Research Fields‎ > ‎

Surface-based decoding

Cortical surface-based searchlight decoding.
Chen Y, Namburi P, Elliott LT, Heinzle J, Soon CS, Chee MW, Haynes JD.
Published in Neuroimage. 2011 May 15;56(2):582-92.

Local voxel patterns of fMRI signals contain specific information about cognitive processes ranging from basic sensory processing to high level decision making. These patterns can be detected using multivariate pattern classification, and localization of these patterns can be achieved with searchlight methods in which the information content of spherical sub-volumes of the fMRI signal is assessed. The only assumption made by this approach is that the patterns are spatially local. We present a cortical surface-based searchlight approach to pattern localization. Voxels are grouped according to distance along the cortical surface-the intrinsic metric of cortical anatomy-rather than Euclidean distance as in volumetric searchlights. Using a paradigm in which the category of visually presented objects is decoded, we compare the surface-based method to a standard volumetric searchlight technique. Group analyses of accuracy maps produced by both methods show similar distributions of informative regions. The surface-based method achieves a finer spatial specificity with comparable peak values of significance, while the volumetric method appears to be more sensitive to small informative regions and might also capture information not located directly within the gray matter. Furthermore, our findings show that a surface centered in the middle of the gray matter contains more information than to the white-gray boundary or the pial surface.

Topographically specific functional connectivity between visual field maps in the human brain.
Heinzle J, Kahnt T, Haynes JD.
Published in Neuroimage. 2011 Jun 1;56(3):1426-36.

Neural activity in mammalian brains exhibits large spontaneous fluctuations whose structure reveals the intrinsic functional connectivity of the brain on many spatial and temporal scales. Between remote brain regions, spontaneous activity is organized into large-scale functional networks. To date, it has remained unclear whether the intrinsic functional connectivity between brain regions scales down to the fine detail of anatomical connections, for example the fine-grained topographic connectivity structure in visual cortex. Here, we show that fMRI signal fluctuations reveal a detailed retinotopically organized functional connectivity structure between the visual field maps of remote areas of the human visual cortex. The structured coherent fluctuations were even preserved in complete darkness when all visual input was removed. While the topographic connectivity structure was clearly visible in within hemisphere connections, the between hemisphere connectivity structure differs for representations along the vertical and horizontal meridian respectively. These results suggest a tight link between spontaneous neural activity and the fine-grained topographic connectivity pattern of the human brain. Thus, intrinsic functional connectivity reflects the detailed connectivity structure of the cortex at a fine spatial scale. It might thus be a valuable tool to complement anatomical studies of the human connectome, which is one of the keys to understand the functioning of the human brain.