by the relative locations of the verbal labels. Mutual homotopic inhibition across the ''corpus callosum'' then produces functional cerebral asymmetries, i.e., complementary activation of homologous ''association'' and ''frontal'' maps within a common focus of attention-a nucleus in the left hemisphere and a fringe in the right hemisphere. An object is recognized as corresponding to a known label when the total activation of both hemispheres (nucleus plus fringe) is strongest for that label. The functional dualities of the cerebral hemispheres are discussed in light of the nucleus/fringe asymmetry. (shrink)

Sterelny’s Thought in a Hostile World ([ 2003 ]) presents a complex, systematically structured theory of the evolution of cognition centered on a concept of decoupled representation. Taking Godfrey-Smith’s ([ 1996 ]) analysis of the evolution of behavioral flexibility as a framework, the theory describes increasingly complex grades of representation beginning with simple detection and culminating with decoupled representation, said to be belief-like, and it characterizes selection forces that drive evolutionary transformations in these forms of representation. Sterelny’s ultimate explanatory target (...) is the evolution of human agency. This paper develops a detailed analysis of the main cognitive aspects. It is argued that some of the major claims are not correct: decoupled representation as defined doesn’t capture belief-like representation, and, properly understood, decoupled representation turns out to be ubiquitous among multicellular animals. However, some of the key ideas are right, or along the right lines, and suggestions are made for modifying and expanding the conceptual framework. (shrink)

Sterelny's Thought in a Hostile World ([2003]) presents a complex, systematically structured theory of the evolution of cognition centered on a concept of decoupled representation. Taking Godfrey-Smith's ([1996]) analysis of the evolution of behavioral flexibility as a framework, the theory describes increasingly complex grades of representation beginning with simple detection and culminating with decoupled representation, said to be belief-like, and it characterizes selection forces that drive evolutionary transformations in these forms of representation. Sterelny's ultimate explanatory target is the evolution of (...) human agency. This paper develops a detailed analysis of the main cognitive aspects. It is argued that some of the major claims are not correct: decoupled representation as defined doesn't capture belief-like representation, and, properly understood, decoupled representation turns out to be ubiquitous among multicellular animals. However, some of the key ideas are right, or along the right lines, and suggestions are made for modifying and expanding the conceptual framework. (shrink)

According to the spreading hypothesis of object-based attention, a subliminal cue that can successfully capture attention to a location within an object should also cause attention to spread throughout the whole cued object and lead to the same-object advantage. Instead, we propose that a subliminal cue favors shifts of attention between objects and strengthens the between-object link, which is coded primarily within the dorsal pathway that governs the visual guidance of action. By adopting the two-rectangle method and using an effective (...) subliminal cue to compare with the classic suprathreshold cue, we found a different result pattern with suprathreshold cues than with subliminal cues. The suprathreshold cue replicated the conventional location and object effects, whereas a subliminal cue led to a different-object advantage with a facilitatory location effect and a same-object advantage with an inhibitory location effect. These results support our consciousness-dependent shifting hypothesis but not the spreading hypothesis. (shrink)