Journal article
Maturational networks of human fetal brain activity reveal emerging connectivity patterns prior to ex-utero exposure
- Abstract:
- A key feature of the fetal period is the rapid emergence of organised patterns of spontaneous brain activity. However, characterising this process in utero using functional MRI is inherently challenging and requires analytical methods which can capture the constituent developmental transformations. Here, we introduce a novel analytical framework, termed “maturational networks” (matnets), that achieves this by modelling functional networks as an emerging property of the developing brain. Compared to standard network analysis methods that assume consistent patterns of connectivity across development, our method incorporates age-related changes in connectivity directly into network estimation. We test its performance in a large neonatal sample, finding that the matnets approach characterises adult-like features of functional network architecture with a greater specificity than a standard group-ICA approach; for example, our approach is able to identify a nearly complete default mode network. In the in-utero brain, matnets enables us to reveal the richness of emerging functional connections and the hierarchy of their maturational relationships with remarkable anatomical specificity. We show that the associative areas play a central role within prenatal functional architecture, therefore indicating that functional connections of high-level associative areas start emerging prior to exposure to the extra-utero environment.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 11.7MB, Terms of use)
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- Publisher copy:
- 10.1038/s42003-023-04969-x
Authors
- Publisher:
- Springer Nature
- Journal:
- Communications Biology More from this journal
- Volume:
- 6
- Issue:
- 1
- Article number:
- 661
- Place of publication:
- England
- Publication date:
- 2023-06-22
- Acceptance date:
- 2023-05-23
- DOI:
- EISSN:
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2399-3642
- Pmid:
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37349403
- Language:
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English
- Keywords:
- Subjects:
- Pubs id:
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1490162
- Local pid:
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pubs:1490162
- Deposit date:
-
2023-09-08
Terms of use
- Copyright holder:
- Karolis et al.
- Copyright date:
- 2023
- Rights statement:
- © The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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