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Gender differences in cortical complexity


Cortical complexity, a measure that quantifies the spatial frequency of gyrification and fissuration of the brain surface, has not been thoroughly characterized with respect to gender differences in the human brain. Using a new three-dimensional (3D) analytic technique with magnetic resonance imaging, we found greater gyrification in women than men in frontal and parietal regions. Increased complexity implies more cortical surface area, which may offset gender differences in brain volume and account for behavioral gender differences.

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Figure 1: The cerebral cortex.


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This work was supported by Deutsche Forschungsgemeinschaft (DFG, JA 737/8-1), research grants from the National Library of Medicine and National Institute on Aging (R01 LM05639), National Institute of Mental Health and National Institute of Neurological Disorders and Stroke (P20 MH065166), resource grants from the National Center for Research Resources (P41 RR013642 & M01 RR000865), an NIMH NRSA Training Grant (MH14584) and NARSAD Young Investigator Award (to K.L.N.), and R21 grants RR19771 and EB01561 (to P.T.). Additional support was provided by the National Institute of Biomedical Imaging and Bioengineering, National Institute of Neurological Disorders and Stroke, and National Institute of Mental Health (P01 EB001955).

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Correspondence to Arthur W Toga.

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Supplementary Figure 1

Calculating cortical complexity. In our analyses (1) ordered hierarchies of parametric meshes with variable resolutions were generated for each lobar region of interest, as shown here for the right superior-frontal region. (2) Subsequently, the logarithmic least squares regression of the measured surface area was plotted against the logarithm of the spatial frequency of the mesh. This dependence of the area measurement on the spatial resolution of the parametric grid is often termed the 'fractal dimension' and reflects the rate at which the measured surface area increases as the spatial detail in the surface representation is increased. For example, the area measured for a flat surface would always be the same at different spatial frequencies; the area of a convoluted surface will increase with increasing spatial resolution. (3) Finally, the slope of the regression plot was derived and added to the number 2, resulting in complexity values between 2 (for a planar or flat surface) and 3 (for a surface with immense numbers of convolutions and extensive folding). Although the slope of the regression plot would provide an equally useful complexity measure, adding the number 2 results in fractal dimension values that agree with the true physical dimension of the surface in the case of a 2D plane (where the fractal dimension turns out to be 2), and a surface that fills all of 3D space (where it is 3). (GIF 53 kb)

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Luders, E., Narr, K., Thompson, P. et al. Gender differences in cortical complexity. Nat Neurosci 7, 799–800 (2004).

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