Whether you are part of our community or are interested in joining us we welcome you to Washington University School of Medicine Physician-scientist studies how technology can improve communication about fertility issues by Diane Duke Williams•July 26 has been named director of the Division of Reproductive Endocrinology & Infertility in the Department of Obstetrics & Gynecology at Washington University School of Medicine in St Kenan Omurtag, MD, an accomplished fertility specialist, educator and mentor, has been named director of the Division of Reproductive Endocrinology & Infertility in the Department of Obstetrics & Gynecology at Washington University School of Medicine in St Louis “Kenan has extensive clinical expertise, is an excellent mentor and has played an important role in our curriculum development,” said Dineo Khabele, MD, the Mitchell and Elaine Yanow Professor and head of the Department of Obstetrics & Gynecology innovative ideas and vision he brings to the division make him ideal for his new role an associate professor of obstetrics & gynecology maintains an active clinical practice focused on in vitro fertilization and medical and surgical treatment of endometriosis and uterine fibroids His research efforts have focused on how technology can be used to disseminate information about fertility issues as well as to improve communication between patients and fertility clinics’ staffs Omurtag also is one of the first to describe experiences of and novel approaches to fertility preservation among transgender and nonbinary adults and adolescents He has published and lectured extensively nationally and internationally on these topics He also serves as medical director of the Washington University Fertility & Reproductive Medicine Center and as co-director of its Integrative Care & Fertility Preservation Program and there are no guarantees for patients,” Omurtag said “The next decade of innovation in fertility care will focus on improving the patient experience and improving access to these services I am honored to take on the role of division director.” earned his bachelor’s and medical degrees in a six-year program at the University of Missouri—Kansas City School of Medicine He completed a residency in obstetrics & gynecology at Emory University School of Medicine/Grady Hospital and a fellowship in reproductive endocrinology and infertility at Washington University School of Medicine He joined Washington University in 2013 as an assistant professor of obstetrics & gynecology and was named an associate professor in 2018 he served as a laborist at Missouri Baptist Hospital/BJC HealthCare and as a health-care policy fellow at Partners Healthcare in Boston williamsdia@wustl.edu Could help determine which patients are likely to benefit from new Alzheimer’s drugs GLP-1 medications tied to decreased risk of dementia At WashU Medicine, we transform lives and shape the future of healthcare through pioneering research, world-class education, and unparalleled patient care. As one of the nation's largest academic clinical practices, we bring the full power of WashU Medicine to every patient, advancing treatment and training the medical leaders of tomorrow at Barnes-Jewish and St. Louis Children's hospitals and more than 130 clinics across Missouri and Illinois Consistently recognized among the nation's top institutions for research we are driven to challenge convention and elevate care for all Metrics details Children born to mothers infected by Zika virus (ZIKV) during pregnancy are at increased risk of adverse neurodevelopmental outcomes including microcephaly collectively known as Congenital Zika Virus Syndrome To study the impact of ZIKV on infant brain development we collected resting-state electroencephalography (EEG) recordings from 28 normocephalic ZIKV-exposed children and 16 socio-demographically similar but unexposed children at 23–27 months of age We assessed group differences in frequency band power and brain synchrony as well as the relationship between these metrics and age Bonferroni corrected) in Inter-Site Phase Coherence was observed: median Pearson correlation coefficients were 0.15 in unexposed children and 0.07 in ZIKV-exposed children Results showed that functional brain networks in the unexposed group were developing rapidly in part by strengthening distal high-frequency and weakening proximal lower frequency connectivity presumably reflecting normal synaptic growth These maturation patterns were attenuated in the ZIKV-exposed group suggesting that ZIKV exposure may contribute to neurodevelopmental vulnerabilities that can be detected and quantified by resting-state EEG These findings underscore the importance of developing functional methods to assess neural synchrony in normocephalic individuals who were prenatally exposed to the Zika virus While structural imaging is invaluable for revealing physical abnormalities in the brain it may not capture the subtle functional disruptions that can occur This study aimed to address the current knowledge gap by investigating EEG-based functional connectivity in ZIKV-exposed normocephalic nonepileptic children (ZEC) compared to demographically matched children unexposed to ZIKV (UC) By focusing on inter-site phase clustering (ISPC) we sought to elucidate potential alterations in brain network organization associated with prenatal ZIKV exposure in the absence of microcephaly or epilepsy particularly in brain areas likely to be affected by the virus together with an analysis pipeline based on the identification of changes in ISPC with age The average duration of EEG recordings in the analysis group was 12.8 min Relative band power and its age-dependence (A) Relative frequency band power (FBP) as a function of frequency for each electrodes site The UC (solid green line) and ZEC (dashed purple) averages are shown (B) Topographic illustration of the correlation of FBP with age for specific frequency ranges for the UC (top row) and ZEC (bottom) Distribution of developmental change in synchrony the correlation of ISPC with age in the UC (purple) and ZEC (green) respectively) are shown by the dashed vertical lines; (B) Scatter plot of rN and rZ with each dot corresponding to an electrode pair and specific frequency and the diagonal dashed line showing rN = rZ These correspond to ISPC in the infant gamma frequency range phase clustering between the left inferior frontal scalp area and the right frontopolar (FP2-F7 at 28–38 Hz) and right parietal areas (P4-F7 at 28–30 Hz) The correlation strength between inter-site phase clustering (ISPC) and age in UC and ZEC are grouped into rows depending on their effect size in UC (A) Rapidly increasing; (B) moderately increasing; (C) stagnating; (D) moderately decreasing; (E) rapidly decreasing Columns 2–5 show randomly selected examples of electrode pairs separated into UC (purple circles) and ZEC (green triangles) groups The distribution of the developmental change in synchrony in frequency bands UC (solid purple) and ZEC (green dashed) for the frequency bands indicated above each subplot The vertical lines indicate the medians of the corresponding distributions Distributions whose medians differ significantly are indicated using an asterisk located between the vertical lines showing the medians (*p < 0.05 Topographic illustration of the developmental changes in connectivity The frequency band for each pair of columns is shown at the top UC (left) and ZEC (right) connectivity development are shown as lines Each row corresponds to a different development speed (A–D) Rapidly developing; (E–H) moderately developing; (I–L) stagnating; (M–P) moderately weakening; (Q–T) rapidly weakening A line’s colour indicates the sign of the change (blue/red for increase/decrease in ISPC with age) and the line’s thickness is proportional to the magnitude of the change as indicated in the figure legend at top right central and frontal areas both inter- and intra-hemispherically Similar patterns of rapid normal development of pervasive high frequency networks were observed also in higher frequency bands (not included in this figure) Graph theoretic characterisation of networks and their dependence on frequency The characteristic path length (A–D) and the clustering coefficient (F–I) based on all pairs of channels at all frequency bands in UC (purple solid) and ZEC (green dashed) The values for individual UC (circles) and ZEC (triangles) and their best fit lines are shown The rightmost column shows the correlation of the path length (E) and of the clustering coefficient (J) with age as a function of the frequency of the connection The shaded regions around each curve indicate the sample standard deviation Dependence of connectivity development on frequency and cortical distance. Distances based on the MNI locations of primary neuronal populations in adult cortex associated with each electrode, for the UC (A) and ZEC (B). See Table 2 for selected electrode pairs and their values of ISPC at the numbered zones 1–10 This suggests a potential association between altered ISPC and the observed visual dysfunction offers a theoretical framework to explore how aberrant neural network organization might underlie these visual impairments Further investigation into this relationship is warranted to elucidate the pathophysiological mechanisms underlying ZIKV-associated visual dysfunction This could have contributed to later neurodevelopmental gain and reiterates the importance of directing at-risk children to appropriate early intervention programs Through the analysis of resting-state measurements performed with a portable EEG system we have uncovered evidence that prenatal ZIKV exposure disrupts the development of large-scale neural network synchrony The extent to which this is transient and recoverable remains unknown the functional implications for the disrupted large-scale neural network development now or in the future remain unknown Our findings shed light on the disruption of normal changes in signal amplitude and shifts from proximal to largely distal functional connectivity as well as network trends toward small-world properties in young children These could form the basis for developing practical methods of EEG scanning to assess neurodevelopment particularly valuable for nonverbal populations for the purpose of early and targeted provision of therapeutic resources This approach could be especially beneficial for addressing global child health disparities particularly in resource-limited settings where children may be disproportionately vulnerable to teratogenic exposures this study suggests that it is feasible to use cost-effective portable EEG with integrated advanced analysis to study and manage the spectrum of ZIKV’s neurodevelopmental effects The study was approved by the Institutional Review Boards of St West Indies (IRB#16061) and Stanford University and granted research clearance by the Grenada Ministry of Health Mothers provided written informed consent for themselves and on behalf of their participating children and all methods were carried out in accordance with relevant guidelines and regulations Caregivers assisted by holding or comforting the children during EEG recordings caregivers spoke to them softly or read to them while the EEG cap was being applied and during the recording session The data contained resting-state EEG recordings from 73 children of whom N = 50 were ZEC (23 female) and N = 23 were UC (11 female) We next determined the clustering coefficient (CC) and characteristic path length (PL) which are commonly used in network analysis CC measures how well connected the neighbours of a typical node are to one another and high values of CC are associated with functional segregation PL is the mean shortest path over all pairs of nodes where the distance was calculated from the inverse of ISPC values PL quantifies the capacity for information transfer across the network and low values of PL are associated with greater functional integration We investigated potential developmental trends in FBP by determining the Pearson correlation of the relevant quantity with age where the correlation was denoted rN and rZ for UC and ZEC the Wilcoxon Signed-Rank test was used for paired values the set of ISPC values in UC for a specific connection versus the set of values in ZEC for the same connection and the Kolmogorov–Smirnov (KS) test when the groups were unpaired the interaction between Zika status and age was assessed with ANCOVA resulting in N(N − 1)/2 = 171 unordered channel pairs a total of 171 × 40 = 6840 distinct ISPC values were analysed The significance threshold was adjusted by dividing the conventional p-value of 0.05 by 6840 yielding p = 0.00000731 as a criterion for statistical significance to control the family-wise error rate across all comparisons The above calculations were implemented via custom code in MATLAB and using the functions signrank All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. All EEG data and analysis scripts are available at https://doi.org/10.5281/zenodo.13311078 Epilepsy surveillance in normocephalic children with and without prenatal Zika virus exposure Delayed childhood neurodevelopment and neurosensory alterations in the second year of life in a prospective cohort of ZIKV-exposed children Neurodevelopment in children exposed to zika virus: What are the consequences for children who do not present with microcephaly at birth? 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BMC Pediatr. https://doi.org/10.1186/s12887-019-1766-2 (2019) American clinical neurophysiology society guideline 5: Minimum technical standards for pediatric electroencephalography Kurtosis based blind source extraction of complex noncircular signals with application in EEG artifact removal in real-time The surface Laplacian technique in EEG: Theory and methods Developmental equations for the electroencephalogram A weighted small world network measure for assessing functional connectivity Download references Geisel School of Medicine at Dartmouth and Dartmouth College Windward Islands Research and Education Foundation State University of New York Downstate Health Sciences University National Health Service Clinical Scientist Training Oxford Maternal and Perinatal Health Institute Nuffield Department of Women’s and Reproductive Health ADL (for serological analyses to establish ZIKV status) Investigation: AO SAB is an employee of Bio-Signal Group Inc owns stock options in BSG and is a coinventor on US patent US9408575B2 AO was previously an employee of BSG and is a coinventor on US patent US9408575B2 All other authors declare no competing interests Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Below is the link to the electronic supplementary material Download citation DOI: https://doi.org/10.1038/s41598-025-90860-0 Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. 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Volume 11 - 2017 | https://doi.org/10.3389/fnhum.2017.00359 We studied the capability of a Hybrid functional neuroimaging technique to quantify human mental workload (MWL) We have used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) as imaging modalities with 17 healthy subjects performing the letter n-back task a standard experimental paradigm related to working memory (WM) The level of MWL was parametrically changed by variation of n from 0 to 3 Nineteen EEG channels were covering the whole-head and 19 fNIRS channels were located on the forehead to cover the most dominant brain region involved in WM Grand block averaging of recorded signals revealed specific behaviors of oxygenated-hemoglobin level during changes in the level of MWL A machine learning approach has been utilized for detection of the level of MWL and EEG+fNIRS signals as the biomarkers of MWL and fed them to a linear support vector machine (SVM) as train and test sets These features were selected based on their sensitivity to the changes in the level of MWL according to the literature We introduced a new category of features within fNIRS and EEG+fNIRS systems the performance level of each feature category was systematically assessed We also assessed the effect of number of features and window size in classification performance SVM classifier used in order to discriminate between different combinations of cognitive states from binary- and multi-class states In addition to the cross-validated performance level of the classifier other metrics such as sensitivity and predictive values were calculated for a comprehensive assessment of the classification system The Hybrid (EEG+fNIRS) system had an accuracy that was significantly higher than that of either EEG or fNIRS Our results suggest that EEG+fNIRS features combined with a classifier are capable of robustly discriminating among various levels of MWL Results suggest that EEG+fNIRS should be preferred to only EEG or fNIRS in developing passive BCIs and other applications which need to monitor users' MWL MWL is a construct that arises from the interaction of the properties of a task, the environment in which it is performed, and the characteristics of the human operator performing it (Longo, 2016) Task properties include the difficulty and monotony of the task and the types of resources that it engages The environment may contain various degrees of distraction and noise The subject characteristics involve training and expertise as well as changing levels of fatigue the MWL can be systematically adjusted by tuning a subset of these variables while controlling for the rest which is a gold-standard for measuring cerebral hemodynamics In addition to the advantages of pooling different types of signals EEG+fNIRS offers new types of features ultimately based on neurovascular coupling (NVC) the cascade of processes by which neural activity modulates local blood flow and oxygenation and NVC related features are not resolvable by a uni-modal signal sensitive to only neural activity (e.g. we built on this work to explore the unique properties of EEG+fNIRS for MWL detection the third aim of this study was to rigorously compare the performance of uni-modal and Hybrid systems 1 female) with a mean age of 26.2 and standard deviation of 7.7 years from University of Houston students or employees participated in the experiment The experimental procedures involving human subjects described in this paper were approved by the Institutional Review Board of the University of Houston The participants gave written informed consent prior to the experiments and were compensated for their effort by being given a gift card from a major retailer During the performance of the verbal n-back task target letters should be detected by the operator by means of pressing Space button on the keyboard All subjects were right-handed and used their dominant hand for performing the experiment This will reduce the variability of brain signals based on the motor function through all subjects None of the subjects had ever taken part in an n-back study subject should find the target letter and interact with the user-interface Schematic illustration of the letter n-back task for n ϵ {0 The program for implementation of this task was written using Presentation software (Neurobehavioral Systems All the information about the appearance time of each letter and also whether the presented letter was a target or not was recorded by this software and stored as a text file for later processing The objective performance of the subjects within each session was computed from this information Subjects who had too low accuracy (<90% in the 0- or <80% in the 1-back) were deemed insufficiently focused on the task Performance level was measured by computing the accuracy defined as the fraction of correct responses We considered a missed target as an incorrect response Experimental design for the letter n-back task NIRScout is a dual wavelength continuous wave system The EEG signal was band-pass filtered (0.5–80 Hz) and a 60 Hz notch filter was used to reduce the power line noise and data transmission to the acquisition platform (b) Coronal view of the subject showing the close view of the placement fNIRS optodes and EEG electrodes (c) Topographical view of fNIRS sources (Si Each pair of source and detector separated by 3 cm creates a channel (CHi) The figure indicates the temporal variations in the fNIRS signals and the EEG frequency bands First and second rows are HbO and HbR of fNIRS channel 17 Third row is the EEG time-frequency map for channel O2 Topographic view of EEG electrodes showing neighborhood pattern for Laplacian spatial filtering Inward arrows to each node indicate the corresponding neighbors used for spatial filtering Sample preprocessed EEG+fNIRS data for one of the subjects Vertical dashes separate different n-back task and rest blocks (a) Concentration changes of oxy-hemoglobin (red curve) and deoxy-hemoglobin (blue) for channel 17 (b) EEG Time-frequency map of the channel O2 In our experiment design we have 40 rest blocks and 10 blocks from each n-back task type and 2 features were extracted when we changed the size of the window from 5 to 25 s and 1 features were extracted when we changed the size of the window from 5 to 25 s Four different epoch styles based on length of windows The task and rest blocks are divided into (A) 5 We extracted from each window three main categories of features for all 19 EEG electrodes and 19 fNIRS channels: EEG (uni-modal) We chose 8 EEG channel pairs between right and left hemispheres (F8-F7 fNIRS features were based on HbO and HbR amplitude (HbO/R Amp.), slope of HbO and HbR (HbO/R slope), standard deviation of HbO and HbR (HbO/R Std.), skewness of HbO and HbR (HbO/R Skew.), and kurtosis of HbO and HbR (HbO/R Kurt.). The statistics of HbO and HbR are commonly used as features in fNIRS studies of MWL and BMIs (Naseer and Hong, 2015; Naseer et al., 2016a,b) Our inspection of the fNIRS data revealed patterns of correlation between HbO and HbR that were time and area dependent we also included the zero-lagged correlation between HbO and HbR (HbO-HbR Corr.) as an additional feature Hybrid features were based on EEG and fNIRS features in addition to specifically Hybrid quantities that depend simultaneously on both systems We chose to focus on a straightforward quantity which can be easily calculated within the time windows of interest: the zero-lagged correlation between the Hb (HbO or HbR) amplitude and the EEG frequency band power (in eight separate bands described above) These neurovascular features based on HbO and HbR were denoted NVO (oxygenated neurovascular coupling) and NVR (deoxygenated neurovascular coupling) To calculate NVO/R for the left hemisphere the correlation between each fNIRS channel (CH1 to CH9) and each frequency band of F7 EEG channel was calculated (band-passed filter within the specific frequency range) the correlation between each fNIRS channel (CH11–CH19) and each frequency band of F8 EEG channel was calculated which is located at the center we used the average of F7 and F8 channels to find NVO and NVR This resulted in 152 (19 × 8) NVO and 152 NVR features from each window Each set of features extracted from one subject's data were dc-shifted and scaled in order to have a mean value of zero and standard deviation of one We pooled all the k confusion matrices of the k-fold cross validation to calculate Sens.A For all the calculations described in this paper we used Matlab v.8.6.0.267246 (R2015b) (The MathWorks The top R2 ranked features for three representative subjects for the binary rest v 3-back classification Behavioral performance of the subjects during task conditions of increasing difficulty showing response accuracy (red) and response time (black) Error bars indicate the standard deviation of inter-subject variability Asterisks indicate statistical significance derived from a two-way ANOVA comparison of each two response accuracy (red) or response time (black) (*p < 0.05 These patterns are not observed in the case of the 0-back task since it is related to perception only and is less involved with WM system We also examined the time course of selected features that were extracted from the signals Grand block average of normalized HbO (red) and HbR (blue) during (a) 0-back The thick curves show the average over all channels and subjects The shaded area indicates the standard deviation of inter-subject variability Grand block average of HbO (f) and HbR (g) for rest (dashed curves) and task (solid) Increasing thickness of solid curves corresponds to increasing task difficulty from 0- to 3-back The figure shows that the theta and alpha bands of EEG are positive during 0- and 1-back although they become negative for 2- and 3-back tasks The positive peak of HbO increases from 0- to 2-back and has a slightly lower peak for 3-back compared to 2-back The figure also shows that the Hybrid features (such as NVO in the delta range) generally resemble the corresponding uni-modal features (such as HbO and PSD in the delta range) however they were dominated by neither suggesting that the Hybrid feature contained additional information Grand block average of normalized features from 5 s windows: (a) PSD (delta Shaded areas indicate the standard deviation of inter-subject variability Table 1 shows the top 10 highest ranked features (based on R2) for three subjects obtained during the 3-back v rest training set The features are characterized by the description (e.g. as described in Section Methods) and the particular frequency band The frequency band is applicable only to the EEG and neurovascular features The table also indicates the order of the feature according to the magnitude of its eigenvalue [ordered from the most energetic (1) to the least (19)] the channel label is given instead of the PC order the highest ranked feature for subject one was the third most energetic PC from the EEG frequency band power in the theta range (4–8 Hz) the highest ranked feature was the second most energetic PC from the neurovascular feature based on the correlation between HbR and the EEG frequency band power in the high beta range (28–32 Hz) The table illustrates that the types of features in the top ranked group may vary among subjects and that high discriminating ability of a feature does not imply high energy in the sense of the PCA Figure 10 shows the classification accuracies of various subsystems as well as the Hybrid system for the 3-back v rest using 5 s windows The error bars represent the standard deviation of inter-subject variability the leftmost bar is the accuracy of a system based only the PSD features On its immediate right is the accuracy of the subsystem based only on PLV features and similarly for PAC and other feature types The rightmost bar in the EEG group shows the accuracy of the full EEG system which includes all feature types based on EEG signals Clearly the PSD is the primary contributor to the discriminating ability of the EEG the accuracy appears to be slightly enhanced by including the other types of features Among the fNIRS systems (red) the leftmost bar indicates that Hb amplitudes together with the HbO-HbR correlation is the primary contributor to the accuracy of detection the other feature types such as slope and higher order statistics significantly enhance the accuracy of the fNIRS system The overall accuracy of the fNIRS system is lower than the overall accuracy of the EEG system The accuracy based only on the neurovascular features is indicated by the leftmost bar in the Hybrid group (green) The middle bar in the Hybrid group represents the pooling of all features from the EEG and fNIRS systems Finally the inclusion of the neurovascular features in the Hybrid system (rightmost green bar) appears to slightly enhance the accuracy Accuracy of types of features in classifying rest v 3-back with 5 s feature windows The error bars indicate the standard deviation of inter-subject variability The union of neurovascular features is abbreviated as NV Features are extracted from different systems: EEG (gray bars) The calculations are for the 3-back v rest using 5 s windows and they qualitatively agree with the results (not shown) of binary classifications of other pairs of classes and window sizes The shaded areas indicate the standard deviation of inter-subject variability (a) Accuracy and (b) cumulative sum of R2 for EEG (black) and Hybrid (green) systems as a function of system size Mean and standard deviation over subjects are indicated by the solid curves and shaded areas The classification task was rest v 3-back and feature window size was 5 s Binary classification accuracy for all subjects included in the study (S1 to S14) for 10-fold cross validation Multi-class classification accuracy for all subjects included in the study (S1 to S14) for 10-fold cross validation the differences of accuracy among the subjects were not significant and there were no interactions between system type and subject while the differences in accuracy between the Hybrid and the uni-modal system was significant with a p < 0.001 Table 4 lists the sensitivity (Sens.) and negative predictive value (NPV) for each individual class within a classification case For example for the case of {Rest v 3back} each one of rest and 3-back classes would have a Sens. this table summarizes all these metrics for EEG and Hybrid systems in order to make it easier to compare between their capabilities and negative predictive value (NPV) are listed in percentage (%) for all classification cases (binary and multi-class) and all systems (EEG The foregoing results corresponded to 5 s windows but qualitatively agreed with patterns we observed with other window sizes as well. We also assessed the effect of window length on classification accuracy for EEG, fNIRS, and Hybrid systems. Figure 12 shows the results of this assessment We examined four different lengths for the windows (5 Change of window length has the same effect on all three types of systems By increasing the length from 5 to 20 the accuracy increases and declines thereafter Accuracy of the rest v 3-back classification as a function of window size for EEG (gray) The functional activity of the human brain can be observed with various imaging techniques including fMRI Each of these modalities has its advantages and disadvantages The advantage of using Hybrid EEG+fNIRS system can be divided into two main categories: First each of these modalities is measuring the changes in a specific brain physiology EEG results directly from the electrical activity of cortical and subcortical neurons with a sub-millisecond temporal resolution fNIRS yields local measures of changes in HbO and HbR concentration and is an indicator of metabolic/hemodynamic changes associated with neural activity the physics of measurement behind EEG and fNIRS are quite different makes EEG signal prone to blink and muscle artifacts Hence using a multimodal recording system we are able to assess brain behavior from different physiological perspectives in addition to compensating for some weaknesses of one modality by the other one Our results suggest that EEG+fNIRS combined with a classifier are capable of robustly discriminating among various levels of MWL the Hybrid system had an accuracy higher than either EEG or fNIRS alone for every subject The pooling of EEG and fNIRS features and the inclusion of neurovascular features resulted in a synergistic enhancement rather than in a diluting effect (which would have given a performance intermediate between the two modalities) In mission-critical contexts such as aviation or surgery even small improvements in MWL detection can translate into significant gains in safety and efficiency Our experiments were designed to use WM load (adjusted through the value of n in the n-back task) as a correlate of MWL in general EEG and fNIRS can be integrated without excessive cost The combination of all these considerations suggests that EEG+fNIRS should be preferred to only EEG or fNIRS he loses his concentration on the task and as a result performance as well as the oxygenated hemoglobin changes decline the subject averaged accuracy of the Hybrid system in binary discrimination was lowest (87.2%) for 1-back v rest and highest (96.6%) for 3-back v 0-back The corresponding lowest and highest results for uni-modal systems were fNIRS (71.6%) and EEG (92.0%) We calculated the overall average of accuracy one time for all of the binary cases and one time for all of the muli-class cases These numbers convey that the accuracy of each one of EEG and Hybrid systems are higher for the binary cases The multi-class accuracies were generally lower; however note that the chance level accuracy for multi-class classification is less than binary classification (33% for 3-back v 2-back v 1-back Selecting an optimal subset from the full set of features is crucial for achieving high accuracy and avoiding over-fitting. In some applications, e.g., those involving on-board real-time analysis, it may also be important to keep the system size small and avoid computational delays. Figure 11b shows the cumulative sum of R2 v number of features for three systems which qualitatively agrees with Figure 11a suggesting that R2 ranking is an effective method of feature selection We have not used an explicit artifact rejection step in our analysis it is well known that PCA can segregate non-cerebral artifacts (typically of higher amplitude than contributions of cortical origin) into distinct PCs Our feature selection based on R2 then assigns a lower rank to such PCs and they are excluded from a truncated system One of the main considerations in developing an online system is computational speed. It is instructive to review the computational loads of particular feature types in conjunction with how effectively they discriminate among rest and task states. For example, Figure 10 shows that PAC is the least discriminating EEG feature This may be important in designing a compact and efficient detector as PAC is also the most computationally time-consuming feature the most effective EEG feature (PSD) was also the fastest to compute the central processing unit (CPU) time required for computing PSD The CPU times required for other features were as follows: HbO/R Amp EEG and fNIRS use different physical processes for detection and the underlying physiology which they detect are different or subject variability leading to a weak signal would selective affect only one modality rather than both The Hybrid advantage may be associated primarily with the complementary nature of the individual modalities They extracted EEG frequency band power and fNIRS Hb amplitude features from 5 s windows and employed them in linear discriminant analysis classifiers They report maximum accuracies of 89.6% (EEG) Their results differed from ours in that in some subjects all their systems had very low accuracies and their Hybrid accuracies were not always higher than those of both uni-modal systems the fact that EEG generally had the higher uni-modal accuracy and that Hybrid could attain the highest observed accuracy were consistent with our findings The differences from our results could be attributed to the relatively lower number of sensors and fewer types of features they employed We defined the band-pass filter cutoff frequency (0.5–80 Hz) based on these criteria Although in the feature extraction section we did not consider gamma frequency range features and have considered this as the future work we implicitly used the assumption that an increase in the level of task difficulty will result in a higher MWL This can be also considered in future studies it is possible that during the course of an experiment the subjects' performance and MWL change through training effects Studying the performance and neural correlates of MWL for subsets of our data could reveal differences in the beginning and at the end of the study This would also require an additional investigation of statistical validity The statistical significance of the results of our study was demonstrated through a two-way ANOVA that showed significant differences in the accuracy of the Hybrid v uni-modal systems we have not investigated whether a smaller group of subjects would still yield a significant result We have investigated the capabilities of various subsets of the types of features that were available It would also be illuminating to investigate the classification accuracy of subsets of the full array of our sensors Such information can help design more compact headsets and is the subject of an ongoing study The headset we used is lightweight and no discomfort was reported by any of the subjects wearing it may nevertheless affect performance and this could be revealed in a parallel set of experiments which we have not done The primary goal of our study was to apply machine learning techniques in discriminating levels of MWL We used multiple statistical techniques to ensure that the statistical significance of the values of accuracy that we obtained for such discrimination Our observations regarding the range of changes of Hb are therefore only qualitative and observational serving to ensure that our results are consistent with expectations will lead to more effective passive BMIs and other applications in neuroergonomics This work is based partly on support by the National Science Foundation I/UCRC for Cyber-Physical Systems for the Hospital Operating Room under Grant no We would also like to thank the Department of Biomedical Engineering and the Cullen College of Engineering at University of Houston for its financial support (Award no AO participated in the development of the wireless portable EEG device (microEEG) He holds a financial interest in Bio-Signal Group which is the maker of microEEG The other authors declare that the 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) distribution or reproduction in other forums is permitted provided the original author(s) or licensor are credited and that the original publication in this journal is cited in accordance with accepted academic practice distribution or reproduction is permitted which does not comply with these terms *Correspondence: Haleh Aghajani, aGFnaGFqYW5pQHVoLmVkdQ== †Present Address: Ahmet Omurtag Nottingham Trent University Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish Metrics details This paper investigates the neural mechanisms underlying the early phase of motor learning in laparoscopic surgery training brain-derived neurotrophic factor (BDNF) concentrations and subjective cognitive load recorded from n = 31 novice participants during laparoscopy training Functional connectivity was quantified using inter-site phase clustering (ISPC) and subjective cognitive load was assessed using NASA-TLX scores The study identified frequency-dependent connectivity patterns correlated with motor learning and BDNF expression Gains in performance were associated with beta connectivity particularly within prefrontal cortex and between visual and frontal areas and were predicted by delta connectivity during the initial rest episode (r = 0.83) The study also found correlations between connectivity and BDNF with distinct topographic patterns emphasizing left temporal and visuo-frontal links By highlighting the shifts in functional connectivity during early motor learning associated with learning and linking them to brain plasticity mediated by BDNF the multimodal findings could inform the development of more effective training methods and tailored interventions involving practice and feedback The skill acquired rapidly during the early phase of laparoscopic training lays the foundation for later consolidation hence insights into its neural correlates are potentially useful for designing more targeted forms of practice and feedback NASA-TLX scores were used to elucidate the cognitive demands imposed by the learning task The results demonstrated simultaneous improvement in speed and accuracy as well as reduction in cognitive load and patterns of frequency-dependent connectivity were correlated with the extent of motor learning as well as BDNF expression We also showed that graph-theoretic properties of the functional networks during rest as well as task performance could be used to discriminate between high- and low-learners could offer a comprehensive understanding of the complex processes underlying the initial phases of motor learning EEG was recorded throughout the experiment from 19 channels positioned at the standard 10–20 sites and performance and self-reported cognitive load were measured Experiments and behavioural and subjective indicators of learning (A) Photograph of Ring Transfer and Threading boards and a task performing participant (C) Completion times of initial (x-axis) and repeat (y-axis) performances of the Ring transfer (blue circles) and Threading (red squares) tasks (D) Change in (repeated minus initial) Error Rate v change in Completion Time for the Ring Transfer task (E) NASA-TLX Effort score for the initial (x-axis) and repeated (y-axis) tasks (F) Change in NASA-TLX Effort score v change in Completion Time Results from the two subjects who reached the 15 min max allowed time in the ring task are indicated by a black plus sign Connectivity was quantified by ISPC to show the extent of clustering in the polar space of the phase angle differences between pairs of narrowly band-limited signals34 There were a total of 5472 distinct ISPC values as each ISPC was associated with a 1 Hz wide frequency band (in the range 1–32 Hz) as well as a specific pair of electrodes (with 171 undirected pairs of 19 electrodes) the effect of task performance (Task (black curves) relative to Rest (green)) was to lower ISPC in the alpha and lower frequency ranges while strengthening beta frequency links across all cortical distances We also examined the topographic locations of the strongest connections during Rest and Task performance. Figure 2F G represent ISPC values by a line connecting a pair of sites These links show the connections with the highest values of ISPC (only top 30 were selected to avoid clutter in the figure) Symmetric inter-hemispheric frontal connectivity (F7-F8) as well as longitudinal inter-hemispheric connections (e.g theta and alpha frequencies were salient in both the initial rest (F) and the task (G) In addition intra-prefrontal connections (e.g Subject averaged functional connectivity during Rest and Task episodes The top row shows the ISPC averaged across connections linking (A) short and (E) long cortical distances as a function of the connection frequency for the Rest (green curves) and Task (black solid) and T1R (black dotted) episodes The range of cortical distance for each of these groups is indicated above each subplot Also shown are ISPC for selected frequencies during initial Rest (F) and initial Task (G) episodes with the frequencies indicated above each column The task-evoked change (Task minus Rest) in ISPC is shown in the bottom row (H) where increase and decrease are indicated by red and blue lines The top 30 connections with the largest differences are shown Each column is for a selected frequency (shown at the top) while the connections whose correlation coefficients are within the distinct ranges have been segregated into separate rows for better visibility The ISPC for each participant in this figure was calculated by averaging the ISPCs corresponding to the red lines in the 3 Hz topographic subplot C The association between functional connectivity and performance improvement quantified by the Pearson correlation between ISPC and Rescaled Speed Increment ISPC was calculated during initial rest (A–D) and initial task performance (E–H) Histograms of correlation coefficients for the frequencies are displayed for rest (A) and task (E) with 95% confidence intervals indicated by grey shaded regions Topographic illustrations are provided for the connections during rest (B) and during task (F) that were strongly anticorrelated (r < – 0.4) with RSI; and during rest (C) and task (G) that were strongly positively correlated (r > 0.4) with RSI Also shown are scatter plots of ISPC v RSI where ISPC was calculated as the average of connectivity (D) at 3 Hz during rest and (H) at 24 Hz during task The association between functional connectivity and BDNF Topographic illustrations are provided for the connections during rest (B) and during task (F) that were strongly anticorrelated (r<–0.4) with BDNF; and during rest (C) and task (G) that were strongly positively correlated (r > 0.4) with BDNF Also shown are scatter plots of ISPC v BDNF where ISPC was calculated as the average of connectivity (D) at 7 Hz during rest and (H) at 16 Hz during task By using ISPC as the weights of edges between nodes represented by electrodes we constructed weighted undirected graphs whose properties provided descriptions of the overall connectivity profile and its association with motor learning For these graphs we calculated the characteristic path length (λ) and clustering coefficient (CC) The reciprocal of λ quantifies network integration or the efficiency of information transfer across the network while CC measures network segregation resulting from the extent to which nodes tend to cluster together Graph theoretic quantities and their association with motor learning quantified by RSI Characteristic Path Length (A) and Clustering Coefficient (C) and the correlation between the Rescaled Speed Increment and Characteristic Path Length (B) and Clustering Coefficient (D) shown as functions of frequency for Rest (green curves) and Task (black) episodes The final Rest or Task episodes are indicated by dotted lines This study presents several novel findings it demonstrates and quantifies within-session learning in laparoscopic surgery training using the Rescaled Speed Increment which is independent of the participants’ baseline performance providing a robust metric to assess skill acquisition during training sessions we utilised narrow-band inter-site phase clustering rather than connectivity measures in the traditional wider frequency bands to quantify the functional connectivity between different brain regions in the participants the study has shown that shifts in brain’s functional connectivity in specific combinations of frequency and topography were linked to performance enhancements as well as blood BDNF concentrations the down-regulation of prefrontal and frontal connectivity was revealed to be a significant promoter of fast motor learning suggesting that cognitive load was not close to levelling off consistent with the longer time-course of the automation process It is also worth noting that if the phase clustering had been driven primarily by volume conduction ISPC would have shown a steady decline with increasing cortical distance rather than the observed non-monotonic dependence The performance of bimanual visuomotor training tasks was expected to strengthen the high-frequency inter-hemispheric connections over the motor regions, as well as the connections linking the occipital (visual) and frontal areas. This hypothesised outcome was indeed observed, as depicted by the red lines in Fig. 2H We used histograms of correlation coefficients as a guide in discovering connectivity related to learning (Fig. 3) since a histogram will deviate from the null distribution only if there is a pervasive pattern of correlations with the same sign outweighing those of the opposite sign; strong individual correlations potentially due to chance are not sufficient to skew the histogram (Figures S2-S5) Investigating the extent to which changes in connectivity correlate with learning (Figure S7) showed that high learners had significantly greater task-evoked declines in delta band connectivity (Figure S7B) Thus our findings about the predictive role of resting and task-evoked changes in delta connectivity for fast motor learning warrants further study However by closely examining the correlations between ISPC with RSI we have found that inter-subject differences in these networks during the pre-task rest episode were in fact predictive of better learning (Figure S2E and H Thus the networks during rest which correlate with RSI share some commonalities with the task activated ones; notably participants with greater alpha desynchronisation of the DMN and high-beta synchronisation of occipital-frontal networks were shown to be better future fast learners and occipitofrontal areas are promising candidates as neural markers for the extent of fast learning in laparoscopy training beta connectivity between left temporal and frontal and central areas were lower during the repeat task and second task relative to initial task performance (Figure S4) However we did not find any correlations between BDNF and RSI (Table S3) which suggests that BDNF may be primarily a facilitator of slow learning although strongly affected by task performance Furthermore we found that network integration and segregation depended strongly on the frequency of the underlying functional connections the task-related shifts in integration were similar to the shifts in segregation This implied that task performance affected connectivity at different cortical distances in similar ways since λ is influenced primarily by long distance and CC by short distance connections while summarising the experiments we focus on the methodology specifically relevant to the results in the present paper A total of 38 healthy adult volunteers without prior experience in laparoscopic surgery participated in a trial to perform predetermined basic laparoscopic tasks on a laparoscopic simulator One participant could not enroll due to their hairstyle which made it impossible to fit the cap and record EEG data Technical problems prohibited the recording of data for four participants Two participants were excluded from the analysis due to issues with the time stamps routine Hence the final sample consisted of 31 participants (17 females 14 males) with a mean age of 21.61 ± 2.12 years All participants provided written informed consent prior to the study and received gift vouchers for their participation The study was approved by the Ethical Committee of the College of Science and Technology at the Nottingham Trent University and all methods were performed in accordance with the relevant guidelines and regulations Informed consent was obtained from all subjects and/or their legal guardian(s) for publication of identifying information/images in an online open-access publication The experiment was conducted in a training laboratory equipped with a Laparoscopic Surgery (LS) trainer box by Inovus Surgical Solutions (The Pyxus laparoscopic box trainer by Inovus Medical—43 cm × 33 cm × 31 cm) and a 21-inch monitor including the time spent to set up the system and devices and perform the tasks participants received instructions about the session via a training video followed by a hands-on introduction to help them become competent before commencing the training The LS trainer box was equipped with a centrally mounted camera and a light source with the entry ports of the instruments separated by 13.5 cm The training bases (14 cm × 10 cm) were placed in the LS trainer box and centred in the camera’s field of view Laparoscopic video was projected onto the monitor which was in the direct view of the participant To perform the primary tasks participants stood in front of the LS trainer box during the performance of Laparoscopic and secondary tasks (Fig. 1A) The laparoscopic tasks completion time was recorded and relocating rings from one rod to another using both surgical instruments Participants used their left-hand to transfer rings from rod A to B then passed each ring from B to C using the left-hand and right-hand and finally moved the rings from C to D using the right-hand only The Threading task consisted of passing a piece of string through holes labelled 1–7 on a Threading base Participants could use both surgical tools and both hands To simulate potential distractions or disruptions (e.g. auditory alarms) that may arise in a realistic setting an auditory task was added to the experiment Participants had to respond to a series of beeps as quickly as possible by pressing down on a foot pedal This was done by using the overall error rate calculated as the average of the rates of two types of error: (i) dropping a ring on the stack board and (ii) dropping it outside the board The raw EEG data underwent a series of pre-processing steps to remove non-brain signals and preserve the brain signal for further analysis Segments of data containing high-frequency likely originating from gross body movements during EEG recording were identified and deleted using a 1 s wide sliding window electrodes exhibiting kurtosis values exceeding 5 were considered invalid channels and removed from the data The signals were then band-pass filtered between 0.16 Hz and 40 Hz to reduce slow drifts and high-frequency artifacts and subsequently down sampled to 200 Hz to optimise computational and storage requirements To segregate components such as eye blinks and movements Independent Component Analysis (ICA) decomposition using the Extended-Infomax algorithm was applied to the filtered EEG data The ADJUST method was then used to automatically detect and remove independent components associated with artifacts and topographic maps of the independent components were visually inspected to further refine the artifact removal process We next determined the clustering coefficient (CC) and characteristic path length (λ) λ is the mean shortest path over all pairs of nodes It quantifies the capacity for information transfer across the network and low values of λ are associated with greater functional integration We investigated potential association of ISPC CC and λ with motor learning by determining the Pearson correlation of the relevant quantity The data and computer programs underlying the study are publicly accessible at https://doi.org/10.5281/zenodo.12810004 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Neuroanat. 89. https://doi.org/10.1016/j.jchemneu.2017.08.003 (2018) Early motor skill acquisition in healthy older adults: brain correlates of the learning process The importance of different learning stages for motor sequence learning after stroke Cross-validating models of continuous data from simulation and experiment by using linear regression and artificial neural networks Decoding human mental states by whole-head EEG + fNIRS during category fluency task performance Toward a proper estimation of phase–amplitude coupling in neural oscillations On the benefits of using surface Laplacian (current source density) methodology in electrophysiology Zero-lag long-range synchronization via Dynamical Relaying Dynamics of neural populations: Stability and synchrony When long-range zero-lag synchronization is feasible in cortical networks Functional connectivity of EEG is subject-specific Controlling the false discovery rate: a practical and powerful approach to multiple testing Download references This research was made possible in part by support from the Foundation for Neurofeedback and Neuromodulation Research (602–2023) provided to A.O All authors reviewed and edited the manuscript The authors declare no competing interests Download citation DOI: https://doi.org/10.1038/s41598-025-89261-0 Alzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million new cases every year. There is a need for relatively less costly and more objective methods of screening and early diagnosis. Functional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD. For a practical clinically relevant system, a smaller number of optimally placed channels are clearly preferable. In this study, we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations. Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study. These scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression. Volume 16 - 2022 | https://doi.org/10.3389/fnhum.2022.1061668 Introduction: Alzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment 50 million people live with dementia worldwide and there are nearly 10 million new cases every year There is a need for relatively less costly and more objective methods of screening and early diagnosis Methods: Functional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD For a practical clinically relevant system a smaller number of optimally placed channels are clearly preferable we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study Results: We have shown that resting-state fNIRS recordings from a small number of prefrontal locations provide a promising methodology for detecting AD and monitoring its progression A high-density continuous-wave fNIRS system was first used to verify the relatively lower hemodynamic activity in the prefrontal cortical areas observed in patients with AD By using the episode averaged standard deviation of the oxyhemoglobin concentration changes as features that were fed into a Support Vector Machine; we then showed that the accuracy of subsets of optical channels in predicting the presence and severity of AD was significantly above chance The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score with ≤5 channels Discussion: These scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression Alzheimer's disease (AD) is the most common cause of dementia in the elderly which impacts 50 million people worldwide (Bonilauri et al., 2020) Functional abnormalities in AD likely start long before its clinical symptoms which primarily affect executive and visuospatial abilities Practical fNIRS systems are a promising solution for the early detection of AD because they can make quick and affordable measurements without requiring expert operators methods based on functional measurements do not rely on patients' ability to respond to questions or follow test instructions Medication and other therapies administered from early stages can retard disease progression and improve patients' quality of life the diagnosis of AD relies heavily on clinical examination and tests administered by expert clinicians there is a need for relatively less costly and more objective methods of screening and early diagnosis Resting-state recordings were collected from 21 patients and 18 healthy controls who also completed standard neuropsychological tests We found reductions in oxygenated hemoglobin in patients with AD consistent with previous studies we assigned univariate priority scores to the optical channels based on their extent of association with the disease state of the participants Then we used subsets of channels selected from the highest priority channels to predict the participants' disease state from the measured signal we used Boston Naming Test and Verbal Memory Total scores as proxies for AD severity The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score These were obtained with ≤5 channels on the forehead Our results provide evidence that fNIRS is a viable technology for accurately and conveniently detecting and monitoring AD as well as investigating the underlying mechanisms of disease progression Among the patients diagnosed with clinical AD had Clinical Dementia Rating Scale (CDR) scores of 1 or 2 used acetylcholinesterase inhibitors and memantine and were capable of leading their daily lives independently were included in the study Exclusion criteria were a history of alcohol/substance abuse mental illnesses including schizophrenia and delirium Patients were examined during routine therapy where the medical treatment was not modified during the study period and no psychiatric or neurological disorder history was included in the study The Research Ethics Board of Medipol University approved this study (10840098-604.01.01-E.1925) and it was performed in agreement with the Declaration of Helsinki All participants signed informed consent and could withdraw from the study at any time and Neuropsychiatric Inventory were also used for neuropsychological evaluation The included subjects and their companions were informed briefly about the whole procedure They were given an informed consent form to read carefully and sign It was made sure that they understood that they could stop and leave the research at any time they wished with a guarantee of not facing any kind of consequences After the researchers decided the given information was understood and informed consent was obtained the subjects were asked to sit on a chair and the fNIRS device was set on the head and optodes were calibrated while the subject was asked to sit silently and in a relaxed position sound or any other distracting stimuli were turned off When the subject confirmed that they were ready for the experiment Following the 30 s of the beginning session to check the optodes were working properly as set before the test the 5-min recording of the resting state was started without any warning the recording signal was briefly checked again and was saved in the following 15 s and the subject was informed that the test was finished Optical imaging data were collected using a high-density fNIRS device (NIRSIT Korea) with 24-light sources at 780 and 850 nm and 32 detectors The channels overlap with parts of the dorsolateral and ventrolateral prefrontal and the upper part of the orbitofrontal and medial PFC Subject averaged prefrontal cortex activations (color bar units on the right in mM) interpolated from channels with 3.35 cm separations Open gray circles indicate the location of the fNIRS channels We repeated the calculations in this study by using only deoxyhemoglobin or by including both oxy- and deoxyhemoglobin concentration changes these did not improve classifier performance relative to using oxyhemoglobin alone deoxyhemoglobin alone resulted in slightly lower accuracies overall Since this is a proof-of-concept investigation we have limited this study to oxyhemoglobin concentration changes only we use the term activation to refer to the standard deviation of the oxyhemoglobin changes We studied the ability of the PFC activations to discriminate between patients and healthy controls and between different subgroups of patient participants we generated features for a machine learning approach by averaging the activation in each channel across the entire recording session of a participant a feature matrix contained rows consisting of individual subjects and columns consisting of channels and its entries were the session-averaged PFC activations The matrix contained a maximum of 48 columns (channels) Because each subject's data occurred in only one row of the feature matrix the training and test partitions never contained data from the same subject The corresponding binary label vector indicated (1) whether the participant was a patient or healthy control or (2) whether the patient participant obtained a high or low score on a neuropsychological test where the high–low cut-off was taken as the median of all patients we assessed multiple filter-type algorithms for rank ordering our features before feeding them into a classifier: filters based on (1) Pearson correlation between a feature and label vector; (2) p-values obtained from chi-squared tests; and (3) searching for sets of features maximally associated with the labels and minimally associated with each other The chi-squared method was selected due to its robustness and the resulting classifier accuracies the features were first prioritized by using chi-squared tests that determined whether each feature was independent of the label vector by calculating a p-value The priority score of a feature was calculated as the natural logarithm of the reciprocal of its p-value The prioritized features were then used to predict the labels of a subset of the participants using a Support Vector Machine or Linear Discriminant Analysis trained on the remaining subset of the participants The results from the Support Vector Machine classifier were overall more accurate hence we only report them in this article The performance of the prediction was characterized using its sensitivity and specificity defined in the following way sensitivity was calculated as the ability to correctly identify a patient and specificity was calculated as the ability to correctly identify a healthy control considering a positive prediction as the prediction that the subject is a patient the sensitivity of the method was defined as the number of true positives divided by the sum of true positives and false negatives The specificity was the number of true negatives divided by the sum of true negatives and false positives the sensitivity was calculated as the ability to correctly identify a high-scoring patient and specificity was calculated as the ability to correctly identify a low-scoring patient Each feature was standardized by centering and scaling with the mean and standard deviation of the corresponding column of the feature matrix The linear kernel was selected for Support Vector Machine and its scale was computed by Matlab using a heuristic procedure We used a fixed random number seed for the reproducibility of the results Optimization of the box constraint and kernel scale parameters was tried to discriminate patients from normal volunteers both based on Matlab's grid search algorithms in the range [0.001 This significantly increased computing times without a noticeable improvement in performance; thus we report only results based on Support Vector Machine without hyperparameter optimization and signrank were used in the above calculations The demographical and neuropsychological test scores of the patient group with Alzheimer's disease (AD) Hemodynamic feature priority scores calculated for purposes of feature selection (A) Univariate feature priority scores ranked in descending order calculated using chi-squared tests (B) The distribution of scores over the prefrontal cortex The accuracy (A) sensitivity and (B) specificity of discriminating patients (N = 21) from normal subjects (N = 18) using the Support Vector Machine and a limited number (x-axis) of the top-ranked hemodynamic features The accuracy is found from 5-fold cross-validation repeated 20 times with different randomly selected partitions The black boxes indicate the accuracy and the green boxes indicate the corresponding null distribution calculated by randomly permuting the labels Statistical significance calculated from the Kolmogorov–Smirnov test is indicated using an asterisk (*p < 0.05 The central mark in a box indicates the median and the bottom and top edges of the box are the 25th and 75th percentiles while the whiskers extend to the most extreme data points not considered outliers Discrimination of high-scoring patients (N = 8) from low-scoring patients (N = 7) in the Boston Naming Test using the Support Vector Machine and a limited number (x-axis in D and E) of the top-ranked hemodynamic features (A) Hemodynamic feature priority scores calculated using chi-squared tests (B) Topographic distribution of feature scores (C) Histogram of Boston Naming Test scores of patients The vertical dotted red line shows the location of the median score used to distinguish high-scoring patients from low-scoring patients (D) Sensitivity of discriminating high-scoring patients (E) Specificity (*p < 0.05 Discrimination of high-scoring patients (N = 8) from low-scoring patients (N = 9) in the Verbal Memory Total Score Recall/15 using the Support Vector Machine and a limited number of the top-ranked hemodynamic features The dotted red line shows the median score used to distinguish high-scoring patients from low-scoring patients The sensitivity and specificity of discriminating patients with AD from healthy controls specificity 0.72) could be achieved with only five features The sensitivity and specificity of discriminating high-scoring patients from low-scoring patients in the Boston Naming Test this is the first study in peer-reviewed literature to use machine learning to quantify the AD-related sensitivity and specificity of the resting-state fNIRS signals from the PFC Resting-state whole-head fNIRS data from patients with AD dementia and amnesic MCI and healthy controls were used to show that the temporal variability of functional connectivity maps was able to distinguish aMCI [area under the curve (AUC 82.5%)] or AD (AUC 86.4%) from the healthy controls (Niu et al., 2019). Further descriptions of related studies can be found in recent extensive reviews (e.g., Bonilauri et al., 2020) Such close scores in different groups may have reduced the accuracy of discrimination patients with scores close to the median could not be removed from this calculation since this would have reduced the already small size of the data set we could have used other classification schemes [e.g. artificial neural network (ANN)] to predict the continuous range of scores ANNs require a greater number of training examples than we had in our patient population By definition, sensitivity is reduced by the occurrence of a higher number of false negatives in the patient group, while specificity is reduced by a higher number of false positives in the healthy control group. Thus, the generally higher sensitivity observed in Figures 3, 4 indicated that PFC hemodynamics was a more robust marker among the patients than it was among healthy controls This could be due to the greater variability of the signals in the healthy group The chance distribution of accuracy is shown by the green boxes in Figures 3, 4 and indicates the median and range of values obtained by repeating the 5-fold cross-validation 10 times with different partitions into training/test sets and randomly reshuffled labels yielded values that are represented by the green boxes the chance accuracies in the Figures fluctuate around 50% they remained close to 50% only if there were a sufficient number of patient responses in each of the high-/low-scoring groups (as was the case with the Boston Naming Test and Verbal Memory Total Score Recall); we used this as a criterion for excluding the other types of tests from this study Figures 3A,B, 4D,E suggest that the accuracy initially increased with an increasing number of optical channels (features) and then remained near a maximum or slightly declined The initial increase in accuracy was clearly due to the fact that additional features brought new information useful for discrimination may have been due to new features adding little or no useful information but instead introducing noise into the system that obscured the differences between groups fNIRS appears to be a good choice for our study with a reasonable trade-off The limitations of our study and possible mitigations are as follows: 1. Only two types of tests were available with a sufficient number of patient responses. A greater number of types of neuropsychological test scores (e.g., Viola et al., 2013) would improve the validity of our findings 2. We only collected PFC data, however, the measurement from additional areas may increase accuracy as there are differences between patients and healthy controls in parietal activation (Li R. et al., 2018) This will become more viable as better-designed headsets and optodes that can conveniently record through hair become available 3. We only used resting-state measurements, however, data collected during cognitive or memory task performance may increase accuracy as there are clear task-evoked differences between patients and healthy controls (Arai et al., 2006; Yeung et al., 2016) These limitations offer opportunities for further study Our results suggest that with further improvements in instrumentation and possibly in conjunction with concurrent EEG and neuropsychological tests a small number of fNIRS channels located in the PFC can be a valuable screening tool for diagnosing and monitoring AD The original contributions presented in this study are included in the article/supplementary material further inquiries can be directed to the corresponding author The studies involving human participants were reviewed and approved by the Research Ethics Board of the Medipol University (10840098-604.01.01-E.1925) The patients/participants provided their written informed consent to participate in this study and writing—review and editing: HK and AO All authors contributed to the article and approved the submitted version Canberk Cengiz for supporting data collection The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher Measuring mental workload with EEG+fNIRS PubMed Abstract | CrossRef Full Text | Google Scholar A quantitative near-infrared spectroscopy study: a decrease in cerebral hemoglobin oxygenation in Alzheimer's disease and mild cognitive impairment Frontal activity during a verbal emotional working memory task in patients with Alzheimer's disease: a functional near-infrared spectroscopy 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Hanoglu L and Omurtag A (2022) Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy Received: 04 October 2022; Accepted: 01 November 2022; Published: 28 November 2022 Copyright © 2022 Keles, Karakulak, Hanoglu and Omurtag. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited *Correspondence: Hasan Onur Keles, aG9rZWxlc0BhbmthcmEuZWR1LnRy var(--popover-size));border-radius:var(--chakra-radii-l3);--popover-z-index:var(--chakra-z-index-popover);z-index:calc(var(--popover-z-index) + var(--layer-index 0));outline:0;transform-origin:var(--transform-origin);max-height:var(--available-height);--popover-padding:var(--chakra-spacing-5);}.css-1v5f30s:is([open] [data-state=open]){transform-origin:var(--transform-origin);-webkit-animation-name:scale-in,fade-in;animation-name:scale-in,fade-in;-webkit-animation-duration:var(--chakra-durations-fast);animation-duration:var(--chakra-durations-fast);}.css-1v5f30s:is([closed] Congratulations to the following Girls U-16 athletes selected for the 2024 AAU Junior Olympic Games! [data-focus]){outline-width:var(--focus-ring-width 2px);outline-offset:var(--focus-ring-offset solid);outline-color:var(--focus-ring-color);outline:none;}.css-puhhl:is(:focus-visible [data-focus-visible]){box-shadow:none;outline-width:3px;outline-style:solid;outline-color:var(--semantics-focus-light);outline-offset:3px;}.css-puhhl:visited{color:var(--components-rte-light-link-color);}.css-puhhl:visited.css-puhhl:visited:is(:active [data-state=open]){color:var(--components-rte-light-link-color-active);}@media (hover: hover){.css-puhhl:visited:is(:hover [data-disabled]){color:var(--components-rte-light-link-color-hover);}}.css-puhhl.css-puhhl:is(:active [data-state=open]){color:var(--components-rte-light-link-color-active);}@media (hover: hover){.css-puhhl:is(:hover white);}}© 2025 Copyright USA Field Hockey - All Rights Reserved hood during May 1997 commencement ceremonies As a student at Missouri University of Science and Technology Youngblood dreamed of breaking down barriers for African Americans “I’ve always seen myself as being out in front a leader,” she said in a 1997 interview with Missouri S&T Magazine “I’ve always seen myself as breaking down walls to let more people through.” In 1992, she became the first African American woman to graduate from the mining engineering program at Missouri S&T she became the first African American woman to earn a Ph.D Dr. Youngblood, of Moon Township, Pennsylvania, died recently at age 46. She was an associate professor of engineering at Robert Morris University in Pittsburgh According to the Fall 1997 issue of Missouri S&T Magazine Illinois in low-income housing with her mother she enrolled at Missouri S&T on a partial scholarship she received her bachelor of science degree in mining engineering becoming the first African American woman in the university’s history to earn a degree from that program She later earned a master’s degree in engineering management from Missouri S&T and in 1997 in engineering management and becoming the first African American woman to receive a Ph.D She credited her dissertation advisor, Dr. Yildirim “Bill” Omurtag, former chair of engineering management at Missouri S&T and founding dean of the School of Engineering Mathematics and Science at Robert Morris University for supporting her during her doctoral studies advisor and friend,” she said in the 1997 interview “He can see a raw piece of coal and know that the end product will be a diamond.” Visitation for Dr. Youngblood will be held from 6-8 p.m. Sunday, March 29, at Gateway Area Bible Fellowship Apostolic Church, 85 Water Street, Cahokia, Illinois. Funeral Services will be held at noon Monday, March 30, at the church, with interment services immediately following at Holy Cross Cemetery in Fairview Heights, Illinois. Arrangements are under the direction of L. King Funeral Chapels of Belleville On March 25, 2015. Posted in Alumni, Featured, People and website in this browser for the next time I comment Δdocument.getElementById( "ak_js_1" ).setAttribute( "value" The dates displayed for an article provide information on when various publication milestones were reached at the journal that has published the article activities on preceding journals at which the article was previously under consideration are not shown (for instance submission All content on this site: Copyright © 2025 Elsevier B.V. Bulgaria’s Minister of Tourism Miroslav Borshosh and Zurab Pololikashvili Secretary-General of the World Tourism Organization (UN Tourism) have officially signed the agreement for Bulgaria to host the 9th Global Conference on Wine Tourism,. The Mini Bulgaria Park is an unusual place for a tourist tour spiritual culture and natural landmarks of Bulgaria meet Gorna Oryahovitsa often remains undeservedly hidden from the eyes of tourists even though it is only about 10 km away from Bulgaria's old capital which lies at the foot of the Balkans on the banks of the. english@bnr.bg People who can no longer communicate through speech or eye movement can use the power of thought to indicate "yes" or "no" thanks to a brainwave reader developed by Nottingham Trent University (NTU) an expert in intelligent engineering systems wanted to support charities which help people with advanced motor neuron disease (MND) and Completely Locked-in Syndrome after his brother-in-law The research has led to the development of a brainwave reader which is made affordable by using off-the-shelf parts and a novel artificial intelligence (AI) algorithm developed by the research team The technology centers on interpreting people's brain signals when they are invited to envisage contrasting imaginary situations to indicate "yes" or "no" answers patients can be asked to imagine the joy of kicking a football to indicate "yes," but be asked to imagine being trapped in a room with an elephant to mean "no." which produce different analog signals in the brain are detected over five seconds by three electroencephalogram (EEG) sensors attached to the patient's head These analog signals are then magnified and converted to digital signals before being interpreted by the AI and relayed to a display screen to show the answer "This technology can allow people who are in the late stages of MND to communicate critical information when they are unable to even blink," said Professor Al-Habaibeh "It could be used for a variety of purposes such as to communicate what a patient's wishes may be "Our aim is to make this technology affordable for organizations such as charities so that it can be used more widely by families or hospices "By allowing better communication in the later stages of MND, it will also allow medical professionals to treat patients better and take key decisions which are in line with the patient's wishes we are confident that this approach could allow a patient to control a cursor on a computer screen potentially with just four imaginations for up "It may also be possible for this technology to be applied to mental health outputs The research found that the technology takes around ten attempts to learn an individual's brain signal pattern and that the individual success rate is around 90% if the patient is able to focus without any distraction The cost of hardware for each reader is estimated at about £300 and the research is being published under a creative commons license to allow organizations to use it freely without copyright Research on the technology has previously been published by the Neuroscience Informatics journal and a working prototype has now been created as the culmination of the project Researcher Sharmila Majumdar, a Ph.D. candidate who worked on the project, said, "This technology has the potential to help dying people communicate when they are in an incredibly vulnerable state "We are proud to have carried out this research to support those with MND and for it to be published freely in the interests of helping others." "Existing medical EEG devices tend to be expensive so I think the capability to decipher people's thoughts using only a few sensors will continue to increase in value and find more applications." A brainwave reader developed using affordable off-the-shelf parts and a novel AI algorithm enables individuals with advanced motor neuron disease to communicate through thought patients can indicate "yes" or "no," with signals detected by EEG sensors and interpreted by AI achieves a 90% success rate after ten attempts and is freely available under a creative commons license Please select the most appropriate category to facilitate processing of your request Thank you for taking time to provide your feedback to the editors we do not guarantee individual replies due to the high volume of messages Daily science news on research developments and the latest scientific innovations The most comprehensive sci-tech news coverage on the web Metrics details Approximately 5% of emergency department (ED) patients with altered mental status (AMS) have non-convulsive seizures (NCS) Patients with NCS should be diagnosed with EEG as soon as possible to initiate antiepileptic treatment Since ED physicians encounter such patients first in the ED they should be familiar with general EEG principles as well as the EEG patterns of NCS/NCSE We evaluated the utility of a brief training module in enhancing the ED physicians’ ability to identify seizures on EEG This was a randomized controlled trial conducted in three academic institutions A slide presentation was developed describing the basic principles of EEG including EEG recording techniques followed by characteristics of normal and abnormal patterns the goal of which was to familiarize the participants with EEG seizure patterns We enrolled board-certified emergency medicine physicians into the trial Subjects were randomized to control or intervention groups Participants allocated to the intervention group received a self-learning training module and were asked to take a quiz of EEG snapshots after reviewing the presentation while the control group took the quiz without the training A total of 30 emergency physicians were enrolled (10 per site Participants were 52% male with median years of practice of 9.5 years (3 The percentage of correct answers in the intervention group (65% 63% and 75%) was significantly different (p = 0.002) from that of control group (50% A brief self-learning training module improved the ability of emergency physicians in identifying EEG seizure patterns This results in delayed initiation of appropriate treatment and worse neurological outcomes it is imperative to diagnose NCS/NCSE early and accurately with electroencephalogram (EEG) and start treatment as soon as possible Once the EEG is being acquired at the bedside the non-expert physician (ED physician) needs to recognize electrographic seizures that require rapid management especially when access to a trained epileptologist is not possible or delayed The objective of this study was to test the utility of a brief training module (a self-learning PowerPoint presentation) to improve the ability of the ED physician to identify electrographic seizures on EEG This study is a pilot study with a small number of subjects which will help determine if the EEG training can be expanded and implemented readily This pilot randomized controlled trial was conducted at the departments of emergency medicine of three academic medical centers All three institutions are academic urban teaching hospitals with emergency medicine residencies Institutional review boards approved the study in each institution Informed consent was obtained from all participants prior to enrollment The trial enrolled board-certified emergency medicine faculty Physicians with previous EEG training were excluded Subjects were recruited via email through faculty directories in each institution The first 10 volunteers in each institution (10 subjects per site 30 subjects in total) were randomized to control or intervention groups using a random number generating software Participants were randomized to the intervention group or the control group Physicians allocated to the intervention group received a self-learning PowerPoint presentation (training module) and were asked to take a quiz after reviewing the PowerPoint presentation The control group was asked to take the quiz without reviewing the training slides Two months after the initial date of their initial quiz the quiz was re-administered without any training slides for either group to test their retention A slide presentation describing the basic principles of EEG including EEG recording techniques and views followed by characteristics of normal and abnormal patterns was developed with assistance of epileptologists and experts in educational research The goal of the presentation was to familiarize the participants with EEG presentations of seizure EEG snapshot showing a right temporal focal electrographic seizure EEG snapshot showing focal slowing over the left temporal region The primary outcome was the percentage of correct answers to the quiz (corresponding to correct interpretation of each EEG snapshot) initially and after 2 months (test of retention) Method of determination of outcomes: Overall scores and percentages of correct answers were calculated by administering the quiz to all participants The total number of correct answers for each participant was counted and divided by 40 (maximum score) to calculate the correct score percentage for each subject Data are reported as medians and quartiles for continuous variables and percentages with quartiles for proportions The outcome (percentages of correct answers) was calculated and compared between the two groups using Mann-Whitney U test We planned a sub-group analysis to compare the responses to seizure versus no seizure questions only between the groups to specifically examine the performance of physicians to identify seizures on EEG A total of 30 emergency physicians were enrolled (10 per site, 30 in total, 15 controls and 15 interventions). Participants were 63% male with median years of practice of 9 years (quartiles 3, 14). Groups were similar in regards to years of practice and gender (Table 1) Comparison of percentages of correct answers between control and intervention groups using Box-Whisker plot In the subgroup analysis evaluating the question of seizure versus no seizure the results were similar to the overall analysis There was a significant difference between the percentages of correct answers identifying seizures between the intervention group (63% this difference was not significant at the time of the follow-up quiz between the intervention group (55% while the final confirmatory study and report is provided by the radiologist later physicians administer sedatives and anticonvulsants to patients with suspected NCS based on clinical suspicion Training ED physicians to recognize EEG seizures will help them identify and treat NCS appropriately This will also reduce the risk of administration of anticonvulsants in patients who are not suffering from NCS Our study evaluated the efficacy of a PowerPoint EEG training module created by a collaboration of an epileptologist and experts in education research to improve recognition of electrographic seizures by ED physicians at the bedside The purpose of this brief training module was to provide very basic practical clinically relevant knowledge to the physicians focusing on identifying normal versus abnormal EEG It was important to include normal patterns besides seizures in the module as some of these could be misinterpreted as abnormal patterns by an untrained individual the ED physicians clearly benefited from the training module as they performed significantly better than the group who were not provided the module Follow-up assessment in 2 months showed that this group of ED physicians retained that knowledge over time the assessment tool scores increased from a mean of 12.00 ± 1.9 before the educational module to 19.7 ± 2.0 (p < 0.001) no guidelines exist regarding the use of quantitative EEGs and trends There are several limitations in this study No sample size analysis was performed as this was a pilot trial 12 months) to evaluate retention of study material The participants only interpreted a one-page snapshot of the EEG which is not representative of the bedside EEG that is recorded for an average of 30 min and can provide much better visualization of patterns and rhythms Our study was a pilot study that provides preliminary data The study module needs further refining and testing before it can be applied to clinical practice Determining patient impacts of risks and benefits of treatment of ED patients with NCS is not within the scope of this pilot study our pilot study may justify conducting a larger study to evaluate the safety and efficacy of such a training module in real-time management of patients suspected of NCS This pilot study demonstrates that providing a brief EEG training module can help emergency department (non-neurology) physicians improve the identification of seizures on bedside EEG Altered mental status: evaluation and etiology in the ED Prevalence of non-convulsive seizures and other EEG abnormalities in ED patients with altered mental status Assessment of acute morbidity and mortality in nonconvulsive status epilepticus Current practice in administration and clinical criteria of emergent EEG Diagnostic accuracy of a novel emergency electroencephalography device (microEEG) in identifying non-convulsive seizures and other EEG abnormalities in the emergency department patients with altered mental status Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support Assessment of emergency physician-performed ultrasound in evaluating nonspecific abdominal pain The effectiveness of a simple novel approach on electroencephalograph instruction for anesthesiology residents Evaluating the long-term retention of a multidisciplinary electroencephalography instructional model The effectiveness of an interdisciplinary approach to EEG instruction for residents(r) Virtual training simulator – designer of EEG signals for tutoring students and doctors to methods of quantitative EEG analysis (qEEG) Non-expert use of quantitative EEG displays for seizure identification in the adult neuro-intensive care unit Trend figures assist with untrained emergency electroencephalogram interpretation Download references The authors would like to thank Paulina Sergot Texas) for their assistance in developing the training module and PowerPoint presentation There are no funding sources used for this study The datasets used and analyzed during the current study are available from the corresponding author on reasonable request University of California at Davis Health System GC contributed to the study concept and design created the PowerPoint training module and EEG quiz and revised and submitted the final manuscript KY contributed to the study concept and design collected and managed the data using REDCap electronic data capture tools and revised and approved the final manuscript DN contributed to the study concept and design and revised and approved the final manuscript AO contributed to the study concept and design revised and approved the PowerPoint training module SZ contributed to the study concept and design All authors read and approved the final manuscript This study was approved by the institutional review boards of the three participating academic teaching hospitals Each subject (emergency medicine physician) signed a consent form to participate in the study Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) provided you give appropriate credit to the original author(s) and the source provide a link to the Creative Commons license Download citation DOI: https://doi.org/10.1186/s12245-019-0228-9 a shareable link is not currently available for this article Metrics details Laparoscopic surgery can be exhausting and frustrating and the cognitive load experienced by surgeons may have a major impact on patient safety as well as healthcare economics As cognitive load decreases with increasing proficiency its robust assessment through physiological data can help to develop more effective training and certification procedures in this area We measured data from 31 novices during laparoscopic exercises to extract features based on cardiac and ocular variables These were compared with traditional behavioural and subjective measures in a dual-task setting We found significant correlations between the features and the traditional measures and completion time were well predicted by the physiology features Reaction times to randomly timed auditory stimuli were correlated with the mean of the heart rate (\(r = - 0.29\)) and heart rate variability (\(r = 0.4\)) Completion times were correlated with the physiologically predicted values with a correlation coefficient of 0.84 We found that the multi-modal set of physiology features was a better predictor than any individual feature and artificial neural networks performed better than linear regression The physiological correlates studied in this paper could help develop standardised and more easily regulated frameworks for training and certification These considerations suggest that performance based metrics alone may not suffice to reveal the trainees' actual state of readiness These traditional measures face some limitations as they may influence or interrupt what they are trying to monitor there is limited research on the extent of the agreement among these distinct measures of effort and no studies to our knowledge in the context of LS training varying levels of effort were generated by differences in subject aptitude and task difficulty as well as by learning and time on task effects We believe physiological responses which track their effects are more direct than behavioural and verbal ones a better understanding of the physiological expression of skill is of potential value for improving training and assessment in LS Experience and performance metrics grouped by type of experimental episode (three boxes on the left of each subplot) and by task type, namely Ring Transfer, Ring Transfer Repeated, Threading and Threading Repeated (four boxes on the right). (a) NASA-TLX Average score. (b) NASA-TLX Effort score. (c) Reaction time. (d) Non-response rate. (e) Task completion time. (f) The rates of errors during the Ring Transfer task. (*p < 0.05). Values of the individual predictor features and targets. Linear fits to the data are shown. The Pearson correlation, \(r\), and the p-value of linear regression (black line) are shown. The quadratic fit (thick grey curve) and its p-value \(p_{2}\) are shown only if \(p_{2} < 0.05\). Predictions of the artificial neural network plotted against the actual values (x-axis) for selected cases. (a) NASA-TLX Average score with \(R_{CV} = 0.60\). (b) Completion Time with \(R_{CV} = 0.84\). The 45-degree diagonal line corresponds to perfect prediction. Heart rate (a) and heart rate variability (b) extracted from NIRS signals for the experimental episodes, and smoothed by a 10 s moving window. The black curves represent subject average and the shaded regions are the standard deviation of subject variability. For the task episodes, 40 s segments at the beginning and end are shown. Relationships among the heart rate (HR) and heart rate variability (HRV) for Rest and Task (a) HR and HRV in resting (black) and task performance (red) Black and red dots respectively represent individual subjects in the resting and task blocks The linear fits to the data are shown as the black and red straight lines The Pearson correlations are \(r = - 0.32\)(resting) and \(r = - 0.23\) (task) The insets at the bottom and on the right illustrate the marginal probability distributions (b) Resting HR and the task related change in HR relative to resting (\(r = 0.11\)) (c) Resting HRV and the task related change in HRV relative to resting (\(r = - 0.96\)) Performance scores (not shown) also contained changes that were statistically significant There did not appear to be a significant difference between the experiences of the Ring Transfer and Threading tasks The non-response rate was a significantly greater for Ring Transfer than for the Threading task The non-response rate was the rate at which a subject failed to respond to the stimulus before the next stimulus onset Error type 10 was dropping a ring on the ring stack board; type 20 was dropping it outside the board; and type 30 was dropping it outside the trainer box Outliers were defined as points greater than \(q_{3} + w(q_{3} - q_{1} )\) or less than \(q_{1} + w(q_{3} - q_{1} )\) where \(q_{k}\) is the \(k^{th}\) quartile and \(w = 2\) for assessing the performance of the linear regression (LR) and artificial neural network (ANN) Regarding the individual features in Table 1 the Pearson correlations show that HR's mean and standard deviation tended to increase with the experienced difficulty as measured by the NASA-TLX score Without reaching statistical significance both were individually positively correlated with it Mean HR was negatively correlated with the Reaction Time and Non-response Rate Higher HR generally implied quicker and more accurate response in the secondary task and fewer errors in the primary task HRV appeared to be an even better predictor The minimum value of HRV was significantly negatively correlated with the NASA-TLX score Many HRV features were significantly positively correlated with the Reaction Time This indicated that higher HRV (which is associated with respiratory modulation of HR and relaxation) degraded performance was significantly negatively correlated with the Reaction Time Those predictors do not have high degree of linear dependence on their target that the value the Pearson coefficient is distinct from its statistical significance (The latter is indicated by an asterisk in the table.) We used linear correlation only as a baseline to compare with the performance of groups of physiological metrics that had predictive utility via machine learning (the right column of the table) With regard to the LR and ANN which used all available features (the last two columns on the right of Table 1) the results indicated that the full set of features collectively outperformed any individual feature in predicting subject experience and performance the table shows that \(R_{adj}\) and \(R_{CV}\) were greater than the absolute values of the individual Pearson correlations except in predicting the Error Rate which was the unique case with \(R_{CV} < R_{adj}\) Non-response Rate and Completion Time on HR are described the same targets are shown plotted against HRV since the NASA-TLX score was traditionally used as a measure of stress (as HR and HRV) we also show in subplots g-i the same targets plotted against the NASA-TLX scores In addition to the linear regression shown as the thin black line in each subplot we also computed a best fit by including the square of the predictor Only if the fit was statistically significant we included this quadratic regression as a thick grey curve in the plot When the quadratic regression was significant (subplots b c and i) the best fits were U-shaped curves suggesting that there was a performance optimum while the NASA-TLX score (A) was the second best For the task episodes only the beginning and end segments are shown since the task duration was different for each subject The figure suggests that during task performance the HR and HRV reach values that are anti-correlated and potentially contain comparable amounts of information about effort the intra-episode time courses reveals a significant difference between these two measures While the HR climbs gradually up to its maximum level within the first minute or so the HRV attains its task-related minimum without any visible delay This indicates that only the HRV of those subjects that have high resting HRV are affected by task performance This paper showed that the cognitive load on novice trainees during LS training has physiological correlates We showed that physiological indicators of cognitive load predict experience and performance we calculated from N = 31 subjects the heart rate We measured their subjective experience by the NASA-TLX reports and their performance in a dual-task setting We used regression and artificial neural networks to discover relationships among the variables Our hypothesis was that the residual capacity revealed traditionally by reports and other measures such as reaction time would be reflected in their physiology The motivation was to develop new metrics to guide training so that surgeons train not only to become good at their primary technical tasks but to have sufficient capacity for planning and for unexpected events HRV and BR as well as NASA-TLX and dual-task performance have been used in the past to investigate workload in surgery we are not aware of other studies which brought all of these variables and machine learning together within the experimental setting of laparoscopy training Given that the stress-performance curves may differ among surgeons objectively evaluating them may improve training as well as optimise intra-operative conditions for performance The physiological metrics we have found correlated well with subjective and dual-task measures We believe physiological correlates may contribute to surgery training not necessarily by eliminating other metrics but by providing additional tools; especially if they are encapsulated in wearable systems We have only considered cardiac and blink variables but the number of relevant physiological metrics could be vast given the complexity of the physiological processes Although insight into such underlying mechanisms is still in progress the metrics can still be used for prediction with the help of machine learning our results do not depend on the specific modalities (fNIRS and EEG) which were used to extract this information Their detection could be based on different principles blinks can be extracted unobtrusively from video We were also driven by the view that wearable sensors stand to play an important role in conveniently tracking the physiological correlates of skill However future research needs to focus more on the effects of the sensors themselves on stress as well as on the normal range of physiological responses These included: (i) Using ANNs without optimisation of parameters; (ii) Not implementing subject-specific calibration; (iii) Not controlling for levels of motivation or psychomotor aptitude among the novice subjects although these variables may have accounted for the distribution in our results; (iv) Recruiting only novice subjects while different known levels of expertise among the subjects would have provided additional insights; (v) Lack of training interventions accompanied by longitudinal tracking We hope and expect that these limitations will provide opportunities for further study Thirty-eight healthy adult volunteers without any prior experience in laparoscopic surgery participated in one main trial to perform pre-determined basic laparoscopic tasks on a laparoscopic simulator We excluded seven participants; one could not enrol in the experiment due to participant’s hairstyle that made it impossible to fit the cap and record EEG; for four participants technical problems prohibited recording; two were excluded from the main analysis due to a problem with the time stamps routine complete data sets from 31 participants were used in this study (17 females and 21 males All participants provided their written informed consent prior to the study commencing and received gift vouchers for participating after the experiment was completed Participants had normal or corrected to-normal vision The Ethical Committee of the College of Science and Technology at the Nottingham Trent University approved the study and all research was performed in accordance with relevant guidelines The experiment was conducted in a training lab that consists of a LS trainer box by Inovus Surgical Solutions (The Pyxus laparoscopic box trainer by Inovus Medical—43 cm × 33 cm × 31 cm) and a 21-inch monitor Each trial took about an hour including total time spent by participants to perform the tasks and setting up the system and devices participants received instructions about the session via a training video followed by a few minutes of hands-on introduction for orientation with the surgical equipment (Maryland Grasper and Needle Holder UK) until they became competent before commencing on the training The LS trainer box was equipped with a centrally mounted camera and a light source with entry ports of the instruments separated by 13.5 cm The training bases (14 cm × 10 cm) were placed in the LS trainer box and centred in the camera’s field of view Laparoscopic video was projected onto the monitor that was in the direct view of the participant The experiment started by performing the secondary task alone for two minutes, which was considered as a baseline (Fig. 1) participants performed primary and secondary tasks simultaneously The primary tasks included two Fundamentals of Laparoscopic Surgery tasks in alternating sequence (Task1 and Task 2) followed by repetition of the first task (Task 1 Repeated) Fingertip blood samples were taken at baseline and immediately after completion of all three LS tasks to determine the serum cortisol and brain-derived neurotropic factor (BDNF) concentrations participants filled in the NASA-TLX questionnaire for each LS task A rest period of 2 min was taken after the initial secondary task performed alone and after each blood sample Blood sample analysis is not included in this paper Participants were instructed to stand in front of the LS trainer box during the performance of Laparoscopic and secondary tasks with a maximum time on task of 15 min after which the participants were told to stop lifting and relocating rings from one rod to another using both surgical instruments and was performed on a ring stack base (Inovus Medical top right-hand and bottom right-hand corners on the ring stack base respectively Four rings were initially put over rod A at the beginning of the trial The procedure includes picking up a ring from rod A and placing it onto rod B with the left-hand only After transferring all four rings to rod B participants used their left-hand only to grasp and lift up each ring pass it to the right-hand and place it on rod C The procedure was completed by moving the rings individually from rod C to D using the right-hand only If any rings were dropped during the task completion they were placed back on the rod they were taken from by an experimenter and participants were allowed to continue the trial The Threading task consisted of passing a piece of string through the holes in a pre-determined order The holes were labelled 1–7 in a zigzag pattern on the Threading base (Supplementary Fig Participants could use both surgical tools no restriction was made on the use of right Timing began upon first grasp of the string that was initially placed on the right-hand side of the Treading base In order to simulate the potential distractions or disruptions (e.g provided an additional measure of the cognitive load on the participants in terms of reaction time and non-response rate The beeps were generated with random frequencies (ranged from 1,000 to 2000 Hz) intervals (ranged from 3,000 to 10,000 Hz) and durations (ranged from 500 to 1,000 ms) These were combined with EEG electrodes into a single head-cap The raw EEG and fNIRS data were analysed offline separately EEG was used only for determining the eye blink event times and fNIRS was used only for extracting cardiac information Analysis of brain activity is not included in this paper due to space limitations the filtered EEG data underwent ICA decomposition using Extended-Infomax algorithm to decompose EEG data into independent components Then the ADJUST method was applied to detect the independent components associated with eye blink time series and topographic maps of the independent components were also visually inspected by the experimenter After removing the components associated with artefacts the pre-processed data was reconstructed for further analysis we determined the blink times by detecting the sharp peaks in the associated independent components The channel-averaged oxy-hemoglobin concentration changes contained a strong oscillatory component related to the cardiac pulsation we assumed that the period of this signal (the interval between every other zero-crossing) was the period of the heartbeat from the heart rate (reciprocal of the period) the heart rate variability was found To prepare for the Fourier transform of the HR we interpolated its values to the regular temporal grid of the original fNIRS signal We separately considered components in the low-frequency range 0.01–0.15 Hz and the high-frequency range 0.15–0.8 Hz The latter envelops the frequencies of normal respiration in the low- and high-frequency ranges were computed The heart rate variability was then calculated as \(HRV = {{HF} \mathord{\left/ {\vphantom {{HF} {\left( {HF + LF} \right)}}} \right \kern-\nulldelimiterspace} {\left( {HF + LF} \right)}}\) thus providing a measure of the extent to which the heart rate was modulated by the respiratory rhythms For every participant and experimental episode we calculated the mean and the maximum and minimum of the HR and HRV only the episode mean was used since blinks were insufficiently frequent to allow reliable averaging within shorter time segments These were used as features for predicting the cognitive load indexed by subjective experience or by performance our predictors were the features derived from physiology while the targets of prediction were derived from NASA-TLX reports and behavioural quantities following common usage in machine learning we are using the term prediction to describe a statistical relationship without implying that the predictor temporally precedes the target In assessing group differences we used the Wilcoxon signed-rank test when the groups contained paired subjects (e.g subjects that performed the first task v second task) and the Kolmogorov–Smirnov test when they did not (e.g subjects that performed Ring Transfer v Threading as the first task) These tests were deemed suitable for our study as they were relatively conservative and did not presuppose the normal distribution We did not utilise a null hypothesis whose rejection would have required multiple comparisons kstest2 and signrank were utilized for implementing some of the calculations described above (Matlab R2017b The data that support the findings of this study are available on request from the corresponding author Laparoscopic versus open gastric bypass: A 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Hospital level under-utilization of minimally invasive surgery in the United States: Retrospective review training and safety of laparoscopic surgery in low and middle-income countries Systematic review of laparoscopic surgery in low-and middle-income countries: Benefits A decade of imaging surgeons’ brain function (part I): Terminology A decade of imaging surgeons’ brain function (part II): A systematic review of applications for technical and nontechnical skills assessment Mobita | A ultimate mobile solution for EEG | TMSi Artinis Medical Systems | fNIRS devices | NIRS devices-Octamon Artinis Medical Systems | fNIRS devices | NIRS devices Shining new light on mammalian diving physiology using wearable near-infrared spectroscopy Artinis Medical Systems | fNIRS devices | NIRS devices-PortaSync (Swartz Center for Computational Neuroscience Optimised use of independent component analysis for EEG signal processing Optimized ICA-based removal of ocular EEG artifacts from free viewing experiments Identifying reliable independent components via split-half comparisons Influence of signal preprocessing on ICA-based EEG decomposition In XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 (ed ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features and ERICA: New Tools for Advanced EEG Processing Hemodynamic correlates of spontaneous neural activity measured by human whole-head resting state EEG+ fNIRS Download references The authors thank Bethany Twigge for her invaluable help in performing the experiments Marc Garbey for help in designing the study Joakim Andreassen for providing the original version of the audio stimulus software Ojeme Amurun for creating the videos used in training the participants This research was made possible in part by support from the School of Science and Technology at Nottingham Trent University via QR funds provided by the Higher Education Funding Council for England (HEFCE) as a result of the Research Excellence Framework 2014 (REF2014) These authors contributed equally: Zohreh Zakeri and Ahmet Omurtag Download citation DOI: https://doi.org/10.1038/s41598-020-69553-3 Volume 4 - 2023 | https://doi.org/10.3389/fnrgo.2023.1215376 Editorial on the Research Topic Effect of neurophysiological conditions and mental workload on physical and cognitive performances: a multidimensional perspective could be administered to assess the psychological conditions of individuals during the execution of various tasks Most of the studies published on this Research Topic have been focused on populations with special needs or pathologies. However, the first manuscript to be published was that of Rinella et al. in which the authors investigated the relationship between the digit ratio (D2:D4) and state and/or trait anxiety in healthy adults and whether there are gender-specific differences 125 participants of both sexes filled in the State-Trait Anxiety Inventory (STAI-Y) questionnaire and their D2:D4 ratio was calculated a low D2:D4 ratio (<1) can be considered a protective factor against anxiety in both men and women and this protection appears to be lifelong a significant negative relationship was found between age In this sense, Rast and Labruyère discussed the use of sensor-based technology to monitor the motor activities of neuromotor impairments in infants and adolescents The authors surveyed health professionals involved in pediatric rehabilitation for their opinions on the use of this technology The results of the survey indicated that health professionals believe sensor-based outcomes can be beneficial for monitoring motor activities and delivering personalized interventions the survey also revealed potential confounding variables that may influence the participants' responses the paper discusses the prospective benefits and difficulties of using sensor-based technology in pediatric rehabilitation Hardy and Hinkin used the NASA-Task Load Index questionnaire (Noyes and Bruneau, 2007) to assess the workload of performing a computerized monitoring task of 32 adults positive for the human immunodeficiency virus The study found that tracking performance decreased as task difficulty increased The scores on the Mental Demand subscale revealed substantial individual differences in workload Mental Demand was discovered to be associated with age and a diagnosis of acquired immune deficiency syndrome Post et al. aimed to investigate the effects of a 10-week resistance training program on motor behavior and physical fitness in young adults with Down syndrome The results showed significant improvements in locomotor and object control skills The participants also reported increased self-confidence The study suggests that a properly designed resistance training program can improve the health status and quality of life of people with Down syndrome The study by Nhan et al. examined the effect of acute submaximal exercise on cognition and brain-derived neurotrophic factor (BDNF) in spinal cord injury patients eight individuals with traumatic spinal cord injury performed submaximal intensity arm cycling or time-matched quiet rest Serum and plasma levels of blood-borne BDNF were measured and cognition was evaluated using the Stroop Test and Task-Switching Test The results demonstrated that acute exercise based on guidelines did not increase BDNF or enhance aspects of cognition in spinal cord injury patients This study lays the groundwork for future research on exercise as a therapeutic strategy for promoting mental health in spinal cord injury patients Loria et al. examined the use of accelerometers to evaluate the function of the paretic limb during therapeutic exercises in stroke patients The patients participated in an auditory-motor intervention in which reaching movements of the paralyzed limb were mapped onto digital musical instruments and sound tablets To quantify the volitional control and temporal consistency of the paretic limb movements the resulting acceleration profiles were analyzed Significant improvements in the acceleration of the paretic limb correlated with improvements in clinical assessments of motor function These results indicate that accelerometry-based measures may be beneficial in stroke rehabilitation The research of Harro et al. investigated the effects of Nordic Walking exercise on walking function and serum BDNF in individuals with idiopathic PD Twelve participants with mild to moderate idiopathic PD participated in 6 weeks of supervised Nordic Walking exercise training with individualized instruction followed by 14 weeks of independent Nordic Walking exercise with remote guidance Results demonstrated that Nordic Walking exercise enhanced walking endurance We believe that the articles on this Research Topic provide a fascinating summary of the current state of research on the effect of neurophysiological status and mental workload on human physical and cognitive performance We hope that they will inspire additional research on this topic that should be not only scientifically rigorous but also highly applicable to real-world situations monitoring physiological functions in healthy and pathological patients could pave the way for innovative evidence-based solutions in clinical practice and sports science to enhance the efficacy of training processes DP and DF wrote the original draft of this editorial All the authors have approved the submitted version of this editorial Measuring mental workload with EEG+ fNIRS PubMed Abstract | CrossRef Full Text | Google Scholar CrossRef Full Text | Google Scholar Classification of drivers' mental workload levels: comparison of machine learning methods based on ECG and infrared thermal signals A self-analysis of the NASA-TLX workload measure PubMed Abstract | CrossRef Full Text | Google Scholar Prediction of state anxiety by machine learning applied to photoplethysmography data Central and peripheral thermal signatures of brain-derived fatigue during unilateral resistance exercise: a preliminary study Priego-Quesada JI and Merla A (2023) Editorial: Effect of neurophysiological conditions and mental workload on physical and cognitive performances: a multidimensional perspective Received: 01 May 2023; Accepted: 05 May 2023; Published: 17 May 2023 Edited and reviewed by: Klaus Gramann Copyright © 2023 Perpetuini, Formenti, Priego-Quesada and Merla. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) *Correspondence: David Perpetuini, ZGF2aWQucGVycGV0dWluaUB1bmljaC5pdA== A new factory for the production of solar panels will be built near the town of Omurtag (Bulgaria). The developer is the Bulgarian company Solar Panel EOOD which will invest BGN 7.35 million in the project. The investment is expected to create 45 new jobs This became clear during the Class "A" project certificate awarding ceremony given by the Minister of Innovation and Growth (Note: These certificates are awarded by the Bulgarian government to encourage and ease priority investments) Modern machinery and equipment necessary for the production process will be purchased for the new plant. It will have a capacity of 200 mW per year The Omurtag production base will also feature a production workshop a warehouse for finished products and an administrative wing The investor company points out that it decided to build the plant given the rapid development of electricity production from renewable sources Solar Panel EOOD was established in 2022 with a capital of EUR 0.5 million It’s owned by the Radita construction company The Bulgarian company Solar Panel EOOD will produce solar panels from "100% European materials" at its plant in Omurtag The automated line was built by the Italian manufacturer of components for solar installations Ecoprogetti and has a capacity of 250 MW We learned about the investment in March when the company received a class "A" certificate for the project The new production plant is in Preslav and a total of BGN 7.35 million will be invested in it This innovative plant is not only the first of its kind in the country but also sets a new standard in terms of technological progress and commitment to sustainability in the Bulgarian solar industry," added the Italian company reps This is achieved thanks to the advanced level of plant automation Each stage of the production process is optimized to ensure maximum efficiency and precision with as little labor as possible The machines supplied to Solar Panel are of the highest level of automation with modern methods for full traceability and production monitoring Designed to produce high-efficiency solar panels suitable for both residential buildings and solar parks the new production line incorporates the latest solar cell technologies and materials suitable for both PERC/PERT and TOPCON technologies The all-electric laminator sets the production line apart from its competitors especially those that rely on conventional manufacturing methods allowing the company to provide a product warranty of up to 30 years on the modules The line is quickly filling its full capacity with an expected production of about 1,400 panels per day or about 30,000 panels per month the announcement represents another step towards affirming the European production of components for photovoltaic installations Ecoprogetti is based in Italy with offices in the Philippines the US and the UAE and claims its production equipment is "100% made in Europe" Foreign Minister Georgi Georgiev has left for Washington where he will participate in the Munich Leaders Meeting (May 5-7 The forum is organised by the Munich Security Conference The foundation Unity- Kočani has sent an open letter to key Bulgarian institutions expressing gratitude for the support and humanitarian assistance provided by Bulgaria after the tragedy of the fire at a nightclub in Kočani The foreign ministers of Bulgaria and Greece Georg Georgiev and Giorgos Gerapetritis signed a joint declaration on the use of the waters of the river Arda on 2 May the BNR reports citing an announcement published by the Greek Foreign Ministry.. people will be able to withdraw money from ATMs only in the new currency according to the website of the Bulgarian. helicopters of the Bulgarian Air Force will fly at low altitude over Sofia in preparation for a military parade marking the Day. The Bulgarian student teams that participated in the European Olympiad of Experimental Sciences EOES 2025 in Zagreb have returned with. HOT: » What kind of news would you like to see more of? A 50-year-old man from the village of Dolna Hubavka has filed a total of 1140 fake signals to the 112 emergency hotline in a week the Regional Police Directorate in the northeastern town of Targovishte reported The tip-off about the abuse was received Friday by the Regional Police Directorate in Omurtag The man was found to have given a huge number of emergency calls in the period August 18 –August 25 with the offender facing a fine of BGN 2000 – 5000 Under Bulgaria's National Emergency Call System Act with a single European number 112 the fine soars to BGN 10 000 – 20 000 if the false alert resulted in the mobilization of emergency response units Police forces in the town of Veliko Tarnovo said Friday they had captured a 28-year-old man from Gorna Oryahovitsa who had used his cell phone for a prank murder call on the 112 emergency number at 21:45 on Thursday The 28-year-old was busted shortly after the abuse and was detained for 24 hours by officers from the Regional Police Directorate in Gorna Oryahovitsa The offender is being subjected to fast-track proceedings We need your support so Novinite.com can keep delivering news and information about Bulgaria A 9-year-old girl has died at a school in Veliko Tarnovo and an investigation is underway to determine the cause of death Three Dutch nationals convicted of producing and synthesizing precursors for high-risk drugs have been sentenced to prison Three individuals sustained injuries following the explosion at the pulp factory near Svishtov A severe storm accompanied by hail struck Sliven and surrounding areas last evening was arrested during a police operation at the municipal administration Excitement mounts as the Regional Ministry announces the commencement of the much-anticipated highway construction linking Ruse to Veliko Tarnovo An 18-year-old girl who had been reported missing in Haskovo has been found dead A 33-year-old man from the village of Semchinovo has been taken into custody by the police for physically assaulting a 10-year-old child A 12-year-old boy from Lukovit has been hospitalized with two broken arms and head injuries after reportedly being assaulted and thrown from a bridge the director of the Plovdiv Customs Office was arrested earlier today for allegedly facilitating a new smuggling route for cigarettes The Sofia Police has launched a targeted operation against drivers of electric scooters and electric motorbikes who engage in reckless behavior in the city's central areas opened fire with a gas pistol near a kindergarten in Sofia's Lyulin district Google Street View Cars Return to Bulgaria for Major Mapping Update Housing Prices Soar in Bulgaria’s Major Cities as Demand and Supply Strain Increase A dramatic drop in oil prices offers mixed results for motorists across the globe – from hefty savings at US pumps to a rare price hike in Venezuela These images taken by Reuters photographers over the last few weeks show how despite all countries having access to the same oil prices on international markets we’d like to thank you for joining the debate - we’re glad you’ve chosen to participate and we value your opinions and experiences Please choose your username under which you would like all your comments to show up Please keep your posts respectful and abide by the community guidelines - and if you spot a comment you think doesn’t adhere to the guidelines please use the ‘Report’ link next to it to let us know Please preview your comment below and click ‘post’ when you’re happy with it former boxing champion and current leader of the Ukrainian party UDAR was nominated by the city organization of the party for a candidate for mayor of Kiev Klitschko said on Wednesday his main goal was to eliminate corruption and to the destroy the barriers that keep Kiev from developing freely and successfully our first priority is corruption prevention It's Kiev's transparent budget and dismissal of corrupt officials,” Klitschko said The Kiev administration should be controlled by society The third priority is the use of the Kiev budget for meeting the needs of the people of Kiev." The paid "blue zone" parking service in Varna will cease operations on December 16 With the national and European Parliament elections drawing near Bulgarian political parties are making significant strides in finalizing their candidate lists It has been 15 days since 17-year-old Ivana from Dupnitsa went missing The search for the Bulgarian girl in Dupnitsa and the surrounding area continues for another day Mayor Vasil Terziev of Sofia has voiced his intention to usher in a new era for the capital city by seeking a replacement for the current chief architect The European Commission is proposing significant changes to EU regulations concerning road safety and vehicle registration According to preliminary data from Eurostat the eurozone economy grew by 0.4% in the first quarter of the year compared to the previous three months doubling the 0.2% increase recorded at the end of 2024 The European Commission has announced a €910 million investment under the European Defence Fund (EDF) to enhance defence manufacturing capabilities across the European Union The European Commission has strongly condemned the circumstances surrounding the death of Ukrainian journalist Viktoriia Roshchyna Friedrich Merz is poised to become Germany's next chancellor following the approval of a coalition agreement between his CDU/CSU bloc European countries are struggling to mobilize even 25,000 troops to Ukraine for a potential peacekeeping mission The requested URL was not found on this server By Carl Collen2009-04-08T11:02:01+01:00 Rewe Group-Owned discount retailer Penny Market has revealed that it will invest up to €100m this year on expanding its operations in Bulgaria which operates stores across Europe in the likes of Austria plans to construct a total of 10 stores and a logistics centre in the village of Stolnik near Sofia According to Penny's CEO for Bulgaria Vasil Fechko while the distribution centre will cost up to €30m The supermarkets will be opened following the launch of the distribution centre Site powered by Webvision Cloud more than 1000 schools have been closed in Bulgaria Primary schools in small towns often struggle to survive In areas with predominant minority population pupils’ poor Bulgarian language proficiency creates additional obstacles to teachers and the problem of children dropping out of the education system continues to be on institutions' agenda a village school has been described as one that has “jumped into the future." The Primary School "Dr Peter Beron" in the village of Plustina is central to the Omurtag municipality It has about 160 students from 13 settlements 10-15% of the children are Romani and the rest are of Turkish origin The latest training technologies have been applied here for 12 years now Classrooms have been equipped with electronic boards and laptops for each teacher an indoor gym with fitness equipment and an outdoor playground Modern school equipment undoubtedly requires a lot of resources "The school owns about 50 acres of farmland The money from rent goes into the school," Deputy Director Nursen Isufova explains “We have been actively working on European and national programs When the first national programs started to be implemented back in 2007/2008 We have built a wonderful sports playground In the indoor sports hall we have fitness equipment and children can also use it in their free time We have also introduced school uniforms because we see how the difference in clothing created embarrassment for some of the students.” Nursen Isufova says that thanks to successful implementation of 2 European projects totaling about 240 thousand euros the school management continued to improve the conditions in the school and on the other hand provided the opportunity for pupils to travel all over Bulgaria participating in forums and festivals and creating partnerships with other schools The students also often go to sports camps and excursions Do your pupils ever want to go on school recess at all The announcement of a two-week Christmas holiday actually was not to the liking of some pupils The efforts of an ambitious team of pedagogues combined with interactive teaching methods have yielded amazing results during the 2014 National External Assessment in Mathematics the school in Plustina achieved an average score of 5.13 and became the only one in the country with a score above 5 The unemployment rate in the region is high so some families work abroad and children are raised by their grandparents "We often need to be in the role of substitute parents," the deputy principal says They seek help and assistance in every way We have been trying to provide them with what they are missing at home." financially distressed families were provided with computers so that children can do their homework and the school also has a dressing room It seems the school management has accomplished everything "Not everything," Nursen Isufova says and adds: "We need to continue developing in the digital sphere Our idea is that students would come to school with just one flash drive with them This would be the newest thing to happen in our school.” Only on the Day of Bravery and Holiday of the Bulgarian Army (May 6) we will provide our visitors with the opportunity to enter three of perhaps the most interesting machines from our outdoor exhibition Dozens of enthusiasts and nature lovers will kick off the 44th edition of the Move and Win campaign with a spring hike to Bozhur Hut The meeting point will be the Vladishki Bridge in Veliko Tarnovo The third edition of the Samardala Festival will be held on 3 May in the central square of Nova Zagora is used as a spice and is harvested at the peak of its flowering in May we will provide our visitors with the opportunity to enter three. The German discount supermarket chain Penny Market will invest EUR 100 M in Bulgaria until the end of 2009 That was announced by company's CEO for Bulgaria Currently Penny Market plans to construct a total of 10 stores in Bulgaria's Lovech Their biggest project will be a logistics center in the village of Stolnik near capital Sofia and will be built on an area of 78 decares The main contractor for the construction is the Bulgarian Mix Construction Penny Market is a discount shops chain which operates 5000 stores around Europe (Germany It is owned by the German retail and tourism company REWE Group Penny Market has been in the Bulgarian market since 2005 the company is looking for terrains in Sofia and bigger Bulgarian cities All the supermarkets will be opened after the logistics center construction is finished former Ukrainian Commander-in-Chief and current Ambassador to the U.K. has provided insights into the pivotal role of the joint Ukrainian-U.S Germany has deployed its first permanent military brigade abroad since World War II A recent report from Germany’s Federal Intelligence Service and the Bundeswehr has revealed concerns that Russia is likely preparing for a large-scale conflict with NATO A nationwide strike by German airport workers led to the cancellation of 12 flights between Bulgaria and Germany on Monday A 40-year-old German man from Ludwigshafen has been detained in connection with the car ramming attack in Mannheim that left at least two people dead and 11 others injured all retailers in Bulgaria will be required to display prices in both leva and euros a major British tour operator specializing in holidays to Bulgaria has halted all its operations effective April 24 Wage growth in Bulgaria is projected at 9.3 percent for 2025 a 15.4 percent rise in the minimum wage since January The World Bank has revised down its forecast for Bulgaria’s economic growth in 2025 Bulgaria is approaching the final stages of preparation for transitioning card payments from the national currency Minister of Economy and Industry Petar Dilov held a meeting with Susan Falatko the Charge d'Affaires at the US Embassy in Bulgaria The town of Targovishte (Northeastern Bulgaria) hosts the orienteering competition 2025 Velikden Cup Moldova and Ukraine have arrived in the city to take part in the orienteering competition The program includes middle-distance and long-distance events on challenging terrain with numerous rocks The program also features a mass start near the village of Ugledno (Omurtag Municiplity) has climbed one place in the Association of Tennis Professionals (ATP) rankings Last week Dimitrov took part in the Masters 1000 tournament in the Spanish capital Madrid Bulgaria’s junior group won all three gold medals at the 2025 Rhythmic Gymnastics European Cup in Baku (Azerbaijan) Bulgaria won the gold medal in the Senior Group Cross Battles at the 2025 Rhythmic Gymnastics European Cup in Baku (Azerbaijan) Danaya Atanasova and Viktoria Georgieva performed. can be seen in the National Archeological Museum It was discovered on November 7 by associate Professor Diana Gergova at the historical and archeology preserve in Sboryanovo which is included in the UNESCO world cultural heritage list The unique find marked the 30th anniversary since the start of the archeological research in Sboryanovo where the capital of the Thracian tribe Getty was situated sanctuaries and necropolises reveal the history of the one-time political and cultural center Here is an interesting fact: series of researches show that the so-called King’s necropolis and the other necropolises of the Getty tribe were projected in accordance with a star map- as reflections of different constellations The start was given by Bulgarian and Italian experts A monumental tomb with pillars of the Doric style dating back to the end of the 4th and the beginning of the 3rd century BC was found there Some experts say that it was of a 7th magnitude at the Richter scale which aimed to reveal how this solid mound was built when we have such powerful machinery we find it hard to excavate this mound” Other researches were also made in the Omurtag mound used for the assembling of the stone blocks as well as studies of the bones found at this place we are very dependant on the geophysical equipment” “Due to the new equipment provided to us 10 years ago we managed to spot the central construction at the mound We can expect to find there a tomb or other major construction.” The site has not been explored for 7-8 years due to the lack of financing and powerful machinery the archeologists received excavation machinery from sponsoring companies On the 3rd day of the exploration they came across a small part of crumbly soil According to Diana Gergova this is a unique find because it was discovered at a high place in a very impressive mound Each stage of its construction was connected to certain ceremonies of immortalization This is why experts suppose that this treasure was in fact a funeral gift the archeologists need more funds and better organization to reveal more interesting facts “We are talking about 2 groups of memorials The first one includes applications to a horse harness among which is a beautiful diadem with figures of various animals and mythical creatures There are 4 golden bracelets with a spiral form and a wonderful golden ring with an embossment of God Eros The interesting thing here is that we found many golden fibres and tiny cylindrical and round golden beads which were once placed over a veil interwoven with gold We are very pleased that there is another effigy in the Kazanlashka tomb (which was also included in the UNESCO cultural heritage list) which reveals the one-time funeral procession A woman with a veil walks behind the man with the casket So we have a full exemplification of a ritual which was once practiced by the Thracian people” said associate professor Gergova in conclusion The site is now to be prepared for the winter scientists will make new geophysical research of the place archeologists will be better prepared for their next researches "You must have strong faith and pray - then the saint will help you and carry your prayer to God," says Father Georgi Markov of the Church of St Athanasius the Great in Gorni Lozen near Sofia He adds that he has often witnessed the miracles of St. marks 1160 years since the baptism of our Bulgarian people into the Orthodox faith and 1170 years since the creation of the Bulgarian alphabet and Slavic literature the Varna and Veliki Preslav Bishopric Metropolis. Bulgaria celebrates 149 years since the April Uprising – an event that led to the liberation of Bulgaria after almost five centuries of Ottoman rule we must not forget that every participant in the April. DNB Stories Africa While some amount of stress is actually good in that it helps one to be motivated and alert but if stress levels escalate it could lead to infertility and lower sperm count For couples who are planning to conceive it is necessary to control the stress levels as it affects conception in a big way meditation and mental exercises are suggested to help in controlling stress levels Diet has a huge impact on sperm count and its quality Diets high in meat and dairy are not just bad for waistlines they have a negative impact below the waist too A good number of studies have listed foods like bananas dark chocolate and garlic as super foods for sperm building Lower sperm counts have long been associated with conditions such as diabetes varicose veins on the testicles and sexually transmitted diseases such as gonorrhea or HIV Lying on your couch watching back-to-back episodes of “Game of Thrones” won’t do you any favors in the baby-making game “If you’re not getting 150 minutes of moderate exercise every week,” Urologist and fertility specialist Dr obesity is one of the key culprits of low sperm production Researchers at Ambroise Paré University Hospital in Paris found that among obese men 32.4 percent had a low sperm count and 6.9 percent had no viable sperm “Tobacco affects motility and shape of the sperm,” says Dr a reproductive endocrinologist and reproductive specialist in St His conclusions are in line with a 2016 study which showed that smokers’ DNA and sperm were damaged in ways that reduce the chances of fertilization Omurtag also says that marijuana and opioid use affect sperm production “They effectively disrupt how the brain talks to the testicles,” he says Advice from doctors to men with fertility problems keeping laptops away from laps and having less sex to give the sperm enough time to build up Comment * document.getElementById("comment").setAttribute( "id" "aecd3eb210eff63287a85262c4c1fc8a" );document.getElementById("i421ca229f").setAttribute( "id" You can also contact us through the Contact Form on our website