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Imaging patterns of brain development and their relationship to cognition
Guray Erus1, Harsha Battapady1, Theodore D Satterthwaite2
1Section of Biomedical Image Analysis, Department of Radiology, and Center for Biomedical Image Computing and Analytics.
We developed a brain development index (BDI) using machine learning to track brain maturation. This index accurately reflects brain development and predicts cognitive processing speed in adolescents and young adults.
Area of Science:
- Neuroscience
- Developmental Neuroscience
- Neuroimaging
Background:
- Brain development is a complex process involving structural maturation.
- Understanding individual variations in brain development is crucial for identifying cognitive differences.
Purpose of the Study:
- To introduce a novel Brain Development Index (BDI) for summarizing brain maturation.
- To investigate the relationship between the BDI and cognitive performance.
Main Methods:
- Utilized machine learning to create a single-dimension BDI from complex neuroimaging data.
- Analyzed data from 621 participants aged 8-22 in the Philadelphia Neurodevelopmental Cohort.
- Correlated BDI with chronological age and cognitive processing speed.
Main Results:
- The BDI showed a high correlation (r = 0.89) with chronological age, indicating a consistent developmental trajectory.
- Deviations from the expected BDI trajectory were linked to cognitive performance.
- Individuals with a higher BDI than chronological age exhibited superior cognitive processing speed.
Conclusions:
- The BDI effectively summarizes multiparametric neuroimaging patterns of brain development.
- The BDI can identify individuals with advanced or delayed cognitive development relative to their age.
- Brain maturation trajectories delineated by the BDI have implications for understanding cognitive precocity and delay.
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