The Need

By analyzing the stimulus­-referred fMRI responses in each voxel of an MR image, retinotopic mapping of human visual cortex can generate cortical maps of the visual space. These maps elucidate the spatial organization of the neuronal responses to visual images. Although numerous studies have been devoted to retinotopic mapping, most use an experimental approach to discover and study the various visual areas. There is a need for a mathematical model that fully considers the intrinsic geometrical features of the underlying cortical structures to develop subject-specific maps that can be compared across patients and at various time points.

The Technology

Researchers at The Ohio State University and Arizona State University, led by Dr. Yalin Wang, have developed a tool that uses computational conformal geometry to quantify sensory maps of the human brain. The invention maps visual cortical surfaces to a topological disk, where local geometry structures are well preserved. This data is smoothed to remove noise, then a coefficient map that is sensitive to local changes in surface area is produced to to reconstruct the retinotopic map.

Commercial Applications

• Medical diagnosis
• Medical research
• Medical Imaging products (e.g. fMRI)

Benefits/Advantages

• Provides a complete quantitative description of the maps that define imaging scores that are important for disease diagnosis and prognosis
• Establishes a rigorous imaging quantification framework
• Allows physicians to develop subject-specific maps that can be compared across various time points