Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2

Author:

Xu Yuehua1234,Liao Xuhong13,Lei Tianyuan234,Cao Miao5,Zhao Jianlong234,Zhang Jiaying234,Zhao Tengda234,Li Qiongling234,Jeon Tina6,Ouyang Minhui67,Chalak Lina8,Rollins Nancy9,Huang Hao67,He Yong23410

Affiliation:

1. School of Systems Science, Beijing Normal University , No. 19 Xinjiekouwai Street, Beijing 100875 , China

2. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University , No. 19 Xinjiekouwai Street, Beijing 100875 , China

3. Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University , No. 19 Xinjiekouwai Street, Beijing 100875 , China

4. IDG/McGovern Institute for Brain Research, Beijing Normal University , No. 19 Xinjiekouwai Street, Beijing 100875 , China

5. Institution of Science and Technology for Brain-Inspired Intelligence, Fudan University , No. 220 Handan Road, Shanghai 200433 , China

6. Department of Radiology, Children’s Hospital of Philadelphia , 3401 Civic Center Blvd, Philadelphia, PA 19104 , United States

7. Department of Radiology, University of Pennsylvania , 3400 Spruce Street, Philadelphia, PA 19104 , United States

8. Department of Pediatrics, University of Texas Southwestern Medical Center , 5323 Harry Hines Blvd, Dallas, TX 75390 , United States

9. Department of Radiology, University of Texas Southwestern Medical Center , 5323 Harry Hines Blvd, Dallas, TX 75390 , United States

10. Chinese Institute for Brain Research , No. 26 Kexueyuan Road, Beijing 102206 , China

Abstract

Abstract The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

Funder

Science, Technology and Innovation

Natural Science Foundation of China

Tang Scholar Award of Beijing Normal University

National Institute of Health

Publisher

Oxford University Press (OUP)

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