scholarly journals Growth faltering is associated with altered brain functional connectivity and cognitive outcomes in urban Bangladeshi children exposed to early adversity

BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Wanze Xie ◽  
Sarah K. G. Jensen ◽  
Mark Wade ◽  
Swapna Kumar ◽  
Alissa Westerlund ◽  
...  
Keyword(s):  
Cognitive Development ◽  
Functional Connectivity ◽  
Path Analysis ◽  
Indirect Effect ◽  
Child Growth ◽  
Cognitive Outcomes ◽  
Physical Growth ◽  
Frequency Bands ◽  
Eeg Data ◽  
Brain Functional Connectivity

Abstract Background Stunting affects more than 161 million children worldwide and can compromise cognitive development beginning early in childhood. There is a paucity of research using neuroimaging tools in conjunction with sensitive behavioral assays in low-income settings, which has hindered researchers’ ability to explain how stunting impacts brain and behavioral development. We employed high-density EEG to examine associations among children’s physical growth, brain functional connectivity (FC), and cognitive development. Methods We recruited participants from an urban impoverished neighborhood in Dhaka, Bangladesh. One infant cohort consisted of 92 infants whose height (length) was measured at 3, 4.5, and 6 months; EEG data were collected at 6 months; and cognitive outcomes were assessed using the Mullen Scales of Early Learning at 27 months. A second, older cohort consisted of 118 children whose height was measured at 24, 30, and 36 months; EEG data were collected at 36 months; and Intelligence Quotient (IQ) scores were assessed at 48 months. Height-for-age (HAZ) z-scores were calculated based on the World Health Organization standard. EEG FC in different frequency bands was calculated in the cortical source space. Linear regression and longitudinal path analysis were conducted to test the associations between variables, as well as the indirect effect of child growth on cognitive outcomes via brain FC. Results In the older cohort, we found that HAZ was negatively related to brain FC in the theta and beta frequency bands, which in turn was negatively related to children’s IQ score at 48 months. Longitudinal path analysis showed an indirect effect of HAZ on children’s IQ via brain FC in both the theta and beta bands. There were no associations between HAZ and brain FC or cognitive outcomes in the infant cohort. Conclusions The association observed between child growth and brain FC may reflect a broad deleterious effect of malnutrition on children’s brain development. The mediation effect of FC on the relation between child growth and later IQ provides the first evidence suggesting that brain FC may serve as a neural pathway by which biological adversity impacts cognitive development.

scholarly journals Child Growth Predicts Brain Functional Connectivity and Future Cognitive Outcomes in Urban Bangladeshi Children Exposed to Early Adversities

2018 ◽  
Author(s):  
Wanze Xie ◽  
Sarah K.G. Jensen ◽  
Mark Wade ◽  
Swapna Kumar ◽  
Alissa Westerlund ◽  
...  
Keyword(s):  
Early Childhood ◽  
Cognitive Development ◽  
Functional Connectivity ◽  
Low Income ◽  
Child Growth ◽  
Cognitive Outcomes ◽  
Physical Growth ◽  
Growth Faltering ◽  
Iq Scores ◽  
Brain Functional Connectivity

AbstractBackgroundFaltered growth has been shown to affect 161 million children worldwide and derail cognitive development from early childhood. The neural pathways by which growth faltering in early childhood affects future cognitive outcomes remain unclear, which is partially due to the scarcity of research using both neuroimaging and sensitive behavioral techniques in low-income settings. We employed EEG to examine the association between growth faltering and brain functional connectivity and whether brain functional connectivity mediates the effect of early adversity on cognitive development.MethodsWe recruited participants from an urban impoverished neighborhood in Dhaka, Bangladesh. One sample consisted of 85 children whose EEG and growth measures (height for age, weight for age, and weight to height) were collected at 6 months and cognitive outcomes were assessed at 27 months. Another sample consisted of 115 children whose EEG and growth measures were collected at 36 months and IQ scores were assessed at 48 months. Path analysis was used to test the effect of growth measures on cognitive outcomes through brain functional connectivity.FindingsFaltered growth was found to be accompanied by overall increased functional connectivity in the theta and low-beta frequency bands for the 36-month-old cohort. For both cohorts, brain functional connectivity was negatively predictive of later cognitive outcomes at 27 and 48 months, respectively. Faltered growth was found to have a negative impact on children’s IQ scores in the older cohort, and this effect was found to be mediated by brain functional connectivity in the low-beta band.InterpretationThe association found between growth measures and brain functional connectivity may reflect a broad deleterious effect of malnutrition on children’s brain development. The mediation effect of functional connectivity on the relation between physical growth and later IQ scores provides the first experimental evidence that brain functional connectivity may mediate the effect of biological adversity on cognitive development.FundingBill and Melinda Gates Foundation (OPP1111625)

scholarly journals Community Determinants of Physical Growth and Cognitive Development among Indian Children in Early Childhood: A Multivariate Multilevel Analysis

2019 ◽  
Vol 17 (1) ◽  
pp. 182
Author(s):  
Jongho Heo ◽  
Aditi Krishna ◽  
Jessica M. Perkins ◽  
Hwa-young Lee ◽  
Jong-koo Lee ◽  
...  
Keyword(s):  
Cognitive Development ◽  
Child Growth ◽  
Community Level ◽  
Physical Growth ◽  
Indian Children ◽  
Individual Level ◽  
Math Scores ◽  
Mathematics Test ◽  
Z Scores ◽  
The Individual

Inadequate child physical growth and cognitive development share common individual-level risk factors. Less understood is how outcomes co-cluster at the community level and to what extent certain community-level characteristics influence the clustering. This study aims to quantify the extent to which child growth and development co-occur across communities, and to identify community-level characteristics associated with the clustering of the two development dimensions. We used longitudinal data from 1824 children (aged 5 years) across 98 communities in Andhra Pradesh, India in round 2 (2006) of the Young Lives study, who were followed up 3 years later in round 3 (2009). A multivariate, multilevel statistical model was estimated wherein the responses were nested within individuals, and communities. We used z-scores of height-for-age, weight-for-age, Peabody Picture Vocabulary Test, and a mathematics test in 2009 as outcome variables. At the community level, we included compositional variables representing community characteristics while controlling for child socio-demographic characteristics at the individual level. At the community level, children’s physical growth and cognitive development were strongly correlated (coefficient: 0.55–0.76) and, even after controlling for individual-level covariables, a more pronounced correlation was shown at the community level than individual level correlation. Greater local healthcare resources were associated with better physical growth. More local programs run by government and NGOs/charities were associated with higher child language skills. Local social problems were inversely associated with math scores. Our study showed that physical growth and cognitive development tended to be clustered and co-occurred within communities as well as individual children.

073 Whole-brain network analysis of neural oscillations during light sleep

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A30-A31
Author(s):  
Joline Fan ◽  
Kiwamu Kudo ◽  
Kamalini Ranasinghe ◽  
Hirofumi Morise ◽  
Anne Findlay ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Information Flow ◽  
Phase Transfer ◽  
Sleep Onset ◽  
Adaptive Beamforming ◽  
Neural Oscillations ◽  
High Temporal Resolution ◽  
Whole Brain ◽  
Frequency Bands ◽  
Brain Functional Connectivity

Abstract Introduction Sleep is a highly stereotyped phenomenon that is ubiquitous across species. Although behaviorally appearing as a homogeneous process, sleep has been recognized as cortically heterogenous and locally dynamic. PET/fMRI studies have provided key insights into regional activation and deactivation with sleep onset, but they lack the high temporal resolution and electrophysiology for understanding neural interactions. Using simultaneous electrocorticography (EEG) and magnetoencephalography (MEG) imaging, we systematically characterize whole-brain neural oscillations and identify frequency specific, cortically-based patterns associated with sleep onset. Methods In this study, 14 healthy subjects underwent simultaneous EEG and MEG imaging. Sleep states were determined by scalp EEG. Eight 15s artifact-free epochs, e.g. 120s sensor time series, were selected to represent each behavioral state: N1, N2 and wake. Atlas-based source reconstruction was performed using adaptive beamforming methods. Functional connectivity measures were computed using imaginary coherence and across regions of interests (ROIs, segmentation of 210 cortical regions with Brainnetome Atlas) in multiple frequency bands, including delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), sigma (12-15Hz), beta (15-30Hz), and gamma (30-50Hz). Directional phase transfer entropy (PTE) was also evaluated to determine the direction of information flow with transition to sleep. Results We show that the transition to sleep is encoded in a spatially and temporally specific dynamic pattern of whole-brain functional connectivity. With sleep onset, there is increased functional connectivity diffusely within the delta frequency, while spatially specific profiles in other frequency bands, e.g. increased fronto-temporal connectivity in the alpha frequency band and fronto-occipital connectivity in the theta band. In addition, rather than a decoupling of anterior-posterior regions with transition to sleep, there is a spectral shift to delta frequencies observed in the synchrony and information flow of neural activity. Conclusion Sleep onset is cortically heterogeneous, composed of spatially and temporally specific patterns of whole-brain functional connectivity, which may play an essential role in the transition to sleep. Support (if any) Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the NIH under Award Number (5TL1TR001871-05 to JMF). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

scholarly journals Distinct Patterns of Functional Connectivity During the Comprehension of Natural, Narrative Speech

2020 ◽  
Vol 30 (03) ◽  
pp. 2050007 ◽  
Author(s):  
Yongjie Zhu ◽  
Jia Liu ◽  
Tapani Ristaniemi ◽  
Fengyu Cong
Keyword(s):  
Functional Connectivity ◽  
Time Window ◽  
Principal Component ◽  
Single Mode ◽  
Brain Regions ◽  
Speech Comprehension ◽  
Analysis Framework ◽  
Eeg Data ◽  
Source Level ◽  
Brain Functional Connectivity

Recent continuous task studies, such as narrative speech comprehension, show that fluctuations in brain functional connectivity (FC) are altered and enhanced compared to the resting state. Here, we characterized the fluctuations in FC during comprehension of speech and time-reversed speech conditions. The correlations of Hilbert envelope of source-level EEG data were used to quantify FC between spatially separate brain regions. A symmetric multivariate leakage correction was applied to address the signal leakage issue before calculating FC. The dynamic FC was estimated based on a sliding time window. Then, principal component analysis (PCA) was performed on individually concatenated and temporally concatenated FC matrices to identify FC patterns. We observed that the mode of FC induced by speech comprehension can be characterized with a single principal component. The condition-specific FC demonstrated decreased correlations between frontal and parietal brain regions and increased correlations between frontal and temporal brain regions. The fluctuations of the condition-specific FC characterized by a shorter time demonstrated that dynamic FC also exhibited condition specificity over time. The FC is dynamically reorganized and FC dynamic pattern varies along a single mode of variation during speech comprehension. The proposed analysis framework seems valuable for studying the reorganization of brain networks during continuous task experiments.

Sign in / Sign up

Export Citation Format

Share Document