The DOI matches its Crossref record; 48 of the 49 references it cites were found in a registry or an index.
Sex Differences in Brain Maturation during Childhood and Adolescence
Abstract
Brain development during childhood and adolescence is characterized by both progressive myelination and regressive pruning processes. However, sex differences in brain maturation remain poorly understood. Magnetic resonance imaging was used to examine the relationships between age and sex with cerebral gray and white matter volumes and corpus callosal areas in 118 healthy children and adolescents (61 males and 57 females), aged 6-17 years. Gender groups were similar on measures of age, handedness, socioeconomic status and Full Scale IQ. Significant age-related reductions in cerebral gray and increases in white matter volumes and corpus callosal areas were evident, while intracranial and cerebral volumes did not change significantly. Significant sex by age interactions were seen for cerebral gray and white matter volumes and corpus callosal areas. Specifically, males had more prominent age-related gray matter decreases and white matter volume and corpus callosal area increases compared with females. While these data are from a cross-sectional sample and need to be replicated in a longitudinal study, the findings suggest that there are age-related sex differences in brain maturational processes. The study of age-related sex differences in cerebral pruning and myelination may aid in understanding the mechanism of several developmental neuropsychiatric disorders.
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In the citing paper
“To limit treatment‐related variability and inherent sex differences in brain development (De Bellis et al., 2001; Gur et al., 1999; Lange, Giedd, Castellanos, Vaituzis, & Rapoport, 1997; Kang, Herron, & Woods, 2011), while maximizing eligible participants, we restricted this study to males only.”
From Brain structure, working memory and response inhibition in childhood leukemia survivors (2017) · cites this paper as De Bellis et al., 2001
In the citing paper
“Firstly, sex is known to modulate brain development (De Bellis et al., 2001; Gur et al., 1999; Lange et al., 1997; Kang et al., 2011) so that manifestation of late effects at any given age may depend on sex (Anderson & Kunin‐Batson, 2009; Buizer, de Sonneville, van den Heuvel‐Eibrink, & Veerman, 2005).”
From Brain structure, working memory and response inhibition in childhood leukemia survivors (2017) · cites this paper as De Bellis et al., 2001
In the citing paper
“Sex differences in applying the model learned from one sex on another support multiple studies suggesting earlier maturation in females (De Bellis et al. 2001;Lenroot et al. 2007).”
From Imaging Patterns of Brain Development and their Relationship to Cognition (2015) · cites this paper as De Bellis et al. 2001
In the citing paper
“We validated the sensitivity of this index to the well-established sex difference in maturation, which is earlier in females (De Bellis et al. 2001;Lenroot et al. 2007), by applying the male predictors to the female sample and vice versa.”
From Imaging Patterns of Brain Development and their Relationship to Cognition (2015) · cites this paper as De Bellis et al. 2001
In the citing paper
“In addition to age, pubertal status and hormone titers significantly interact with sex to affect white matter volume in multiple tracts in the human brain, including those connecting higher association cortices (Asato et al., 2010; Chavarria et al., 2014; De Bellis et al., 2001; Herting et al., 2012; Peper et al., 2008; Perrin et al., 2008; Perrin et al., 2009).”
From Does puberty mark a transition in sensitive periods for plasticity in the associative neocortex? (2017) · cites this paper as De Bellis et al., 2001
In the citing paper
“When controlling for age, both pubertal hormones and stage of puberty correlate with changes in gray matter across adolescent development in disparate regions of cortex (De Bellis et al., 2001), including in the frontal cortex (Bramen et al., 2011; Gogtay et al., 2004; Herting et al., 2014; Herting et al., 2015; Koolschijn et al., 2014; Neufang et al., 2009; Peper et al., 2009a; Raznahan et al., 2”
From Does puberty mark a transition in sensitive periods for plasticity in the associative neocortex? (2017) · cites this paper as De Bellis et al., 2001
Citations
Cites
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Brain development during childhood and adolescence: a longitudinal MRI study
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Variations in the pattern of pubertal changes in boys
Marshall, W. A., & Tanner, J. M. (1970) · Archives of Disease in Childhood · doi:10.1136/adc.45.239.13 · Cited by 5,147
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Decreased Dendritic Spine Density on Prefrontal Cortical Pyramidal Neurons in Schizophrenia
Glantz, L. A., & Lewis, D. A. (2000) · Archives of General Psychiatry · doi:10.1001/archpsyc.57.1.65 · Cited by 1,636
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Why do many psychiatric disorders emerge during adolescence?
Paus, T., Keshavan, M., & Giedd, J. N. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2513 · Cited by 3,123
Unbiased average age-appropriate atlases for pediatric studies
Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.033 · Cited by 2,290
“…al., 1996; Lange et al., 1997; Kennedy et al., 1998, 2003; Paus et al., 1999; Sowell et al., 1999, 2002, 2003, 2004a,b; Courchesne et al., 2000; Bartzokis et al., 2001; Blanton et al., 2001, 2004; De Bellis et al., 2001; Durston et al., 2001; Mazziotta et al., 2001a,b; Gogtay et al., 2002, 2004).”
Trajectories of brain development: point of vulnerability or window of opportunity?
Andersen, S. L. (2003) · Neuroscience & Biobehavioral Reviews · doi:10.1016/s0149-7634(03)00005-8 · Cited by 1,503
“[47] De Bellis MD, Keshavan MS, Beers SR, Hall J, Frustaci K, Masalehdan A, Noll J, Boring AM.”
BackgroundSexual dimorphism of brain developmental trajectories during childhood and adolescence
Lenroot, R. K., Gogtay, N., Greenstein, D. K., Wells, E. M., Wallace, G. L., Clasen, L. S., Blumenthal, J. D., Lerch, J., Zijdenbos, A. P., Evans, A. C., et al. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.053 · Cited by 1,309
“In a cross-sectional sample of 118 healthy children and adolescents growth rates were faster in males than females for total gray and white matter volumes and the area of the corpus callosum (De Bellis et al., 2001).”
A meta-analysis of sex differences in human brain structure
Ruigrok, A. N. V., Salimi-Khorshidi, G., Lai, M.-C., Baron-Cohen, S., Lombardo, M. V., Tait, R. J., & Suckling, J. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.12.004 · Cited by 1,192
Metadata
- Authors
- De Bellis, M. D.
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-06-01
- Volume
- 11
- Issue
- 6
- Pages
- 552-557
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2119268056
- Cited by
- 728
- References
- 49
- Citations by year
- 2026: 10 · 2025: 26 · 2024: 28 · 2023: 20 · 2022: 28 · 2021: 31 · 2020: 27 · 2019: 42 · 2018: 36 · 2017: 29 · 2016: 34 · 2015: 31 · 2014: 36 · 2013: 39 · 2012: 32
- FWCI
- 14.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cerebral Cortex (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1r03mh043687-01)
- National Institute on Alcohol Abuse and Alcoholism (AA08746-08, P50AA008746)
- National Institute of Mental Health (P01MH041712, MH-41712, K08MH001324, MH 01180, 5 K08 MHO1324-02, MH-43687, K02MH001180)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- sex differences, brain maturation, brain development, childhood, adolescence, gray matter volume, white matter volume, corpus callosum, myelination, synaptic pruning, intracranial volume
- MeSH terms
- Adolescent, Age Factors, Brain, Child, Female, Humans, Magnetic Resonance Imaging, Male, Myelin Sheath, Puberty, Sex Characteristics, Linear Models
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