0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Fetal, infant, and toddler (FIT) neuroimaging researchers study early brain development to gain insights into neurodevelopmental processes and identify early markers of neurobiological vulnerabilities to target for intervention. However, the field has historically excluded people from global majority countries and from marginalized communities in FIT neuroimaging research. Inclusive and representative samples are essential for generalizing findings across neuroimaging modalities, such as magnetic resonance imaging, magnetoencephalography, electroencephalography, functional near-infrared spectroscopy, and cranial ultrasonography. These FIT neuroimaging techniques pose unique and overlapping challenges to equitable representation in research through sampling bias, technical constraints, limited accessibility, and insufficient resources. The present article adds to the conversation around the need to improve inclusivity by highlighting modality-specific historical and current obstacles and ongoing initiatives. We conclude by discussing tangible solutions that transcend individual modalities, ultimately providing recommendations to promote equitable FIT neuroscience.

          Related collections

          Most cited references171

          • Record: found
          • Abstract: not found
          • Article: not found

          Most people are not WEIRD.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology.

            This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy- and deoxyhemoglobin and approaches for data analysis are also reviewed. From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects. Copyright © 2013 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Brain charts for the human lifespan

              Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. MRI data from more than 100 studies have been aggregated to yield new insights about brain development and ageing, and create an interactive open resource for comparison of brain structures throughout the human lifespan, including those associated with neurological and psychiatric disorders.
                Bookmark

                Author and article information

                Contributors
                Journal
                Dev Cogn Neurosci
                Dev Cogn Neurosci
                Developmental Cognitive Neuroscience
                Elsevier
                1878-9293
                1878-9307
                03 January 2025
                April 2025
                03 January 2025
                : 72
                : 101505
                Affiliations
                [a ]Department of Psychology, Northeastern University, Boston, MA, USA
                [b ]Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA
                [c ]Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA
                [d ]Department of Psychology, Lancaster University, Lancaster, UK
                [e ]Department of Neuroscience, Psychology and Pharmacology, University College London, UK
                [f ]Centre for the Developing Brain, King’s College London, UK
                [g ]McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
                [h ]Research Institute of the McGill University Health Centre, McGill University, Montreal QC, Canada
                [i ]Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
                [j ]School of Psychology, Trinity College Dublin, Dublin 2, Ireland
                [k ]Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
                [l ]Department of Human Development, Teachers College, Columbia University, NY, United States
                [m ]Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, Cape Town
                [n ]The Neuroscience Institute, University of Cape Town, Cape Town, South Africa
                [o ]Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
                [p ]Fralin Biomedical Research Institute at VTC, Roanoke, VA, USA
                [q ]Department of Human Development and Family Science, Virginia Tech, Blacksburg, VA, USA
                [r ]Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
                [s ]Department of Biomedical Engineering, Yale University, New Haven, CT, United States
                [t ]Department of Statistics & Data Science, Yale University, New Haven, CT, United States
                [u ]Child Study Center, Yale School of Medicine, New Haven, CT, United States
                [v ]Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA
                Author notes
                [* ]Corresponding author. marta.korom@ 123456nih.gov
                [1]

                Equal contributions

                Article
                S1878-9293(24)00166-X 101505
                10.1016/j.dcn.2024.101505
                11875194
                39954600
                56a87986-48f7-4e2a-99a5-e9d799ed385d

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 21 September 2024
                : 20 December 2024
                : 30 December 2024
                Categories
                Original Research

                Neurosciences
                fetal, infant, toddler,neuroimaging,brain development,diversity,inclusive representation,recruitment

                Comments

                Comment on this article