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Networks of anatomical covariance
Abstract
Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.
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“Microscopic alterations in brain volume and anisotropy can be caused by changes in synaptogenesis, neuronal morphology, fiber density, and axonal branching as well as by extraneuronal changes, such as glial cell number or angiogenesis (65).”
From Neuroanatomic differences associated with stress susceptibility and resilience (2016) · cites this paper as [65]
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“Although changes in the cellular organization of a specific brain region can result from the molecular processes after neuronal activity (65,68)”
From Neuroanatomic differences associated with stress susceptibility and resilience (2016) · cites this paper as [65]
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Metadata
- Authors
- Evans, A. C.
- Affiliations
- Montreal Neurological Institute and Hospital (CA)
- Corresponding author
- Evans, Alan C.
- ORCID
- Evans, Alan C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 489-504
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2081828863
- Cited by
- 429
- References
- 261
- Citations by year
- 2026: 35 · 2025: 28 · 2024: 29 · 2023: 34 · 2022: 30 · 2021: 43 · 2020: 38 · 2019: 29 · 2018: 41 · 2017: 34 · 2016: 33 · 2015: 36 · 2014: 15 · 2013: 4
- FWCI
- 2.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- brain connectivity, morphometrics, anatomical MRI, brain development, brain aging, experience-dependent plasticity, brain disorders
- MeSH terms
- Animals, Brain, Brain Diseases, Humans, Models, Anatomic, Models, Neurological, Nerve Net, Models, Statistical, Connectome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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