Abstract
Early childhood Protein Energy Malnutrition (PEM) is an increasing worldwide phenomenon with lifelong neurodevelopmental consequences. There is thus a need for inexpensive imaging technologies to objectively identify and follow up the neural impact of malnutrition—Electroencephalography being an obvious choice. But EEG studies of PEM are scarce, performed on subjects with multiple stressors, only in the acute phase. A unique opportunity to improve these enquiries is the still ongoing Barbados Nutrition Study (BNS) which enrolled (1967–72) children with PEM during their first year of life. Under the direction of Frank Ramsey and E. Roy John, 248 digital EEG recordings were obtained (children 5–11 years) at the time that the Brain Research Lab and the Cuban Neuroscience Centre were developing quantitative EEG (qEEG; John et al., 1977). Recently, a large subsample of these digital EEGs was recovered. A unique opportunity to identify a qEEG fingerprint of early PEM has thus arisen, and which we here report. The final sample comprised 46 PEM and 62 control recordings (1 min resting state, eyes-closed,19 electrodes 10/20 system, sampling 100 Hz). Qualitative EEG was evaluated using a Likert-type scale. Multivariate Item Response Theory identified a neurophysiological state (NS) as a single latent variable explaining 0.88 of sample variance. qEEG evaluation at the electrodes (topography) consisted in calculating the log-power spectrum both at the scalp electrodes and sources and computing the z transform with regard to the Cuban normative database. Quantitative tomographic EEG (qEEGt) was carried out with CNEURO’s VARETA source analysis procedure based upon an MNI probabilistic template—necessary since MRIs where not available at that time. Multivariate permutation tests (N = 1000) were applied to t-tests in order to assess differences between groups. Qualitative analysis revealed highly significant changes in the latent variable (NS) with the PEM group showing excessive slow-wave, paroxysmal and focal abnormality activity, with a statistically significant effect for groups (p < 0.00001). qEEG (topographic) revealed (PEM) an increment of slow activities (<5 Hz) in centro-parietal electrodes and a decrease of alpha in fronto-central electrodes around 8.98 Hz as well as a significant increase of fast activity >15.2 Hz. qEEGT analysis: the PEM group, showed a significant increment in source power at lower frequencies (<5 Hz) and a decrease of power in alpha (8.9 Hz) in frontal region. The consistent differences in qEEG and qEEGt values between PEM and controls suggest they may be affordable biomarkers for the long-term actual brain impact of early childhood PEM. Excess slow-waves activity and decreased alpha activity in PEM children, may be a qEEG fingerprint of early PEM predicting which is correlated with many types of neuropathology, learning and performance difficulties.
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