Concepts are the building blocks of human cognition, providing the basic content for language, episodic memory, social interaction, planning, and many other essential capabilities. Modern evidence suggests that human conceptual knowledge is represented in a widely distributed and hierarchically organized system involving much of the brain. Despite the central importance of this cognitive domain, there are large gaps in our understanding of very fundamental issues concerning how concepts are represented and organized at a systems level. This project addresses several of these gaps using a novel, high-dimensional, biologically based model of word meaning that captures the extent to which a concept is derived from various types of sensory, action, emotional, spatial, temporal, and cognitive experiences. We use this model in a series of information-based analyses of fMRI data and multivariate analyses of lesion-deficit correlations in patients with stroke. Our main hypothesis is that much of conceptual knowledge is represented in abstract form within content-specific experiential networks and multi-level convergences between these networks.
Aim 1 is to clarify the detailed architecture of these hierarchical convergences, including intermediate crossmodal networks that we hypothesize arise in the brain due to proximity of neural processing streams and systematic covariation between experiential dimensions.
Aim 2 is to test the hypothesis that event concepts (e.g., PARTY, ACCIDENT, SNEEZE) are primarily represented in inferior parietal convergence networks due to strong contributions from motion, action, spatial, and temporal experiences in the formation of these concepts, whereas object concepts have stronger representation in temporal lobe convergence networks that capture static multisensory experiences.
Aim 3 is to clarify how concept categories are differentially represented and how this organization gives rise to category-related impairments in patients with focal brain damage. We hypothesize that neural representations of both concrete and abstract categories emerge from differently weighted mixtures of experiential information at high levels in the representational hierarchy. The high-dimensional, experiential representation of word meaning on which these hypotheses are based, combined with advanced fMRI techniques for mapping information content, makes it possible to address these basic knowledge gaps systematically for the first time. Combining state-of-the-art lesion-deficit correlation analyses with these healthy brain fMRI studies provides a powerful means of establishing causal links between fMRI activity patterns and successful concept retrieval. Understanding this large, complex, and particularly human brain system has far- reaching implications for understanding a range of neurological conditions that impair knowledge representation and retrieval, is likely to be transformative in the realm of functional mapping for brain surgery, and will be a prerequisite for developing rational and effective rehabilitation strategies for such patients, including future therapies involving modulatory stimulation, brain-machine interfaces, and biological repair.

Public Health Relevance

Concept knowledge, such as knowledge of the features that define different kinds of objects, people, places, and events, is essential to every aspect of human life, but our understanding of how the brain stores this knowledge is very incomplete. This project aims to produce the first detailed maps showing how concepts are stored and organized into categories in the brain. This information will be useful for minimizing risks of brain surgery and provide an essential foundation for designing better rehabilitation strategies in people with brain damage.

National Institute of Health (NIH)
National Institute on Deafness and Other Communication Disorders (NIDCD)
Research Project (R01)
Project #
Application #
Study Section
Language and Communication Study Section (LCOM)
Program Officer
Cooper, Judith
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Medical College of Wisconsin
Schools of Medicine
United States
Zip Code