Project Abstract/Summary
People recognize faces, words, and other common objects with remarkable speed and accuracy. This project addresses the way that visual knowledge of faces, words, and objects becomes organized in the brain through learning. Prior research has shown that the right cerebral hemisphere is specialized for the representation of faces, whereas the left cerebral hemisphere has a stronger representation for words, with the representation of objects approximately balanced across both hemispheres. These differences in hemispheric specialization are a matter of degree and vary across individuals. Investigation of these differences requires behavioral testing of recognition abilities, combined with neuroimaging of brain structure and brain activation patterns, to understand how the visual recognition system is organized both within and between the two cerebral hemispheres, how this organization emerges with visual experience, and how and why it varies across individuals. In parallel with human behavioral and neuroimaging studies, another facet of this project is the development of a computational simulation of the visual recognition system, using an artificial neural network that learns to recognize faces, words and objects as well as people do. This simulation model is designed to mimic the properties of the brain. Variants of the model can reproduce the behavior and even capture the underlying differences in brain organization of different individuals. This project advances our understanding of the neural basis and underlying brain organization for acquisition of face and word recognition. This research has profound therapeutic implications for millions of Americans who require remediation of developmental disorders like dyslexia, who need assistance to overcome difficulties in letter and word recognition, and remediation for recovery of reading and language abilities after stroke or neurosurgery.
Visual recognition is supported by a network of brain regions in both cerebral hemispheres, that starts with some initial structure in early childhood and then develops through experience to have graded specialization for different types of stimuli. To understand better how recognition occurs, this large-scale study investigates brain structure (e.g., white matter connectivity), brain function (e.g., selectivity of neural activation) and behavior (e.g., with visual stimuli such as faces, words, and objects presented to one hemisphere) over a large group of subjects. This multi-pronged approach allows us to test the prediction that participants with greater within-hemisphere and/or weaker between-hemisphere connectivity will show greater lateralization for faces to the left hemisphere and words to the right hemisphere (but no difference for objects). A second study tests predictions that variability in language lateralization of the brain (across right- and left-handed individuals) explains individual differences in word lateralization, and this, in turn, influences face lateralization. A final study examines fine-grained changes in brain activity as individuals are exposed to, and learn, novel visual object categories, allowing us to test predictions about competition in representing new information compared with known categories (faces and words). In parallel with these studies, this research includes the development of a computational model of the visual recognition system by training a spatially constrained multi-layer artificial neural network to recognize a large number of faces, words, and objects. The model’s performance is evaluated against data of the human studies to determine whether this model can re-create and explain aspects of the system under investigation, including the distinct patterns of different individuals. In identifying the principles underlying the organization of high-level visual information, the work has important implications for knowledge acquisition and learning, both in typical individuals across the lifespan, and in those facing difficulties due to developmental or neuropsychological disorders.
This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.
Principal Investigator
David Plaut – Carnegie-Mellon University located in PITTSBURGH, PA
Co-Principal Investigators
Marlene Behrmann, David Plaut
Funders
Funding Amount
$750,205.00
Project Start Date
09/01/2021
Project End Date
08/31/2025
Will the project remain active for the next two years?
The project has more than two years remaining
Source: National Science Foundation
Please be advised that recent changes in federal funding schemes may have impacted the project’s scope and status.
Updated: April, 2025