The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation
Open accessAbstract
Recent in vivo structural imaging studies have shown spatial and temporal patterns of brain maturation between childhood, adolescence, and young adulthood that are generally consistent with postmortem studies of cellular maturational events such as increased myelination and synaptic pruning. In this study, we conducted detailed spatial and temporal analyses of growth and gray matter density at the cortical surface of the brain in a group of 35 normally developing children, adolescents, and young adults. To accomplish this, we used high-resolution magnetic resonance imaging and novel computational image analysis techniques. For the first time, in this report we have mapped the continued postadolescent brain growth that occurs primarily in the dorsal aspects of the frontal lobe bilaterally and in the posterior temporo-occipital junction bilaterally. Notably, maps of the spatial distribution of postadolescent cortical gray matter density reduction are highly consistent with maps of the spatial distribution of postadolescent brain growth, showing an inverse relationship between cortical gray matter density reduction and brain growth primarily in the superior frontal regions that control executive cognitive functioning. Inverse relationships are not as robust in the posterior temporo-occipital junction where gray matter density reduction is much less prominent despite late brain growth in these regions between adolescence and adulthood. Overall brain growth is not significant between childhood and adolescence, but close spatial relationships between gray matter density reduction and brain growth are observed in the dorsal parietal and frontal cortex. These results suggest that progressive cellular maturational events, such as increased myelination, may play as prominent a role during the postadolescent years as regressive events, such as synaptic pruning, in determining the ultimate density of mature frontal lobe cortical gray matter.
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“Prior imaging studies show regional nonlinear changes in gray matter (GM) density during childhood and adolescence with prepubertal increase followed by postpubertal loss (11–14).”
From Dynamic mapping of human cortical development during childhood through early adulthood (2004) · cites this paper as [12]
In the citing paper
“A further MRI study of 35 normally developing children (7-11 years), adolescents (12-16 years) and young adults (23-30 years) demonstrated a sharp acceleration in the loss of grey matter between childhood and adolescence in the dorsal prefrontal cortex and the parietal cortex (Sowell et al., 2001).”
From Development of the adolescent brain: implications for executive function and social cognition (2006) · cites this paper as Sowell et al., 2001
In the citing paper
“The gradual decrease in grey matter density that occurs after puberty in certain brain regions has been attributed to post-pubescent synaptic pruning (Giedd et al., 1999a;Sowell et al., 2001;Gogtay et al., 2004).”
From Development of the adolescent brain: implications for executive function and social cognition (2006) · cites this paper as Sowell et al., 2001
In the citing paper
“One such study of participants aged between 7 and 30 revealed that the loss of grey matter in the frontal cortex accelerated during adulthood between the early 20s and up to the age of 30 (Sowell et al., 2001).”
From Development of the adolescent brain: implications for executive function and social cognition (2006) · cites this paper as Sowell et al., 2001
In the citing paper
“protracted maturation of the prefrontal cortex (PFC) and parietal regions”
From Adolescent risk taking, impulsivity, and brain development: Implications for prevention (2010) · cites this paper as Sowell, Thompson, Tessner, & Toga, 2001
In the citing paper
“Previous studies have shown that right frontal cortical thinning occurs prior to left frontal cortical thinning in children 5--11 years of age (Sowell et al. 2001).”
From Puberty influences medial temporal lobe and cortical gray matter maturation differently in boys than girls matched for sexual maturity (2011) · cites this paper as Sowell et al. 2001
Citations
Cites
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Brain development during childhood and adolescence: a longitudinal MRI study
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., Paus, T., Evans, A. C., & Rapoport, J. L. (1999) · Nature Neuroscience · doi:10.1038/13158 · Cited by 5,552 · cited 5×
“Using the methods described here, it is possible to find smaller regions of gray matter density gain and loss (or growth and shrinkage) within the same larger lobar regions typically measured in volumetric studies (Jernigan et al., 1991; Reiss et al., 1996; Giedd et al., 1999; Sowell et al., 2001b).”
BackgroundMethodResultInfluentialDiffusion tensor MR imaging of the human brain
Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di Chiro, G. (1996) · Radiology · doi:10.1148/radiology.201.3.8939209 · Cited by 2,664 · cited 2×
“Future studies should also use diffusion tensor imaging (Pierpaoli et al., 1996) as an approach to disentangle increased white matter from synaptic loss, because increased myelination would increase the local diffusion anisotropy, whereas synaptic pruning should not increase the directional…”
BackgroundSynaptic density in human frontal cortex —Developmental changes and effects of aging
Peter R., H. (1979) · Brain Research · doi:10.1016/0006-8993(79)90349-4 · Cited by 2,645 · cited 4×
“It may not be unreasonable to hypothesize that improved accuracy (i.e., improved cognitive task performance) may result from regressive changes such as synaptic pruning, given that unused or less efficient synaptic connections are being pruned away during this age range ( Huttenlocher, 1979 ).”
BackgroundResultInfluential(1967) · Medical Entomology and Zoology · Cited by 1,713
MRI-PET Registration with Automated Algorithm
Woods, R. P., Mazziotta, J. C., & Cherry, A. S. R. (1993) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199307000-00004 · Cited by 1,636 · cited 3×
“MR images from each individual were processed with a series of manual and automated procedures that included the following steps: (1) automated linear transformation (Woods et al., 1993) of the images into a standard orientation with scaling to remove global differences in head size allowing assessment of local change…”
MethodInfluentialA Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development
Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P. T., & Lancaster, J. L. (1995) · NeuroImage · doi:10.1006/nimg.1995.1012 · Cited by 1,578 · cited 1×
“…that is continuously deformed to fit a cortical surface tissue threshold intensity value (signal value that best differentiates cortical CSF on the outer surface of the brain from the underlying cortical gray matter) from the brain volume aligned in standard ICBM-305 space (Mazziotta et al., 1995).”
BackgroundSelf-citationIn vivo evidence for post-adolescent brain maturation in frontal and striatal regions
Sowell, E. R., Thompson, P. M., Holmes, C. J., Jernigan, T. L., & Toga, A. W. (1999) · Nature Neuroscience · doi:10.1038/13154 · Cited by 1,439 · cited 15×
“Because the greatest changes in gray matter density occur in the dorsal frontal cortex between adolescence and adulthood (Sowell et al., 1999a), this was the region that we targeted in the permutation analyses (all gray matter brain tissue anterior to the central sulcus and superior to the axial…”
BackgroundResultInfluentialSelf-citationPfefferbaum, A., Mathalon, D. H., Sullivan, E. V., Rawles, J. M., Zipursky, R. B., & Lim, K. O. (1994) · Archives of Neurology · doi:10.1001/archneur.1994.00540210046012 · Cited by 1,363 · cited 3×
“As shown in Figure 5, between adolescence and adulthood, large, diffuse regions of shrinkage or decreased DFC are observed in frontal and parietal regions surrounding the frontal and temporal growth areas, probably resulting from large increases in cortical CSF known to occur more prominently between adolescence and a…”
BackgroundStructural maturation of neural pathways in children and adolescents: in vivo study
Paus, T., Zijdenbos, A., Worsley, K., Collins, D. L., Blumenthal, J., Giedd, J. N., Rapoport, J. L., & Evans, A. C. (1999) · Science · doi:10.1126/science.283.5409.1908 · Cited by 1,322 · cited 2×
“…cortical gray matter density has been observed primarily in the dorsal parietal and some frontal regions between childhood and adolescence (Sowell et al., 1999b) along with an increase in white matter density in the posterior limb of the internal capsule and arcuate fasciculus (Paus et al., 1999).”
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Metadata
- Authors
- Sowell, E. R., Thompson, P. M., Tessner, K. D., & Toga, A. W.
- Affiliations
- University of California, Los Angeles (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2001-11-15
- Volume
- 21
- Issue
- 22
- Pages
- 8819-8829
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6762261
- OpenAlex
- W2095621691
- Cited by
- 983
- References
- 34
- Citations by year
- 2026: 12 · 2025: 19 · 2024: 24 · 2023: 24 · 2022: 27 · 2021: 34 · 2020: 78 · 2019: 52 · 2018: 35 · 2017: 28 · 2016: 37 · 2015: 51 · 2014: 45 · 2013: 67 · 2012: 50
- FWCI
- 10.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (9601356)
- National Institutes of Health (5t32mh016381-20)
- National Institute of Mental Health (K01 MH 01733, 5-T32-MH16381, K01MH001733, P20 MH/DA52176)
- National Institute of Neurological Disorders and Stroke (NS38753, R01NS038753)
- National Center for Research Resources (P41RR013642, RR 13642, P41 RR13642)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- brain maturation, myelination, synaptic pruning, parietal cortex, executive function, developmental neuroimaging, children, adolescents and young adults
- MeSH terms
- Adolescent, Adult, Aging, Brain, Brain Mapping, Cell Count, Child, Female, Frontal Lobe, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Occipital Lobe, Temporal Lobe
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