Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects.

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

Fourier phase index for extracting signatures of determinism and nonlinear features in time series.

Detecting determinism and nonlinear properties from empirical time series is highly nontrivial. Traditionally, nonlinear time series analysis is based on an error-prone phase space reconstruction that is only applicable for stationary, largely noise-free data from a low-dimensional system and requires the nontrivial adjustment of various parameters. We present a data-driven index based on Fourier phases that detects determinism at a well-defined significance level, without using Fourier transform surrogate data. It extracts nonlinear features, is robust to noise, provides time-frequency resolution by a double running window approach, and potentially distinguishes regular and chaotic dynamics. We test this method on data derived from dynamical models as well as on real-world data, namely, intracranial recordings of an epileptic patient and a series of density related variations of sediments of a paleolake in Tlaxcala, Mexico.

Opportune warning of COVID-19 in a Mexican health care worker cohort: Discrete beta distribution entropy of smartwatch physiological records.

We present a statistical study of heart rate, step cadence, and sleep stage registers of health care workers in the Hospital General de México "Dr. Eduardo Liceaga" (HGM), monitored continuously and non-invasively during the COVID-19 contingency from May to October 2020, using the Fitbit Charge 3® Smartwatch device. The HGM-COVID cohort consisted of 115 participants assigned to areas of COVID-19 exposure. We introduce a novel biomarker for an opportune signal for the likelihood of SARS-CoV-2 infection based on the Shannon Entropy of the Discrete Generalized Beta Distribution fit of rank ordered smartwatch registers. Our statistical test indicated infection for 94% of patients confirmed by positive polymer chain reaction (PCR+) test, 47% before the test, and 47% in coincidence. These results required innovative data preprocessing for the definition of a new biomarker index. The statistical method parameters are data-driven, confidence estimates were calibrated based on sensitivity tests using appropriately derived surrogate data as a benchmark. Our surrogate tests can also provide a benchmark for comparing results from other anomaly detection methods (ADMs). Biomarker comparison of the negative Immunoglobulin G Antibody (IgG-) subgroup with the PCR+ subgroup showed a statistically significant difference (p < 0.01, effect size = 1.44). The distribution of the uninfected population had a lower median and less dispersion than the PCR+ population. A retrospective study of our results confirmed that the biomarker index provides an early warning of the likelihood of COVID-19, even several days before the onset of symptoms or the PCR+ test request. The method can be calibrated for the analysis of different SARS-CoV-2 strains, the effect of vaccination, and previous infections. Furthermore, our biomarker screening could be implemented to provide general health profiles for other population sectors based on physiological signals from smartwatch wearable devices.

How to orchestrate a soccer team: Generalized synchronization promoted by rhythmic acoustic stimuli.

Interpersonal coordination requires precise actions concerted in space and time in a self-organized manner. We found, using soccer teams as a testing ground, that a common timeframe provided by adequate acoustic stimuli improves the interplay between teammates. We provide quantitative evidence that the connectivity between teammates and the scoring rate of male soccer teams improve significantly when playing under the influence of an appropriate acoustic environment. Unexpectedly, female teams do not show any improvement under the same experimental conditions. We show by follow-up experiments that the acoustic rhythm modulates the attention level of the participants with a pronounced tempo preference and a marked gender difference in the preferred tempo. These results lead to a consistent explanation in terms of the dynamical system theory, nonlinear resonances, and dynamic attention theory, which may illuminate generic mechanisms of the brain dynamics and may have an impact on the design of novel training strategies in team sports.

A non-parametric model: free analysis of actigraphic recordings of acute insomnia patients.

Both parametric and non-parametric approaches to time-series analysis have advantages and drawbacks. Parametric methods, although powerful and widely used, can yield inconsistent results due to the oversimplification of the observed phenomena. They require the setting of arbitrary constants for their creation and refinement, and, although these constants relate to assumptions about the observed systems, it can lead to erroneous results when treating a very complex problem with a sizable list of unknowns. Their non-parametric counterparts, instead, are more widely applicable but present a higher detrimental sensitivity to noise and low density in the data. For the case of approximately periodic phenomena, such as human actigraphic time series, parametric methods are widely used and concepts such as acrophase are key in chronobiology, especially when studying healthy and diseased human populations. In this work, we present a non-parametric method of analysis of actigraphic time series from insomniac patients and healthy age-matched controls. The method is fully data-driven, reproduces previous results in the context of activity offset delay and, crucially, extends the concept of acrophase not only to circadian but also for ultradian spectral components.

Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales.

Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.

EEG functional brain connectivity strengthens with age during attentional processing to faces in children.

Studying functional connectivity may generate clues to the maturational changes that occur in children, expressed by the dynamical organization of the functional network assessed by electroencephalographic recordings (EEG). In the present study, we compared the EEG functional connectivity pattern estimated by linear cross-correlations of the electrical brain activity of three groups of children (6, 8, and 10 years of age) while performing odd-ball tasks containing facial stimuli that are chosen considering their importance in socioemotional contexts in everyday life. On the first task, the children were asked to identify the sex of faces, on the second, the instruction was to identify the happy expressions of the faces. We estimated the stable correlation pattern (SCP) by the average cross-correlation matrix obtained separately for the resting state and the task conditions and quantified the similarity of these average matrices comparing the different conditions. The accuracy improved with higher age. Although the topology of the SCPs showed high similarity across all ages, the two older groups showed a higher correlation between regions associated with the attentional and face processing networks compared to the youngest group. Only in the youngest group, the similarity metric decreased during the sex condition. In general, correlation values strengthened with age and during task performance compared to rest. Our findings indicate that there is a spatially extended stable brain network organization in children like that reported in adults. Lower similarity scores between several regions in the youngest children might indicate a lesser ability to cope with tasks. The brain regions associated with the attention and face networks presented higher synchronization across regions with increasing age, modulated by task demands.

The Influence of EEG References on the Analysis of Spatio-Temporal Interrelation Patterns.

The characterization of the functional network of the brain dynamics has become a prominent tool to illuminate novel aspects of brain functioning. Due to its excellent time resolution, such research is oftentimes based on electroencephalographic recordings (EEG). However, a particular EEG-reference might cause crucial distortions of the spatiotemporal interrelation pattern and may induce spurious correlations as well as diminish genuine interrelations originally present in the dataset. Here we investigate in which manner correlation patterns are affected by a chosen EEG reference. To this end we evaluate the influence of 7 popular reference schemes on artificial recordings derived from well controlled numerical test frameworks. In this respect we are not only interested in the deformation of spatial interrelations, but we test additionally in which way the time evolution of the functional network, estimated via some bi-variate interrelation measures, gets distorted. It turns out that the median reference as well as the global average show the best performance in most situations considered in the present study. However, if a collective brain dynamics is present, where most of the signals get correlated, these schemes may also cause crucial deformations of the functional network, such that the parallel use of different reference schemes seems advisable.

Increased perfusion in dynamic gadolinium-enhanced MRI correlates with areas of bone repair and of bone necrosis in patients with Kienböck's disease.

BACKGROUND: Osteonecrosis of the lunate, Kienböck's disease, can lead to fragmentation of the lunate, carpal collapse, and severe osteoarthritis. Since the etiology of Kienböck's disease is impaired circulation, a diagnostic method capable of assessing perfusion would be valuable. Recent studies have suggested that dynamic contrast-enhanced (DCE) MR examinations at 3 T can assess perfusion in healthy carpal bones. PURPOSE: To evaluate the use of DCE-MR for assessing perfusion in the lunate bone in patients with Kienböck's disease. Furthermore, to compare perfusion with histopathology with a focus on bone viability. STUDY TYPE: Prospective case-control study. POPULATION: Fourteen patients with Kienböck's disease and a control group of 19 healthy subjects. Field Strength: 3 T with T1 -weighted fat-saturated contrast-enhanced gradient echo series. ASSESSMENT: Features of the enhancement curves from the DCE-MR examinations, time to peak (TTP), maximum slope (MS), and maximum enhancement (ME) assessed by a radiologist. Six of 14 patients were surgerized with lunate excision, allowing comparison between features of the enhancement curves and histopathology. STATISTICAL TESTS: Mann-Whitney U-test. P < 0.05 was considered a statistically significant difference. RESULTS: Patients with Kienböck's disease showed significantly higher and faster perfusion parameters compared with the control group, the mean value of the TTP in patients was 126.73 sec, in controls 189.79 sec (P = 0.024), ME in patients 173.55 AU, in controls 28.46 AU (P < 0.001), and MS in patients 5.04 AU, in controls 1.06 AU (P < 0.001). When compared with histopathology, increased perfusion was seen in areas of bone formation but also in necrosis. Areas of normal bone showed low perfusion. DATA CONCLUSION: DCE-MRI at 3 T can diagnose altered perfusion in patients with Kienböck's disease. Increased perfusion cannot definitely be used as a marker of bone viability. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:481-489.

Irregular Liesegang-type patterns in gas phase revisited. I. Experimental setup, data processing, and test of the spacing law.

Since the early work on Liesegang rings in gels, they have been a reference point for the study of pattern formation in chemical physics. Here we present a variant of the Liesegang experiment in gas phase, where ammonia and hydrochloric acid react within a glass tube producing a precipitate, which deposits along the tube wall producing a spatial pattern. With this apparently simple experiment a wide range of rich phenomenon can be observed due to the presence of convective flows and irregular dynamics reminiscent of turbulent behavior, for which precise measurements are scarce. In this first part of our work, we describe in detail the experimental setup, the method of data acquisition, the image processing, and the procedure used to obtain an intensity profile, which is representative of the amount of precipitate deposited at the tube walls. Special attention is devoted to the techniques rendering a data series reliable for statistical studies and model building, which may contribute to a characterization and understanding of the pattern formation phenomenon under consideration. As a first step in this direction, based on our data, we are able to show that the observed band pattern follows, with slight deviations, the spacing law encountered in common Liesegang rings, despite that the experimental conditions are very different. A further statistical correlation analysis of the data constitutes Paper II of this research.

Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis.

We present a statistical analysis of Liesegang-type patterns formed in a gaseous HCl-NH3 system by ammonium chloride precipitation along glass tubes, as described in Paper I [J. C. Torres-Guzmán et al., J. Chem. Phys. 144, 174701 (2016)] of this work. We focus on the detection and characterization of short and long-range correlations within the non-stationary sequence of apparently irregular precipitation bands. To this end we applied several techniques to estimate spatial correlations stemming from different fields, namely, linear auto-correlation via the power spectral density, detrended fluctuation analysis (DFA), and methods developed in the context of random matrix theory (RMT). In particular RMT methods disclose well pronounced long-range correlations over at least 40 bands in terms of both, band positions and intensity values. By using a variant of the DFA we furnish proof of the nonlinear nature of the detected long-range correlations.

On the dynamics of Liesegang-type pattern formation in a gaseous system.

Liesegang pattern formations are widely spread in nature. In spite of a comparably simple experimental setup under laboratory conditions, a variety of spatio-temporal structures may arise. Presumably because of easier control of the experimental conditions, Liesegang pattern formation was mainly studied in gel systems during more than a century. Here we consider pattern formation in a gas phase, where beautiful but highly complex reaction-diffusion-convection dynamics are uncovered by means of a specific laser technique. A quantitative analysis reveals that two different, apparently independent processes, both highly correlated and synchronized across the extension of the reaction cloud, act on different time scales. Each of them imprints a different structure of salt precipitation at the tube walls.

On the estimation of phase synchronization, spurious synchronization and filtering.

Phase synchronization, viz., the adjustment of instantaneous frequencies of two interacting self-sustained nonlinear oscillators, is frequently used for the detection of a possible interrelationship between empirical data recordings. In this context, the proper estimation of the instantaneous phase from a time series is a crucial aspect. The probability that numerical estimates provide a physically relevant meaning depends sensitively on the shape of its power spectral density. For this purpose, the power spectrum should be narrow banded possessing only one prominent peak [M. Chavez et al., J. Neurosci. Methods 154, 149 (2006)]. If this condition is not fulfilled, band-pass filtering seems to be the adequate technique in order to pre-process data for a posterior synchronization analysis. However, it was reported that band-pass filtering might induce spurious synchronization [L. Xu et al., Phys. Rev. E 73, 065201(R), (2006); J. Sun et al., Phys. Rev. E 77, 046213 (2008); and J. Wang and Z. Liu, EPL 102, 10003 (2013)], a statement that without further specification causes uncertainty over all measures that aim to quantify phase synchronization of broadband field data. We show by using signals derived from different test frameworks that appropriate filtering does not induce spurious synchronization. Instead, filtering in the time domain tends to wash out existent phase interrelations between signals. Furthermore, we show that measures derived for the estimation of phase synchronization like the mean phase coherence are also useful for the detection of interrelations between time series, which are not necessarily derived from coupled self-sustained nonlinear oscillators.

Evaluation of metal artifacts in clinical MR images of patients with total hip arthroplasty using different metal artifact-reducing sequences.

PURPOSE: To evaluate the distortion and artifact area of metal in MR images and to compare artifact reduction using different metal artifact-reducing sequences in patients with metal-on-metal (MoM) and non-MoM total hip prostheses. MATERIALS AND METHODS: Thirty-six MoM and 15 non-MoM prostheses were examined in a 1.5-T MR scanner using T1-weighted (T1-w) sequences: turbo spin echo (TSE) high-readout bandwidth (hiBW), T1-w; TSE view angle tilting (VAT), T1-w; TSE VAT + slice encoding for metal artifact correction (SEMAC); short tau inversion recovery (STIR) hiBW or matched RF pulses (mRFp). Distortion was quantified using a new method measuring the acetabular roof angle (ARA). The artifact area was defined in the mid-coronal plane of the artifact. RESULTS: The T1 VAT + SEMAC sequence showed the least distortion compared to T1 VAT and T1-hiBW (150°, 127° and 102°, p < 0.001, in MoM; 152°, 143° and 128°, p ≤ 0.014, in non-MoM). The artifact area was smaller in MoM prostheses using the T1 VAT sequence compared to T1 hiBW and T1 VAT + SEMAC (2506 mm(2), 3160 mm(2) and 3214 mm(2), p < 0.001) and smaller in non-MoM prostheses using T1 VAT compared to T1-hiBW (4296 mm(2) and 4831 mm(2), p = 0.041). STIR-mRFp substantially reduced the artifact size compared with STIR-hiBW (MoM 4559 mm(2) and 6323 mm(2); non-MoM 5625 mm(2) and 8764 mm(2), p < 0.001). CONCLUSION: Metal artifacts in MR imaging examinations of hip prostheses can be evaluated for distortion using a distortion angle (ARA) and the degree of signal artifact as determined by measuring the largest cross-sectional artifact area. T1 VAT + SEMAC showed the least distortion; T1 VAT and STIR-mRFp were most efficient for reduction of the artifact area.

MR imaging with metal artifact-reducing sequences and gadolinium contrast agent in a case-control study of periprosthetic abnormalities in patients with metal-on-metal hip prostheses.

OBJECTIVE: To apply and compare magnetic resonance imaging (MRI) metal artifact reducing sequences (MARS) including subtraction imaging after contrast application in patients with metal-on-metal (MoM) hip prostheses, investigate the prevalence and characteristics of periprosthetic abnormalities, as well as their relation with pain and risk factors. MATERIALS AND METHODS: Fifty-two MoM prostheses (35 cases with pain and or risk factors, and 17 controls) in 47 patients were examined in a 1.5-T MR scanner using MARS: turbo spin echo (TSE) with high readout bandwidth with and without view angle tilting (VAT), TSE with VAT and slice encoding for metal artifact correction (SEMAC), short tau inversion recovery (STIR) with matched RF pulses, and post-contrast imaging. The relations of MRI findings to pain and risk factors were analyzed and in five revised hips findings from operation, histology, and MRI were compared. RESULTS: TSE VAT detected the highest number of osteolyses. Soft tissue mass, effusion, and capsular thickening were common, whereas osteolysis in acetabulum and femur were less frequent. Contrast enhancement occurred in bone, synovia, joint capsule, and the periphery of soft tissue mass. There was no significant relation between MRI findings and pain or risk factors. CONCLUSIONS: MARS and gadolinium subtraction imaging are useful for evaluation of complications to MoM prosthesis. TSE VAT had the highest sensitivity for osteolysis. Contrast enhancement might indicate activation of aseptic lymphocyte-dominated vasculitis-associated lesion (ALVAL). Pain, small head, or steep prosthesis inclination angle are not useful predictors of periprosthetic abnormalities, and wide indications for MR follow-up are warranted.

Assessment of perfusion in normal carpal bones with dynamic gadolinium-enhanced MRI at 3 Tesla.

PURPOSE: To investigate the normal enhancement patterns of the scaphoid, lunate, and capitate bones with dynamic contrast-enhanced magnetic resonance imaging (MRI). MATERIALS AND METHODS: The study was approved by the hospital's Ethics Committee. Nineteen volunteers (13 female, 6 male; mean age 38 years) were examined and all gave written consent. Perfusion was assessed at 3 Tesla using dynamic contrast-enhanced MRI. After two-dimensional (2D) motion correction of the data set, regions of interest were placed in the capitate, lunate, and distal and proximal pole of scaphoid bone and from the mean signal intensities (SI), the enhancement was computed. The four locations were compared for time to peak, delay time, maximum enhancement, and maximum slope using Friedman's two-way analysis of variance. RESULTS: Typical SI versus time curves revealed two components: a faster component with strong contrast enhancement and a slow component with prolonged enhancement. The mean value (standard deviation, SD) for maximum enhancement was 51 (33)% in the capitate, 54 (25)% in the lunate, 51 (34)% in the proximal pole and 51 (28)% in the distal pole of the scaphoid. The result of the Friedman test showed no significant difference (P < 0.05) in the perfusion variables between the capitate, lunate, and distal and proximal scaphoid bones. CONCLUSION: Assessment of perfusion in normal carpal bone using contrast-enhanced MRI is possible. Optimization of the method and understanding of the normal perfusion may allow evaluation of pathological conditions such as osteonecrosis.

Dorsal agenesis of the pancreas - a rare cause of abdominal pain and insulin-dependent diabetes.

Dorsal agenesis of the pancreas is a rare congenital disorder. We report a case of a 65-year-old man with mild abdominal pain and insulin-dependent diabetes mellitus. Computed tomography (CT) of the abdomen showed a short pancreas with no pancreatic tissue ventral to the splenic vein. Magnetic resonance cholangiopancreatography (MRCP) visualized the absence of a dorsal duct system and confirmed the suspicion of complete agenesis of the dorsal pancreas. Endoscopic ultrasound (EUS) was also performed to rule out pancreatic malignancy.

Evolution of genuine cross-correlation strength of focal onset seizures.

To quantify the evolution of genuine zero-lag cross-correlations of focal onset seizures, we apply a recently introduced multivariate measure to broad band and to narrow-band EEG data. For frequency components below 12.5 Hz, the strength of genuine cross-correlations decreases significantly during the seizure and the immediate postseizure period, while higher frequency bands show a tendency of elevated cross-correlations during the same period. We conclude that in terms of genuine zero-lag cross-correlations, the electrical brain activity as assessed by scalp electrodes shows a significant spatial fragmentation, which might promote seizure offset.

Low carotid calcium score is associated with higher levels of glycosaminoglycans, tumor necrosis factor-alpha, and parathyroid hormone in human carotid plaques.

BACKGROUND AND PURPOSE: Computed tomography (CT) is used to study coronary artery plaques, but little is known about its potential to characterize plaque composition. This study assesses the relation between carotid calcium score (CCS) by CT and plaque composition, namely extracellular matrix, inflammatory mediators, and calcium metabolites. METHODS: Thirty patients with significant carotid stenosis underwent preoperative CT. CCS was quantified by Agaston calcium score. Plaque components were studied histologically and biochemically (collagen, elastin, and glycosaminoglycans). Fraktalkine, interferon-γ, interleukin-10, interleukin-12 p70, interleukin-1ß, interleukin-6, monocyte chemoattractant protein-1, platelet-derived growth factor-AB/BB, RANTES and tumor necrosis factor-α, and parathyroid hormone were measured using Luminex technology. RESULTS: Plaques with CCS ≥400 had more calcium (P=0.012), less glycosaminoglycan (P=0.002), tumor necrosis factor-α (P=0.013), and parathyroid hormone (P=0.028) than those with CCS <400. CCS correlated with plaque content of calcium (r=0.62; P<0.001) and inversely with glycosaminoglycan (r=-0.49; P=0.006) and tumor necrosis factor-α (r=-0.56; P=0.001). CONCLUSIONS: Human carotid plaques with high CCS are richer in calcium and have lower amounts of glycosaminoglycan, parathyroid hormone, and tumor necrosis factor-α, which is one of the main proinflammatory cytokines involved in atherosclerosis. This suggests that CCS not only reflects the degree of calcification, but also other important biological components relevant for stability such as inflammation.