Unfolding the mystery of cortical surface development

Lauren I. Rugani

Researchers affiliated with MIT and Harvard University, both in Cambridge, Mass., have applied a variety of analytical methods to characterizing the development of morphological features on the cortical surface. The team was able to determine both where and how fast cortical folding occurs at different ages, as well as the order in which large-scale and finer folding patterns develop.

The researchers began the multiple-stage analysis by taking high-resolution magnetic resonance scans of each of the 84 older, mentally healthy participants; of eight normal neonates; and of three children under the age of 7. They enhanced the images with computer software to correct for topological defects, mapping them onto a parameterized sphere.

Application of the developed growth model revealed the temporal ordering of the development of large-scale and progressively finer-scale folds in newborns. The largest folds develop fastest in infants born more than seven weeks early; medium-scale folds develop fastest in infants born between seven and two weeks early. Finer-scale folds develop the most quickly in older infants and children.

Aligning the reconstructed cortical surface patterns allowed the scientists to detect anatomically similar points across the wide variety of subjects.

They then applied both spherical harmonics and spherical wavelets to compare the techniques’ abilities in extracting shape features from the reconstructed surfaces. Although the spherical harmonics method is restricted to global representations of cortical surfaces, spherical wavelets are constructed such that they provide information about local surface changes at multiple spatial resolutions. Using a set of spherical wavelet functions at each level decomposes the cortical surface into a low-resolution part and a detail part, represented by wavelet coefficients. Coefficients at increasing levels depict finer surface variations, and larger coefficients represent deeper surface folds at specific locations.

To identify variations of a particular structure across the subjects, the researchers employed principal component analysis, a tool used for investigating patterns in high-dimensional data. The analysis is performed separately on wavelet coefficients at different frequency levels to discern local variations among the subjects with increasingly finer resolution. When applied to the elderly population, the analysis revealed wide variation in both the overall shape of the cortex and in the finer local details. Reconstructed surface images indicated the degrees of folding on the surface, with lighter colors representing greater localized folding.

The researchers also studied cortical shape variations related to aging in the healthy adult subjects. For a group of female subjects of increasing age, the researchers discovered decreased folding on the precentral sulcus and increased folding on the occipital lobe. The narrowing and elongation of the respective regions are suggestive of white matter atrophy. A similar investigation of male subjects did not reveal any significant changes.

Finally, the researchers studied cortical folding development by building a growth model based on the Comport function, which captures both the speed of growth and the age at which folding development is fastest. The results indicated that primary folds develop first and slowly, while secondary folds representing shape variations on smaller spatial scales develop later but much faster. The fastest rate of development for the respectively finer folding occurs after 38 weeks of gestation. Understanding this development and recognizing patterns may aid in detecting neurological disorders in newborns.

The team is working on other folding development models and aims to expand these and other statistical and analytical tools to more neuroanatomical structures.

IEEE Transactions on Medical Imaging, April 2007, pp. 582-597.