Search

A biophysical model of arousal dynamics is used to study mechanisms of synchronisation and loss of synchrony among the three key oscillators controlling sleep-wake cycles: the circadian, homeostatic, and light oscillators. Synchronisation of these rhythms promotes sleep and brain clearance and is critical for human health. Conversely, their desynchrony is linked to impaired performance and disease. We find that the default state of the model corresponds to the endogenous homeostatic period that is far from ~24 h of the circadian and light-dark cycles. Combined action of light and circadian oscillator on the homeostatic rhythm is required to achieve the typical sleep-wake pattern of healthy people. Change of homeostatic clearance is found to induce two types of desynchronisation: (i) fast clearance rates desynchronise the homeostatic oscillator from the circadian, while the circadian rhythm remains entrained to light, and (ii) slow clearance maintains synchronisation between the homeostatic and circadian oscillators, but the period is different from that of the light-dark cycle. Between these regimes, all three rhythms are synchronised under the studied conditions. The system is highly sensitive to external inputs to the neuronal populations of the sleep-wake switch, which can lead to complete loss of sleep. The model shows that loss of synchronisation can be caused by changes in the homeostatic clearance rate or external input to the neuronal populations of the sleep-wake switch. This has implications for understanding individual variability in sleep-wake patterns and in mechanisms of sleep and circadian disorders.

A manual measurement of blood vessels diameter is a conventional component of routine visual assessment of microcirculation, say, during optical capillaroscopy. However, many modern optical methods for blood flow measurements demand the reliable procedure for a fully automated detection of vessels and estimation of their diameter that is a challenging task. Specifically, if one measure the velocity of red blood cells by means of laser speckle imaging, then visual measurements become impossible, while the velocity-based estimation has their own limitations. One of promising approaches is based on fast switching of illumination type, but it drastically reduces the observation time, and hence, the achievable quality of images. In the present work we address this problem proposing an alternative method for the processing of noisy images of vascular structure, which extracts the mask denoting locations of vessels, based on the application of the continuous wavelet transform with the Morlet wavelet having small central frequencies. Such a method combines a reasonable accuracy with the possibility of fast direct implementation to images. Discussing the latter, we describe in details a new MATLAB program code realization for the CWT with the Morlet wavelet, which does not use loops completely replaced with element-by-element operations that drastically reduces the computation time., Comment: 6 pages, 3 figures