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Valdes-Sosa, P.

Publications and source records attributed to Valdes-Sosa, P..

2 recordsLinked to original sources

Harmonized-Multinational qEEG Norms (HarMNqEEG)

This paper extends our frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. i) Create lifespan Hermitian Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control developmental equations for the mean and standard deviation of qEEG traditional and Hermitian Riemannian descriptive parameters were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. ii) We also show that the multinational harmonized Hermitian Riemannian norms produce z-scores with increased diagnostic accuracy to predict brain dysfunction at school-age produced by malnutrition only in the first year of life. We provide data and software for constructing norms. iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings. HighlightsO_LIWe create lifespan Hermitian Riemannian qEEG norms for cross-spectral tensors. C_LIO_LIThe norms are based on 9 countries, 12 devices, and 14 studies, with 1564 subjects. C_LIO_LIWe demonstrate qEEG "batch effects", providing harmonization methods to remove them. C_LIO_LIMultinational harmonized z-scores increase diagnostic accuracy of brain dysfunction. C_LIO_LIData and software are available for norm and individual z-scores calculation. C_LI

neuroscience↗

Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation

In this paper, we describe a novel methodology, BC-VARETA, for estimating the Inverse Solution (sources activity) and its Precision Matrix (connectivity parameters) in the frequency domain representation of Stationary Time Series. The aims of this method are three. First: Joint estimation of Source Activity and Connectivity as a frequency domain linear dynamical system identification approach. Second: Achieve super high resolution in the connectivity estimation through Sparse Hermitian Sources Graphical Model. Third: To be a populational approach, preventing the Inverse Solution and Connectivity statistical analysis across subjects as a postprocessing, by modeling population features of Source Activity and Connectivity. Our claims are supported by a wide simulation framework using realistic head models, realistic Sources Setup, and Inverse Crime effects evaluation. Also, a fair quantitative analysis is performed, based on a diversification of quality measures on which state of the art Inverse Solvers were tested.

neuroscience↗