Simplified gyral pattern in severe developmental microcephalies? New insights from allometric modeling for spatial and spectral analysis of gyrification
The strong positive-allometric relationship between brain size, cortical extension and gyrification complexity, recently highlighted in the general population, could be modified by brain developmental disorders. Indeed, in case of brain growth insufficiency, the pathophysiological relevance of the “...
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Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2014-11, Vol.102 (2), p.317-331 |
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Zusammenfassung: | The strong positive-allometric relationship between brain size, cortical extension and gyrification complexity, recently highlighted in the general population, could be modified by brain developmental disorders. Indeed, in case of brain growth insufficiency, the pathophysiological relevance of the “simplified gyral pattern” phenotype is strongly disputed since almost no genotype–phenotype correlations have been found in primary microcephalies. Using surface scaling analysis and newly-developed spectral analysis of gyrification (Spangy), we tested whether the gyral simplification in groups of severe microcephalies related to ASPM, PQBP1 or fetal-alcohol-syndrome could be fully explained by brain size reduction according to the allometric scaling law established in typically-developing control groups, or whether an additional disease effect was to be suspected. We found the surface area reductions to be fully explained by scaling effect, leading to predictable folding intensities measured by gyrification indices. As for folding pattern assessed by spectral analysis, scaling effect also accounted for the majority of the variations, but an additional negative or positive disease effect was found in the case of ASPM and PQBP1-linked microcephalies, respectively. Our results point out the necessity of taking allometric scaling into account when studying the gyrification variability in pathological conditions. They also show that the quantitative analysis of gyrification complexity through spectral analysis can enable distinguishing between even (predictable, non-specific) and uneven (unpredictable, maybe disease-specific) gyral simplifications.
•Surface ratios measure folding intensity; spectral analysis reveals folding pattern.•Scaling models in controls allow the study of gyral simplification in microcephalies.•Allometric scaling explains intensity reduction and most pattern simplification.•Additional small negative or positive disease effect may alter folding pattern.•Even (predictable, non-specific) vs. uneven (disease-specific) gyral simplification |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2014.07.057 |