Early development of structural networks and the impact of prematurity on brain connectivity
- Submitting institution
-
King's College London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 97628728
- Type
- D - Journal article
- DOI
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10.1016/j.neuroimage.2017.01.065
- Title of journal
- NeuroImage
- Article number
- -
- First page
- 379
- Volume
- 149
- Issue
- -
- ISSN
- 1053-8119
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- Yes
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
11
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This study combined model-based diffusion MRI analysis and graph theoretical approaches and is the first characterisation of the preterm brain network weighted by microstructural features. The analyses were undertaken at different levels of network density (from 0.05 -0.5) and the findings were consistent over this wide range. Our approach ensured a reduced amount of false positive connections, which maximises reproducibility. These methods have identified impaired brain development in infants with Congenital Heart Disease (e.g. DOI: 10.1016/j.nicl.2020.102423) and were included in a successful MRC programme proposal (£3.3 million MR/V002465/1) to study other cohorts of at-risk infants.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -