Neurophotonics · 2026
Poverty and caregiver mental health are related to infant and toddler resting-state brain networks: insights from fNIRS.
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Jasińska Kaja K, Whitehead Hannah L, Wolf Sharon, Tanoh Fabrice, Bugden Stephanie, Wortsman Brooke, Ogan Amy
Аннотация
SIGNIFICANCE: The first 3 years of life represent a period of heightened neural plasticity, during which early adversity-such as poverty and maternal stress-can shape long-term developmental trajectories. However, little is known about how these adversities are linked to neural network organization in infants and toddlers living in low-resource settings.
AIM: We examined how prenatal exposure to maternal poverty and mental health symptoms relates to neural network organization in early childhood.
APPROACH: We conducted a longitudinal study with 42 children (6 to 36 months old) from economically vulnerable households in rural Côte d'Ivoire. Maternal multidimensional poverty and mental health symptoms were assessed around conception and during pregnancy. Two years later, children's development was measured using the Caregiver Reported Early Development Instruments, and resting-state brain activity was recorded using portable functional near-infrared spectroscopy. Graph-theoretic metrics of functional connectivity, including segregation, integration, and small-worldness, were computed to characterize neural network organization.
RESULTS: Greater exposure to poverty was associated with reduced network segregation and integration. By contrast, higher maternal mental health symptoms were linked to increased segregation and integration. These findings suggest that deprivation and maternal stress differentially relate to early neural network architecture.
CONCLUSIONS: Our results align with dimensional models of adversity and suggest that deprivation (related to poverty) and threat/unpredictability (related to maternal mental health and caregiving) may become biologically embedded. These findings underscore the importance of addressing both structural poverty and maternal mental health during pregnancy and early childhood to promote healthy brain development in high-adversity contexts.
AIM: We examined how prenatal exposure to maternal poverty and mental health symptoms relates to neural network organization in early childhood.
APPROACH: We conducted a longitudinal study with 42 children (6 to 36 months old) from economically vulnerable households in rural Côte d'Ivoire. Maternal multidimensional poverty and mental health symptoms were assessed around conception and during pregnancy. Two years later, children's development was measured using the Caregiver Reported Early Development Instruments, and resting-state brain activity was recorded using portable functional near-infrared spectroscopy. Graph-theoretic metrics of functional connectivity, including segregation, integration, and small-worldness, were computed to characterize neural network organization.
RESULTS: Greater exposure to poverty was associated with reduced network segregation and integration. By contrast, higher maternal mental health symptoms were linked to increased segregation and integration. These findings suggest that deprivation and maternal stress differentially relate to early neural network architecture.
CONCLUSIONS: Our results align with dimensional models of adversity and suggest that deprivation (related to poverty) and threat/unpredictability (related to maternal mental health and caregiving) may become biologically embedded. These findings underscore the importance of addressing both structural poverty and maternal mental health during pregnancy and early childhood to promote healthy brain development in high-adversity contexts.