Presently, despite a large number of studies, the problem associated with the detection of speech patterns on the EEG is still relevant. In this study, we aimed to detect the spatial-frequency localization of specific EEG patterns associated with cognitive load related to the process of real and inner speech. To achieve this, we developed a methodology to identify epochs of stimulus-independent signals containing these patterns. Frequency localization was determined using the Ochiai coefficient, and spatial localization using one-way analysis of variance. The specific EEG pattern represent the frequency coherence coefficients in the resulting spectral-spatial window. It was shown that the realization of verbal activity causes the formation of spatiotemporal patterns of EEG activity in the gamma rhythm sub-band of frequencies 60–65 Hz in bilateral channels, which correspond to the following cortical regions: frontal superior (Fp1, Fp2), temporal superior (F7, F8, Ft7, Ft8), mid-temporal (T3, T4), temporo-parietal (Tp7, Tp8), temporal inferior (T5, T6), temporo-central (Cp3, Cp4), parietal (P3, P4, P5, P6), parieto-occipital (Po3, Po4, Po7, Po8). Mapping and optimization of the feature space for EEG patterns associated with inner speech was performed. Stable and efficient registration of such patterns makes it possible to solve the problem of establishing a neural control channel for brain-computer neural interface systems.

BCI based on inner speech become a promising and user-friendly systems for human-machine interaction. In resent years interest for this technology has significantly grown due to latest advancements in machine learning and neural networks. In our study the EEG inner speech database containing patterns of 7 word-directions obtained from 13 subjects was formed. Various machine learning techniques were applied to separate word patterns for future application in BCI system. Based on these results, we proposed a cascade machine learning model achieving an overall accuracy of 35.7

Monitoring excited hydroxyl (OH*) airglow is broadly used for characterizing the state and dynamics of the terrestrial atmosphere. Recently, the existence of excited hydroxyl was confirmed using satellite observations in the Martian atmosphere. The location and timing of its detection on Mars were restricted to a winter season at the north pole. We present three-dimensional global simulations of excited hydroxyl over a Martian year. The predicted spatio-temporal distribution of the OH* can provide guidance for future observations, namely by indicating where and when the airglow is likely to be detected.

The spinal cord, nerves, and skeletal muscles arise from neuromesodermal progenitors (NMPs). We have developed a growth-factor screening strategy, utilizing ES and iPS cells, facilitating the indefinite self-renewal of two types of human axial stem cells (AxSCs), closely resembling mouse NMPs (NM-AxSCs) and posterior neural tube progenitors (N-AxSCs). Under specific regimens— Wnt/CHIR99021, FGF2, and TGF-β inhibitor SB431542 (CFS) and excluding FGF2 (CS), respectively—these AxSCs self-renew and sustain telomeres. Single cell transcriptomics and proteomics have revealed expression of posterior growth-zone and dorsoventral neural tube markers in NM-AxSCs, and correspondingly, differentiation to a wide spectrum of neural tube neurons and myocytes. N-AxSCs rapidly matured into dorsal sensory subsets and neural crest. Crucially, neither AxSC type produces teratomas, and analogous mouse NM-AxSCs integrated successfully into the neural tube and somites. Capturing of AxSCs from patient and GMP ES / iPS cells without transgenesis unveils ontogeny and promises modeling and therapy in neuropathies. ### Competing Interest Statement The authors have declared no competing interest.

In recent years, interest for brain computer interfaces (BCI) and their potential applications has been grown. However, despite their potential benefits, there are still many challenges which should be solved before BCIs can be widely used outside of laboratory conditions. One of the key issues is the real-time discrimination of movement- related EEG phenomena, which is essential for the use of portable EEG devices in everyday life. In this study different machine learning approaches with preliminary statistical and spectral feature extraction were compared in classification of movement-related artifacts. Dataset in this research was obtained from experiment with portable EEG of our development. Tested methods demonstrated high accuracy up to 80 percent in 7-classes discrimination task.

The data for Remote Sensing article figures.

mp3 file (7.8 MB). In the February edition of the Cancer Discovery podcast, Executive Editor Mark Landis talks with Hani Gabra about his paper, which demonstrates that OPCML binds the extracellular domains of specific receptor tyrosine kinases to induce their endocytic internalization and proteasomal degradation.

The study was aimed at developing a new automatic search technique for specific invariant patterns of movement-related brain potentials reflected in multidimensional electroencephalogram (EEG) signals. An adaptive band-pass filter with bandwidth closely matching the spectrum of the desired EEG pattern at the observed moment was synthesized based on the Singular Spectrum Analysis methodology. The preliminary filtering of the original EEG signals provides the required sensitivity for subsequent searching of time boundaries in patterns. The correctness of the developed method was confirmed with standard machine learning tools through the validation of the adaptive search method carried out on the general set of initial data. It is shown that the synthesized method has provided a reliable automatic search for induced pre-movement EEG patterns and the correct determination of their time boundaries (accuracy up 29% on average and reached maximum values to 100% for some individuals). The developed method expands the existing tools to improve the functionality and reliability of various Brain-computer interfaces for various purposes, including medical applications for paralyzed patients.

We present a novel biologically plausible model of cerebellar learning. The study includes three substantial points. First, we show that the effective model of cerebellum does not need any explicit error signals of organism actions to perform learning tasks. In our model the synapses weights from granule cells to Purkinje cells change so that the latter learn to reconstruct extracerebellar input to its climbing fiber cells of inferior olives (ClFCs). The second point is that we demonstrate the emergence of chaotic behaviour in our model which does not depend on electrical synapses between the cells of inferior olives. Third, we compare climbing fiber cells activity in the model with the Purkinje cells complex spikes sequences in guinea pig cerebellum using ordinal analysis method and three other independent statistical properties (variation coefficients, autocorrelation functions and intervalograms). We conclude that all examined theoretical and experimental properties are in good accordance with each other. The plausible importance of the revealed phenomenae for cerebellar function is discussed.

An approach to classification of three different imaginary movements based on linear discriminant analysis transformations and applicable to brain-computer interface implementations is considered.First, search for discriminative frequencies individual for each subject and each movement is conducted.It is shown that this procedure leads to an increase in classification accuracy compared to conventional common spatial patterns algorithm followed by linear classifier considered as a baseline approach.In addition, an original approach to finding discriminative time segments for each movement is tested.This approach led to further increase in accuracy if Hjorth parameters and inter-channel correlation coefficients were used as features calculated for the found segments.Particularly, classification by the latter feature led to the best accuracy of 69,4% averaged over all subjects.Besides, scatter plots demonstrated that two out of three movements pairs were discriminated by the approach presented.

It is quite clear that a person can make mistakes in the process of speech: badly pronounced letters, “missing” syllables. This situation poses certain difficulties for developments in the field of mental or inner speech-based BCI technology. The inability to separate errors from correct speech can significantly reduce the effectiveness of BCIs. In this study, we used words representing the direction in space and pseudowords made randomly from individual syllables, that is, pseudowords were phonetically close to words. The aim of the study was to explore the possibilities of neural network classification of words and pseudo-words-related EEG coherence patterns in the task of mental and spoken speech. It was shown that the preparation and pronunciation of pseudowords takes a long time and is performed non-lexically with sublexical components. It is shown that the structure of EEG patterns with high coherence values registered in both hemispheres in the gamma range is homotopically equivalent and seems to be related to attention mechanisms. The EEG patterns with low coherence are significantly different, which indicates the specifics of right hemisphere involvement in speech processes. The most stable coherence patterns with a significant difference between words and pseudo-words are found in the left hemisphere in gamma frequencies. The main conclusion is that the neural network classification of inner speech-related EEG coherence patterns based on the multilayer perceptron (MLP) demonstrates an accuracy up to 90

Observations of vibrationally excited hydroxyl (OH*) emissions are widely used to obtain information about the dynamics and composition of the atmosphere. We present some analytical approximations for the characteristics of the hydroxyl layer in the Martian atmosphere such as OH* concentration at the maximum and height of the maximum, as well as relations for estimating the influence of various factors on the OH* layer in night conditions. These characteristics depend on the temperature of the environment, concentration of atomic oxygen, and their vertical gradients. The relations are applied to the results of numerical modeling using the global atmospheric circulation model for prediction of seasonal behavior of the hydroxyl layer on Mars. Annual and intra-annual variations in the concentration of excited hydroxyl and layer height from the modeling data have both some similarities with those of the Earth and significant differences. The concentration and height maximum in the equatorial, northern and southern midlatitudes vary depending on the season; the maximum concentration and the minimum height fall on the first half of the year. Model calculations confirmed the presence of the peak OH* concentration at polar latitudes in winter at an altitude of approximately 50 km with the volume emission densities of 2.1, 1.4, and 0.6 × 10 4 photons cm –3 s –1 for vibrational level transitions 1–0, 2–1, and 2–0, respectively. The relations obtained may be used for the analysis of measurements and interpretation of their variations.

Within the framework of this work, using a three-dimensional numerical model of the general circulation of the Martian atmosphere MAOAM (Martian Atmosphere: Observation and Modeling), also known as MPI-MGCM (Max Planck Institute Martian General Circulation Model), we simulated the planet's hydrological cycle during the 28 and 34 Martian years (MY28 and MY34) dust storm seasons. A quantitative assessment of the photodissociation of water vapor under the influence of solar radiation at the Lyman-alpha wavelength has been carried out. The simulation results are compared with individual profiles obtained with the Atmospheric Chemistry Suite (ACS) spectrometer installed on the ExoMars Trace Gas Orbiter (TGO) spacecraft. The MAOAM model has a spectral dynamical core and successfully predicts the temperature regime of Mars through the use of physical parameterizations that are characteristic of both Earth and Martian models. The hydrodynamic block of the model includes the transfer scheme, microphysics of water vapor and ice, heterogeneous nucleation, sedimentation, photodissociation, and exchange of water with the surface. Studies show the effect of dust storms on both the total water vapor content in the atmosphere and its vertical distribution. More intense pumping of water vapor into the upper atmosphere during dust storms provides more intense photodissociation of water vapor (in some seasons up to 6.5 tons per second in total in the entire atmosphere). The strongest photodissociation is observed at heights of 50 to 80 km for MY34 and 70 to 80 km for MY28. The dissociated water vapor can then potentially become a source of hydrogen dissipation into space, followed by a decrease in the mass of water on the planet.

This article analyzes known data on the systemic functions of vision, such as discrimination and recognition of visual objects, visual seeking, assessment of the emotional content of scenes, and decision-making in the foveal and peripheral visual fields. Existing hypotheses for the possible mechanisms of functional phenomena occurring in the human peripheral field are discussed. A neurological informatic approach to solving problems of the interaction of foveal and peripheral vision based on inspection trajectories, areas of interest, and return gaze fixations are described. Computer experiments showed that the structure of an inspection trajectory model correlates with the number of return fixations of the “input window” of the model. This suggested that the probability of return fixations could be regarded as a quantitative criterion for identifying the type of attention (focal or spatial) and the moment of attention-switching.

A linear discriminant analysis transformation-based approach to the classification of three different motor imagery types for brain–computer interfaces was considered. The study involved 16 conditionally healthy subjects (12 men, 4 women, mean age of 21.5 years). First, the search for subject-specific discriminative frequencies was conducted in the task of movement-related activity. This procedure was shown to increase the classification accuracy compared to the conditional common spatial pattern (CSP) algorithm, followed by a linear classifier considered as a baseline approach. In addition, an original approach to finding discriminative temporal segments for each motor imagery was tested. This led to a further increase in accuracy under the conditions of using Hjorth parameters and interchannel correlation coefficients as features calculated for the EEG segments. In particular, classification by the latter feature led to the best accuracy of 71.6%, averaged over all subjects (intrasubject classification), and, surprisingly, it also allowed us to obtain a comparable value of intersubject classification accuracy of 68%. Furthermore, scatter plots demonstrated that two out of three pairs of motor imagery were discriminated by the approach presented.

The northern white rhinoceros (NWR) is probably the earth's most endangered mammal. To rescue the functionally extinct species, we aim to employ induced pluripotent stem cells (iPSCs) to generate gametes and subsequently embryos in vitro. To elucidate the regulation of pluripotency and differentiation of NWR PSCs, we generated iPSCs from a deceased NWR female using episomal reprogramming, and observed surprising similarities to human PSCs. NWR iPSCs exhibit a broad differentiation potency into the three germ layers and trophoblast, and acquire a naïve-like state of pluripotency, which is pivotal to differentiate PSCs into primordial germ cells (PGCs). Naïve culturing conditions induced a similar expression profile of pluripotency related genes in NWR iPSCs and human ESCs. Furthermore, naïve-like NWR iPSCs displayed increased expression of naïve and PGC marker genes, and a higher integration propensity into developing mouse embryos. As the conversion process was aided by ectopic BCL2 expression, and we observed integration of reprogramming factors, the NWR iPSCs presented here are unsuitable for gamete production. However, the gained insights into the developmental potential of both primed and naïve-like NWR iPSCs are fundamental for in future PGC-specification in order to rescue the species from extinction using cryopreserved somatic cells.

This paper describes the hardware and software system to connect the brain-computer interface system and the virtual reality environment. The software package includes a virtual reality game application, which control is paired with the performance of mental equivalents of real movements. The motivational component of the technique is based on a game interface in a virtual reality environment. The combination of software package and virtual reality contributes to deep immersion of the user in the process of ideomotor training. A neural network classifier, which was trained and tested using publicly available data, was implemented to solve the problem of recognition and classification of mental ideomotor commands.

Simulations with the Max Planck Institute Martian general circulation model for Martian years 28 and 34 reveal details of the water "pump" mechanism and the role of gravity wave (GW) forcing. Water is advected to the upper atmosphere mainly by upward branches of the meridional circulation: in low latitudes during equinoxes and over the south pole during solstices. Molecular diffusion plays little role in water transport in the middle atmosphere and across the mesopause. GWs modulate the circulation and temperature during global dust storms, thus changing the timing and intensity of the transport. At equinoxes, they facilitate water accumulation in the polar warming regions in the middle atmosphere followed by stronger upwelling over the equator. As equinoctial storms decay, GWs tend to accelerate the reduction of water in the thermosphere. GWs delay the onset of the transport during solstitial storms and change the globally averaged amount of water in the upper atmosphere by 10%-25%.

Observations of vibrationally excited hydroxyl (OH*) emissions are widely used to obtain information on atmospheric dynamics and composition. In this paper, several analytical approximations are presented for characteristics of the hydroxyl layer in the Martian atmosphere, such as OH* concentrations at the maximum and the height of the maximum. Relationships are also given for estimating the influence of various factors on the OH* layer in nighttime conditions. These characteristics are determined by the ambient temperature and the concentration of atomic oxygen, including their vertical gradients. The obtained relationships are applied to the results of numerical modeling using the global atmospheric circulation model to predict the seasonal behavior of the hydroxyl layer on Mars. Based on the modeling data, the annual and intra-annual variations in the concentration of excited hydroxyl and the height of the OH* layer on Mars show both similarities to and considerable differences from those on Earth. The concentration and the height of the maximum in the equatorial, northern, and southern middle latitudes vary with the season, with the maximum concentrations and the lowest height being recorded in the first half of the year. Model calculations confirmed the presence of a peak in the OH* concentration in polar latitudes in winter at a height of approximately 50 km with volume emission densities of 2.1, 1.4, and 0.6 × 104 photons cm–3 s–1 for the transitions of vibrational levels 1–0, 2–1, and 2– 0, respectively. The resulting relationships can be used to analyze measurements and interpret their variations.