This PDF file contains the front matter associated with SPIE Proceedings Volume 10063, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Based on the recent studies the prognosis of patients after cardiac arrest (CA) remains poor. Thus it is extremely important to understand fine mechanisms related to the influence of CA on the brain and Cerebral Blood Flow (CBF) during and after cardiac arrest. Recently our group introduced Transcranial Optical Vascular Imaging (TOVI) approach that combines laser speckle and dynamic fluorescent imaging. TOVI proved to be useful during various preclinical brain research applications. For example it allows imaging of brain blood vessels of a mouse in vivo through the intact cranium. Herein for the first time we present the use of TOVI during cardiac arrest. TOVI possibly could be a useful tool for preclinical studies of CBF during and after CA.

The aim of this work was to study the possibilities of the laser Doppler flowmetry method for the joint study of microhaemo- and lymph circulation of human skin.

Conducting a series of experimental studies allowed to trace the relationship of recorded signals of microcirculation of blood flow and lymph flow, as well as to study their oscillation nature by using wavelet analysis.

We report on the development of a unified Monte-Carlo based computational model for exploring speckle pattern formation in swept-source optical coherence tomography (OCT). OCT is a well-established optical imaging modality capable of acquiring cross-sectional images of turbid media, including biological tissues, utilizing back scattered low coherence light. The obtained OCT images include characteristic features known as speckles. Currently, there is a growing interest to the OCT speckle patterns due to their potential application for quantitative analysis of medium’s optical properties. Here we consider the mechanisms of OCT speckle patterns formation for swept-source OCT approaches and introduce further developments of a Monte-Carlo based model for simulation of OCT signals and images. The model takes into account polarization and coherent properties of light, mutual interference of back-scattering waves, and their interference with the reference waves. We present a corresponding detailed description of the algorithm for modeling these light-medium interactions. The developed model is employed for generation of swept-source OCT images, analysis of OCT speckle formation and interpretation of the experimental results. The obtained simulation results are compared with selected analytical solutions and experimental studies utilizing various sizes / concentrations of scattering microspheres.

A novel speckle-based sensing technique for cost-effective heart-rate monitoring is demonstrated. This technique detects periodical changes in the spatial distribution of energy on the speckle pattern at the output of a Step-Index Polymer Optical Fiber (SI-POF) lead by using a low-cost webcam. The scheme operates in reflective configuration thus performing a centralized interrogation unit scheme. The prototype has been integrated into a mattress and its functionality has been tested with 5 different patients lying on the mattress in different positions without direct contact with the fiber sensing lead.

Laser speckle patterns are granular patterns produced as a result of random interference of light waves. Optical vortices (OVs) are phase singularities in such speckle fields, characterized by zero intensity and an undefined phase. Decorrelation of the speckle fields causes these OVs to move in both time and space. In this work, a variety of parameters of these OVs have been studied. The speckle fields were simulated to undergo three distinct decorrelation behaviors- Gaussian, Lorentzian and constant decorrelations. Different decorrelation behaviors represent different dynamics. For example, Lorentzian and Gaussian decorrelations represent Brownian and ordered motions, respectively. Typical dynamical systems in biophysics are generally argued to be a combination of these. For each of the decorrelation behaviors under study, the vortex trails were tracked while varying the rate of decorrelation. Parameters such as the decorrelation length, average trail length and the deviation of the vortices as they traversed in the speckle field, were studied. Empirical studies were also performed to define the distinction between trails arising from different speckle decorrelation behaviors. The initial studies under stationary speckle fields were followed up by similar studies on shifting fields. A new idea to employ Poincaŕe plots in speckle analysis has also been introduced. Our studies indicate that tracking OVs can be a potential method to study cell and tissue dynamics.

Monitoring cerebral blood flow (CBF) during neurosurgery is essential for detecting ischemia in a timely manner for a wide range of procedures. Multiple clinical studies have demonstrated that laser speckle contrast imaging (LSCI) has high potential to be a valuable, label-free CBF monitoring technique during neurosurgery. LSCI is an optical imaging method that provides blood flow maps with high spatiotemporal resolution requiring only a coherent light source, a lens system, and a camera. However, the quantitative accuracy and sensitivity of LSCI is limited and highly dependent on the exposure time. An extension to LSCI called multi-exposure speckle imaging (MESI) overcomes these limitations, and was evaluated intraoperatively in patients undergoing brain tumor resection. This clinical study (n = 7) recorded multiple exposure times from the same cortical tissue area, and demonstrates that shorter exposure times (≤1 ms) provide the highest dynamic range and sensitivity for sampling flow rates in human neurovasculature. This study also combined exposure times using the MESI model, demonstrating high correlation with proper image calibration and acquisition. The physiological accuracy of speckle-estimated flow was validated using conservation of flow analysis on vascular bifurcations. Flow estimates were highly conserved in MESI and 1 ms exposure LSCI, with percent errors at 6.4% ± 5.3% and 7.2% ± 7.2%, respectively, while 5 ms exposure LSCI had higher errors at 21% ± 10% (n = 14 bifurcations). Results from this study demonstrate the importance of exposure time selection for LSCI, and that intraoperative MESI can be performed with high quantitative accuracy.

Affixed Transmission Speckle Analysis (ATSA) is a method recently developed to measure blood flow that is based on laser speckle imaging miniaturized into a clip-on form factor the size of a pulse-oximeter. Measuring at a rate of 250 Hz, ATSA is capable or obtaining the cardiac waveform in blood flow data, referred to as the Speckle-Plethysmogram (SPG). ATSA is also capable of simultaneously measuring the Photoplethysmogram (PPG), a more conventional signal related to light intensity. In this work we present several novel algorithms for extracting physiologically relevant information from the combined SPG-PPG waveform data. First we show that there is a slight time-delay between the SPG and PPG that can be extracted computationally. Second, we present a set of frequency domain algorithms that measure harmonic content on pulse-by-pulse basis for both the SPG and PPG. Finally, we apply these algorithms to data obtained from a set of subjects including healthy controls and individuals with heightened cardiovascular risk. We hypothesize that the time-delay and frequency content are correlated with cardiovascular health; specifically with vascular stiffening.

Due to the huge abundance and the major role that viruses and membrane vesicles play in the seas or rivers ecosystems it is necessary to develop simple, sensitive, compact and reliable methods for their detection and characterization. Our approach is based on the measurement of the weak light level scattered by the biotic nanoparticles. We describe a new full-field, incoherently illuminated, shot-noise limited, common-path interferometric detection method coupled with the analysis of Brownian motion to detect, quantify, and differentiate biotic nanoparticles. The last developments take advantage of a new fast (700 Hz) camera with 2 Me- full well capacity that improves the signal to noise ratio and increases the precision of the Brownian motion characterization. We validated the method with calibrated nanoparticles and homogeneous DNA or RNA.viruses. The smallest virus size that we characterized with a suitable signal-to-noise ratio was around 30 nm in diameter with a target towards the numerous 20 nm diameter viruses. We show for the first time anisotropic trajectories for myoviruses meaning that there is a memory of the initial direction of their Brownian motions. Significant improvements have been made in the handling of the sample as well as in the statistical analysis for differentiating the various families of vesicles and virus. We further applied the method for vesicles detection and for analysis of coastal and oligotrophic samples from Tara Oceans circumnavigation as well of various rivers.

OCT fluctuation spectroscopy provides a quantitative and non-invasive tool to monitor 3D mammary epithelial cell (MEC) models which recapitulate features of breast cancer in vivo. Cellular dynamic fluctuation measurements allow for assessing drug responses due to different mechanisms of inhibition in 3D models in vitro. Here we report on pre-malignant MEC responses to two toxicants: Taxol, which stabilizes microtubules against depolymerization, and has emerged as an important chemotherapeutic agent in the treatment of breast cancer, and blebbistatin, a small molecule inhibitor with high affinity and selectivity toward Myosin II. Here we propose a quantitative method for measuring toxicant responses of MECs in 3D cultures from OCT speckle fluctuation spectroscopy. OCT fluctuation spectra were quantified within the 9-440 mHz band, from which the inverse power-law exponent (α) and the fractional modulation amplitude (M) were extracted. Pre-malignant MECs treated with Taxol (0, 10 μM and 20 μM) exhibit an increase (p<0.001) in α along time (t=0, 1 hour, 24 hours, 48 hours and 6 days), indicating selective inhibition of high frequency fluctuations, with a concomitant decrease (p<0.001) in M over time. However, only M of pre-malignant MECs treated with Blebbistatin (0, 25 uM and 50 uM) exhibited a decrease (p<0.001) along time, but no significant change (p>0.05) in α, since myosin II isn’t highly expressed in non-migratory pre-malignant MECs. We demonstrated the feasibility of OCT fluctuation spectroscopy to quantify MEC toxicant response. Microtubule stabilization was found to be a major contributor to pre-malignant MEC fluctuation signals, while myosin II inhibition was not.

The adaptive growth of collateral vessels, termed “arteriogenesis”, is crucial for maintaining regional blood supply during arterial obstruction and offsetting the adverse effect of tissue ischemia. Stimulation of arteriogenesis has been applied for the treatment of occlusive vascular diseases, and in vivo imaging of the progressive development of collateral vessel will facilitate a better understanding of the mechanism. We present using high-resolution OCT-based microangiography (OMAG) to image arteriogenesis process longitudinally in mouse cerebral cortex after middle cerebral artery occlusion (MCAO). We imaged the collateral arterioles at the arteriolo-arteriolar anastomosis (AAA) within 7-day period after MCAO to reveal key elements of collateral vessel remodeling, including alteration in vessel morphology, velocity and directionality of blood flow. The magnitudes of changes in these parameters matched the time course of the active building of collateral vessels stated in previous studies using histology. Hence, OMAG is a promising imaging tool for non-invasive longitudinal study of functional collateral vessel growth in small animal models and can be potentially applied in the experimental study of arteriogenesis stimulation.

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

Previous studies have shown that bone growth acceleration can occur in many animal species after periosteal resection (removal of a strip of periosteum) with minimum morbidity. This has numerous clinical applications, including treatment of limb length differences. Here we use Second Harmonic Generation (SHG) imaging microscopy to evaluate changes in collagen architecture reflective of the different strains the periosteum may encounter during bone growth. Specifically, we image rabbit tibial periosteum strips at -20%, 0%, 5%, and 10% strains. We first quantify these changes using the SHG creation ratio (Forward/Backward) or the initially emitted SHG directionality to provide information on the fibril level of assembly. The in situ (i.e. physiological) strain had the highest creation ratio compared to the non-in situ strains of -20%, 5%, and 10%, which were shown to be significantly different via RCBD statistical analysis. These trends are consistent with SHG phasematching considerations, where more organized fibrils/fibers result in primarily forward emitted components, which here is the physiological strain. We further use the relative SHG conversion efficiency to assess the tissue structure under strain, where this results from the combination of collagen concentration and organization. The 0% strain SHG conversion efficiency was significantly higher than all other strains, where this is expected as the fibers have the highest local density and organization, and is consistent with the emission directionality results. Importantly, due to the underlying physical process, the label-free SHG imaging modality can non-invasively monitor the effect of treatments for bone growth and other orthopedic disorders.

The tissue optical clearing technique could significantly enhance the biomedical optical imaging depth, but current investigations are mainly limited to in vitro studies. In vivo tissue optical clearing method should be enough rapid, transparent and safe, which makes it more difficult, especially, for hard tissue. During the past years, we developed skull optical clearing methods for in vivo cortical imaging. This presentation will report recent progress in skull optical clearing method, including their efficacy, safety, and applications. The skull optical clearing method is proved to be effective for adult mice ages in different month and permit various imaging techniques to monitor cortical blood flow, blood oxygen, and vascular with high resolution and contrast, not only for local cortex, but also for whole cortex. The long-term and short-term observation show that there is no obvious effect on cortical vascular function when laser speckle contrast imaging and hyperspectral imaging are used to repeatedly image the cortical blood flow, blood oxygen. Finally, we will demonstrate some applications for physiological or pathological situation, including monitoring the anoxia, drug-induced cortical response, et al.

In brain studies, the function of the cerebrospinal fluid (CSF) awakes growing interest, particularly related to studies of the glymphatic system in the brain, which is connected with the complex system of lymphatic vessels responsible for cleaning the tissues. The CSF is a clear, colourless liquid including water (H2O) approximately with a concentration of 99 %. In addition, it contains electrolytes, amino acids, glucose, and other small molecules found in plasma. The CSF acts as a cushion behind the skull, providing basic mechanical as well as immunological protection to the brain. Disturbances of the CSF circulation have been linked to several brain related medical disorders, such as dementia.

Our goal is to develop an in vivo method for the non-invasive measurement of cerebral blood flow and CSF circulation by exploiting optical and capacitive sensing techniques simultaneously. We introduce a prototype of a wearable probe that is aimed to be used for long-term brain monitoring purposes, especially focusing on studies of the glymphatic system. In this method, changes in cerebral blood flow, particularly oxy- and deoxyhaemoglobin, are measured simultaneously and analysed with the response gathered by the capacitive sensor in order to distinct the dynamics of the CSF circulation behind the skull. Presented prototype probe is tested by measuring liquid flows inside phantoms mimicking the CSF circulation.

Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.

In clinical medicine, a pathologist often needs to examine cells or thin slices of tissues to identify abnormalities that are markers or precursors of diseases. Various chemical and immunohistochemical staining techniques have been developed to selectively label certain components to bring up the contrasts of specific microstructures. It is well known that a Mueller matrix contains rich information on the microstructure and optical properties of a sample. Using proper data analysis techniques, Mueller matrix images can also be transformed into new polarization parameters sensitive only to specific microstructural features. These new polarization parameters can selectively enhance the contrast of specific features in images of unstained pathological slide to help identify abnormalities. In recent studies, we set up a modulus design Mueller matrix microscope by adding polarization optics components into the optical path of a commercial transmission microscope. We take multiple measurements of the unstained pathological slide at different polar and azimuth angles, then derive an intrinsic Mueller matrix (IMM) which represents only the microstructural characters of the sample without the interference by the sample orientation. Such orientation-independent IMM images preserve to the maximum extent the pathological information of the tissue samples. Using Mueller matrix decomposition and transformation techniques, we demonstrate in preliminary tests that we are able to selectively enhance different characteristic features in different cancer tissues. With the fast advances in big-data analysis techniques, it is expected that label-free Mueller matrix microscopy is a potentially powerful tool for the histopathologists to identify characteristic features in complex tissue samples.

Sensing and imaging methods based on the dynamic scattering of coherent light, including laser speckle, laser Doppler, and diffuse correlation spectroscopy quantify scatterer motion using light intensity (speckle) fluctuations. The underlying optical field autocorrelation (OFA), rather than being measured directly, is typically inferred from the intensity autocorrelation (IA) through the Siegert relationship, by assuming that the scattered field obeys Gaussian statistics. In this work, we demonstrate interferometric near-infrared spectroscopy (iNIRS) for measurement of time-of-flight (TOF) resolved field and intensity autocorrelations in fluid tissue phantoms and in vivo. In phantoms, we find a breakdown of the Siegert relationship for short times-of-flight due to a contribution from static paths whose optical field does not decorrelate over experimental time scales, and demonstrate that eliminating such paths by polarization gating restores the validity of the Siegert relationship. Inspired by these results, we developed a method, called correlation gating, for separating the OFA into static and dynamic components. Correlation gating enables more precise quantification of tissue dynamics. To prove this, we show that iNIRS and correlation gating can be applied to measure cerebral hemodynamics of the nude mouse in vivo using dynamically scattered (ergodic) paths and not static (non-ergodic) paths, which may not be impacted by blood. More generally, correlation gating, in conjunction with TOF resolution, enables more precise separation of diffuse and non-diffusive contributions to OFA than is possible with TOF resolution alone. Finally, we show that direct measurements of OFA are statistically more efficient than indirect measurements based on IA.

We present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce random components after recording the spectra (e.g., Savitzky-Golay filtering, polynomial approximation, denoising by empirical mode decomposition). We present noise sources generated in detectors of Raman scattered photon stream. We consider the methods of background noise reduction by increasing averaging time when the background noise comprises of white noise and 1/f noise components. We consider how the background noise reduces the accuracy of chemical compounds estimation using Raman spectra and prediction model based on linear (e.g., Principal Component Analysis) or nonlinear (e.g., Support Vector Machine) methods. Finally, we give some remarks about synchronous detection and background noise reduction.

The ability of diagnostics of oral lichen planus (OLP) based on spectral analysis of saliva using the THz spectroscopy is presented. The study included 8 patients with clinically proven OLP. The comparison group consisted of 8 healthy volunteers. Absorption spectra of the saliva was measured using time-domain spectrometer T-spec (EXPLA) in the range 0.2-3THz and have been considered as the feature vectors of the state. The spatial distribution of the objects under study in the feature space was analyzed using principle component analysis. The groups under study were shown to separate in full. Thus, the saliva analysis by the THz spectroscopy technique can be potentially used as a method of noninvasive diagnostics of the OLP.

Optical microangiography (OMAG) is a powerful optical angiographic tool to visualize micro-vascular flow in vivo. Despite numerous demonstrations for the past several years of the qualitative relationship between OMAG and flow, no convincing quantitative relationship has been proven. In this paper, we attempt to quantitatively correlate the OMAG signal with flow. Specifically, we develop a simplified analytical model of the complex OMAG, suggesting that the OMAG signal is a product of the number of particles in an imaging voxel and the decorrelation of OCT (optical coherence tomography) signal, determined by flow velocity, interframe time interval, and wavelength of the light source. Numerical simulation with the proposed model reveals that if the OCT amplitudes are correlated, the OMAG signal is related to a total number of particles across the imaging voxel cross-section per unit time (flux); otherwise it would be saturated but its strength is proportional to the number of particles in the imaging voxel (concentration). The relationship is validated using microfluidic flow phantoms with various preset flow metrics. This work suggests OMAG is a promising quantitative tool for the assessment of vascular flow.

Optical Coherence Tomography (OCT) is well-suited to study in vivo dynamics of blood circulation and lymphatic flow because of the technique’s combination of rapid image acquisition, micron spatial resolution, and penetration depth in turbid tissues. However, OCT has been historically constrained by a dearth of contrast agents that are readily distinguished from the strong scattering intrinsic to biological tissues. In this study, we demonstrate large gold nanorods (LGNRs) as optimized contrast agents for OCT. LGNRs produce 32-fold greater backscattering than GNRs previously tested for contrast-enhanced OCT. Furthermore, LGNRs exhibit 110-fold stronger spectral signal than conventional GNRs when coupled with custom spectral detection algorithms. This signal enhancement enables picomolar OCT detection sensitivity in vivo and single-particle detection against optically-clear backgrounds. Moreover, the ability to synthesize LGNRs with tunable spectral peaks provides a viable platform for multiplexed imaging studies. To explore the advantages of LGNRs as OCT contrast agents, we implemented them for noninvasive 3D imaging of tumor blood supply and active lymphatic drainage in mice. Spectral detection of LGNRs enabled 100% improvement in imaging depth for detecting microvasculature (vessels ∼ 20 μm in diameter) in U87MG glioblastoma xenografts in mice pinnae. We also demonstrated our approach’s ability to map the spatial dependence of lymph drainage and flow directionality within lymphatic capillaries. Using LGNRs with distinct spectra, we further identified the functional states of individual lymphatic valves in vivo. Thus, this approach provides a powerful new platform for functional imaging that may be extended for future molecular imaging studies with OCT.

In this paper, we make use of the empirical mode decomposition (EMD) to discriminate the cervical cancer tissues from normal ones based on elastic scattering spectroscopy. The phase space has been reconstructed through decomposing the optical signal into a finite set of bandlimited signals known as intrinsic mode functions (IMFs). It has been shown that the area measure of the analytic IMFs provides a good discrimination performance. Simulation results validate the efficacy of the IMFs followed by SVM based classification.

In this contribution, we report the application of higher order statistical moments using decision tree and ensemble based learning methodology for the development of diagnostic algorithms for optical diagnosis of cancer. The classification results were compared to those obtained with an independent feature extractors like linear discriminant analysis (LDA). The performance and efficacy of these methodology using higher order statistics as a classifier using boosting has higher specificity and sensitivity while being much faster as compared to other time-frequency domain based methods.

Diffuse reflectance spectroscopy (DRS) has been acknowledged as a valuable optical biopsy tool for in vivo characterizing pathological modifications in epithelial tissues such as cancer. In spatially resolved DRS, accurate and robust estimation of the optical parameters (OP) of biological tissues is a major challenge due to the complexity of the physical models. Solving this inverse problem requires to consider 3 components: the forward model, the cost function, and the optimization algorithm. This paper presents a comparative numerical study of the performances in estimating OP depending on the choice made for each of the latter components. Mono- and bi-layer tissue models are considered. Monowavelength (scalar) absorption and scattering coefficients are estimated. As a forward model, diffusion approximation analytical solutions with and without noise are implemented. Several cost functions are evaluated possibly including normalized data terms. Two local optimization methods, Levenberg-Marquardt and TrustRegion-Reflective, are considered. Because they may be sensitive to the initial setting, a global optimization approach is proposed to improve the estimation accuracy. This algorithm is based on repeated calls to the above-mentioned local methods, with initial parameters randomly sampled. Two global optimization methods, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), are also implemented. Estimation performances are evaluated in terms of relative errors between the ground truth and the estimated values for each set of unknown OP. The combination between the number of variables to be estimated, the nature of the forward model, the cost function to be minimized and the optimization method are discussed.

In this paper, the spectroscopy signals have been analyzed in recurrence plots (RP), and extract recurrence quantification analysis (RQA) parameters from the RP in order to classify the tissues into normal and different precancerous grades. Three RQA parameters have been quantified in order to extract the important features in the spectroscopy data. These features have been fed to different classifiers for classification. Simulation results validate the efficacy of the recurrence quantification as potential bio-markers for diagnosis of pre-cancer.

The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system.

We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate).

We consider changes in the volume of blood and oxygen saturation caused by a pulse wave and their influence on the diffuse reflectance spectra in the visible/NIR spectral range. CUDA-based Monte-Carlo model was used for routine simulation of detector depth sensitivity (sampling volume) and skin spectra, and their variations associated with physiological changes in the human skin. The results presented in the form of animated graphs of sampling volume changes for scaling of the parameters of the main human skin layers related to the results of experimental measurements are of particular interest for pulse oximetry, photoplethysmography, Doppler flowmetry, reflectance spectroscopy.

Characteristics of intermittency during the perception of ambiguous images have been studied in the case the Necker cube image has been used as a bistable object for demonstration in the experiments, with EEG being simultaneously measured. Distributions of time interval lengths corresponding to the left-oriented and right-oriented Necker cube perception have been obtain. EEG data have been analyzed using continuous wavelet transform which was shown that the destruction of alpha rhythm with accompanying generation of high frequency oscillations can serve as a electroencephalographical marker of Necker cube recognition process in human brain.

The contrast in laser speckle imaging with controlled polarization conditions for illumination and imaging was studied in a blood vessel mimic flow phantom. Either linear or circular polarization was used to illuminate samples. The polarization in imaging was controlled, to be either orthogonal (cross) or parallel to the polarization of the illumination beam. Temporal contrast imaging, was obtained by calculating the pixelwise contrast among a series of successfully recorded snapshot images. Then, temporal-spatial contrast imaging was calculated from temporal contrast imaging by calculating the spatial contrast among the pixels in a temporal contrast image. The results have shown that the parallel polarization setting had a near doubled contrast dynamic range compared to the cross polarization setting. Linear polarization and circular polarization did not show significant differences in contrast dynamic range. The results obtained here can be generally applied to all laser speckle based imaging, because they are all interference based imaging, and it is suggested that parallel polarization imaging setting can be considered for a better imaging contrast between flow and solid tissue background. In addition, in a preliminary flow speed test, the temporal-spatial contrast values did not show a statistical difference among different flow speeds due to the current experiment settings.

We found the intermittent phase synchronization in human epileptic brain. We show that the phases of the synchronous behavior are observed both during the epileptic seizures and in the fields of the background activity of the brain. We estimate the degree of intermittent phase synchronization in both considered cases and found that the epileptic seizures are characterized by the higher degree of synchronization in comparison with the fields of background activity. For estimation of synchronization degree the modification of the method for estimation of zero conditional Lyapunov exponent from time series proposed in [PRE 92 (2015) 012913] has been used.

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

In the paper we study the appearance of the complex patterns in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. A new method based on the calculation of the maximum energy component for the continuous wavelet transform (skeletons) is proposed. Skeleton analysis allows us to identify specific patterns in the EEG data set, appearing in the perception of ambiguous objects. Thus, it becomes possible to diagnose some cognitive processes associated with the concentration of attention and recognition of complex visual objects. The article presents the processing results of experimental data for 6 male volunteers.

The luminescence spectra of upconversion nanoparticles (UCNPs) imbedded in fat tissue were measured in a wide temperature range, from room to human body and further to hyperthermic temperatures. The two types of synthesized UCNP [NaYF₄:Yb³⁺, Er³⁺] specimens, namely, powdered as-is and embedded into polymer film, were used. The results show that the luminescence of UCNPs placed under the adipose tissue layer is reasonably good sensitive to temperature change and reflects phase transitions of lipids in tissue cells. The most likely, multiple phase transitions are associated with the different components of fat cells such as phospholipids of cell membrane and lipids of fat droplets. In the course of fat cell heating, lipids of fat droplet first transit from a crystalline form to a liquid crystal form and then to a liquid form, which is characterized by much less scattering. The phase transitions of lipids were observed as the changes of the slope of the temperature dependence of UCNP luminescence intensity. The obtained results confirm a high sensitivity of the luminescent UCNPs to the temperature variations within tissues and show a strong potential for providing a controllable tissue thermolysis.

In this paper we investigate the impact of competition between layers of adaptive multiplex network on pattern formation in the system under study and discuss the possibility of the further application of the obtained results for the analysis of the neural network of brain. To describe the dynamics of interacting nodes we use the Kuramoto model of coupled phase oscillators. To understand the macroscopic processes that take place in this system we calculate and compare the values of layer and global order parameter, which describe the degree of coherence between the nodes in each layer and over whole network, respectively. We find that in such adaptive network the low values of order inside layers corresponding to the formation of similar topologies among them. Nevertheless, the cluster synchronization results in divergence of layer structures from each other.

Near-infrared spectroscopy has been recognized as a potential technology for noninvasive blood glucose sensing. However, the detected spectral signal is unstable mainly because of (1) the weak light absorption of glucose itself within NIR range, (2) the influence of temperature and individual differences of biotissue. Our previous results demonstrated that the synergistic effect of both transmittance and reflectance could enhance the strength of the detection signal. In this talk, we design a set of experiments to analyze the effect of earlobe thickness on Near Infrared spectroscopic measurement by using home-made optical fiber probe within the wavelength of 1000-1600nm. Firstly, we made a MC simulation of single-layer skin model and five-layer skin model to get the diffused transmittance spectra and diffused reflectance spectra under different optaical path lengths. And then we obtain the spectra of the earlobes from different volunteers by the same way. The experimental results showed that with the increase of the thickness,the light intensity of diffused transmittance decreases, and the light intensity of diffused reflectance remaines substantially unchanged.

Near Infrared Spectroscopy (NIRS) technology has been recognized as one of the most promising non-invasive blood glucose measurement methods due to its convenience, high efficiency, noninvasiveness, and real-time monitoring. We build a system to measure transmittance and reflectance within NIR range simultaneously. And contact measuring method has been performed in order to reduce the influence of specular reflectance of the measured skin tissue. However, in this way, the optical probe could press the skin tissue and make it distorted, which might make the internal structure and the constituent distribution of tissue changed and further the tissue optical parameter changed. This could eventually change the distribution of transmittance spectra and reflectance spectra. In this talk, we collect the transmittance spectra and the diffused reflectance spectra of human earlobe within the wavelength of 900-1700nm under the different contact pressures. The results show that the diffused reflectance spectra decrease and the diffused transmittance spectra increase with the increase of the contact pressure between the probe and the earlobe. In order to improve the precision and stability of NIRS, the contact position of the deformation of 0.75mm is determined to be an optimal contact state measurement position.

In the paper we propose the novel method for dealing with the physiological artifacts caused by intensive activity of facial and neck muscles and other movements in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We introduce the mathematical algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from movement artifacts and show high efficiency of the method.

Biodynamic imaging is a novel 3D optical imaging technology based on short-coherence digital holography that measures intracellular motions of cells inside their natural microenvironments. Here both common-path and Mach-Zehnder designs are presented. Biological tissues such as tumor spheroids and ex vivo biopsies are used as targets, and backscattered light is collected as signal. Drugs are applied to samples, and their effects are evaluated by identifying biomarkers that capture intracellular dynamics from the reconstructed holograms. Through digital holography and coherence gating, information from different depths of the samples can be extracted, enabling the deep-tissue measurement of the responses to drugs.

In this paper we study the conditions of chimera states excitation in ensemble of non-locally coupled Kuramoto-Sakaguchi (KS) oscillators. In the framework of current research we analyze the dynamics of the homogeneous network containing identical oscillators. We show the chimera state formation process is sensitive to the parameters of coupling kernel and to the KS network initial state. To perform the analysis we have used the Ott-Antonsen (OA) ansatz to consider the behavior of infinitely large KS network.

In the paper we study the possibility to control the frequency of the sub-THz source, based on the semiconductor superlattice by means of optimal spatial distribution of the doping density. We propose the appropriate mathematical model, which allows to describe the collective transport of charge in miniband semiconductor, where the spatial profile of the equilibrium charge density is defined by function. As the example we consider the uniform spatial distribution of doping density, contained local inhomogeneity, caused by local increase of density and described approximately by Gaussian function. We show that such inhomogeneity being placed in different areas of the transport region can affect the dynamics of charge domain, which, in turn, leads to increase (or decrease) of the frequency of current oscillations.

We numerically study the interaction between the ensembles of the Hindmarsh-Rose (HR) neuron systems, arranged in the multilayer network model. We have shown that the fully identical layers, demonstrated individually different chimera due to the initial mismatch, come to the identical chimera state with the increase of inter-layer coupling. Within the multilayer model we also consider the case, when the one layer demonstrates chimera state, while another layer exhibits coherent or incoherent dynamics. It has been shown that the interactions chimera-coherent state and chimera-incoherent state leads to the both excitation of chimera as from the ensemble of fully coherent or incoherent oscillators, and suppression of initially stable chimera state

Optical properties of biological tissues are unique and may be used for tissue identification, tissue discrimination or even to identify pathologies. Early stage colorectal cancer evolves from adenomatous polyps that arise in the inner layer of the colorectal tube — the mucosa. The identification of different optical properties between healthy and pathological colorectal tissues might be used to identify different tissue components and to develop an early stage diagnosis method using optical technologies. Since most of the biomedical optics techniques use light within the visible and near infrared wavelength ranges, we used the inverse adding-doubling method to make a fast estimation of the optical properties of colorectal mucosa and early stage adenocarcinoma between 400 and 1000 nm. The estimated wavelength dependencies have provided information about higher lipid content in healthy mucosa and higher blood content in pathological tissue. Such data has also indicated that the wavelength dependence of the scattering coefficient for healthy mucosa is dominated by Rayleigh scattering and for pathological mucosa it is dominated by Mie scattering. Such difference indicates smaller scatterer size in healthy mucosa tissue. Such information can now be used to develop new diagnosis or treatment methods for early cancer detection or removal. One possibility is to use optical clearing technique to improve tissue transparency and create localized and temporary tissue dehydration for image contrast improvement during diagnosis or polyp laser removal. Such techniques can now be developed based on the different results that we have found for healthy and pathological colorectal mucosa.