Square bananas, blue horses: the relative weight of shape and color in concept recognition and representation

The present study investigates the role that shape and color play in the representation of animate (i.e., animals) and inanimate manipulable entities (i.e., fruits), and how the importance of these features is modulated by different tasks. Across three experiments participants were shown either images of entities (e.g., a sheep or a pineapple) or images of the same entities modified in color (e.g., a blue pineapple) or in shape (e.g., an elongated pineapple). In Experiment 1 we asked participants to categorize the entities as fruit or animal. Results showed that with animals color does not matter, while shape modifications determined a deterioration of the performance - stronger for fruit than for animals. To better understand our findings, in Experiments 2 we asked participants to judge if entities were graspable (manipulation evaluation task). Participants were faster with manipulable entities (fruit) than with animals; moreover alterations in shape affected the response latencies more for animals than for fruit. In Experiment 3 (motion evaluation task), we replicated the disadvantage for shape-altered animals, while with fruits shape and color modifications produced no effect. By contrasting shape- and color- alterations the present findings provide information on shape/color relative weight, suggesting that the action based property of shape is more crucial than color for fruit categorization, while with animals it is critical for both manipulation and motion tasks. This contextual dependency is further revealed by explicit judgments on similarity - between the altered entities and the prototypical ones - provided after the different tasks. These results extend current literature on affordances and biofunctionally embodied understanding, revealing the relative robustness of biofunctional activity compared to intellectual one

Conceptual Spaces in Object-Oriented Framework

The aim of this paper is to show that the middle level of mental representations in a conceptual spaces framework is consistent with the OOP paradigm. We argue that conceptual spaces framework together with vague prototype theory of categorization appears to be the most suitable solution for modeling the cognitive apparatus of humans, and that the OOP paradigm can be easily and intuitively reconciled with this framework. First, we show that the prototypebased OOP approach is consistent with Gärdenfors’ model in terms of structural coherence. Second, we argue that the product of cloning process in a prototype-based model is in line with the structure of categories in Gärdenfors’ proposal. Finally, in order to make the fuzzy object-oriented model consistent with conceptual space, we demonstrate how to define membership function in a more cognitive manner, i.e. in terms of similarity to prototype

The contribution of fMRI in the study of visual categorization and expertise

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Microgenesis, immediate experience and visual processes in reading

The concept of microgenesis refers to the development on a brief present-time scale of a percept, a thought, an object of imagination, or an expression. It defines the occurrence of immediate experience as dynamic unfolding and differentiation in which the ‘germ’ of the final experience is already embodied in the early stages of its development. Immediate experience typically concerns the focal experience of an object that is thematized as a ‘figure’ in the global field of consciousness; this can involve a percept, thought, object of imagination, or expression (verbal and/or gestural). Yet, whatever its modality or content, focal experience is postulated to develop and stabilize through dynamic differentiation and unfolding. Such a microgenetic description of immediate experience substantiates a phenomenological and genetic theory of cognition where any process of perception, thought, expression or imagination is primarily a process of genetic differentiation and development, rather than one of detection (of a stimulus array or information), transformation, and integration (of multiple primitive components) as theories of cognitivist kind have contended. My purpose in this essay is to provide an overview of the main constructs of microgenetic theory, to outline its potential avenues of future development in the field of cognitive science, and to illustrate an application of the theory to research, using visual processes in reading as an example

Analyzing equivalalences in discourse: are discourse theory and membership categorization analysis comptatible

Facing a crucial leap from political philosophy to empirical analysis, the approach to discourse analysis that arose in the aftermath of Laclau and Mouffe (1985), and that is currently known as the Essex school of discourse theory (DT), has in recent years repeatedly been accused of suffering from a methodological deficit. This paper examines to what extent membership categorization analysis (MCA), a branch of ethnomethodology that investigates lay actors' situated descriptions-in-context as practical activity, can play a part in rendering poststructuralist DT notions such as articulation and equivalence analytically tangible in empirically observable discourse. Based on a review of Laclau and Mouffe's foundational text as well as on Glynos and Howarth's recent exposition of the framework (2007), it is argued that MCA empirically substantiates many poststructuralist claims about the indeterminacy of signification. However, MCA consistently falters - and willingly so - at the point where DT would articulate emerging equivalences between identity categories as part of a second-order explanatory concept, such as Glynos and Howarth’s notion of political logic. Nevertheless, MCA also contains the kernel of an "endogenous" notion of the political that comes fairly close to DT’s all-pervasive understanding of the concept. To support these arguments, a variety of empirical sources are mobilized, ranging from the transcript of a political talk show, a newspaper report regarding a discrimination case in a dance class, to data drawn from earlier research on the way that minority members are treated by the Belgian criminal justice system

Learning Grammatical Models for Object Recognition

Many object recognition systems are limited by their inability to share common parts or structure among related object classes. This capability is desirable because it allows information about parts and relationships in one object class to be generalized to other classes for which it is relevant. With this goal in mind, we have designed a representation and recognition framework that captures structural variability and shared part structure within and among object classes. The framework uses probabilistic geometric grammars (PGGs) to represent object classes recursively in terms of their parts, thereby exploiting the hierarchical and substitutive structure inherent to many types of objects. To incorporate geometric and appearance information, we extend traditional probabilistic context-free grammars to represent distributions over the relative geometric characteristics of object parts as well as the appearance of primitive parts. We describe an efficient dynamic programming algorithm for object categorization and localization in images given a PGG model. We also develop an EM algorithm to estimate the parameters of a grammar structure from training data, and a search-based structure learning approach that finds a compact grammar to explain the image data while sharing substructure among classes. Finally, we describe a set of experiments that demonstrate empirically that the system provides a performance benefit

The very same thing: Extending the object token concept to incorporate causal constraints on individual identity

The contributions of feature recognition, object categorization, and recollection of episodic memories to the re-identification of a perceived object as the very same thing encountered in a previous perceptual episode are well understood in terms of both cognitive-behavioral phenomenology and neurofunctional implementation. Human beings do not, however, rely solely on features and context to re-identify individuals; in the presence of featural change and similarly-featured distractors, people routinely employ causal constraints to establish object identities. Based on available cognitive and neurofunctional data, the standard object-token based model of individual re-identification is extended to incorporate the construction of unobserved and hence fictive causal histories (FCHs) of observed objects by the pre-motor action planning system. Cognitive-behavioral and implementation-level predictions of this extended model and methods for testing them are outlined. It is suggested that functional deficits in the construction of FCHs are associated with clinical outcomes in both Autism Spectrum Disorders and later-stage stage Alzheimer's disease.\u