Publications

Background

In patients with psychotic disorders, sleep spindles are reduced, supporting the hypothesis that the thalamus and glutamate receptors play a crucial etio-pathophysiological role, whose underlying mechanisms remain unknown. We hypothesized that a reduced function of NMDA receptors is involved in the spindle deficit observed in schizophrenia.

Methods

An electrophysiological multisite cell-to-network exploration was used to investigate, in pentobarbital-sedated rats, the effects of a single psychotomimetic dose of the NMDA glutamate receptor antagonist ketamine in the sensorimotor and associative/cognitive thalamocortical (TC) systems.

Results

Under the control condition, spontaneously-occurring spindles (intra-frequency: 10–16 waves/s) and delta-frequency (1–4 Hz) oscillations were recorded in the frontoparietal cortical EEG, in thalamic extracellular recordings, in dual juxtacellularly recorded GABAergic thalamic reticular nucleus (TRN) and glutamatergic TC neurons, and in intracellularly recorded TC neurons. The TRN cells rhythmically exhibited robust high-frequency bursts of action potentials (7 to 15 APs at 200–700 Hz). A single administration of low-dose ketamine fleetingly reduced TC spindles and delta oscillations, amplified ongoing gamma-(30–80 Hz) and higher-frequency oscillations, and switched the firing pattern of both TC and TRN neurons from a burst mode to a single AP mode. Furthermore, ketamine strengthened the gamma-frequency band TRN-TC connectivity. The antipsychotic clozapine consistently prevented the ketamine effects on spindles, delta- and gamma−/higher-frequency TC oscillations.

Conclusion

The present findings support the hypothesis that NMDA receptor hypofunction is involved in the reduction in sleep spindles and delta oscillations. The ketamine-induced swift conversion of ongoing TC-TRN activities may have involved at least both the ascending reticular activating system and the corticothalamic pathway.

This study covers the application of asymmetric accuracy metrics in the daily retail sales prediction problem. The paper is focused on the empirical validation of an accuracy metric derived from the newsvendor model. We scrutinize the accuracy metric’s advantages and describe its properties. This paper uses two main accuracy metrics: quantile-weighted and mean absolute error. We compare the economic effect of accuracy metrics for different models trained on food retail chain data. The results show that the asymmetric loss based on quantile-weighted absolute loss leads to lower business costs than the mean absolute error. The research is of interest to store managers, inventory management specialists, and logistics specialists in retail and restaurant chains. Our findings provide a better understanding of how to implement forecasting methods in order to obtain more accurate sales predictions that meet practitioner expectations.

The most common tools to understand perception of food products are hall tests, surveys and observations. However, these approaches require large samples to get reliable results and they are rather costly and time-consuming. Furthermore, they are also highly expert-dependent and rely on the assumption that study participants can express their preferences consciously and explicitly. In our paper, we suggest an electroencephalography- based (EEG) approach to evaluate perceived product similarity in a cross-modal taste-visual task. We tested two potential neurometrics measured from Fz electrode: the amplitude of the N400-like evoked response potentials (ERP) and the power of induced gamma oscillations during 400-600 ms period after visual stimulus presentation. Both metrics showed a strong correlation with the perceived similarity scores at both individual and group levels; however, N400-like amplitude had greater inter-subject variability making it less suitable for practical applications. The results based on the power of induced gamma oscillations (N=18) could be compared to traditional hall-tests (N=200) and may potentially reveal subtle differences in food perception that can not be captured in the hall-tests.

In this paper, we address several aspects of applying classical machine learning algorithms to a regression problem. We compare the predictive power to validate our approach on a data about revenue of a large Russian restaurant chain. We pay special attention to solve two problems: data heterogeneity and a high number of correlated features. We describe methods for considering heterogeneity — observations weighting and estimating models on subsamples. We define a weighting function via Mahalanobis distance in the space of features and show its predictive properties on following methods: ordinary least squares regression, elastic net, support vector regression, and random forest.

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Transcranial magnetic stimulation (TMS) is a promising diagnostic and therapeutic approach. TMSeffects depend on multiple technical and individual factors, including anatomical variability. The lattermay become particularly important in pathological conditions and contribute to the ambiguity in theresults from clinical trials and meta-analyses. Theoretical studies suggest that TMS effects strongly depend on the local orientation of the stimulated fibers. However, these models remain unconfirmed by experimental studies, since current modeling tools compute the induced and not the effective electric field. Here we propose a tool, incorporating information on fiber orientation into TMS effects modeling.This tool may be useful for relating the theoretical mechanisms to the experimentally observed TMS effects and for future development of the personalized TMS approaches.

This paper investigates the influence of individual mobility on consumer choice in the mobile phone market. The aim is to understand whether consumer mobility influences the switching of an individual to another tariff within one mobile operator. Data were obtained from 1,154 mobile phone users of one of the largest mobile operators in Russia for the period from November 2011 to November 2012. Customers had limited choices in fast and low-cost switching from one operator to another. Hence, we use data of users switching between tariffs within one operator. The data were analyzed by a mixed logit model which is applied to a discrete choice from a variety of disordered alternatives. This solves the restriction of the standard logit model by allowing for random taste variation. We developed three mobility metrics limiting the drawbacks of established metrics. The results show that mobility does influence consumer choices. Tariff plans differ from each other according to the categories of people that use them. Subscriber mobility is one of the features that separate these categories. There are tariffs preferred by highly mobile people, and those that are preferred by people with low mobility. When the individual’s mobility changes, it is highly likely that she will switch to another tariff plan. Mobile operators should take consumer mobility into account when analyzing consumer behavior to increase retention rates.

Studies of the biomarkers of atrial cardiopathy seem to be promising for identifying patients with cryptogenic stroke (CS), in which an intensive search for atrial fibrillation is indicated. Nevertheless, the diagnostic value of these markers and their threshold values require clarification.

Objective: to present the characteristics of echocardiographic markers for atrial cardiopathy and the serum concentration of N-terminal pro-Btype natriuretic peptide (NT-proBNP) in embolic CS versus cardioembolic stroke (CES) and non-cardioembolic stroke (non-CES) to determine the threshold values of parameters with the highest sensitivity and specificity in differentiating CES and non-CES.

Patients and methods. A total of 259 patients with ischemic stroke were examined. The standard examination additionally involved calculation of the parameters that reflected left atrial LA) function (LAF): LA emptying fraction (LAEF), and LA functional index (LAFI). The serum NT-proBNP concentration was also determined in 75 patients.

Results and discussion. The patients with CES versus those with CS and non-CES were characterized by a considerable increase in LA diameter (4.3 [3.5; 4.5] cm vs 3.7 [3.4; 4.0] cm vs 3.7 [3.4; 3.9] cm; p=0.005 and p=0.009, respectively), LAVI (35.7 [30.5; 39.9] ml/m2 vs 28.5 [25.6; 34.6] ml/m2 vs 27.1 [24.5; 31.2] ml/m2 ; p< 0.001) and NT-proBNP level (559 [409; 1144] pg/ml vs 164 [65; 308] pg/ml vs 191 [63; 446] pg/ml; p=0.002 and p=0.019, respectively), as well as by a lower LAEF value [50.3 [48.5; 51.1]% vs 54.7 [51.6; 56.6]% vs 54.9 [52.5; 56.8]%; p< 0.001). The only parameter that showed significant differences between all the three groups (CES, CS, and nonCES) was LAFI (0.24 [0.2; 0.32] units vs 0.37 [0.3; 0.47] units vs 0.40 [0.34; 0.47] units; p<0.00 1), while maintaining the differences in the values for the two groups (CS and non-CES) (p=0.004). The following threshold values of biomarkers were obtained for CES and nonCES; these were a LA diameter of 41.5 mm (p< 0.001), a LAVI of 36.3 ml/m2 (p< 0.001), a LAEF of 51.8% (p< 0.001), a LAFI of 0.28 units (p< 0.001), and an NT-proBNP of 316 pg/ml (p< 0.001). Analysis of the ROC curves and the area under the curve (AUC) revealed that the most informative criteria for sensitivity and specificity were LAEF (79 and 88%, AUC 0.89), NT-proBNP (67 and 91%, AUC 0.89) and LAFI (93 and 72%, AUC 0.81).

Conclusion. The CS group and non-CES one are comparable in the echocardiographic manifestations of atrial cardiopathy and in serum NTproBNP values. LAEF and NT-proBNP concentrations are promising biomarkers to classify CS patients into potential arterio- and cardioembolic types.

Understanding neurological mechanisms of motor recovery after stroke is important for selecting appropriate therapeutic and rehabilitation strategies. One of the most widely-used but yet rather controversial MRI predictors is a co-called lesion load on the cortico-spinal tract (CST). This metric corresponds to the overlap between the volumes of the lesion and the cortico-spinal tract which is responsible for conducting neuronal signals that lead to motion generation. In this study we evaluated the potential of the lesion load to explain the motor outcome in a cohort of patients with chronic ischemic stroke. Lesions were automatically identified on structural T1-weighted images using LINDA package. Once lesions are identified, lesion loads on CST were calculated automatically using PALS software package (Ito et al., 2018). Finally, the obtained results were used to classify patients according to their motor outcome using decision tree classifier J48 implemented in WEKA software. However, the classification accuracy was much lower compared to the classification results based on another widely accepted MRI parameter: asymmetry of the fractional anisotropy in the internal capsule of the CST.

The degree of mental attention in childhood and adolescence determines in the future the effectiveness of working memory (ability to store and manipulate information). Attention has been previously found to be related to the prefrontal and parietal areas of the human cortex. But the relationship between attention and white matter properties are still largely unknown. The goal of this study was to identify the relationships between attention and fractional anisotropy (FA) of diffusion MRI in bilateral superior longitudinal fasciculus (in three subdivisions SLF 1- 3), arcuate fasciculus (AF), and corpus callosum (CC) in children and adolescents. Subjects: 14 children (9-11 years) and 13 teenagers (12-15 years). During the experiments participants had to establish a match between the colors on the screen and the colors on the previous slide. The task had six difficulty levels and both performance accuracy (m-score) and reaction time (RT) were measured. There was a positive correlation for m-score and a negative correlation for RT with FA in СС (levels 1-3) in the children's group (p<0.05). On the contrary, when FA increases in the right SLF 3 (level 6), there is a decrease in m-score, and when FA increases in the left SLF 3 and AF, there is an increase in RT at 2,3,4 and 6 levels. In contrast, a decrease in RT with an increase FA of bilateral SLF 3 (level 6) and left AF (level 4) was observed for adolescents, which reflects the redistribution of the roles between fiber tracts with age. FA values of the left (level 2) and right (level 1) SLF 2 negatively correlated with mscore (p <0.05) in the same group. For females (n=13) (regardless the age), there was only a negative correlation for m-score (2,3,5 levels) and the only positive correlation for RT (level 2) with FA of the right SLF 1, left and right SLF 2, in the left SLF 3 and СС (p<0.05). For males (n=13), on the contrary, there were positive correlations between m-score and FA of the СС (1,3,4 levels) and the left SLF 1 (5 level), and inverse correlations between RT and FA for the same fibers of the white matter (1 level) (p<0,05). Interestingly, an increase in FA with age was found in males in all the components of the white matter (p<0.01), except for the СС, and in females, on thecontrary – only in the СС. Further research is needed, taking into account gender, to fully understand the influence of white matter on the development of mental attention.

Patent foramen ovale (PFO) is an important cause of embolic cryptogenic stroke (ECS) in young patients. The main mechanism in this case is paradoxical embolism (PE), the basis for which is a right-to-left (R-L) shunt. Objective: to comparatively characterize patients who have undergone ECS, with and without an R-L shunt, as evidenced by transcranial Doppler with the bubble test (TCD-BT).

The most common tools to understand perception of food products are hall-tests, surveys, observations, etc. However to get reliable results these approaches require large samples, making them costly and time-consuming. Furthermore, they are also highly expert-dependent and rely on the assumption that study participants can express their preferences consciously and explicitly. Here we suggested an EEG-based approach to evaluate perceived product similarity in a cross-modal taste-visual task. Two candidate neurometrics measured from Fz electrode were tested: the amplitude of N430-620 from evoked response potentials (ERP) and the power of induced gamma oscillations during 400-600 ms period after visual stimulus presentation. Both suggested metrics showed a strong correlation with the perceived similarity scores at both individual and group levels, however N430-630 had greater inter-subject variability making it less suitable for practical applications. The results based on the power of induced gamma oscillations (N=18) not only reflected the results from traditional hall-tests (N=200) but also allowed better discrimination between different food products.

Processing of mathematical operations and solving numerical tasks implicate a distributed set of brain regions. These regions include the superior and inferior parietal lobules that underlie numerical processing such as size judgments, and additional prefrontal regions that are needed for formal mathematical operations such as addition, subtraction and multiplication [Arsalidou, Taylor, 2011]. Critically, little is known about the connectivity between these regions and the association between math performance and the anatomical structure of white matter tracts. The present study investigates connectivity and white matter tracks associated with networks related to math performance: arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Participants performed a computerized task with mathematical operations (addition, subtraction, multiplication, and division) with three levels of difficulty; accuracy and reaction time were recorded. Diffusion tensor imagining (DTI) recordings provided indices on fractional anisotropy (FA) — a measure of the direction of white matter tracks in the brain. The relation between FA and math performance scores is reported.

This paper is an empirical study of the changing nature of the dependence of fundamental factors on the stock market index, which is the trend identified earlier in the Russian stock market. We empirically test the impact of daily values of fundamental factors on the MOEX Russia Index from 2003 to 2018. The analysis of the ARIMA-GARCH (1,1) model with a rolling window reveals that the change in the power and direction of the influence of the fundamental factors on the Russian stock market persists. The Quandt-Andrews breakpoint test and Bai-Perron test identify the number and likely location of structural breaks. We find multiple breaks probably associated with the dramatic falls of the stock market index. The results of the regression models over the different regimes, defined by the structural breaks, can vary markedly over time. This research is of value in macroeconomic forecasting and in the investment strategy development

This paper studies how the influence of the fundamental factors on the Russian stock market changes retrospectively. We empirically test the impact of daily values of fundamental factors (indexes of foreign stock markets, oil price, exchange rate and interest rates in Russia and the USA) on the MOEX Russia Index over long time interval from 2003 to 2018. The analysis of the ARIMA-GARCH (1,1) model with a rolling window reveals the changes in the power and direction of the influence of the fundamental factors which are probably caused by the structural instability revealed earlier in Russia and other stock markets. The Quandt-Andrews breakpoint test and Bai-Perron test identify the number and likely location of the structural breaks. We find multiple breaks probably associated with dramatic falls in the stock market index, for example with the significant falls of the then MICEX index in the spring of 2006 and the global financial crisis of 2008-2009. The results of the regression models over the different regimes, defined by the structural breaks, can vary markedly over time.

This paper describes the results of research project on optimal pricing for LLC "Perm Local Rail Company". In this study we propose a regression tree based approach for estimation of demand function for local rail tickets considering high degree of demand heterogeneity by various trip directions and the goals of travel. Employing detailed data on ticket sales for 5 years we estimate the parameters of demand function and reveal the significant variation in price elasticity of demand. While in average the demand is elastic by price, near a quarter of trips is characterized by weakly elastic demand. Lower elasticity of demand is correlated with lower degree of competition with other transport and inflexible frequency of travel.