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Abstract Background Iron deficiency (ID) and iron deficiency anemia (IDA) are highly-prevalent nutrient deficiencies and have been shown to have a range of negative effects on cognition and brain function. Human intervention studies including measures at three levels—blood, brain, and behavior—are rare and our objective was to model the relationships among measures at these three levels in school-going Indian adolescents. Methods Male and female adolescents in rural India were screened for ID/IDA. Subjects consumed 2 meals/day for 6 months; half were randomly assigned to consume meals made from a standard grain (pearl millet) and half consumed meals made from an iron biofortified pearl millet (BPM). Prior to and then at the conclusion of the feeding trial, they completed a set of cognitive tests with concurrent electroencephalography (EEG). Results Overall, serum ferritin (sFt) levels improved over the course of the study. Ten of 21 possible measures of cognition showed improvements from baseline (BL) to endline (EL) that were larger for those consuming BPM than for those consuming the comparison pearl millet (CPM). Critically, the best model for the relationship between change in iron status and change in cognition had change in brain measures as a mediating factor, with both change in serum ferritin as a primary predictor and change in hemoglobin as a moderator. Conclusions A dietary intervention involving a biofortified staple grain was shown to be efficacious in improving blood iron biomarkers, behavioral measures of cognition, and EEG measures of brain function. Modeling the relationships among these variables strongly suggests multiple mechanisms by which blood iron level affects brain function and cognition. Trial registration Registered at ClinicalTrials.gov, NCT02152150 , 02 June 2014.

Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.