Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied for getting a glance to the microscopic interactions occurring in a neurophysiological system, namely, in the thalamo-cortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities, and to estimate the regions' participation in the generation of the different levels of consciousness

Synchronization of low-frequency rhythms in electroencephalogram by respiration with linear dependent time frequency.

The aim of the present study was to investigate the features of interaction of low-frequency rhythms in delta band of electroencephalogram (EEG) and processes in vegetative regulation of circulation with respiration. Materials and methods. 19 leads of EEG, photoplethysmogram (PPG) and respiration were simultaneously recorded in four healthy males (19-25 years old) during 30 minutes physiological test with linearly increasing frequency of respiration. Modern methods of nonlinear dynamics were used to diagnose the presence of phase and frequency synchronization between respiration and low-frequency rhythms in delta band of EEG and in PPG. Results. We found significantly long sections of synchronization of delta rhythms in cervical leads of EEG and low-frequency rhythms in PPG by respiration with linearly increasing frequency. Conclusion. Obtained results correlate well with established hypothesis which suggest that low-frequency rhythms in baroreflectory regulation of circulation are in complex dynamic relationships with structures of brain stem. A method was proposed for quantitative evaluation of synchronization strength between respiration and low-frequency rhythms in electrical brain activity in physiological tests with respiration with frequency linearly increasing in time

EEG biomarkers of activation of the lymphatic drainage system of the brain during sleep and opening of the blood-brain barrier

The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB