Early deprivation alters structural brain development from middle childhood to adolescence

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Abstract

Hypotheses concerning the biologic embedding of early adversity via developmental neuroplasticity mechanisms have been proposed on the basis of experimental studies in animals. However, no studies have demonstrated a causal link between early adversity and neural development in humans. Here, we present evidence from a randomized controlled trial linking psychosocial deprivation in early childhood to changes in cortical development from childhood to adolescence using longitudinal data from the Bucharest Early Intervention Project. Changes in cortical structure due to randomization to foster care were most pronounced in the lateral and medial prefrontal cortex and in white matter tracts connecting the prefrontal and parietal cortex. Demonstrating the causal impact of exposure to deprivation on the development of neural structure highlights the importance of early placement into family-based care to mitigate lasting neurodevelopmental consequences associated with early-life deprivation.

Abstract

An RCT demonstrates that early-life deprivation alters patterns of neural development from childhood to adolescence.

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Most cited references 84

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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Yoav Benjamini, Yosef Hochberg (1995)

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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Rahul Desikan, Florent Ségonne, Bruce Fischl … (2006)

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

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A hybrid approach to the skull stripping problem in MRI.

F Ségonne, A M Dale, E. Busa … (2004)

We present a novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models. Our method takes advantage of the robustness of the former as well as the surface information available to the latter. The algorithm first localizes a single white matter voxel in a T1-weighted MRI image, and uses it to create a global minimum in the white matter before applying a watershed algorithm with a preflooding height. The watershed algorithm builds an initial estimate of the brain volume based on the three-dimensional connectivity of the white matter. This first step is robust, and performs well in the presence of intensity nonuniformities and noise, but may erode parts of the cortex that abut bright nonbrain structures such as the eye sockets, or may remove parts of the cerebellum. To correct these inaccuracies, a surface deformation process fits a smooth surface to the masked volume, allowing the incorporation of geometric constraints into the skull-stripping procedure. A statistical atlas, generated from a set of accurately segmented brains, is used to validate and potentially correct the segmentation, and the MRI intensity values are locally re-estimated at the boundary of the brain. Finally, a high-resolution surface deformation is performed that accurately matches the outer boundary of the brain, resulting in a robust and automated procedure. Studies by our group and others outperform other publicly available skull-stripping tools. Copyright 2004 Elsevier Inc.

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Author and article information

Contributors

Margaret A. Sheridan:

ORCID: https://orcid.org/0000-0002-0745-4342

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Cora E. Mukerji:

ORCID: https://orcid.org/0000-0003-0132-5299

Role: VisualizationRole: Writing - original draftRole: Writing - review & editing

Mark Wade: Role: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing - review & editing

Kathryn L. Humphreys:

ORCID: https://orcid.org/0000-0002-5715-6597

Role: Data curationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draftRole: Writing - review & editing

Kathryn Garrisi:

ORCID: https://orcid.org/0000-0002-4808-8836

Role: MethodologyRole: Visualization

Srishti Goel:

ORCID: https://orcid.org/0000-0003-4697-8840

Role: Formal analysis

Kinjal Patel:

ORCID: https://orcid.org/0000-0003-2829-906X

Role: Formal analysisRole: MethodologyRole: Visualization

Nathan A. Fox: Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draftRole: Writing - review & editing

Charles H. Zeanah: Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing - original draftRole: Writing - review & editing

Charles A. Nelson: Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - original draftRole: Writing - review & editing

Katie A. McLaughlin:

ORCID: https://orcid.org/0000-0002-1362-2410

Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - original draftRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): sciadv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: October 2022

Publication date (Electronic, pub): 07 October 2022

Volume: 8

Issue: 40

Electronic Location Identifier: eabn4316

Affiliations

[ ¹ ]Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, 235 E. Cameron Street, Chapel Hill, NC 27599, USA.

[ ² ]Department of Psychology, Bryn Mawr College, 101 North Merion Ave, Bryn Mawr, PA 19010, USA.

[ ³ ]Division of Developmental Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, USA.

[ ⁴ ]University of Toronto, Department of Applied Psychology and Human Development, 252 Bloor St. West, Toronto, ON M5S 1V6, Canada.

[ ⁵ ]Department of Psychology and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA.

[ ⁶ ]Department of Psychology, Yale University, Box 208205, New Haven, CT 06520-8205, USA.

[ ⁷ ]Department of Human Development, University of Maryland, College Park, MD 20740, USA.

[ ⁸ ]Department of Psychiatry and Behavioral Sciences, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA 70112, USA.

[ ⁹ ]Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.

[ ¹⁰ ]Harvard Graduate School of Education, 13 Appian Way, Cambridge, MA 02138, USA.

[ ¹¹ ]Department of Psychology, Harvard University, 33 Kirkland St, Cambridge, MA, 02138, USA.

Author notes

[* ]Corresponding author. Email: sheridan.margaret@ 123456unc.edu

Author information

Margaret A. Sheridan https://orcid.org/0000-0002-0745-4342

Cora E. Mukerji https://orcid.org/0000-0003-0132-5299

Kathryn L. Humphreys https://orcid.org/0000-0002-5715-6597

Kathryn Garrisi https://orcid.org/0000-0002-4808-8836

Srishti Goel https://orcid.org/0000-0003-4697-8840

Kinjal Patel https://orcid.org/0000-0003-2829-906X

Katie A. McLaughlin https://orcid.org/0000-0002-1362-2410

Article

Publisher ID: abn4316

DOI: 10.1126/sciadv.abn4316

PMC ID: 9544316

PubMed ID: 36206331

SO-VID: e78c4afb-b985-4eeb-9e2b-62e642dc2bad

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

History

Date received : 25 November 2021

Date accepted : 24 August 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;

Award ID: RO1-MH091363

Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;

Award ID: KO1-MH092555

Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;

Award ID: RO1-MH115004

Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;

Award ID: K01-MH092526

Funded by: FundRef http://dx.doi.org/10.13039/100000870, John D. and Catherine T. MacArthur Foundation;

Award ID: N/A

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Early deprivation alters structural brain development from middle childhood to adolescence

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Fracture and Structural Integrity

Most cited references 84

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

A hybrid approach to the skull stripping problem in MRI.

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Cited by 8

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