COLLABORATIVE RESEARCH: Categorization and Expertise in Human Visual Cognition II

Vanderbilt University, Nashville TN

Investigators

Abstract

Visual object recognition occurs at different levels of abstraction ranging from categorical levels, e.g., "dog," to the more specific individual level, e.g., "my English hound." Moreover, we can develop "expertise" at one of these levels for a given category; for instance, bird watchers are experts at the species level. This research will continue to investigate the roles of level of categorization and perceptual expertise in the development of cognitive and neural mechanisms selective for object categories (such as faces or birds). Because different methods offer different strengths and weaknesses, this research will involve converging evidence, including behavioral psychophysics, functional brain imaging (fMRI), and event related potentials (ERPs) in normal humans, as well as extending these techniques to brain-injured individuals. The research program is divided into four sections addressing different questions: 1) How do people become perceptual experts? A first set of experiments will manipulate whether subjects rely on their own observations or require feedback and supervision. A second set of studies will examine whether non-visual knowledge about objects contributes to the learning process and affects the organization of category-specific areas. Other experiments will test the plasticity of the brain regions, which support object recognition, investigating whether damage to one area can be compensated for by reorganization of other areas. 2) What are the computational roles of different brain areas within the network that mediates expertise with visually-similar objects? Experiments using a combination of fMRI, ERP, and behavioral measures will investigate how different category-selective brain areas support identification at the categorical, subordinate, and individual levels. 3) What is the capacity of perceptual expertise? Experiments will test whether one can become an expert with many different classes of objects (e.g., birds, dogs, cars, faces, flowers, etc.), as well as whether there is interference when objects from different expertise domains are processed at the same time. 4) Can perceptual expertise be acquired more easily with some object geometries? In particular, adaptive pressures for accurate face recognition may have "biased" the system to prefer face-like configurations. By manipulating the visual structure of stimulus objects, behavioral and fMRI experiments will investigate the geometric constraints on the acquisition of expertise. Overall, these experiments should help us to better understand the nature of visual object recognition, elucidating how a single system can support the wide range of recognition tasks we are able to perform. The implications of these findings vary from possible protocols for the rehabilitation of brain-injured individuals to the better education of learning-impaired children (e.g., as in autism) to the development of more effective and robust machine vision systems for face and object recognition.