Harmonized-Multinational qEEG norms (HarMNqEEG).

This paper extends 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 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 Riemannian DPs 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 harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (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.

Electrophysiological signatures of resting state networks under new environmental conditions.

It is assumed that cognitive processes are provided by the regulatory interactions of different brain networks. The three most stable resting state networks, among which the default mode network (DMN), the central executive network (CEN) and the salience network (SN) are considered to be the key neurocognitive networks for understanding higher cognitive functions. Peculiarities of changes in the connectivity of resting state networks of an individual entering a new environment and after a year of adaptation in this environment remain poorly studied. The aim of this study was to investigate the peculiarities of the connectivity of resting state networks calculated in EEG data in students right after moving to an unfamiliar environment and one year after moving. 128-channel EEGs were recorded in the resting state in 45 students (all men) aged from 18 to 29 years, who moved to the North region of Russia (Yakutsk, Republic of Sakha (Yakutia)). Resting state networks were calculated by the seed-based method. The subjects had increased SN connectivity with the sensorimotor cortex and the posterior node of DMN (posterior cingulate cortex and precuneus) in the condition when they were exposed to a new unfamiliar environment, compared to the condition after a year in the same environment. In general, the obtained data are consistent with the notion of increased SN functioning when encountering new significant stimuli and tasks, i.e. new environmental conditions, and the representation of SN as closely related to the function of homeostasis regulation according to organism's internal goals and environmental requirements.