Individualized prediction of future cognition based on developmental changes in cortical anatomy
Predictive modeling studies have started to reveal brain measures underlying cognition; however, most studies are based on cross-sectional data (brain measures acquired at one time point). Since brain development comprises of continuously ongoing events leading to cognitive development, predictive m...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
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| Series: | NeuroImage: Reports |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666956022000514 |
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| Summary: | Predictive modeling studies have started to reveal brain measures underlying cognition; however, most studies are based on cross-sectional data (brain measures acquired at one time point). Since brain development comprises of continuously ongoing events leading to cognitive development, predictive modeling studies need to consider ‘longitudinal brain change’ as opposed to ‘cross-sectional brain measures’. Using longitudinal neuroimaging and cognitive data (global executive composite score, an index of executive function) from 82 individuals (aged 5–14 years, scanned 3 times), we built highly accurate prediction models (r = 0.61, p = 1.6e-09) of future cognition (assessed at visit 3) based on developmental changes in cortical anatomy (from visit 1 to 2). More importantly, longitudinal brain change (i.e. change in cortical anatomy from visit 1 to 2) and cross-sectional brain measures (cortical anatomy at visit 1 and 2) were critical for predicting future cognition, suggesting the need for considering longitudinal brain change in predicting cognitive outcomes. |
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| ISSN: | 2666-9560 |