Poster No:
1974
Submission Type:
Abstract Submission
Authors:
Ruolin Li1,2, Tianjia Zhu1,2, Ziqin Zhang1,2, Kay Sindabizera1, Yuhan Chen1, J. Christopher Edgar1, Minhui Ouyang1,3, Hao Huang4,3
Institutions:
1Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 3Department of Radiology, University of Pennsylvania, Philadelphia, PA, 4Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA
First Author:
Ruolin Li
Department of Radiology, Children's Hospital of Philadelphia|Department of Bioengineering, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Co-Author(s):
Tianjia Zhu
Department of Radiology, Children's Hospital of Philadelphia|Department of Bioengineering, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Ziqin Zhang
Department of Radiology, Children's Hospital of Philadelphia|Department of Bioengineering, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Kay Sindabizera
Department of Radiology, Children's Hospital of Philadelphia
Philadelphia, PA
Yuhan Chen
Department of Radiology, Children's Hospital of Philadelphia
Philadelphia, PA
Minhui Ouyang
Department of Radiology, Children's Hospital of Philadelphia|Department of Radiology, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Hao Huang
Department of Radiology, Children’s Hospital of Philadelphia|Department of Radiology, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Introduction:
During human infancy, the brain undergoes rapid and dynamic changes across multiple dimensions (Ouyang, 2019), including structural, functional, and neurophysiological development (Ouyang, 2024). However, the developmental trajectories of these processes and the interactions between them remain poorly understood. Multi-modal neuroimaging, combining high-resolution structural and diffusion MRI with MEG (Chen, 2023) provides a unique window into both structural and functional maturations of the brain. In this study, we aim to delineate the developmental trajectories of auditory and visual systems, and relationships between human brain structural and functional development during infancy with advanced MRI and MEG techniques.
Methods:
Infant MRI and MEG data acquisition and processing: A total of 364 typically developing infants aged 0 to 24 months were recruited for this study, with 247 infants undergoing brain MRI on a 3.0T Siemens Prisma system. In this study we have processed 102 infants' T1-weighted (MPRAGE, 0.8 mm isotropic) and T2-weighted (SPACE, 0.8 mm isotropic) images, and computed the T1w/T2w ratio maps for assessing myelination maturation. We also processed 96 infants' diffusion MRI data (1.2 mm isotropic) for diffusion tensor and kurtosis fitting through lab internal pipeline (Zhu, 2023), yielding high-resolution maps of mean kurtosis (MK) to capture microstructural development. Regions corresponding to auditory and visual MEG responses were localized using a customized infant brain atlas specifically adapted for this dataset. Additionally, a total of 114 infants' whole-head auditory and visual task-based MEG data were recorded using the Artemis 123™ system (Roberts TP, 2014). All MEG data were processed using Brainstorm and obtained the latency and amplitude measurements from both auditory and visual cortex responses (Otten K, 2024).
Segmented regression analysis and partial correlation: To identify distinct developmental phases in microstructural and functional changes during infancy, we applied segmented regression to detect break points in age-related trajectories of imaging and MEG measures. To examine the relationship between MEG latency and both T1w/T2w ratio and MK, we used partial correlation analysis, controlling for age to isolate the direct associations between structural and functional metrics.
Results:
Schematics of MRI and MEG acquisition processes are shown in Fig. 1A. Multi-contrasts MRI images, T1w/T2w based myelination maps, and cortical MK maps are shown for milestone ages across infancy (Fig. 1B). The latency of the P2 auditory and N1 visual evoked responses are extracted from task-based MEG signals in specific region of interest (ROI). Fig. 2 presents developmental trajectories of T1w/T2w, cortical MK, and MEG latencies. The breakpoint for auditory P2 latency occurs later than for visual N1 latency, reflecting different developmental timelines for auditory and visual functions. In the auditory cortex, breakpoints follow the order: T1w/T2w, cortical MK, and auditory latency, implying an earlier fast-development period in microstructure than auditory function.

·Fig.1. Multi-modal MRI and MEG imaging across infant developmental stages.

·Fig. 2. Age-related changes in T1w/T2w ratio (myelination, top), mean kurtosis (MK, middle), and MEG response (bottom) are shown for the left and right auditory and visual cortices.
Conclusions:
The MEG-based latency maturational trajectories suggest that visual system maturation may precede auditory system maturation. Additionally, cortical cytoarchitecture and auditory/visual development unfold differently. The distinct breakpoints in cytoarchitecture and functional development indicate that cortical myelination occurs before increases in dendritic density (reflected by MK), both of which may facilitate auditory functional development. The negative correlation between cytoarchitecture measures and auditory/visual latencies suggests that cytoarchitecture development is closely linked with functional maturation. More sophisticated analysis on a larger, acquired cohort of subjects with both MRI and MEG is ongoing, other modalities such as functional MRI will also be integrated to provide a more comprehensive functional perspective to the study.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
Novel Imaging Acquisition Methods:
MEG
Multi-Modal Imaging 1
Keywords:
Cortex
MEG
MRI
Myelin
PEDIATRIC
Other - Infant Brain
1|2Indicates the priority used for review
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
I accept
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information.
Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
I am submitting this abstract as an original work to be reproduced. I am available to be the “source party” in an upcoming team and consent to have this work listed on the OSSIG website. I agree to be contacted by OSSIG regarding the challenge and may share data used in this abstract with another team.
Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.
Yes, I have IRB or AUCC approval
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
MEG
Structural MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
FSL
Free Surfer
Other, Please list
-
DiffeoMap
Provide references using APA citation style.
1. Ouyang, M., Dubois, J., Yu, Q., Mukherjee, P. & Huang, H. Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 185, 836–850 (2019).
2. Ouyang, M., Detre, J. A., Hyland, J. L., Sindabizera, K. L., Kuschner, E. S., Edgar, J. C., ... & Huang, H. (2024). Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy. Nat Commun 15, 8944 (2024)
3. Chen, Y., Green, H. L., Putt, M. E., Allison, O., Kuschner, E. S., Kim, M., Blaskey, L., Mol, K., McNamee, M., Bloy, L., Liu, S., Huang, H., Roberts, T. P. L., & Edgar, J. C. (2023). Maturation of auditory cortex neural responses during infancy and toddlerhood. NeuroImage, 275, 120163. https://doi.org/10.1016/j.neuroimage.2023.120163
4. Zhu, T., Ouyang, M., Sindabizera, K., Kim, J. & Huang, H. A robust image analysis pipeline for high fidelity kurtosis and tensor fitting of 1.2mm isotropic infant brain diffusion MRI. International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition (2023)
5. Roberts TP, Paulson DN, Hirschkoff E, Pratt K, Mascarenas A, Miller P, Han M, Caffrey J, Kincade C, Power B, Murray R, Chow V, Fisk C, Ku M, Chudnovskaya D, Dell J, Golembski R, Lam P, Blaskey L, Kuschner E, Bloy L, Gaetz W, Edgar JC. Artemis 123: development of a whole-head infant and young child MEG system. Front Hum Neurosci. 2014 Mar 3;8:99. doi: 10.3389/fnhum.2014.00099. PMID: 24624069; PMCID: PMC3939774.
6. Otten K, Edgar JC, Green HL, Mol K, McNamee M, Kuschner ES, Kim M, Liu S, Huang H, Nordt M, Konrad K, Chen Y. The maturation of infant and toddler visual cortex neural activity and associations with fine motor performance. bioRxiv [Preprint]. 2024 Jun 11:2024.06.11.598480. doi: 10.1101/2024.06.11.598480. PMID: 38915536; PMCID: PMC11195154.
No