PURPOSE: The Core Outcome Measures Index (COMI) is a short, multidimensional instrument translated into several languages that covers five domains recommended in the assessment of outcome in patients with low-back and neck pain. The purpose of this study was to cross-culturally adapt the COMI from English to Czech language and to test the face and construct validity and reproducibility of its results in patients with low-back and neck pain. METHODS: Participants (n = 125) were included from primary and secondary care. The participants reported moderate pain and disability levels. All participants filled in the COMI forms before and after surgery. Descriptive statistics, Wilcoxon paired test, Crombach's alpha, principal component analysis and information entropy calculation were used. RESULTS: The instrument was successfully forward and back-translated. It can be seen that the questionnaire applied as part of our intervention study produces answers with a sufficient degree of variability and with a satisfactory degree of representation of extreme values. It can be also seen that the questionnaire can diagnose an objectively occurring change associated with the surgeon within the intervention procedure. Our other findings support the idea of ​​a possible reduction in the number of questions that measure the same latent variable. Our investigations also showed that it is possible to reduce the range of the point scale of the perception of pain to 5 degrees of intensity and thus unify the range with the other questions. CONCLUSION: The Czech COMI shows acceptable properties and is thus suitable to use as a short instrument for measuring important domains in patients with low-back and neck pain.

• MeSH
• Neck Pain * diagnosis   MeSH
• Adult MeSH
• Outcome Assessment, Health Care methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Low Back Pain * diagnosis   MeSH
• Pain Measurement methods   MeSH
• Disability Evaluation MeSH
• Surveys and Questionnaires standards   MeSH
• Reproducibility of Results MeSH
• Aged MeSH
• Cross-Cultural Comparison * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH

INTRODUCTION: The use of antidepressants in bipolar disorder (BD) remains contentious, in part due to the risk of antidepressant-induced mania (AIM). However, there is no information on the architecture of mood regulation in patients who have experienced AIM. We compared the architecture of mood regulation in euthymic patients with and without a history of AIM. METHODS: Eighty-four euthymic participants were included. Participants rated their mood, anxiety and energy levels daily using an electronic (e-) visual analog scale, for a mean (SD) of 280.8(151.4) days. We analyzed their multivariate time series by computing each variable's auto-correlation, inter-variable cross-correlation, and composite multiscale entropy of mood, anxiety, and energy. Then, we compared the data features of participants with a history of AIM and those without AIM, using analysis of covariance, controlling for age, sex, and current treatment. RESULTS: Based on 18,103 daily observations, participants with AIM showed significantly stronger day-to-day auto-correlation and cross-correlation for mood, anxiety, and energy than those without AIM. The highest cross-correlation in participants with AIM was between mood and energy within the same day (median (IQR), 0.58 (0.27)). The strongest negative cross-correlation in participants with AIM was between mood and anxiety series within the same day (median (IQR), -0.52 (0.34)). CONCLUSION: Patients with a history of AIM have a different underlying mood architecture compared to those without AIM. Their mood, anxiety and energy stay the same from day-to-day; and their anxiety is negatively correlated with their mood.

• MeSH
• Affect * drug effects   MeSH
• Antidepressive Agents * therapeutic use   adverse effects   MeSH
• Bipolar Disorder * drug therapy   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Mania * drug therapy   chemically induced   MeSH
• Psychiatric Status Rating Scales MeSH
• Anxiety drug therapy   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROND: One of the important areas of heart research is to analyze heart rate variability during (HRV) walking. OBJECTIVE: In this research, we investigated the correction between heart activation and the variations of walking paths. METHOD: We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus the Shannon entropy of different walking paths and accordingly evaluated their relation. RESULTS: According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series. CONCLUSION: The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.

• MeSH
• Time Factors MeSH
• Walking * MeSH
• Electrocardiography * MeSH
• Entropy MeSH
• Humans MeSH
• Heart Rate physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Analysis of the reactions of different organs to external stimuli is an important area of research in physiological science. OBJECTIVE: In this paper, we investigated the correlation between the brain and facial muscle activities by information-based analysis of electroencephalogram (EEG) signals and electromyogram (EMG) signals using Shannon entropy. METHOD: The EEG and EMG signals of thirteen subjects were recorded during rest and auditory stimulations using relaxing, pop, and rock music. Accordingly, we calculated the Shannon entropy of these signals. RESULTS: The results showed that rock music has a greater effect on the information of EEG and EMG signals than pop music, which itself has a greater effect than relaxing music. Furthermore, a strong correlation (r= 0.9980) was found between the variations of the information of EEG and EMG signals. CONCLUSION: The activities of the facial muscle and brain are correlated in different conditions. This technique can be utilized to investigate the correlation between the activities of different organs versus brain activity in different situations.

• MeSH
• Acoustic Stimulation MeSH
• Electroencephalography * methods   MeSH
• Electromyography methods   MeSH
• Humans MeSH
• Brain physiology   MeSH
• Facial Muscles * physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart's activity, a relationship should exist among their activities. OBJECTIVE: In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis. METHODS: Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6 F, 18-22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked. RESULTS: The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ=-0.9566). CONCLUSION: We conclude that heart and brain activities are related.

• MeSH
• Adult MeSH
• Electroencephalography * MeSH
• Electrocardiography MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Brain MeSH
• Heart * MeSH
• Heart Rate physiology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Publication type
• Journal Article MeSH

The apparent stochastic nature of neuronal activity significantly affects the reliability of neuronal coding. To quantify the encountered fluctuations, both in neural data and simulations, the notions of variability and randomness of inter-spike intervals have been proposed and studied. In this article we focus on the concept of the instantaneous firing rate, which is also based on the spike timing. We use several classical statistical models of neuronal activity and we study the corresponding probability distributions of the instantaneous firing rate. To characterize the firing rate variability and randomness under different spiking regimes, we use different indices of statistical dispersion. We find that the relationship between the variability of interspike intervals and the instantaneous firing rate is not straightforward in general. Counter-intuitively, an increase in the randomness (based on entropy) of spike times may either decrease or increase the randomness of instantaneous firing rate, in dependence on the neuronal firing model. Finally, we apply our methods to experimental data, establishing that instantaneous rate analysis can indeed provide additional information about the spiking activity.

• Publication type
• Journal Article MeSH

In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients' health using clustering method, ML-based binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to extract the most informative genes taking into account both the subtypes of disease or state of the patient's health for further reconstruction of gene regulatory networks based on the allocated genes and following simulation of the reconstructed models. We used the publicly available gene expressions data as the experimental ones which were obtained using DNA microarray experiments and contained two types of patients' gene expression profiles-the patients with lung cancer tumor and healthy patients. The stepwise procedure of the data processing assumes the following steps-in the beginning, we reduce the number of genes by removing non-informative genes in terms of statistical criteria and Shannon entropy; then, we perform the stepwise hierarchical clustering of gene expression profiles at hierarchical levels from 1 to 10 using the SOTA (Self-Organizing Tree Algorithm) clustering algorithm with correlation distance metric. The quality of the obtained clustering was evaluated using the complex clustering quality criterion which is considered both the gene expression profiles distribution relative to center of the clusters where these gene expression profiles are allocated and the centers of the clusters distribution. The result of this stage execution was a selection of the optimal cluster at each of the hierarchical levels which corresponded to the minimum value of the quality criterion. At the next step, we have implemented a classification procedure of the examined objects using four well known binary classifiers-logistic regression, support-vector machine, decision trees and random forest classifier. The effectiveness of the appropriate technique was evaluated based on the use of ROC (Receiver Operating Characteristic) analysis using criteria, included as the components, the errors of both the first and the second kinds. The final decision concerning the extraction of the most informative subset of gene expression profiles was taken based on the use of the fuzzy inference system, the inputs of which are the results of the appropriate single classifiers operation and the output is the final solution concerning state of the patient's health. To our mind, the implementation of the proposed stepwise procedure of the informative gene expression profiles extraction create the conditions for the increasing effectiveness of the further procedure of gene regulatory networks reconstruction and the following simulation of the reconstructed models considering the subtypes of the disease and/or state of the patient's health.

• Publication type
• Journal Article MeSH

BACKGROUND: Mood regulation is a complex and poorly understood process. In this study, we aimed to analyze the underlying dynamics of mood regulation in unaffected first degree relatives of patients diagnosed with bipolar disorder using time-series analysis. METHODS: We recruited 30 unaffected first-degree relatives of bipolar disorder patients. Participants rated their mood, anxiety and energy levels using a paper-based visual analog scale; they recorded their sleep and life events as well. Participants provided information on these variables over a three month period, twice per day. We compared their data using Box-Jenkins time series analysis with data from 30 healthy controls (HC) and 30 euthymic bipolar patients (BD) to obtain information on the autocorrelation and cross-correlation of the series, and calculated entropy for mood, anxiety and energy series. RESULTS: We analyzed 14,980 data points: 5200 in the healthy control group; 4970 in the bipolar group and 4810 in the unaffected relatives group. There were no significant differences between groups in terms of age, sex or education levels. Using Kolmogorov-Smirnov test, we found that individual measures were normally distributed in the whole sample (D = 0.23, p > 0.1). Autocorrelation functions for mood in all groups are governed by the ARIMA (1,1,0) model, which means that current values in the series are related to one previous point only. In terms of entropy for the mood series, unaffected relatives and bipolar patients showed lower values [mean (SD) : 1.028 ± 0.679; 1.042 ± 0.680], respectively, compared to healthy controls [(1.476 ± 0.33); F (2,74) = 4.39, p < 0.01]. The same case was seen in the energy series, with lower values in the unaffected relatives and bipolar patient groups [mean (SD) : 1.644 ± 0.566; 1.511 ± 0.879], respectively, compared to healthy controls [2.230 ± 0.531; F(2, 75) = 7.89, p < 0.001]. LIMITATIONS: Low resolution for the visual analog scale. CONCLUSIONS: Using nonlinear analyses, we found that the underlying structure of mood regulation in unaffected relatives is undistinguishable from the one found in bipolar patients. Compared to healthy controls, both bipolar patients and their unaffected relatives showed lower entropy levels, which is in keeping with a more rigid system, not as flexible to cope with the demands of a changing environment.

• MeSH
• Affect * MeSH
• Bipolar Disorder diagnosis   psychology   MeSH
• Cyclothymic Disorder psychology   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Nonlinear Dynamics MeSH
• Self-Control psychology   MeSH
• Case-Control Studies MeSH
• Anxiety psychology   MeSH
• Visual Analog Scale MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Although in real life people frequently perform visual search together, in lab experiments this social dimension is typically left out. Here, we investigate individual, collaborative and competitive visual search with visualization of search partners' gaze. Participants were instructed to search a grid of Gabor patches while being eye tracked. For collaboration and competition, searchers were shown in real time at which element the paired searcher was looking. To promote collaboration or competition, points were rewarded or deducted for correct or incorrect answers. Early in collaboration trials, searchers rarely fixated the same elements. Reaction times of couples were roughly halved compared with individual search, although error rates did not increase. This indicates searchers formed an efficient collaboration strategy. Overlap, the proportion of dwells that landed on hexagons that the other searcher had already looked at, was lower than expected from simulated overlap of two searchers who are blind to the behavior of their partner. The proportion of overlapping dwells correlated positively with ratings of the quality of collaboration. During competition, overlap increased earlier in time, indicating that competitors divided space less efficiently. Analysis of the entropy of the dwell locations and scan paths revealed that in the competition condition, a less fixed looking pattern was exhibited than in the collaborate and individual search conditions. We conclude that participants can efficiently search together when provided only with information about their partner's gaze position by dividing up the search space. Competing search exhibited more random gaze patterns, potentially reflecting increased interaction between searchers in this condition.

• MeSH
• Adult MeSH
• Competitive Behavior physiology   MeSH
• Humans MeSH
• Young Adult MeSH
• Reward MeSH
• Eye Movements physiology   MeSH
• Reaction Time MeSH
• Social Behavior * MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH