Unravelling COVID-19 waves in Rio de Janeiro city: Qualitative insights from nonlinear dynamic analysis

Since the COVID-19 pandemic was first reported in 2019, it has rapidly spread around the world. Many countries implemented several measures to try to control the virus spreading. The healthcare system and consequently the general quality of life population in the cities have all been significantly impacted by the Coronavirus pandemic. The different waves of contagious were responsible for the increase in the number of cases that, unfortunately, many times lead to death. In this paper, we aim to characterize the dynamics of the six waves of cases and deaths caused by COVID-19 in Rio de Janeiro city using techniques such as the Poincaré plot, approximate entropy, second-order difference plot, and central tendency measures. Our results reveal that by examining the structure and patterns of the time series, using a set of non-linear techniques we can gain a better understanding of the role of multiple waves of COVID-19, also, we can identify underlying dynamics of disease spreading and extract meaningful information about the dynamical behavior of epidemiological time series. Such findings can help to closely approximate the dynamics of virus spread and obtain a correlation between the different stages of the disease, allowing us to identify and categorize the stages due to different virus variants that are reflected in the time series.

Comprehensive linear and nonlinear analysis of the effects of spinning on dynamic balancing ability in Hungarian folk dancers

PURPOSE

In the case of Hungarian folk dancers, it is crucial to maintain correct posture and promptly respond to imbalances. However, traditional dances often lack specific training to develop these skills.

METHODS

In this present study, twelve dancers (8 male, 4 female, age: 21.7 ± 3.6 years) and ten non-dancers subjects forming a control group (6 male, 4 female, age: 21.6 ± 2.87 years) participated. During the measurements a 60-second long bipedal balancing test on the balance board was completed two times, and a spinning intervention was inserted in between the two sessions. The balance capabilities of the two groups were assessed through the characterization of motion on an unstable board, and the analysis of subject's center of mass and head movements.

RESULTS

Dancers applied a more sophisticated and resource-intensive strategy to address the balancing task, yielding a better balancing performance in terms of balance board parameters. By preferring a solid stability in the medio-lateral direction, a greater fluctuation in the anterior-posterior direction can be observed (e.g., significantly lower SampEn values). The overall more successful performance is further evidenced by within-subject comparison since significant differences were observed mostly within the control group. Based on the results, the advanced balancing ability of the folk dancer group is more likely to be acquired through years of experience.

CONCLUSION

The results indicate that additional specialized training could further enhance this ability, encouraging the reliance on poorly memorized corrective movements and reducing the risk of injury.

Nonlinear neural patterns are revealed in high frequency functional near infrared spectroscopy analysis

Functional Near Infrared Spectroscopy (fNIRS) is a useful tool for measuring hemoglobin concentration. Linear theory of the hemodynamic response function supports low frequency analysis (<0.2 Hz). However, we hypothesized that nonlinearities, arising from the complex neurovascular interactions sustaining vasomotor tone, may be revealed in higher frequency components of fNIRS signals. To test this hypothesis, we simulated nonlinear hemodynamic models to explore how blood flow autoregulation changes may alter evoked neurovascular signals in high frequencies. Next, we analyzed experimental fNIRS data to compare neural representations between fast (0.2-0.6 Hz) and slow (<0.2 Hz) waves, demonstrating that only nonlinear representations quantified by sample entropy are distinct between these frequency bands. Finally, we performed group-level distance correlation analysis to show that the cortical distribution of activity is independent only in the nonlinear analysis of fast and slow waves. Our study highlights the importance of analyzing nonlinear higher frequency effects seen in fNIRS for a comprehensive analysis of cortical neurovascular activity. Furthermore, it motivates further exploration of the nonlinear dynamics driving regional blood flow and hemoglobin concentrations.

Modeling of oncolytic viruses in a heterogeneous cell population to predict spread into non-cancerous cells

New cancer treatment modalities that limit patient discomfort need to be developed. One possible new therapy is the use of oncolytic (cancer-killing) viruses. It is only recently that our ability to manipulate viral genomes has allowed us to consider deliberately infecting cancer patients with viruses. One key consideration is to ensure that the virus exclusively targets cancer cells and does not harm nearby non-cancerous cells. Here, we use a mathematical model of viral infection to determine the characteristics a virus would need to have in order to eradicate a tumor, but leave non-cancerous cells untouched. We conclude that the virus must differ in its ability to infect the two different cell types, with the infection rate of non-cancerous cells needing to be less than one hundredth of the infection rate of cancer cells. Differences in viral production rate or infectious cell death rate alone are not sufficient to protect non-cancerous cells.

Tissue-based trace element pollution of clam Ruditapes philippinarum in China: Hotspot identification and multiple nonlinear analysis

Considering the complexity of coastal and estuarine systems, a great challenge of environmental health assessment is to distinguish between natural and anthropogenically induced stress. Quantification of trace element accumulation in the tissues of sedentary bivalves with subsequent hotspot identification is important to assess the pollution status. The present study conducted a nationwide mapping of bioavailable macro- and trace elements in a widely distributed biomonitoring clam Ruditapes philippinarum from China. Ag, As, Cd, Cr, Cu, and Zn concentrations in the clams showed similar levels as those documented previously in mussels, but were lower than those in oysters at similar sites from China. Notably, the total As concentrations in clams at Xinkai Estuary and Beibu Bay were relatively higher than those at other sites in China. After normalization by tissue biomass, salinity (Na) and nutrient (P), some hotspots were identified with high pollution of trace elements at Liaodong Bay of Bohai Sea, Gold Beach of Qingdao, Dongling Port of Yellow Sea, Hangzhou Bay and adjacent coasts of East China Sea, and Pearl River Estuary and Beibu Bay of South China Sea. This study demonstrated that most trace elements had a path-dependent effect of biomass, except for Cd which showed an indirect pathway of AgNi related accumulation. Results showed significant correlations between Cd, Zn, Ag and Ni, and between Pb/Cr and Ti in clams. After mass normalization, all trace elements displayed significantly positive correlations with Na or P. Simultaneously, the clam biomass played an intermediary role in trace element accumulation in non-linear patterns related to salinity and nutrient. These results are important in evaluating the composite ambiguous information of the historical data of trace element biomonitoring.

Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences

The breathing process possesses a complex variability caused in part by the respiratory central pattern generator in the brainstem; however, it also arises from chemical and mechanical feedback control loops, network reorganization and network sharing with nonrespiratory motor acts, as well as inputs from cortical and subcortical systems. The notion that respiratory fluctuations contain hidden information has prompted scientists to decipher respiratory signals to better understand the fundamental mechanisms of respiratory pattern generation, interactions with emotion, influences on the cortical neuronal networks associated with cognition, and changes in variability in healthy and disease-carrying individuals. Respiration can be used to express and control emotion. Furthermore, respiration appears to organize brain-wide network oscillations via cross-frequency coupling, optimizing cognitive performance. With the aid of information theory-based techniques and machine learning, the hidden information can be translated into a form usable in clinical practice for diagnosis, emotion recognition, and mental conditioning.

Cardiorespiratory coupling strength in athletes and non-athletes

PURPOSE

Despite the relevant presence of nonlinear components on heart period (HP) likely due to cardiorespiratory coupling (CRC), the HP is frequently analyzed in absence of concomitant recordings of respiratory movements (RESP). This study aims to assess the cardiovascular dynamics and CRC during postural challenge in athletes and non-athletes via joint symbolic analysis (JSA).

METHODS

A cross-sectional study was conducted in 50 men, aged between 20 and 40 yrs, divided into athletes (n = 25) and non-athletes (n = 25) groups. The electrocardiogram, blood pressure and RESP signals were recorded during 15 min in both supine position (REST) and after active postural maneuver (STAND). From the beat-to-beat series of HP, systolic arterial pressure (SAP) and RESP, we computed the time and frequency domain indexes and baroreflex sensitivity. The JSA was based on the definition of symbolic HP and RESP patterns and on the evaluation of the rate of their simultaneous occurrence in both HP and RESP series.

RESULTS

The JSA analysis was able to identify higher CRC strength at REST in athletes. Moreover, the response of CRC to STAND depended on the time scales of the analysis and was much more evident in athletes than in non-athletes, thus indicating a more reactive autonomic control in athletes.

CONCLUSION

Assessing CRC in athletes via JSA provides additional information compared to standard linear time and frequency domain tools likely due to the more relevant presence of nonlinearities in HP-RESP variability relationship.

Analysis of contamination in cluster randomized trials of malaria interventions

Background

In cluster randomized trials (CRTs) of interventions against malaria, mosquito movement between households ultimately leads to contamination between intervention and control arms, unless they are separated by wide buffer zones.

Methods

This paper proposes a method for adjusting estimates of intervention effectiveness for contamination and for estimating a contamination range between intervention arms, the distance over which contamination measurably biases the estimate of effectiveness. A sigmoid function is fitted to malaria prevalence or incidence data as a function of the distance of households to the intervention boundary, stratified by intervention status and including a random effect for the clustering. The method is evaluated in a simulation study, corresponding to a range of rural settings with varying intervention effectiveness and contamination range, and applied to a CRT of insecticide treated nets in Ghana.

Results

The simulations indicate that the method leads to approximately unbiased estimates of effectiveness. Precision decreases with increasing mosquito movement, but the contamination range is much smaller than the maximum distance traveled by mosquitoes. For the method to provide precise and approximately unbiased estimates, at least 50% of the households should be at distances greater than the estimated contamination range from the discordant intervention arm.

Conclusions

A sigmoid approach provides an appropriate analysis for a CRT in the presence of contamination. Outcome data from boundary zones should not be discarded but used to provide estimates of the contamination range. This gives an alternative to “fried egg” designs, which use large clusters (increasing costs) and exclude buffer zones to avoid bias.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13063-021-05543-8).

Nonlinear analysis of the movement variability structure can detect aging-related differences among cognitively healthy individuals

Studying the dynamics of nonlinear systems can provide additional information about the variability structure of the system. Within the current study, we examined the application of regularity and local stability measures to capture motor function alterations due to dual-tasking using a previously validated upper-extremity function (UEF). We targeted young (ages 18 and 30 years) and older adults (65 years or older) with normal cognition based on clinical screening. UEF involved repetitive elbow flexion without counting (ST) and while counting backward by one (DT1) or three (DT3). We measured the regularity (measured by sample entropy (SE)), local stability (measured by the largest Lyapunov exponent (LyE)), as well as conventional peak-dependent variability measures (coefficient of variation of kinematics parameters) to capture motor dynamic alterations due to dual-tasking. Within both groups, only SE showed significant differences between all pairs of UEF condition comparisons, even ST vs DT1 (p = 0.007, effect size = 0.507), for which no peak-dependent parameter showed significant difference. Among all measures, the only parameter that showed a significant difference between young and older adults was LyE (p < 0.001, effect size = 0.453). Current findings highlight the potential of nonlinear analysis to detect aging-related alterations among cognitively healthy participants.

RCOVID19: Recurrence-based SARS-CoV-2 features using chaos game representation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic. It was first detected in China and was rapidly spread to other countries. Several thousands of whole genome sequences of SARS-CoV-2 have been reported and it is important to compare them and identify distinctive evolutionary/mutant markers. Utilizing chaos game representation (CGR) as well as recurrence quantification analysis (RQA) as a powerful nonlinear analysis technique, we proposed an effective process to extract several valuable features from genomic sequences of SARS-CoV-2. The represented features enable us to compare genomic sequences with different lengths. The provided dataset involves totally 18 RQA-based features for 4496 instances of SARS-CoV-2.

On the application of entropic half-life and statistical persistence decay for quantification of time dependency in human gait

Entropic half-life (ENT½) and statistical persistence decay (SPD) was recently introduced as measures of time dependency in stride time intervals during walking. The present study investigated the effect of data length on ENT½ and SPD and additionally applied these measures to stride length and stride speed intervals. First, stride times were collected from subjects during one hour of treadmill walking. ENT½ and SPD were calculated from a range of stride numbers between 250 and 2500. Secondly, stride times, stride lengths and stride speeds were collected from subjects during 16 min of treadmill walking. ENT½ and SPD were calculated from the stride times, stride lengths and stride speeds. The ENT½ values reached a plateau between 1000 and 2500 strides whereas the SPD increased linearly with the number of included strides. This suggests that ENT½ can be compared if 1000 strides or more are included, but only SPD obtained from same number of strides should be compared. The ENT½ and SPD of the stride times were significantly longer compared to that of the stride lengths and stride speeds. This indicates that the time dependency is greater in the motor control of stride time compared to that of stride lengths and stride speeds.

Filtering affects the calculation of the largest Lyapunov exponent

The calculation of the largest Lyapunov exponent (LyE) requires the reconstruction of the time series in an N-dimensional state space. For this, the time delay (Tau) and embedding dimension (EmD) are estimated using the Average Mutual Information and False Nearest Neighbor algorithms. However, the estimation of these variables (LyE, Tau, EmD) could be compromised by prior filtering of the time series evaluated. Therefore, we investigated the effect of filtering kinematic marker data on the calculation of Tau, EmD and LyE using several different computational codes. Kinematic marker data were recorded from 37 subjects during treadmill walking and filtered using a low pass digital filter with a range of cut-off frequencies (23.5-2Hz). Subsequently, the Tau, EmD and LyE were calculated from all cut-off frequencies. Our results demonstrated that the level of filtering affected the outcome of the Tau, EmD and LyE calculations for all computational codes used. However, there was a more consistent outcome for cut-off frequencies above 10 Hz which corresponded to the optimal cut-off frequency that could be used with this data. This suggested that kinematic data should remain unfiltered or filtered conservatively before calculating Tau, EmD and LyE.

Influence of sampling frequency and number of strides on recurrence quantifiers extracted from gait data

In this study, the influence of the sampling frequency and number of strides on recurrence quantifiers extracted from gait data was investigated in order to provide baseline values and preserve the system's non-linear dynamical characteristics expressed by these recurrence quantifiers. Recurrence quantifiers were extracted from a recurrence plot (RP), which required the reconstruction of a high-dimensional state space capable of reproducing the dynamical characteristics of the analyzed system. In this study, the following quantifiers were extracted: rate of recurrence (RR), determinism (DET), average diagonal lines length (AVG), maximum diagonal lines length (MaxL), Shannon entropy (EntD), and measure of trend (TREND). Data collected during treadmill walking were statistically analyzed to compare the distribution characteristics (mean, median, and standard deviation) and the quantifiers' correlation with those obtained from a control time series with an acquisition time corresponding to 150 strides and a 100-Hz sampling frequency, which are common values used in gait studies. It was not possible to reduce the number of strides for the MaxL or TREND. However, for the RR, DET, AVG, and EntD, it was possible to reduce the number of strides by 60% when analyzed together. The minimum sampling frequency required to extract all quantifiers simultaneously was 100 Hz. This potential reduction in the number of strides is appropriate for evaluating fast gait events, with short temporal localization in the RP, by applying the sliding window method to the recurrence plot.

Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cues

Background

During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA, while being computed from continuous signals without preliminary discretization. Its use would facilitate complexity analysis from a larger variety of gait measures, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization.

Methods

Thirty-six healthy adults walked 30 min on an instrumented treadmill under three conditions: no cueing, auditory cueing (metronome walking), and visual cueing (stepping stones). The center-of-pressure trajectory was discretized into time series of gait parameters, after which a complexity index (scaling exponent alpha) was computed via DFA. Continuous pressure position signals were used to compute the ACI. Correlations between ACI and DFA were then analyzed. The predictive ability of DFA and ACI to differentiate between cueing and no-cueing conditions was assessed using regularized logistic regressions and areas under the receiver operating characteristic curves (AUC).

Results

DFA and ACI were both significantly different among the cueing conditions. DFA and ACI were correlated (Pearson’s r = 0.86). Logistic regressions showed that DFA and ACI could differentiate between cueing/no cueing conditions with a high degree of confidence (AUC = 1.00 and 0.97, respectively).

Conclusion

Both DFA and ACI responded similarly to changes in cueing conditions and had comparable predictive power. This support the assumption that ACI could be used instead of DFA to assess the long-range complexity of continuous gait signals. However, future studies are needed to investigate the theoretical relationship between DFA and ACI.

Complex cardiac vagal regulation to mental and physiological stress in adolescent major depression

BACKGROUND

Cardiovagal control is known to be reduced in major depressive disorder (MDD), however, the neurocardiac reflex control to distinct types of stressors is still unclear. We aimed to study parasympathetically mediated cardiac reflex functioning in response to mental and physiological stressors using heart rate variability (HRV) linear and nonlinear analysis in adolescent MDD.

METHODS

We examined 60 adolescents (40 girls) with MDD (age 14.9 ± 0.3 years) and 60 age and gender-matched controls. ECG was continuously recorded during stress protocol: baseline, Go/NoGo test, recovery, supine position, and orthostasis. Evaluated HRV linear and nonlinear indices: RR interval, pNN50, rMSSD, HF-HRV, Poincaré plot (SD1), symbolic dynamics 2UV%. Cardiovagal reactivity expressed as percentual change (%) was calculated in response to both stressors.

RESULTS

In each phase of stress protocol, the MDD group had significantly reduced HRV parameters compared to controls, except for symbolic dynamics index 2UV% in supine position. The reactivity of HRV indices was significantly greater in response to orthostasis in MDD compared to controls. No significant differences were found in response to Go/NoGo test.

LIMITATIONS

The smoking status and the menstrual cycle phase potentially affecting the HRV parameters were not monitored. Future research is needed to expand a sample size with respect to sex and to study neurocardiac response to other different stressors in MDD.

CONCLUSIONS

This study revealed reduced resting cardiovagal regulation and greater vagal withdrawal indicating abnormal neurocardiac reflex functioning to physiological stressor (orthostasis) in adolescent MDD patients. Nonlinear HRV analysis was sensitive to detect cardiac-linked regulatory differences in adolescent depression.

Development of seismic vulnerability index methodology for reinforced concrete buildings based on nonlinear parametric analyses

This paper presents a simplified method in the seismic vulnerability assessment of reinforced concrete (RC) buildings based on proposed seismic vulnerability index (SVI) methodology. The employed procedure is derived with some modifications from the Italian GNDT and the European Macro-seismic approaches. Eight parameters were modeled in three distinct vulnerability classes to estimate the vulnerability indices of RC structures. The vulnerability classes were categorized based on the earthquake resistant design (ERD) defined as; (Low, Moderate, and High)-ERDs. Nonlinear time history analysis (NL-THA) and nonlinear static analysis (NL-SA) were carried out to define the weight of each parameter in order to calculate the seismic vulnerability index in a specific intensity (PGA) of an earthquake event. Knowing that it ranges from 0 to 1 from less vulnerable to most vulnerable with respect to the seismic intensity. In addition, the engineering demand parameter (EDP) used to determine the vulnerability index as the maximum top displacement of the structure. After determining the (SVI), The mean damage states were developed to evaluate the estimated physical damage of buildings in distinct seismic intensities. •This simplified methodology helps to manage and implements strategies for the safety of the communities before earthquake takes place by investigating the vulnerability classes for each building type.•Modeling the parameters that have an influence on the structural behavior without considering the past-damages observations through an analytical approach.•Developing the seismic vulnerability index can reduce or limit the role of the rapid visual screening methods, which is based on expert opinion decisions, and depends on observations of damages caused by earthquakes, and can be a useful framework criterion in earthquake filed.

Effects of sensory manipulations on the dynamical structure of center-of-pressure trajectories of children with cerebral palsy during sitting

AIM

To investigate the effects of manipulating visual information and the compliance of the support surface on the area of sway and dynamical trajectories of center-of-pressure (CoP) in children with CP and children with typical development during static sitting.

METHODS

32 typical children, 14 children with mild CP and 12 with moderate-to-severe CP were tested for CoP sway during static sitting under four sensory conditions: (1) eyes open on a rigid surface; (2) eyes closed on a rigid surface; (3) eyes open on foam; (4) eyes closed on foam.

RESULTS

Children with moderate-to-severe CP showed greater regularity and local stability of dynamical CoP trajectories and lower complexity in their motor patterns than typical children and children with mild CP. Moreover, removing vision and sitting on a compliant surface reduced the regularity of CoP trajectories.

CONCLUSION

Children with CP were able to adjust the structure and complexity of their postural control responses to sensory challenges, although the structure of their postural responses was poorer than in typical children.

Selection Procedures for the Largest Lyapunov Exponent in Gait Biomechanics

The present study was aimed at investigating the effectiveness of the Wolf et al. (LyE_W) and Rosenstein et al. largest Lyapunov Exponent (LyE_R) algorithms to differentiate data sets with distinctly different temporal structures. The three-dimensional displacement of the sacrum was recorded from healthy subjects during walking and running at two speeds; one low speed close to the preferred walking speed and one high speed close to the preferred running speed. LyE_R and LyE_W were calculated using four different time series normalization procedures. The performance of the algorithms were evaluated based on their ability to return relative low values for slow walking and fast running and relative high values for fast walking and slow running. Neither of the two algorithms outperformed the other; however, the effectiveness of the two algorithms was highly dependent on the applied time series normalization procedure. Future studies using the LyE_R should normalize the time series to a fixed number of strides and a fixed number of data points per stride or data points per time series while the LyE_W should be applied to time series normalized to a fixed number of data points or a fixed number of strides.

Postural control of individuals with spinal fusion for adolescent idiopathic scoliosis

BACKGROUND

The purpose of the study was to assess the postural stability and complexity of postural control for moderately physically active individuals with spinal fusion for adolescent idiopathic scoliosis at two years post-operation.

METHODS

Limit of stability test and sensory organization test were conducted for 10 moderately physically-active participants with spinal fusion and 10 controls pair-matched for mass, height and physical activity level. During the limit of stability test, participants were instructed to lean the center of gravity as far as possible toward 8 predetermined directions and the maximum excursion and direction control were analyzed. During the sensory organization test, participants were instructed to maintain as still as possible in six test conditions and equilibrium scores and sway area of center of pressure were analyzed. Multi-scale entropy of center of pressure was calculated to quantify sway complexity.

FINDINGS

Most postural stability outcomes of spinal fusion participants were comparable to controls except for significantly reduced equilibrium scores (p = 0.039, partial η² = 0.217). Moreover, spinal fusion participants exhibited tendencies of reduced direction control (p = 0.053) during the limit of stability test and greater sway area (p = 0.052) during the sensory organization test.

INTERPRETATION

Although the center of gravity control might be affected, spinal fusion individuals who were moderately physically active likely progressively learned to adapt postoperatively to their fused spine to meet the postural demands required when performing physical movements. We suggest that spinal fusion is a satisfactory treatment in regard to the recovery of postural stability.

Automatic Seizure Detection Based on Nonlinear Dynamical Analysis of EEG Signals and Mutual Information

Introduction:

In this paper, nonlinear dynamical analysis based on Recurrence Quantification Analysis (RQA) is employed to characterize the nonlinear EEG dynamics. RQA can provide useful quantitative information on the regular, chaotic, or stochastic property of the underlying dynamics.

Methods:

We use the RQA-based measures as the quantitative features of the nonlinear EEG dynamics. Mutual Information (MI) was used to find the most relevant feature subset out of RQA-based features. The selected features were fed into an artificial neural network for grouping of EEG recordings to detect ictal, interictal, and healthy states. The performance of the proposed procedure was evaluated using a database for different classification cases.

Results:

The combination of five selected features based on MI achieved 100% accuracy, which demonstrates the superiority of the proposed method.

Conclusion:

The results showed that the nonlinear dynamical analysis based on Rcurrence Quantification Analysis (RQA) can be employed as a suitable approach for characterizing the nonlinear EEG dynamics and detecting the seizure.

Nonlinear analysis of electrodermal activity signals for healthy subjects and patients with chronic obstructive pulmonary disease

It is known that signals recorded from physiological systems represent nonlinear features. Several recent studies report that quantitative information about signal complexity is obtained by using nonlinear analysis algorithms. Chronic obstructive pulmonary disease (COPD) is one of the causes of mortality worldwide with an increasing prevalence. This study aims to investigate nonlinear parameters such as largest Lyapunov exponent (LLE) and correlation dimension of electrodermal activity signals recorded from healthy subjects and patients with COPD. Electrodermal activity signals recorded from 14 healthy subjects and 24 patients with COPD were analysed. Auditory and tactile stimuli were applied at different time intervals during the recording process. Signals were reconstructed in the phase space compatible with theory and LLE and correlation dimension values were calculated. Statistical analysis was performed by using Shapiro-Wilk normality test, one-way analysis of variance (ANOVA) with Bonferroni post-test and Kruskal-Wallis non-parametric test. It was determined that the chaoticity and the complexity of the system increased in the presence of COPD. The systematic auditory stimuli increases chaoticity more than random auditory stimuli. Furthermore it was observed that participants develop habituation to the same auditory stimuli in time. There is no significant difference between COPD groups. Different results were found for the tactile stimuli applied to right or left ear. The results revealed that the nonlinear analysis of physiological data can be used for the development of new strategies for the diagnosis of chronic diseases.

Chess databases as a research vehicle in psychology: Modeling large data

The game of chess has often been used for psychological investigations, particularly in cognitive science. The clear-cut rules and well-defined environment of chess provide a model for investigations of basic cognitive processes, such as perception, memory, and problem solving, while the precise rating system for the measurement of skill has enabled investigations of individual differences and expertise-related effects. In the present study, we focus on another appealing feature of chess—namely, the large archive databases associated with the game. The German national chess database presented in this study represents a fruitful ground for the investigation of multiple longitudinal research questions, since it collects the data of over 130,000 players and spans over 25 years. The German chess database collects the data of all players, including hobby players, and all tournaments played. This results in a rich and complete collection of the skill, age, and activity of the whole population of chess players in Germany. The database therefore complements the commonly used expertise approach in cognitive science by opening up new possibilities for the investigation of multiple factors that underlie expertise and skill acquisition. Since large datasets are not common in psychology, their introduction also raises the question of optimal and efficient statistical analysis. We offer the database for download and illustrate how it can be used by providing concrete examples and a step-by-step tutorial using different statistical analyses on a range of topics, including skill development over the lifetime, birth cohort effects, effects of activity and inactivity on skill, and gender differences.

Dynamic structure of lower limb joint angles during walking post-stroke

BACKGROUND

Variability in joint kinematics is necessary for adaptability and response to everyday perturbations; however, intrinsic neuromotor changes secondary to stroke often cause abnormal movement patterns. How these abnormal movement patterns relate to joint kinematic variability and its influence on post-stroke walking impairments is not well understood.

OBJECTIVE

The purpose of this study was to evaluate the movement variability at the individual joint level in the paretic and non-paretic limbs of individuals post-stroke.

METHODS

Seven individuals with hemiparesis post-stroke walked on a treadmill for two minutes at their self-selected speed and the average speed of the six-minute walk test while kinematics were recorded using motion-capture. Variability in hip, knee, and ankle flexion/extension angles during walking were quantified with the Lyapunov exponent (LyE). Interlimb differences were evaluated.

RESULTS

The paretic side LyE was higher than the non-paretic side at both self-selected speed (Hip: 50%; Knee: 74%), and the average speed of the 6-min walk test (Hip: 15%; Knee: 93%).

CONCLUSION

Differences in joint kinematic variability between limbs of persons post-stroke supports further study of the source of non-paretic limb deviations as well as the clinical implications of joint kinematic variability in persons post-stroke. The development of bilaterally-targeted post-stroke gait interventions to address variability in both limbs may promote improved outcomes.

Comparing EEG Nonlinearity in Deficit and Nondeficit Schizophrenia Patients: Preliminary Data

Electroencephalogram (EEG) contains valuable information obtained noninvasively that can be used for assessment of brain's processing capacity of patients with psychiatric disorders. The purpose of the present work was to evaluate possible differences in EEG complexity between deficit (DS) and nondeficit (NDS) subtypes of schizophrenia as a reflection of the cognitive processing capacities in these groups. A particular nonlinear metric known as Lempel-Ziv complexity (LZC) was used as a computational tool in order to determine the randomness in EEG alpha band time series from 3 groups (deficit schizophrenia [n = 9], nondeficit schizophrenia [n = 10], and healthy controls [n = 10]) according to time series randomness. There was a significant difference in frontal EEG complexity between the DS and NDS subgroups ( p = .013), with DS group showing less complexity. A significant positive correlation was found between LZC values and Positive and Negative Syndrome Scale (PANSS) general psychopathology scores (ie, larger frontal EEG complexity correlated with more severe psychopathology), explained partially by the emotional component subscore of the PANSS. These findings suggest that cognitive processing occurring in the frontal networks in DS is less complex compared to NDS patients as reflected by EEG complexity measures. The data also suggest that there may be a relationship between the degree of emotionality and the complexity of the frontal EEG signal.

Determinants of gait stability while walking on a treadmill: A machine learning approach

Dynamic balance in human locomotion can be assessed through the local dynamic stability (LDS) method. Whereas gait LDS has been used successfully in many settings and applications, little is known about its sensitivity to individual characteristics of healthy adults. Therefore, we reanalyzed a large dataset of accelerometric data measured for 100 healthy adults from 20 to 70 years of age performing 10 min treadmill walking. We sought to assess the extent to which the variations of age, body mass and height, sex, and preferred walking speed (PWS) could influence gait LDS. The random forest (RF) and multiple adaptive regression splines (MARS) algorithms were selected for their good bias-variance tradeoff and their capabilities to handle nonlinear associations. First, through variable importance measure (VIM), we used RF to evaluate which individual characteristics had the highest influence on gait LDS. Second, we used MARS to detect potential interactions among individual characteristics that may influence LDS. The VIM and MARS results indicated that PWS and age correlated with LDS, whereas no associations were found for sex, body height, and body mass. Further, the MARS model detected an age by PWS interaction: on one hand, at high PWS, gait stability is constant across age while, on the other hand, at low PWS, gait instability increases substantially with age. We conclude that it is advisable to consider the participants' age as well as their PWS to avoid potential biases in evaluating dynamic balance through LDS.

Evaluation of Structural Robustness against Column Loss: Methodology and Application to RC Frame Buildings

A computational methodology is presented for evaluating structural robustness against column loss. The methodology is illustrated through application to reinforced concrete (RC) frame buildings, using a reduced-order modeling approach for three-dimensional RC framing systems that includes the floor slabs. Comparisons with high-fidelity finite-element model results are presented to verify the approach. Pushdown analyses of prototype buildings under column loss scenarios are performed using the reduced-order modeling approach, and an energy-based procedure is employed to account for the dynamic effects associated with sudden column loss. Results obtained using the energy-based approach are found to be in good agreement with results from direct dynamic analysis of sudden column loss. A metric for structural robustness is proposed, calculated by normalizing the ultimate capacities of the structural system under sudden column loss by the applicable service-level gravity loading and by evaluating the minimum value of this normalized ultimate capacity over all column removal scenarios. The procedure is applied to two prototype 10-story RC buildings, one employing intermediate moment frames (IMFs) and the other employing special moment frames (SMFs). The SMF building, with its more stringent seismic design and detailing, is found to have greater robustness.

Alzheimer's disease: The state of the art in resting-state magnetoencephalography

Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with magnetoencephalography (MEG). Here, we systematically review the studies that have examined resting-state MEG changes in AD and identify areas that lack scientific or clinical progress. Three levels of MEG analysis will be covered: (i) single-channel signal analysis, (ii) pairwise analyses over time series, which includes the study of interdependencies between two time series and (iii) global network analyses. We discuss the findings in the light of other functional modalities, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Overall, single-channel MEG results show consistent changes in AD that are in line with EEG studies, but the full potential of the high spatial resolution of MEG and advanced functional connectivity and network analysis has yet to be fully exploited. Adding these features to the current knowledge will potentially aid in uncovering organizational patterns of brain function in AD and thereby aid the understanding of neuronal mechanisms leading to cognitive deficits.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition

BACKGROUND

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches.

NEW METHOD

In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution.

RESULTS

The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis.

COMPARISON WITH EXISTING METHODS

Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity.

CONCLUSIONS

Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods.

Shoulder pain and time dependent structure in wheelchair propulsion variability

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1m/s for 3min. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ(2)(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain.

A comparison of linear and nonlinear stability parameters in different clinical forms of multiple sclerosis

Background

Multiple sclerosis (MS) is one of the neurological diseases that affect the ability of subjects to stand and walk. The stability of MS subjects has been evaluated in various studies, mostly based on linear approach. Based on this approach it is controversial weather stability of MS subjects differ from normal or not. Therefore, the aim of this study was to evaluate stability in three groups of MS subjects (spastic, ataxic and ataxic-spastic) using both linear and non-linear approaches.

Method

Seventeen healthy and 36 subjects with MS participated in this study. The MS group presenting with spastic, ataxic and ataxic-spastic (each group consisted of 12 subjects) participated in the study. The stability of the subjects was evaluated using Kistler force plate. The difference between stability of the subjects was evaluated using the Multi Analysis of Variance and significant value was set at P < 0.05.

Result

There was a significant difference in the mean value of Approximate Entropy (ApEn) in anterior-posterior direction between normal (0.66 ± 0.13) and ataxic (0.85 ± 0.12) and ataxic-spastic (0.90 ± 0.12) subjects (P < 0.05) and no difference between normal and spastic groups (0.76 ± 0.13). The results of both linear and nonlinear approaches confirmed that both ataxic and ataxic-spastic subjects had more instability than normal subjects. Although, the mean values of stability parameters increased in spastic compared to normal, the difference was not statistically significant.

Conclusion

Subjects with ataxic and ataxic-spastic MS disorder had difficulty in controlling their stability during quiet standing. The results of this study also confirmed that spasticity of muscles surrounding the hip and knee joints did not influence standing stability in patients with spastic MS.

The psychosis-like effects of Δ(9)-tetrahydrocannabinol are associated with increased cortical noise in healthy humans

BACKGROUND

Drugs that induce psychosis may do so by increasing the level of task-irrelevant random neural activity or neural noise. Increased levels of neural noise have been demonstrated in psychotic disorders. We tested the hypothesis that neural noise could also be involved in the psychotomimetic effects of delta-9-tetrahydrocannabinol (Δ(9)-THC), the principal active constituent of cannabis.

METHODS

Neural noise was indexed by measuring the level of randomness in the electroencephalogram during the prestimulus baseline period of an oddball task using Lempel-Ziv complexity, a nonlinear measure of signal randomness. The acute, dose-related effects of Δ(9)-THC on Lempel-Ziv complexity and signal power were studied in humans (n = 24) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, .015 and .03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design.

RESULTS

Δ(9)-THC increased neural noise in a dose-related manner. Furthermore, there was a strong positive relationship between neural noise and the psychosis-like positive and disorganization symptoms induced by Δ(9)-THC, which was independent of total signal power. Instead, there was no relationship between noise and negative-like symptoms. In addition, Δ(9)-THC reduced total signal power during both active drug conditions compared with placebo, but no relationship was detected between signal power and psychosis-like symptoms.

CONCLUSIONS

At doses that produced psychosis-like effects, Δ(9)-THC increased neural noise in humans in a dose-dependent manner. Furthermore, increases in neural noise were related with increases in Δ(9)-THC-induced psychosis-like symptoms but not negative-like symptoms. These findings suggest that increases in neural noise may contribute to the psychotomimetic effects of Δ(9)-THC.

An Analysis of the Stress induced in the Periodontal Ligament during Extrusion and Rotation Movements- Part II: A Comparison of Linear vs Nonlinear FEM Study

BACKGROUND

Optimal orthodontic forces are those which stimulate tooth movement with minimal biological trauma to the tooth, periodontal ligament (PDL) during and alveolar bone. Among various types of tooth movements, extrusion and rotational movements are seen to be associated with the least amount of root resorption and have not been studied in detail. The mechanical behavior of the PDL is known to be nonlinear elastic and thus a nonlinear simulation of the PDL provides precision to the calculated stress values. Therefore in this study, the stress patterns in the PDL were evaluated with extrusion and rotational movements using the nonlinear finite element method (FEM).

MATERIALS AND METHODS

A three-dimensional (3D) FEM model of the maxillary incisors was generated using SOLIDWORKS modelling software. Stresses in the PDL were evaluated with extrusive and rotational movements by a 3D FEM using ANSYS software with nonlinear material properties.

RESULTS

It was observed that with the application of extrusive load, the tensile stresses were seen at the apex whereas the compressive stress was distributed at the cervical margin. With the application of rotational movements, maximum compressive stress was distributed at the apex and cervical third whereas the tensile stress was distributed on cervical third of the PDL on the lingual surface.

CONCLUSION

For rotational and extrusion movements, stress values over the periodontal ligament was within the range of optimal stress value as proposed by Lee, with a given force system by Proffit as optimum forces for orthodontic tooth movement using nonlinear properties. During rotation there are stresses concentrated at the apex, hence due to the concentration of the compressive forces at the apex a clinician must avoid placing heavy stresses during tooth movement.

Nonlinear feature extraction for objective classification of complex auditory brainstem responses to diotic perceptually critical consonant-vowel syllables

OBJECTIVE

To examine if nonlinear feature extraction method yields appropriate results in complex brainstem response classification of three different consonant vowels diotically presented in normal Persian speaking adults.

METHODS

Speech-evoked auditory brainstem responses were obtained in 27 normal hearing young adults by using G.tec EEG recording system. 170ms synthetic consonant-vowel stimuli /ba/, /da/, /ga/ were presented binaurally and the recurrence quantification analysis was performed on the responses. The recurrence time of second type was proposed as a suitable feature. ANOVA was also used for testing the significance of extracted feature. Post-comparison statistical method was used for showing which means are significantly different from each other.

RESULTS

Dimension embedding and state space reconstruction were helpful for visualizing nonlinearity in auditory system. The proposed feature was successful in the objective classification of responses in window time 20.1-35.3ms, which belonged to formant transition period of stimuli. Also the p value behavior of recurrence time of second type feature as a discriminant feature was close to the nature of the response that includes transient and sustained parts. On the other hand, the /ba/ and /ga/ classification period was wider than the others.

CONCLUSION

The extracted feature shown in this paper is helpful for the objective of distinguishing individuals with auditory processing disorders in the structurally similar voices. On the other hand, differing nonlinear feature is meaningful in a special region of response, equal to formant transition period, and this feature is related to the state space changes of brainstem response. It can be assumed that more information is within this region of signal and it is a sign of processing role of brainstem. The state changes of system are dependent on input stimuli, so the existence of top down feedback from cortex to brainstem forces the system to act differently.

Hyperbilirubinemia and phototherapy in newborns: Effects on cardiac autonomic control

BACKGROUND

Neonatal jaundice and its phototherapeutic treatment can lead to several side effects involving activation of autonomic control mechanisms.

AIM

The aims of this study are to investigate the autonomic nervous system changes in icteric neonates using heart rate variability (HRV) and to assess the effect of phototherapy on short-term heart rate dynamics as an indicator of autonomic nervous control of cardiovascular system.

METHODS

HRV recordings from 20 icteric full-term neonates before, during and after phototherapy and from 20 healthy controls were analyzed. In addition to traditional time and frequency domain measures, heart rate complexity parameters including normalized complexity index (NCI), normalized unpredictability index (NUPI), pattern classification indices (0V%, 1V%, 2LV%, 2UV%) and irreversibility index (P%) on four time scales were evaluated. All measures were derived from data segments of 1000 RR intervals.

RESULTS

The analysis revealed higher values of 1V%, 2LV%, and lower P% in neonates with hyperbilirubinemia compared to controls. While HRV magnitude did not change, mean heart rate increased during and after the phototherapy. Nonlinear analysis showed a decrease of complexity, unpredictability and pattern classification measures 2LV% and 2UV%. In contrast, 0V% and irreversibility index P% were increased during and at least 30min after phototherapy.

CONCLUSION

The results suggest a shifted autonomic balance in icteric neonates compared to the controls and its further alterations during phototherapy. As the nonlinear HRV parameters are independent of the linear methods, they can provide new information about the cardiac regulatory mechanisms and their changes in neonates.

FE analysis of stress and displacements occurring in the bony chain of leg

AIMS

The aim of this study was to assess how the stress shielding can influence the integrity and resistance of bones.

METHODS

With this purpose a complete FE model of the human leg was realised. A load of 700 N has been applied at the top of pelvis and the feet, at the tip, was rigidly fixed.

RESULTS

Obtained results reveal interesting consequences deriving by taking into account the complete bony chain.

CONCLUSION

A comparison among the literature data and our models can furnish a complete vision of the global spreading of the forces along the various bony components.

Acoustic assessment of the voices of children using nonlinear analysis: proposal for assessment and vocal monitoring

OBJECTIVE

To analyze the accuracy of recurrence measurements, both isolated and combined, to assess the intensity of vocal disorders in children.

METHOD

A total of 93 children of both sexes (48 girls and 45 boys), aged between 3 and 10 years, participated. The vocal-deviation intensity was evaluated by the consensus of three speech therapists from the pronunciation of vowel /ε/ using the visual analog scale. In the acoustic analysis, eight recurrence plot characteristics were evaluated and extracted with neighborhood radius values that maintained the recurrence rate at 1%, 2%, 3%, 4%, and 5%. The classification was performed using quadratic discriminant analysis applied for individual and combined measurements. The performance was evaluated by measuring the accuracy, which related the cases correctly classified to all the analyzed cases.

RESULTS

In the classification cases concerning individual measure performance, the trapping time and maximum length of the diagonal lines showed the best classification potential to discriminate between healthy and disturbed voices, with accuracy rates above 80%. In the healthy and mild deviation cases, the trend (TREND) measure was also relevant. For the mild versus moderate deviation classification, the best performance was obtained by the TREND measure (85.00% ± 7.64%). A gain was obtained in the classification rate when the measures of recurrence were combined, reaching an accuracy of 95.00% ± 5.00%, for discriminating between healthy voices and those with mild deviation.

CONCLUSIONS

The measures of recurrence, either alone or combined, may be useful in detecting healthy and disturbed voices and in differentiating the intensity of vocal disorders in children.

Munc18-1 haploinsufficiency results in enhanced anxiety-like behavior as determined by heart rate responses in mice

Heterozygous (HZ) missense mutations in the gene encoding syntaxin binding protein 1 (Stxbp1 or Munc18-1), a presynaptic protein essential for neurotransmitter release, causes early infantile epileptic encephalopathy, abnormal brain structure and mental retardation in humans. Here we investigated whether the mouse model mimics symptoms of the human phenotype. The effects of the deletion of munc18-1 were studied in HZ and wild-type (WT) mice based on heart rate (HR) and its variability (HRV) as independent measures to expand previous behavioral results of enhanced anxiety and impaired emotional learning suggesting mild cognitive impairments. HR responses were assessed during novelty exposure, during the expression and extinction of conditioned tone-dependent fear and during the diurnal phase. Novelty exposure yielded no differences in activity patterns between the two genotypes, while maximum HR differed significantly (WT: 770 bpm; HZ: 790 bpm). Retention tests after both auditory delay and trace fear conditioning showed a delayed extinction of the conditioned HR response in HZ mice compared to WT mice. Since the HR versus HRV correlation and HR dynamics assessed by nonlinear methods revealed similar function in HZ and WT mice, the higher HR responses of munc18-1 HZ mice to different emotional challenges cannot be attributed to differences in autonomic nervous system function. Thus, in contrast to the adverse consequences of deletion of a single allele of munc18-1 in humans, C57BL/6J mice show enhanced anxiety responses based on HR adjustments that extend previous results on the behavioral level without support of cognitive impairment, epileptic seizures and autonomic dysregulation.

Children with cerebral palsy have greater stochastic features present in the variability of their gait kinematics

Children with CP have a more variable gait pattern. However, it is currently unknown if these variations arise from deterministic variations that are a result of a change in the motor command or stochastic features that are present in the nervous system. The aim of this investigation was to use a Langevin equation methodology to evaluate the deterministic and stochastic features that are present in the variability of the gait kinematics of children with cerebral palsy (CP). Ten children with spastic diplegic CP and nine typically developing (TD) children participated in this investigation. All of the children walked on a treadmill for 2 min while a three-dimensional motion capture system recorded the step kinematics. Our major findings for this investigation were: (1) children with CP had greater variability in their gait patterns than TD children, (2) the variability of the children with CP and TD children had similar deterministic features, (3) the variability had greater stochastic features for the children with CP, and (4) the increase in the amount of variability was strongly correlated with the increase in stochastic features. These results indicate that the variability seen in the gait patterns of children with CP may be due to the inability to suppress the noise that is present in the neuromuscular system.

Center of pressure and the projection of the time-course of sitting skill acquisition

A normal time-course for the acquisition of sitting is essential. A delay in sitting may affect other developmental milestones, resulting in deficiencies in overall skill. Therefore, our aim was to identify variables whose measures at the very beginning of sitting would allow for the projection of the evolution of the sitting skill. Center of pressure data were collected from the postural sway of twenty-six typically developing infants while sitting on a force platform with a beginning ability to sit upright. Spatial, temporal and frequency variables of postural sway were obtained from both the medial/lateral and anterior/posterior directions of sway. Discriminant function analysis was conducted to identify potential predictors of the duration between onset and fully independent sitting. Gender (p=0.025), median frequency (p=0.006), and correlation dimension (p=0.002) were identified to be predictive of grouping with 73.1% correct classification of the participating infants into short, mid, and long delay groups. In conclusion, measures taken at the earliest stage of sitting may allow the projection of the time-course to achieve independent sitting for typical infants. This approach may be useful for monitoring typical development.

Complexity of spontaneous brain activity in mental disorders

Recent reports of functional and anatomical studies have provided evidence that aberrant neural connectivity lies at the heart of many mental disorders. Information related to neural networks has elucidated the nonlinear dynamical complexity in brain signals over a range of temporal scales. The recent advent of nonlinear analytic methods, which have served for the quantitative description of the brain signal complexity, has provided new insights into aberrant neural connectivity in many mental disorders. Although many studies have underpinned aberrant neural connectivity, findings related to complexity behavior are still inconsistent. This inconsistency might result from (i) heterogeneity in mental disorders, (ii) analytical issues, (iii) interference of typical development and aging. First, most mental disorders are heterogeneous in their clinical feature or intrinsic pathological mechanisms. Second, neurophysiologic output signals from complex brain connectivity might be characterized with multiple time scales or frequencies. Finally, age-related brain complexity changes must be considered when investigating pathological brain because typical brain complexity is not constant across generations. Future systematic studies addressing these issues will greatly expand our knowledge of neural connections and dynamics related to mental disorders.

Investigation of changes in EEG complexity during memory retrieval: the effect of midazolam

The aim of this study is applying nonlinear methods to assess changes in brain dynamics in a placebo-controlled study of midazolam-induced amnesia. Subjects injected with saline and midazolam during study, performed old/new recognition memory tests with EEG recording. Based on previous studies, as midazolam causes anterograde amnesia, we expected that midazolam would affect the EEG's degree of complexity. Recurrence quantification analysis, and approximate entropy were used in this assessment. These methods compare with other nonlinear techniques such as computation of the correlation dimension, are suitable for non-stationary EEG signals. Our findings suggest that EEG's complexity decreases during memory retrieval. Although this trend is observed in nonlinear curves related to the midazolam condition, the overall complexity were greater than in the saline condition. This result implies that impaired memory function caused by midazolam is associated with greater EEG's complexity compared to normal memory retrieval in saline injection.