Post-adolescent developmental changes in cortical complexity

BackgroundPost-adolescence is known to be a period of general maturation and development in the human brain. In brain imaging, volumetric and morphologic cortical grey-matter changes can easily be assessed, but the analysis of cortical complexity seems to have been broadly neglected for this age interval.MethodsMagnetic resonance imaging (MRI) was used to acquire structural brain images. The study involved 17 adolescents (mean age 14.1 ± 0.27, 11 girls) who were compared with 14 young adults (mean age 24.24 ± 2.76, 7 women) for measures of brain complexity (fractal dimension - FD), grey matter (GM) volume and surface-area of cortical ribbon. FD was calculated using box-counting and Minkowski-Bouligand methods; FD and GM volume were measured for the whole brain, each hemisphere and lobes: frontal, occipital, parietal and temporal.ResultsThe results show that the adults have a lower cortical complexity than the adolescents, which was significant for whole brain, left and right hemisphere, frontal and parietal lobes for both genders; and only for males in left temporal lobe. The GM volume was smaller in men than in boys for almost all measurements, and smaller in women than in girls just for right parietal lobe. A significant Pearson correlation was found between FD and GM volume for whole brain and each hemisphere in both genders. The decrease of the GM surface-area was significant in post-adolescence for males, not for females.ConclusionsDuring post-adolescence there are common changes in cortical complexity in the same regions for both genders, but there are also gender specific changes in some cortical areas. The sex differences from different cortical measurements (FD, GM volume and surface-area of cortical ribbon) could suggest a maturation delay in specific brain regions for each gender in relation to the other and might be explained through the functional role of the corresponding regions reflected in gender difference of developed abilities.

[1]  A. Dekaban,et al.  Changes in brain weights during the span of human life: Relation of brain weights to body heights and body weights , 1978, Annals of neurology.

[2]  T. Paus,et al.  Sexual dimorphism in the adolescent brain: Role of testosterone and androgen receptor in global and local volumes of grey and white matter , 2010, Hormones and Behavior.

[3]  Kuo-Kai Shyu,et al.  Using three-dimensional fractal dimension to analyze the complexity of fetal cortical surface from magnetic resonance images , 2009 .

[4]  Wlodzimierz Klonowski,et al.  Fractals in the Neurosciences, Part II , 2015, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[5]  D. Stoyan,et al.  Mandelbrot, B. B., Fractals: Form, Chance, and Dimension. San Francisco. W. H. Freeman and Company. 1977. 352 S., 68 Abb., $14.95 , 1979 .

[6]  Alison D. Murray,et al.  Structural brain complexity and cognitive decline in late life — A longitudinal study in the Aberdeen 1936 Birth Cohort , 2014, NeuroImage.

[7]  A. Toga,et al.  Localizing Age-Related Changes in Brain Structure between Childhood and Adolescence Using Statistical Parametric Mapping , 1999, NeuroImage.

[8]  Gordon D. Waiter,et al.  Brain structural complexity and life course cognitive change , 2012, NeuroImage.

[9]  Anders M. Dale,et al.  A hybrid approach to the Skull Stripping problem in MRI , 2001, NeuroImage.

[10]  N. De Stefano,et al.  Longitudinal changes in grey and white matter during adolescence , 2010, NeuroImage.

[11]  D. Kennedy,et al.  Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imaging. , 1989, IEEE transactions on medical imaging.

[12]  P. Villoslada,et al.  OP39.02: MRI cerebral fractal dimension analysis in preterm infants with and without intrauterine growth restriction , 2010 .

[13]  Guang H. Yue,et al.  Quantifying degeneration of white matter in normal aging using fractal dimension , 2007, Neurobiology of Aging.

[14]  K. Hugdahl,et al.  Working Memory Deficit in Dyslexia: Behavioral and fMRI Evidence , 2010, The International journal of neuroscience.

[15]  Sven Strauss,et al.  The Asymmetrical Brain , 2016 .

[16]  A. W. Toga,et al.  Localizing Age-related Changes in Brain Structure between Childhood and Adolescence Using Statistical Mapping Techniques , 1998, NeuroImage.

[17]  Ivo D. Dinov,et al.  Sex Matters during Adolescence: Testosterone-Related Cortical Thickness Maturation Differs between Boys and Girls , 2012, PloS one.

[18]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[19]  Eileen Luders,et al.  Gender differences in cortical complexity , 2004, Nature Neuroscience.

[20]  A. Lundervold,et al.  Sex-differences in grey–white matter structure in normal-reading and dyslexic adolescents , 2008, Neuroscience Letters.

[21]  P. Huttenlocher Synaptic density in human frontal cortex - developmental changes and effects of aging. , 1979, Brain research.

[22]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[23]  Pablo Villoslada,et al.  Fractal-dimension analysis detects cerebral changes in preterm infants with and without intrauterine growth restriction , 2010, NeuroImage.

[24]  A. Kaufman,et al.  Comparison of three WISC-III short forms: Weighing psychometric, clinical, and practical factors. , 1996 .

[25]  Jing Z. Liu,et al.  A three-dimensional fractal analysis method for quantifying white matter structure in human brain , 2006, Journal of Neuroscience Methods.

[26]  Soon Beom Hong,et al.  Fractal dimension in human cortical surface: Multiple regression analysis with cortical thickness, sulcal depth, and folding area , 2006, Human brain mapping.

[27]  Brandon Brown,et al.  Fractal dimension analysis of the cortical ribbon in mild Alzheimer's disease , 2010, NeuroImage.

[28]  D. Kennedy,et al.  Magnetic resonance technology in human brain science: Blueprint for a program based upon morphometry , 1989, Brain and Development.

[29]  A. Toga,et al.  Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation , 2001, The Journal of Neuroscience.

[30]  A. Villringer,et al.  Sexual dimorphism in the human brain: evidence from neuroimaging. , 2013, Magnetic resonance imaging.

[31]  Finn Egil Tønnessen,et al.  Dyslexic Children Show Short-Term Memory Deficits in Phonological Storage and Serial Rehearsal: An fMRI Study , 2009, The International journal of neuroscience.

[32]  Paul M. Thompson,et al.  Sexual dimorphism of brain developmental trajectories during childhood and adolescence , 2007, NeuroImage.

[33]  Kenneth Hugdahl,et al.  Executive working memory processes in dyslexia: behavioral and fMRI evidence. , 2010, Scandinavian journal of psychology.

[34]  K. Cosgrove,et al.  Evolving Knowledge of Sex Differences in Brain Structure, Function, and Chemistry , 2007, Biological Psychiatry.

[35]  Siegfried Kasper,et al.  Regional sex differences in grey matter volume are associated with sex hormones in the young adult human brain , 2010, NeuroImage.

[36]  Arvid Lundervold,et al.  Evaluation of automated brain MR image segmentation and volumetry methods , 2009, Human brain mapping.

[37]  Mick Brammer,et al.  Sex-dependent age modulation of frontostriatal and temporo-parietal activation during cognitive control , 2009, NeuroImage.

[38]  C. Sisk,et al.  The neural basis of puberty and adolescence , 2004, Nature Neuroscience.

[39]  Thomas G Maris,et al.  Fractal dimension as an index of brain cortical changes throughout life. , 2007, In vivo.

[40]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[41]  Arvid Lundervold,et al.  Fractal dimension analysis of MR images reveals grey matter structure irregularities in schizophrenia , 2008, Comput. Medical Imaging Graph..

[42]  A. Toga,et al.  Mapping Changes in the Human Cortex throughout the Span of Life , 2004, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[43]  P. Yakovlev,et al.  The myelogenetic cycles of regional maturation of the brain , 1967 .

[44]  J. Talairach,et al.  Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .

[45]  Sun I. Kim,et al.  Analysis of the hemispheric asymmetry using fractal dimension of a skeletonized cerebral surface , 2004, IEEE Transactions on Biomedical Engineering.

[46]  A. Connelly,et al.  Developmental changes in cerebral grey and white matter volume from infancy to adulthood , 2010, International Journal of Developmental Neuroscience.

[47]  J. Martinot,et al.  1910s' brains revisited. Cortical complexity in early 20th century patients with intellectual disability or with dementia praecox , 2014, Acta psychiatrica Scandinavica.

[48]  Gereon R Fink,et al.  Sex differences and the impact of steroid hormones on the developing human brain. , 2009, Cerebral cortex.

[49]  A. Toga,et al.  Mapping cortical asymmetry and complexity patterns in normal children , 2001, Psychiatry Research: Neuroimaging.

[50]  A. Toga,et al.  In vivo evidence for post-adolescent brain maturation in frontal and striatal regions , 1999, Nature Neuroscience.

[51]  A. Minkowski,et al.  Regional Development of the Brain in Early Life , 1968 .

[52]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.