Viewer Options
Surface Opacity:

Left Hemisphere
Right Hemisphere
Surface Overlay: Threshold

Surface Overlay Display Range:
Histogram Min: Max:

Minimum Track Length:

The pial surface is the "outer" cortical surface and represents the boundary between gray matter and cerebrospinal fluid. Typically, it is the surface that comes to mind when visually thinking of a brain. The gray matter is usually only a few millimeters thick and plays a key role in higher functioning and consciousness.

The white matter surface marks the boundary between the outer gray tissue and the inner white tissue. The white matter (is more accurately pinkish white to the naked eye but appears white when preserved with formaldehyde) consists of organized bundles of fibers. Each fiber is wrapped in a sheath of lipid (fat) myelin that allows for faster conduction of nerve signals vis-a-vis unsheathed gray matter. The organized fiber tracks in the white matter connect various cortical regions to each other. To stretch an analogy, if the gray matter of the brain is thought of as CPU cores, the white matter represents the wiring connecting the cores together. In this experiment, the "wiring" can be seen by dialing down the surface opacity. Tracks that tend to run inferior/superior are blue; lateral/medial are red; and anterior/posterior are green.

Surface overlay functions are calculated at each point on a surface, and colored according to value. Adjust the "Surface Overlay Display Range" slider to enhance the color contrast. Any surface embedded in 3D space, has, at each point, curvatures in all directions along the surface from that point. The minimum and maximum curvatures are known as the principal curvatures: the maximal curvature is called k₁ and the minimal curvature is called k

We have the following surface overlays (which are calculated at each vertex point on a surface mesh):

  • k₁: Maximum principal curvature -- tends to highlight the folds of the brain along their main axes.
  • k₂: Minimal principal curvature -- tends to tag small undulations along brain folds.
  • K = kk₂: Gaussian curvature -- a property intrinsic to a surface; highlights whether folds are "simple" cylinder or "sheared" spherical.
  • H = ½(k₁ + k₂): Mean curvature -- an extrinsic surface property; provides the average curvature at a point.
  • BE = k₁² + k₂²: Bending Energy -- related to the energy required to bend a flat sheet into shape at a point.
  • C = √(½(k₁² + k₂²)): Curvedness -- tends to "soften" the BE map.
  • S = (k₁ - k₂)²: Sharpness -- highlights the "sharpest" parts on gyral peaks and within sulcal troughs.
  • FI = |k₁| (|k₁| - |k₂|): Folding Index
  • thickness = The "thickness" of the cortex (i.e. the distance between the gray and white surfaces) at each surface point.


Surfaces generated with FreeSurfer:

Dale, A.M., Fischl, B., Sereno, M.I., 1999. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9, 179-194.

Tractography generated with Diffusion Toolkit:

Wang R., Benner T., Sorensen A. G., and Wedeen V.J.. Diffusion Toolkit: A Software Package for Diffusion Imaging Data Processing and Tractography. ISMRM abstract Proc. Intl. Soc. Mag. Reson. Med. 15 (2007) 3720

Curvature generation described in:

Pienaar R., Fischl B., Caviness V., Makris N., Grant P.E. Methodology for Analyzing Curvature in the developing brain from preterm to Adult. Int J Imaging Syst Technol. 2008 Jun 1;18(1):42-68. PMID: 19936261. PMCID: PMC2779548.

WebGL viewer developed by:

Dan Ginsburg
Rudolph Pienaar
at Children's Hospital Boston
Fetal-Neonatal Neuroimaging and Development Science Center