Isabel Gauthier - US grants

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.

DESCRIPTION (adapted from applicant's abstract): Behavioral, functional brain imaging (fMRI), electrophysiological (ERP) and neuropsychological experiments will investigate how letters are perceived. The project is motivated by a framework accounting for specialization for faces and letters in extrastriate cortex by a detailed analysis of the different recognition goals and the information available for the recognition of these categories. The experiments will evaluate the hypothesis that what is "special" about expert letter perception is that regularities in letter style (including orientation, case and font) is used to facilitate letter recognition (access to letter identities). In particular, we will investigate how readers may learn to use the regularity of print to facilitate letter perception at the basic level, how this ability differs from general object recognition strategies and whether it leads to specialization of letter-specific areas in visual cortex. This project has four aims: I) identify behavioral effects that are special to the way experienced readers recognize letters; II) study the basic properties of letter-selective areas in visual cortex with ERP and fMRI; III) use behavioral, fMRI and ERP measurements to investigate the hypothesis that a history of poor reading expertise in dyslexic individuals leads to abnormal specialization of the letter-specific system; IV) test predictions about lesions in areas of the visual cortex specialized for letters in individuals with acquired peripheral dyslexia (pure alexia). This research will investigate how much visual factors alone contribute to specialization for letters. This information is necessary to understand linguistic influences on reading and would extend an emerging framework interpreting category-specific effects in extrastriate cortex in terms of the recruitment through experience of processes best suited for different recognition goals. Understanding what characterizes expert letter perception is also necessary to understand disorders in which this expertise is not acquired (such as dyslexia) or is lost (such as low vision).

DESCRIPTION (provided by applicant): Continuing support is requested for investigations of the neural bases and behavioral outcomes of visual expertise training with objects, focusing on comparisons between training protocols. The proposed experimental designs contrast with state-of-the-art neuroimaging training studies, which test the effects of one training procedure at a time, making it difficult to attribute expertise effects to any specific aspect of experience. Human subjects will be trained to acquire perceptual expertise with novel objects in various training conditions, and functional magnetic resonance imaging (fMRI) as well as psychophysical techniques will be used to measure expertise effects. The work is motivated by a theoretical framework, the process-map hypothesis, which proposes that differences in patterns of brain activity that are elicited automatically, in a task-independent manner, by object categories, reflect the tuning of object representations to the demands of training conditions. In the proposed investigations, we will develop new training procedures to address the following questions: 1) Can experience determine the visual areas recruited by an object category, independent of its geometry? 2) What are the effects of prior exposure to an object category, either during passive viewing or during perceptual learning, in the subsequent acquisition of perceptual expertise? 3) Can geometry interact with conceptual information learned about an object to constrain the effects of experience in the acquisition of expert skills? The planned experiments will begin to build a framework in which it will become possible to predict, based on specific aspects of a training situation (e.g., object geometry, set properties, training tasks, past exposure, non-visual conceptual knowledge), behavioral and neural effects of experience with objects. PUBLIC HEALTH RELEVANCE: Visual expertise is part of many critical human activities, from face perception to reading, as well as the acquisition of the perceptual skills necessary in many careers. This project aims at understanding how different types of training change the visual system to allow expert performance. This knowledge may help develop better training protocols for various diseases, including dyslexia and visual agnosia.

PROJECT SUMMARY The long-term goal of this line of research is to understand individual differences in our ability to recognize faces and objects. Prior research has suggested a genetic basis for individual differences in face recognition that is independent from our ability to recognize objects. However, evidence suggests that the ability to recognize objects is well measured by existing methods, and that the relationship between face and object recognition is mediated by experience with objects. In particular, this research seeks to investigate a possible link between the ability to recognize faces and the ability to individuate visually similar non-face objects, given a controlled amount of experience. This relationship is postulated on the basis of prior findings revealing that when people acquire experience individuating objects, they process them as wholes, or holistically, rather than as a collection of parts, and such holistic processing is known to be hallmark of face processing. We will seek evidence for an underlying domain-general ability that supports individuation of visually similar objects for which one has experience, by testing a model in which this ability is expressed across different measures of individuation and across different object categories (Aim 1). During training, participants will learn to individuate visually similar objects within each of four visually distinct categories. Using confirmatory factor analysis (CFA) we will specify and test two alternative models specifying that a superordinate and/or broad factor of individuation ability can be identified that accounts for substantial variance in performance across tasks and categories. Using the best-fitting model from step 1, we will then test whether individuating objects and recognizing faces are related abilities (Aim 2) by conducting a second CFA that links measures of face and object recognition. Understanding the nature of the abilities that are linked to object and face recognition will facilitate prediction in a number of domains where skilled perception is important, including medical diagnosis. It will further our understanding of the underlying mechanisms and neural substrates underlying these abilities and should also facilitate behavioral genetic studies of high-level vision, contributing to our understanding of a hereditary form of a visual face recognition deficit, developmental prosopagnosia, with a prevalence in the normal population estimated by one study to be as high as 2.5%.

Recognizing and discriminating among faces and objects is a critical human ability, particularly for jobs that require highly specialized visual skills such as in forensics, medical imaging, and homeland security. Recent research suggests that there is vast individual variability among people in their perceptual abilities, including the ability to recognize faces and non-face objects. However, people are poor at predicting their perceptual abilities relative to others, making it difficult to capitalize on this variability. This project applies a psychometric approach to the study of individual differences in perceptual abilities. From a theoretical perspective, studying these individual differences provides a new avenue for understanding mechanisms underlying visual perception. Practically speaking, these tools can identify individuals with the greatest aptitude for work that demands specific visual skills, such as baggage screening, satellite imagery analysis, and radiology. Creating and validating reliable psychometric tools in high-level vision can be useful to basic and applied science, education, and industry. Some jobs require hundreds of perceptual decisions each day, and some organizations rely on combining perceptual decisions from many individuals. The ability to predict even a small amount of variance between people could culminate in improved accuracy, increased efficiency, and decreased cost.

This project focuses on holistic processing, a visual strategy associated with face recognition, but also with other examples of expert perception. This project will exend recent efforts to measure individual differences in holistic processing by creating and testing measures that will enable the researchers to address questions about individual differences in holistic processing in a reliable manner. The project will then explore the construct validity of holistic processing using these measures to address several questions: Is holistic face processing related to domain-general abilities? How is holistic processing related to face recognition ability? How are these relationships mediated by learning that may occur within a test? Finally, experiments will focus on the interplay between domain-general and domain-specific factors during the acquisition of holistic processing, asking whether holistic processing correlates across domains, and as a function of training experiences. This represents a bridge between experimental work on the mechanisms of acquisition of holistic processing and an individual differences approach. These studies will help determine whether there is one or several possible causes of holistic processing effects, and how to choose a training method on the basis of basic cognitive measures to achieve a given training outcome. Thus, this project will combine correlational and experimental methods to establish the validity of holistic processing and elucidate its role in the network of relationships within which it operates.

This Science of Learning Collaborative Network brings together researchers from Vanderbilt University, Carnegie-Mellon University, and University of California-San Diego to investigate how and why people differ in their ability to recognize, remember, and categorize faces and objects. Many important real-world problems, such as forensics, medical imaging, and homeland security demand precise visual understanding from human experts. Understanding individual differences in high-level visual cognition has received little attention compared to other aspects of human performance. Recent studies indicate that there likely is far greater variability than commonly acknowledged in the ability to learn high-level visual skills and that such ability is poorly predicted by general intelligence. This project supports a collaborative interdisciplinary research network that aims to develop measures of individual differences in visual recognition, relate behavioral and neural markers of individual differences, develop models that explain individual differences, and relate models with neural data. Because outcomes in many real-world domains depend on decisions based on visual information, developing measures, markers, and models of individual differences can have broader impacts on identifying real-world visual talent and improving visual performance and training. Students and fellows conducting research as part of this collaborative network, including female scientists and underrepresented minorities, will be mentored by scientists from multiple disciplines, providing them with an understanding far deeper than that achievable by a single discipline.

The project will support the activities of a collaborative research network on the study of individual differences in visual recognition. The scientists involved in these interdisciplinary efforts include experts in brain imaging at ultra-high field strength, cutting-edge methods in the development of psychological tests, and cognitive and "deep" convolutional neural network models of high-level vision. The project will investigate how functional brain activity and anatomical brain structure can predict the quality and time-course of visual performance and visual learning. The team will develop and validate tests of visual ability that can be used to make precise predictions about brain activity and behavioral performance. These brain measures and behavioral tests will be related to deep convolutional neural network models; such models are the most successful computer vision models to date, and higher layers of these hierarchical networks provide outstanding models of brain areas critical to object recognition. So far these models have not been used to understand individual differences. Instead of the typical approach seeking to achieve the best performance possible, the collaborative team will seek models that can mirror human variability, making errors when people make errors, being slow when people are slow, and displaying a range of visual abilities and learning as observed in humans.

The award is from the Science of Learning-Collaborative Networks (SL-CN) Program, with funding from the SBE Division of Behavioral and Cognitive Sciences (BCS), the SBE Office of Multidisciplinary Activities (SMA), and the CISE Division of Computer and Network Systems (CNS).