Quantitative EEG Tomography of Early Childhood Malnutrition

Abstract

The goal of this study is to identify the quantitative electroencephalographic (qEEG) signature of early childhood malnutrition [protein-energy malnutrition (PEM)]. To this end, archival digital EEG recordings of 108 participants in the Barbados Nutrition Study (BNS) were recovered and cleaned of artifacts (46 children who suffered an episode of PEM limited to the first year of life) and 62 healthy controls). The participants of the still ongoing BNS were initially enrolled in 1973, and EEGs for both groups were recorded in 1977–1978 (at 5–11 years). Scalp and source EEG Z-spectra (to correct for age effects) were obtained by comparison with the normative Cuban Human Brain Mapping database. Differences between both groups in the z spectra (for all electrode locations and frequency bins) were assessed by t-tests with thresholds corrected for multiple comparisons by permutation tests. Four clusters of differences were found: (a) increased theta activity (3.91–5.86 Hz) in electrodes T4, O2, Pz and in the sources of the supplementary motor area (SMA); b) decreased alpha1 (8.59–8.98 Hz) in Fronto-central electrodes and sources of widespread bilateral prefrontal are; (c) increased alpha2 (11.33–12.50 Hz) in Temporo-parietal electrodes as well as in sources in Central-parietal areas of the right hemisphere; and (d) increased beta (13.67–18.36 Hz), in T4, T5 and P4 electrodes and decreased in the sources of bilateral occipital-temporal areas. Multivariate Item Response Theory of EEGs scored visually by experts revealed a neurophysiological latent variable which indicated excessive paroxysmal and focal abnormality activity in the PEM group. A robust biomarker construction procedure based on elastic-net regressions and 1000-cross-validations was used to: (i) select stable variables and (ii) calculate the area under ROC curves (AUC). Thus, qEEG differentiate between the two nutrition groups (PEM vs Control) performing as well as visual inspection of the EEG scored by experts (AUC = 0.83). Since PEM is a global public health problem with lifelong neurodevelopmental consequences, our finding of consistent differences between PEM and controls, both in qualitative and quantitative EEG analysis, suggest that this technology may be a source of scalable and affordable biomarkers for assessing the long-term brain impact of early PEM.

An Age-Adjusted EEG Source Classifier Accurately Detects School-Aged Barbadian Children That Had Protein Energy Malnutrition in the First Year of Life

“…A complete description of the EEG procedures has been previously reported in Taboada-Crispi et al (2018). Briefly, EEGs were recorded in 1977–1978 when the BNS children were 5–11 years of age by trained staff at the Barbados Nutrition Centre, who were blinded to the child’s nutritional history.…”

“…We recently recovered EEG data that was collected in BNS participants in 1977–1978 at ages 5–11 years. EEG analyses using qEEGt (Taboada-Crispi et al, 2018) showed the following results in study participants with histories of childhood malnutrition: (1) increased theta activity (3.91–5.86 Hz) in electrodes T4, O2, Pz and in the supplementary motor area (SMA); (2) decreased alpha1 (8.59–8.98 Hz) in fronto-central electrodes and sources of widespread bilateral prefrontal area; (3) increased alpha2 (11.33–12.50 Hz) in temporo-parietal electrodes as well as in sources in central-parietal areas of the right hemisphere; and (4) increased beta (13.67–18.36 Hz), in T4, T5, and P4 electrodes and decreased in bilateral occipital-temporal regions of PEM versus control groups. Earlier EEG studies in children with histories of childhood malnutrition (e.g., Bartel et al, 1979) similarly found increased slow wave rhythms (theta band), as well as decreased alpha.…”

“…It is therefore preferable to carry out EEG Source Imaging (ESI) (He et al, 2019) for increased biological validity. Our earlier report (Taboada-Crispi et al, 2018) partially addressed these issues by:…”

“…However, Taboada-Crispi et al (2018) were not able to develop a classification procedure for malnutrition based on ESI measures. This was due to the extremely large number of highly correlated variables produced by VARETA.…”

Impact of early childhood malnutrition on the adult brain function: an ERP study

“…Bartel and colleagues (Bartel et al, 1979) studied malnourished children five to ten years after their hospitalization and confirmed that their rest EEG still had a significantly diminished alpha and increased theta and delta frequencies compared to a control group. In a recent study, brain function alterations in the resting state activity of previously malnourished 5-11 year old children of the BNS cohort were reported, namely an excess of theta, alpha2 and beta frequencies and a decrease of alpha 1, which suggest a maturational lag in cortical development (Taboada-Crispi et al, 2018). It is clear from these behavioral and EEG findings that malnutrition at a young age has important acute deleterious effects on brain function, cognition and multiple other life fonctionning aspects.…”