Format

Send to

Choose Destination
Neuroimage. 2014 Nov 15;102 Pt 2:317-31. doi: 10.1016/j.neuroimage.2014.07.057. Epub 2014 Aug 6.

Simplified gyral pattern in severe developmental microcephalies? New insights from allometric modeling for spatial and spectral analysis of gyrification.

Author information

1
INSERM, UMR 1129, F-75015 Paris, France; CEA, NeuroSpin, UNIACT, UNIPEDIA, F-91191 Gif sur Yvette, France; AP-HP, Hôpital Robert Debré, Service de Neuropédiatrie et Pathologie Métabolique, F-75019 Paris, France; Univ Paris Diderot, Sorbonne Paris Cité, Faculté de Médecine Paris Diderot, F-75010 Paris, France. Electronic address: david.germanaud@rdb.aphp.fr.
2
Aix-Marseille Université, CNRS, LSIS lab, UMR 7296, F-13397 Marseille, France.
3
CEA, NeuroSpin, UNATI, LNAO, F-91191 Gif sur Yvette, France.
4
Groupe Hospitalier Sud-Réunion, Pôle de Radiologie, Service de Neuroradiologie, F-97410 Saint-Pierre, La Réunion, France.
5
HCL, Hôpital Femme Mère Enfant, Centre de Référence "Déficiences Intellectuelles de Causes Rares", F-69677 Bron, France; Université Lyon 1, Université de Lyon, Faculté de médecine Lyon Sud - Charles Mérieux, F-69008 Lyon, France; CNRS, Université Lyon 1, Université de Lyon, L2C2, Institut des Sciences Cognitives, UMR 5304, F-69675 Bron, France.
6
Office Médico-Pédagogique, Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland.
7
AP-HP, Hôpital Robert Debré, Service d'Imagerie Pédiatrique, F-75019 Paris, France.
8
Fondation Père Favron, IMS Charles Isautier, CAMPS, F-97450 Saint-Louis, La Réunion, France.
9
Univ Paris Diderot, Sorbonne Paris Cité, Faculté de Médecine Paris Diderot, F-75010 Paris, France; INSERM, UMR 1141, F-75019 Paris, France; Univ Paris Diderot, Sorbonne Paris Cité, UMR 1141, F-75019 Paris, France; AP-HP, Hôpital Robert Debré, Service de Génétique Clinique, F-75019 Paris, France.
10
Office Médico-Pédagogique, Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland; Stanford Cognitive and Systems Neuroscience Laboratory, Stanford University School of Medicine, CA, USA.
11
Univ Paris Diderot, Sorbonne Paris Cité, Faculté de Médecine Paris Diderot, F-75010 Paris, France; AP-HP, Hôpital Robert Debré, Service de Génétique Clinique, F-75019 Paris, France.
12
CNRS, Genes, synapses and cognition, URA 2182, Institut Pasteur, F-75015 Paris, France; Institut Pasteur, Human Genetics and Cognitive Functions, F-75015 Paris, France.
13
INSERM, UMR 1129, F-75015 Paris, France; CEA, NeuroSpin, UNIACT, UNIPEDIA, F-91191 Gif sur Yvette, France; Univer Paris Descartes, Sorbonne Paris Cité, UMR 1129, F-75015 Paris, France.

Abstract

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.

KEYWORDS:

Allometry; Complexity; Gyrification; Microcephaly; Spectral

[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center