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Published on: May 26, 2015
Quantitative EEG Tomography of Early Childhood Malnutrition
Alberto Taboada-Crispi1,2, Maria L Bringas-Vega1,3, Jorge Bosch-Bayard4
1The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Insights
Quantitative electroencephalography (qEEG) reveals distinct brain activity patterns in children with early protein-energy malnutrition (PEM). These qEEG signatures may serve as biomarkers for assessing long-term neurodevelopmental impacts of childhood malnutrition.
Area of Science:
- Neuroscience
- Developmental Neuroscience
- Public Health
Background:
- Early childhood protein-energy malnutrition (PEM) has lasting neurodevelopmental consequences.
- Identifying reliable biomarkers for assessing PEM's long-term brain impact is crucial for global public health.
Purpose of the Study:
- To identify the quantitative electroencephalographic (qEEG) signature of early childhood protein-energy malnutrition (PEM).
- To explore the potential of qEEG as a scalable and affordable biomarker for assessing the long-term brain impact of PEM.
Main Methods:
- Archival EEG recordings from 108 participants (46 PEM, 62 controls) in the Barbados Nutrition Study were analyzed.
- EEG Z-spectra were compared between groups using t-tests and permutation tests to identify significant differences.
- Multivariate Item Response Theory and elastic-net regressions with cross-validation were used for biomarker development and performance assessment (AUC).
Main Results:
- Four clusters of significant EEG differences were identified between PEM and control groups, including altered theta, alpha, and beta activity.
- qEEG analysis demonstrated significant differences in brain activity patterns between children with and without a history of PEM.
- The developed qEEG biomarker differentiated between the two groups with an AUC of 0.83, comparable to expert visual EEG scoring.
Conclusions:
- Quantitative EEG analysis reveals consistent differences in brain activity between children with and without early PEM.
- qEEG shows promise as a scalable and affordable biomarker for assessing the long-term neurodevelopmental consequences of early childhood malnutrition.
- These findings support the use of qEEG technology for evaluating the brain impact of PEM in public health initiatives.
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.
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