Expressions of emotion are often brief, providing only fleeting images from which to base important social judgments. We sought to characterize the sensitivity and mechanisms of emotion detection and expression categorization when exposure to faces is very brief, and to determine whether these processes dissociate. Observers viewed 2 backward-masked facial expressions in quick succession, 1 neu...

We first describe SLIP (Strategy Length & Internal Practicability) a formal model for thinking about categorization, in particular about categorization through time. We then discuss an early application of this model to basic-levelness. We continue with novel evidence for discrete processing cycles through time. We then turn to aspects of categorization through time that have been neglected in ...

It is widely agreed that in object categorization bottom-up and top-down influences interact. How top-down processes affect categorization has been primarily investigated in isolation, with only one higher level process at a time being manipulated. Here, we investigate the combination of different top-down influences (by varying the level of category, the animacy and the background of the objec...

Collaborative categorization is an emerging direction for research and innovative applications. Arguably, collaborative categorization on the Web is an especially promising emerging form of collaborative Web systems because of both, the widespread use of the conventional Web and the emergence of the Semantic Web providing with more semantic information on Web data. This paper discusses this iss...

The present study examined functional MRI (fMRI) BOLD signal changes in response to object categorization during response selection and inhibition. Young adults (N=16) completed a Go/NoGo task with varying object categorization requirements while fMRI data were recorded. Response inhibition elicited increased signal change in various brain regions, including medial frontal areas, compared with ...

In automated multi-label text categorization, an automatic categorization system should output a label set, whose size is unknown a priori, for each document under analysis. Many machine learning techniques have been used for building such automatic text categorization systems. In this paper, we examine virtual generalizing random access memory weightless neural networks (VG-RAM WNN), an effect...

The AI system NARS contains a categorization model, in the sense that categorization and reasoning are two aspects of the same mechanism. As a theory of categorization, the NARS model unifies several existing theories. In this paper, the logic used in NARS is briefly described, and the categorization model is compared with the others.

Previous research has demonstrated dissociations between categorization and recognition performance in amnesic patients, supporting the idea that separate memory systems govern these tasks. However, previous research has also demonstrated that these dissociations are predicted by a single-system model that allows for reasonable parameter differences across groups. Generally, previous studies ha...

We taught a novel animal category by rule-based and similarity-based processes to participants with Alzheimer's disease (AD), corticobasal degeneration (CBD), and healthy age-matched participants. Healthy participants successfully categorized by either process. AD patients' rule-based categorization was impaired, while their similarity-based categorization resembled that of healthy participants...