| Title |
A voxel-based morphometric study of age- and sex-related changes in white matter volume in the normal aging brain
|
|---|---|
| Published in |
Neuropsychiatric Disease and Treatment, February 2016
|
| DOI | 10.2147/ndt.s90674 |
| Pubmed ID | |
| Authors |
Haijing Liu, Lixin Wang, Zuojun Geng, Qingfeng Zhu, Zhenhu Song, Ruiting Chang, Huandi Lv |
| Abstract |
To carry out a cross-sectional study of 187 cognitively normal Chinese adults using the voxel-based morphometry (VBM) approach to delineate age-related changes in the white matter volume of regions of interest in the brain and further analyze their correlation with age. A total of 187 cognitively normal adults were divided into the young, middle, and old age-groups. Conventional magnetic resonance imaging was performed with the Achieva 3.0 T system. Structural images were processed using VBM8 and statistical parametric mapping 8. Regions of interest were obtained by WFU PickAtlas, and all realigned images were spatially normalized. Females showed significantly greater total white matter volume than males (t=2.36, P=0.0096, false-discovery rate [FDR] corrected). VBM demonstrated statistically significant age-related differences in white matter volume between the young age-group and the middle age-group (P<0.05, FDR corrected) and between the middle age-group and the old age-group (P<0.05, FDR corrected). No interaction was found between age and sex on white matter volume (P<0.05, FDR corrected). Logistic regression analysis revealed nonlinear correlation between total white matter volume and age (R (2)=0.124, P<0.001). White matter volume gradually increased before 40 years of age, peaked around 50 years of age, and rapidly declined after 60 years of age. Significant age-related differences are present in white matter volume across multiple brain regions during aging. The VBM approach may help differentiate underlying normal neurobiological aging changes of specific brain regions from neurodegenerative impairments. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 1% |
| Unknown | 68 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 22% |
| Student > Bachelor | 7 | 10% |
| Student > Doctoral Student | 7 | 10% |
| Student > Ph. D. Student | 7 | 10% |
| Student > Master | 7 | 10% |
| Other | 9 | 13% |
| Unknown | 17 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 9 | 13% |
| Medicine and Dentistry | 8 | 12% |
| Psychology | 8 | 12% |
| Agricultural and Biological Sciences | 6 | 9% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Other | 14 | 20% |
| Unknown | 20 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 March 2016.
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#3,450,818
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Outputs from Neuropsychiatric Disease and Treatment
#497
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Outputs of similar age
#57,388
of 407,504 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#20
of 71 outputs
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