Implementing neuroimaging and eye tracking methods to assess neurocognitive development of young infants in low- and middle-income countries.

EEG eye tracking fNIRS global health infancy low-and middle-income countries (LMIC) neurocognitive development

Journal

Gates open research
ISSN: 2572-4754
Titre abrégé: Gates Open Res
Pays: United States
ID NLM: 101717821

Informations de publication

Date de publication:
2019
Historique:
accepted: 01 08 2019
entrez: 12 9 2019
pubmed: 12 9 2019
medline: 12 9 2019
Statut: epublish

Résumé

Infants and children in low- and middle-income countries (LMICs) are frequently exposed to a range of environmental risk factors which may negatively affect their neurocognitive development. The mechanisms by which factors such as undernutrition and poverty impact development and cognitive outcomes in early childhood are poorly understood. This lack of knowledge is due in part to a paucity of objective assessment tools which can be implemented across different cultural settings and in very young infants. Over the last decade, technological advances, particularly in neuroimaging, have opened new avenues for research into the developing human brain, allowing us to investigate novel biological associations. This paper presents functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG) and eye tracking (ET) as objective, cross-cultural methods for studying infant neurocognitive development in LMICs, and specifically their implementation in rural Gambia, West Africa. These measures are currently included, as part of a broader battery of assessments, in the Brain Imaging for Global Health (BRIGHT) project, which is developing brain function for age curves in Gambian and UK infants from birth to 24 months of age. The BRIGHT project combines fNIRS, EEG and ET with behavioural, growth, health and sociodemographic measures. The implementation of these measures in rural Gambia are discussed, including methodological and technical challenges that needed to be addressed to ensure successful data acquisition. The aim is to provide guidance to other groups seeking to implement similar methods in their research in other LMICs to better understand associations between environmental risk and early neurocognitive development.

Identifiants

pubmed: 31508580
doi: 10.12688/gatesopenres.12951.2
pmc: PMC6719506
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1113

Subventions

Organisme : Medical Research Council
ID : G0400120
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P012019/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U123292701
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0300025
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0701458
Pays : United Kingdom

Déclaration de conflit d'intérêts

No competing interests were disclosed.

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Auteurs

Laura Katus (L)

Great Ormond Street Institute of Child Health, University College London, London, London, WC1N 1EH, UK.

Nathan J Hayes (NJ)

GKT School of Medical Education, King's College London, London, UK.

Luke Mason (L)

Centre for Brain and Cognitive Development, Birkbeck University of London, London, UK.

Anna Blasi (A)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Samantha McCann (S)

Department of Women and Children's Health, King's College London, London, UK.

Momodou K Darboe (MK)

Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, The Gambia, The Gambia.

Michelle de Haan (M)

Great Ormond Street Institute of Child Health, University College London, London, London, WC1N 1EH, UK.
Great Ormond Street Hospital for Children, London, UK.

Sophie E Moore (SE)

Department of Women and Children's Health, King's College London, London, UK.
Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, The Gambia, The Gambia.

Sarah Lloyd-Fox (S)

Centre for Brain and Cognitive Development, Birkbeck University of London, London, UK.
Department of Psychology, University of Cambridge, Cambridge, UK.

Clare E Elwell (CE)

Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Classifications MeSH