The dynamics of the baseline brain state vary among different subjects under the influence of cognitive tests and blood glucose levels changes

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Based on individualized resting EEG analysis, we studied how changes in blood glucose levels as well as performance of a cognitive task affect the background brain state. Twenty-four healthy adults aged 18–35 performed a word classification test twice: once in a fasting state and once after glucose intake. EEG recordings were analyzed in resting-state conditions with eyes closed (EC) and eyes open (EO), before and after the test at each stage. Changes in integral parameters derived from the structural function of multichannel EEG were evaluated. These parameters served as measures of the spatial (pS) and temporal (pT) organization of EEG activity. Individual analysis revealed significant changes in pT and pS parameters in all participants due to increased glucose levels and the cognitive task, with a significant interaction effect between these factors. Group-averaged results masked these effects due to the variability in individual responses. On an individual level, performing the cognitive test after glucose intake led to a significant increase in pS for most participants, indicating higher differentiation and reduced spatial coherence of EEG processes. This was accompanied by a significant linear correlation between the increase in pS and the reduction in reaction time, suggesting heightened CNS activation. This effect was more pronounced in the eyes-open condition than with eyes closed. A positive correlation between fasting blood glucose levels and pT values was found. After the test, a tendency for pT to increase—reflecting reduced temporal coherence and potentially indicating enhanced functional flexibility of neural processes—was observed. The proposed method for calculating integral parameters that characterize spatial and temporal coherence in multichannel EEG can be used to monitor and study changes in the brain’s functional state during cognitive activity and the effects of substances affecting brain metabolism.

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E. Galperina

Sechenov Institute of Evolutionary Physiology and Biochemistry RAS

编辑信件的主要联系方式.
Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

O. Kruchinina

Sechenov Institute of Evolutionary Physiology and Biochemistry RAS

Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

Yu. Chiligina

Sechenov Institute of Evolutionary Physiology and Biochemistry RAS

Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

V. Ivanov

Herzen Russian State Pedagogical University

Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

M. Trifonov

Sechenov Institute of Evolutionary Physiology and Biochemistry RAS

Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

V. Rozhkov

Sechenov Institute of Evolutionary Physiology and Biochemistry RAS

Email: galperina-e@yandex.ru
俄罗斯联邦, St. Petersburg

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2. Fig. 1. Examples of first-order structural functions (FOSF) of a multichannel electroencephalogram (EEG), calculated for a real EEG (A, a), an EEG with randomly mixed time samples (A, b), random signals simulating an EEG (A, c), and the amplitude spectrum of FOSF of a real EEG (B). Subject No. 2.

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3. Fig. 2. Changes in reaction time (ms, abscissa axis) and percentage of correct answers (%, ordinate axis) in subjects in the test of classifying nouns into "edible" (circles) and "inedible" (triangles) after glucose intake. Each point on the graph corresponds to one subject, the number is the subject's number. a - increase in the proportion of correct answers and decrease in reaction time; b - increase in the proportion of correct answers and increase in reaction time; c - decrease in the proportion of correct answers and decrease in reaction time; d - decrease in the proportion of correct answers and increase in reaction time.

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4. Fig. 3. Changes in pT and pS in the dynamics of successive epochs of electroencephalogram analysis throughout the study. Subject #20. Background_1 - Background_4 - resting state number. Each epoch of analysis is represented by one icon. Lines projected onto scattering clouds are a linear approximation of parameter changes in the dynamics of analysis epochs for each state. Gray icons indicate the state with eyes closed, white icons indicate the state with eyes open.

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5. Fig. 4. Number of subjects (the value is indicated inside the columns, n) with an increase (a), decrease (c), or no change (b) in the parameters pS and pT at successive stages of the study. A – resting state with eyes closed; B – with eyes open. Along the ordinate axis: relative number of subjects in each subgroup, in % (n = 24). Along the abscissa axis – numbers of the compared resting states: 2–1 – change in the ratio in the subgroups before and after the test; 3–2 – before and after glucose intake; 4–3 – complex effect of the test and glucose. * – differences in the number (in proportions) of subjects with an increase or decrease in the value of the integral parameter are significant, * – p < 0.05, ** – p < 0.01.

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6. Fig. 5. Correlation coefficients between the glucose level (on an empty stomach – A, after glucose intake – B) and the values of the integral parameters pT and pS. Along the ordinate axis: r – values of the correlation coefficients in relative units, along the abscissa axis: Background_1, …, Background_4 – states of rest in sequence during the study. Triangles – r values for the pT parameter, circles – r values for the pS parameter, light figures – the state of rest with open eyes (OE), dark figures – the state of rest with closed eyes (CE). * – p < 0.05.

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7. Fig. 6. Correlation coefficients (n = 24) between the values of integral parameters (pT, pS) and the test performance indicators on an empty stomach (A) and after glucose intake (B). On the ordinate axis: r – correlation coefficient, relative units, on the abscissa axis: stimulus categories I – “edible”, II – “inedible”, RT – reaction time, RC – rest with eyes closed, OG – rest with eyes open, 1–4 – rest states in order. * – p < 0.05.

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