The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Methods and considerations for longitudinal structural brain imaging analysis across development
Open accessAbstract
Magnetic resonance imaging (MRI) has allowed the unprecedented capability to measure the human brain in vivo. This technique has paved the way for longitudinal studies exploring brain changes across the entire life span. Results from these studies have given us a glimpse into the remarkably extended and multifaceted development of our brain, converging with evidence from anatomical and histological studies. Ever-evolving techniques and analytical methods provide new avenues to explore and questions to consider, requiring researchers to balance excitement with caution. This review addresses what MRI studies of structural brain development in children and adolescents typically measure and how. We focus on measurements of brain morphometry (e.g., volume, cortical thickness, surface area, folding patterns), as well as measurements derived from diffusion tensor imaging (DTI). By integrating finding from multiple longitudinal investigations, we give an update on current knowledge of structural brain development and how it relates to other aspects of biological development and possible underlying physiological mechanisms. Further, we review and discuss current strategies in image processing, analysis techniques and modeling of brain development. We hope this review will aid current and future longitudinal investigations of brain development, as well as evoke a discussion amongst researchers regarding best practices.
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Cited by
Tamnes, C. K., Herting, M. M., Goddings, A.-L., Meuwese, R., Blakemore, S.-J., Dahl, R. E., Güroğlu, B., Raznahan, A., Sowell, E. R., Crone, E. A., et al. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3302-16.2017 · Cited by 685
Self-citationInvestigating white matter fibre density and morphology using fixel-based analysis.
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“However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability.”
BackgroundInfluentialMills, K. L., Goddings, A.-L., Herting, M. M., Meuwese, R., Blakemore, S.-J., Crone, E. A., Dahl, R. E., Güroğlu, B., Raznahan, A., Sowell, E. R., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.044 · Cited by 600
Self-citationPuberty and the human brain: insights into adolescent development
Vijayakumar, N., Op de Macks, Z., Shirtcliff, E. A., & Pfeifer, J. H. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.06.004 · Cited by 437
Studying individual differences in human adolescent brain development
Foulkes, L., & Blakemore, S.-J. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0078-4 · Cited by 413
Metadata
- Authors
- Mills, K. L., & Tamnes, C. K.
- Venue
- Developmental Cognitive Neuroscience
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 9
- Pages
- 172-190
- ISSN
- 1878-9293 (ISSN-L)
- OpenAlex
- W2069239049
- Cited by
- 266
- References
- 42
- FWCI
- 16.84
- Type
- journal article
- Language
- en
- Open access
- gold
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