Anatomic magnetic resonance imaging of the developing child and adolescent brain and effects of genetic variation.

paper Cited Public

Authors: Giedd, Jay N; Stockman, Michael; Weddle, Catherine; Liverpool, Maria; Alexander-Bloch, Aaron; Wallace, Gregory L; Lee, Nancy R; Lalonde, Francois; Lenroot, Rhoshel K
Year: 2010
Journal: Neuropsychology review
PMID: 21069466
DOI: 10.1007/s11065-010-9151-9
PMCID: PMC3268519

Fig. 1

Scatterplot of longitudinal measurements of total brain volume for males (N=475 scans, shown in dark gray) and females (N=354 scans, shown in light gray) (Lenroot et al. 2007)

LLM interpretation

This scatterplot shows longitudinal measurements of total brain volume (cc³) across age (years) for males (dark gray) and females (light gray). The x-axis ranges from 0 to 30 years, and the y-axis ranges from 500 to 1500 cc³. Data points are connected by lines for individual subjects, showing a general trend of volume increase during childhood followed by stabilization or slight decline in adolescence and early adulthood, with males generally exhibiting higher volumes than females.

Fig. 2

Mean volume by age in years for males (N=475 scans) and females (N=354 scans). Middle lines in each set of three lines represent mean values, and upper and lower lines represent upper and lower 95% confidence intervals. a Total brain volume, b Gray matter volume, c White matter volume, d Lateral ventricle volume, e Mid-sagittal area of the corpus callosum, f Caudate volume (Lenroot et al. 2007)

LLM interpretation

This figure consists of six line graphs (a-f) showing the mean volume or area of various brain structures across ages 7 to 19 years for males and females. Each plot displays two sets of lines representing the mean and 95% confidence intervals for each sex, with the x-axis representing age in years and the y-axis representing volume in cubic centimeters (cc) or area in $\text{cc}^2$. Trends vary by structure: total brain, gray matter, and caudate volumes generally peak in early adolescence before plateauing or declining, while white matter, lateral ventricle, and corpus callosum measurements show a steady increase with age.

Fig. 3

Right lateral and top views of the dynamic sequence of GM maturation over the cortical surface. The side bar shows a color representation in units of GM volume (Gogtay et al. 2004)

LLM interpretation

This figure presents a dynamic sequence of brain surface maps showing gray matter (GM) maturation from age 5 to 20. The visualization includes right lateral and top views of the cortex, with a color scale indicating GM volume. A clear trend of decreasing GM volume is visible over time, as the colors shift from warm (red/yellow) to cool (blue/purple) tones across the cortical surface.

Fig. 4

Graphic representation of structural equation modeling with genetically informative data

LLM interpretation

This is a structural equation modeling diagram of an ACE model comparing two individuals (Phenotype Twin 1 and Phenotype Twin 2). The model shows that each phenotype is influenced by three latent variables: additive genetic effects (A), common environmental effects (C), and unique environmental effects (E). Double-headed arrows indicate correlational relationships between the twins' latent variables, with specified coefficients of 1 for C and either 0.5 or 1 for A.

Fig. 5

Heritability at ages 5, 12, and 18 years for superior, inferior, right and left cortical surfaces. Colorbar shows scale of heritability values from 0.0 to 1.0 (Lenroot et al. 2009)

LLM interpretation

This figure consists of a series of brain surface maps showing heritability values across three age groups: 5 years (column a), 12 years (column b), and 18 years (column c). The maps display superior, inferior, right, and left cortical surfaces, with a colorbar indicating heritability values ranging from 0.0 (purple) to 1.0 (red). Visually, heritability appears lowest at age 12 and highest at age 18, with the most intense colors (higher heritability) concentrated in the 18-year-old group.

Fig. 6

Vertex maps of areas showing statistically significant differences in the rate of cortical thinning between genotype groups. Pheu607Leu top panel, Ser704Cys bottom panel. Phe carriers (PheCar) showed a significant attenuation of cortical thinning relative to Leu homozygotes (LeuLeu) in the colored regions shown. The inset plot illustrates estimated genotype group trajectories for the left superior frontal focus. Ser homozygotes (SerSer) showed a significant acceleration of cortical thinning in the colored regions shown. The inset plot illustrates estimated genotype group trajectories for the left posterior superior temporal focus. In all instances ‘Warmer’ colors indicate thickness trajectory differences of greater statistical significance (Raznahan et al. 2010)

LLM interpretation

This figure consists of two panels of cortical vertex maps paired with line graphs showing cortical thickness trajectories over age (7 to 22 years). The top panel shows regions where Phe carriers (PheCar) have attenuated cortical thinning compared to Leu homozygotes (LeuLeu), while the bottom panel shows regions where Ser homozygotes (SerSer) have accelerated thinning compared to Cys carriers (CysCar). Colored regions on the brain maps indicate statistical significance, with warmer colors representing higher significance levels.

#	Section	Preview
0	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence	Data taken from the Child Psychiatry Branch (CPB) cohort has shown several striking findings. One is…
1	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence	childhood and adolescence in this sample the group average brain size for males is approximately 10%…
2	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence	These findings highlight one of the most important principles emerging from neuroimaging research,…
3	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Trajectories of Brain Volumes	Brain volume follows an inverted U shape trajectory, which peaks at approximately age 10.5 in girls…
4	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Trajectories of Brain Volumes	White matter volumes instead increase throughout childhood and adolescence (Fig. 2c). At lobar…
5	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Trajectories of Brain Volumes	The corpus callosum (CC) is the most prominent white matter structure and easily visualized on mid…
6	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Trajectories of Brain Volumes	Increasing white matter during childhood and adolescence allows for greater integration of disparate…
7	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Trajectories of Brain Volumes	Recognition of the importance of white matter development for brain function has stimulated the…
8	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Subcortical Structures — Basal Ganglia	The basal ganglia are a collection of subcortical nuclei (caudate, putamen, globus pallidus,…
9	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Subcortical Structures — Amygdala and Hippocampus	The temporal lobes, amygdala, and hippocampus are integral players in the arenas of emotion,…
10	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Subcortical Structures — Amygdala and Hippocampus	Description of the amygdala and hippocampus has been performed using manual tracing by expert…
11	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Lateral Ventricles	The lateral ventricles are distinctive as a brain morphometry measure, as they are compartments…
12	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Cerebellum	Although only about 1/9 the volume of the cerebrum, the cerebellum (Latin for “little brain”)…
13	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Cerebellum	peak size occurring at 11.3 in girls and 15.6 in boys, similar to the cerebrum. However, these…
14	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Regional Differences in Cortical Thickness	Although some functional implications may be gleaned by examining GM at the lobar level, a…
15	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Regional Differences in Cortical Thickness	We have created movies of changes in cortical thickness over development by analyzing scans acquired…
16	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Regional Differences in Cortical Thickness	The thinning associated with cortical maturation appears to occur first in primary sensorimotor…
17	Mapping Developmental Anatomic Trajectories During Typical Childhood and Adolescence — Regional Differences in Cortical Thickness	Another potential contributor to decreased GM volume and cortical thickness is the ongoing…
18	Genetic and Environmental Influences on Brain Development: Quantitative Genetics	Individual variation in the trajectory of brain development arises from the interaction of genetic…
19	Genetic and Environmental Influences on Brain Development: Quantitative Genetics	In the classical twin model, it is assumed that the amount of genetic material shared by a pair of…

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