Biomedical subjects

Christian Wallraven

Publications and source records attributed to Christian Wallraven.

4 recordsLinked to original sources

PubMed2006

Multimodal similarity and categorization of novel, three-dimensional objects.

Similarity has been proposed as a fundamental principle underlying mental object representations and capable of supporting cognitive-level tasks such as categorization. However, much of the research has considered connections between similarity and categorization for tasks performed using a single perceptual modality. Considering similarity and categorization within a multimodal context opens up a number of important questions: Are the similarities between objects the same when they are perceived using different modalities or using more than one modality at a time? Is similarity still able to explain categorization performance when objects are experienced multimodally? In this study, we addressed these questions by having subjects explore novel, 3D objects which varied parametrically in shape and texture using vision alone, touch alone, or touch and vision together. Subjects then performed a pair-wise similarity rating task and a free sorting categorization task. Multidimensional scaling (MDS) analysis of similarity data revealed that a single underlying perceptual map whose dimensions corresponded to shape and texture could explain visual, haptic, and bimodal similarity ratings. However, the relative dimension weights varied according to modality: shape dominated texture when objects were seen, whereas shape and texture were roughly equally important in the haptic and bimodal conditions. Some evidence was found for a multimodal connection between similarity and categorization: the probability of category membership increased with similarity while the probability of a category boundary being placed between two stimuli decreased with similarity. In addition, dimension weights varied according to modality in the same way for both tasks. The study also demonstrates the usefulness of 3D printing technology and MDS techniques in the study of visuohaptic object processing.

Concept Formation↗

PubMed2006

Processing of facial identity and expression: a psychophysical, physiological, and computational perspective.

A deeper understanding of how the brain processes visual information can be obtained by comparing results from complementary fields such as psychophysics, physiology, and computer science. In this chapter, empirical findings are reviewed with regard to the proposed mechanisms and representations for processing identity and emotion in faces. Results from psychophysics clearly show that faces are processed by analyzing component information (eyes, nose, mouth, etc.) and their spatial relationship (configural information). Results from neuroscience indicate separate neural systems for recognition of identity and facial expression. Computer science offers a deeper understanding of the required algorithms and representations, and provides computational modeling of psychological and physiological accounts. An interdisciplinary approach taking these different perspectives into account provides a promising basis for better understanding and modeling of how the human brain processes visual information for recognition of identity and emotion in faces.

Brain↗

PubMed2005

Learning from humans: computational modeling of face recognition.

In this paper, we propose a computational architecture of face recognition based on evidence from cognitive research. Several recent psychophysical experiments have shown that humans process faces by a combination of configural and component information. Using an appearance-based implementation of this architecture based on low-level features and their spatial relations, we were able to model aspects of human performance found in psychophysical studies. Furthermore, results from additional computational recognition experiments show that our framework is able to achieve excellent recognition performance even under large view rotations. Our interdisciplinary study is an example of how results from cognitive research can be used to construct recognition systems with increased performance. Finally, our modeling results also make new experimental predictions that will be tested in further psychophysical studies, thus effectively closing the loop between psychophysical experimentation and computational modeling.

Area Under Curve↗

PubMed2004

The role of characteristic motion in object categorization.

We report three experiments where we investigated the role of movement in object recognition. Previous studies have suggested a distinct and separate mechanism for object motion encoding, related to the action or motor-based system. To date, however, the role of an object's motion in long-term memory representations has not been explicitly tested. Here we were specifically interested in whether an object's characteristic motion patterns are integrated with static properties in an object's representation in memory. To that end, we used a simple categorization task where novel objects were categorized on the basis of two static (color and shape) and two dynamic (action and path) properties. The "action" of an object referred to its intrinsic motion pattern, whereas "path" referred to an object's extrinsic motion pattern (i.e., the route an object took). In Experiment 1, we found that all properties were relevant for categorization with the exception of path. This result was not due to path being less salient than other properties (Experiment 2). In Experiment 3, we found that when the action property was redundant that path was now used for categorization, suggesting that path was not used with action in Experiment 1 because of temporal order effects. Our findings argue for a cue-integrated model of object representation in memory.

Adolescent↗