Cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney statistical tests

Cluster-based permutation tests are widely used in neuroscience studies for the analysis of high-dimensional electroencephalography (EEG) and event-related potential (ERP) data as it may address the multiple comparison problem without reducing the statistical power. However, classical cluster-based permutation analysis relies on parametric t-tests, whose assumptions may not be verified in case of non-normality of the data distribution and alternative options may be considered. To overcome this limitation, here we present a new software for a cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney tests. We tested both t-test and non-parametric Wilcoxon implementations in two independent datasets of ERPs and EEG spectral data: while t-test-based and non-parametric Wilcoxon-based cluster analyses showed similar results in case of ERP data, the t-test implementation was not able to find clustered effects in case of spectral data. We encourage the use of non-parametric statistics for a cluster permutation analysis of EEG data, and we provide a publicly available software for this computation

Thermosensory mapping of skin wetness sensitivity across the body of young males and females at rest and following maximal incremental running

Key points: Humans lack skin receptors for wetness (i.e. hygroreceptors), yet we present a remarkable wetness sensitivity. Afferent inputs from skin cold-sensitive thermoreceptors are key for sensing wetness; yet, it is unknown whether males and females differ in their wetness sensitivity across their body and whether high intensity exercise modulates this sensitivity. We mapped sensitivity to cold, neutral and warm wetness across five body regions and show that females are more sensitive to skin wetness than males, and that this difference is greater for cold than warm wetness sensitivity. We also show that a single bout of maximal exercise reduced the sensitivity to skin wetness (i.e. hygro-hypoesthesia) of both sexes as a result of concurrent decreases in thermal sensitivity. These novel findings clarify the physiological mechanisms underpinning this fundamental human sensory experience. In addition, they indicate sex differences in thermoregulatory responses and will inform the design of more effective sport and protective clothing, as well as thermoregulatory models. Abstract: Humans lack skin hygroreceptors and we rely on integrating cold and tactile inputs from A-type skin nerve fibres to sense wetness. Yet, it is unknown whether sex and exercise independently modulate skin wetness sensitivity across the body. We mapped local sensitivity to cold, neutral and warm wetness of the forehead, neck, underarm, lower back and dorsal foot in 10 males (27.8 ± 2.7 years; 1.92 ± 0.1 m2 body surface area) and 10 females (25.4 ± 3.9 years; 1.68 ± 0.1 m2 body surface area), at rest and post maximal incremental running. Participants underwent our quantitative sensory test where they reported the magnitude of thermal and wetness perceptions (visual analogue scale) resulting from the application of a cold (5°C below skin temperature) wet (0.8 mL of water), neutral wet and warm wet (5°C above skin temperature) thermal probe (1.32 cm2) to five skin sites. We found that: (i) females were ∼14% to ∼17% more sensitive to cold-wetness than males, yet both sexes were as sensitive to neutral- and warm-wetness; (ii) regional differences were present for cold-wetness only, and these followed a craniocaudal increase that was more pronounced in males (i.e. the foot was ∼31% more sensitive than the forehead); and (iii) maximal exercise reduced cold-wetness sensitivity over specific regions in males (i.e. ∼40% decrease in foot sensitivity), and also induced a generalized reduction in warm-wetness sensitivity in both sexes (i.e. ∼4% to ∼6%). For the first time, we show that females are more sensitive to cold wetness than males and that maximal exercise induce hygro-hypoesthesia. These novel findings expand our knowledge on sex differences in thermoregulatory physiology

Methodological Considerations on EEG Electrical Reference: A Functional Brain-Heart Interplay Study

The growing interest in the study of functional brain-heart interplay (BHI) has motivated the development of novel methodological frameworks for its quantification. While a combination of electroencephalography (EEG) and heartbeat-derived series has been widely used, the role of EEG preprocessing on a BHI quantification is yet unknown. To this extent, here we investigate on four different EEG electrical referencing techniques associated with BHI quantifications over 4-minute resting-state in 15 healthy subjects. BHI methods include the synthetic data generation model, heartbeat-evoked potentials, heartbeat-evoked oscillations, and maximal information coefficient (MIC). EEG signals were offline referenced under the Cz channel, common average, mastoids average, and Laplacian method, and statistical comparisons were performed to assess similarities between references and between BHI techniques. Results show a topographical agreement between BHI estimation methods depending on the specific EEG reference. Major differences between BHI methods occur with the Laplacian reference, while major differences between EEG references are with the MIC analysis. We conclude that the choice of EEG electrical reference may significantly affect a functional BHI quantification

Multivariate Pattern Analysis of Entropy estimates in Fast- and Slow-Wave Functional Near Infrared Spectroscopy: A Preliminary Cognitive Stress study

Functional near infrared spectroscopy (fNIRS) is a modality that can measure shallow cortical brain signals and also contains pulsatile oscillations that originate from heartbeat dynamics. In particular, while fNIRS slow waves (0 Hz to 0.6 Hz) refer to the standard hemodynamic signal, fast-wave (0.8 Hz to 3 Hz) fNIRS signals refer to cardiac oscillations. Using a cognitive stress experiment paradigm with mental arithmetic, the aim of this study was to assess differences in cortical activity when using slow-wave or fast-wave fNIRS signals. Furthermore, we aimed to see whether fNIRS fast and slow waves provide different information to discriminate mental arithmetic tasks from baseline. We used data from 10 healthy subjects from an open dataset performing mental arithmetic tasks and assessed fNIRS signals using mean values in the time domain, as well as complexity estimates including sample, fuzzy, and distribution entropy. A searchlight representational similarity analysis with pairwise t-test group analysis was performed to compare the representational dissimilarity matrices of each searchlight center. We found significant representational differences between fNIRS fast and slow waves for all complexity estimates, at different brain regions. On the other hand, no statistical differences were observed for mean values. We conclude that entropy analysis of fNIRS data may be more sensitive than traditional methods like mean analysis at detecting the additional information provided by fast-wave signals for discriminating mental arithmetic tasks and warrants further research

The Role of EEG Electrical Reference in the Assessment of Functional Brain-Heart Interplay: A Preliminary Study

Recent studies have proposed computational models for a functional brain-heart interplay (BHI) assessment based on electroencephalography (EEG). Nevertheless, the role of the EEG electrical reference on such BHI estimates has not been investigated yet. Here we present a pilot study assessing BHI in 4 minutes resting-state in 10 healthy subjects through methods including heartbeat-evoked potentials (HEP) and oscillations, Maximal Information Coefficient, and our recently proposed model based on Synthetic Data Generation (SDG). EEG signals were re-referenced to the Cz channel, common average, mastoids, and Laplacian. Results for EEG power in the alpha band indicate that the most significant differences between BHI methods are with the Laplacian reference while a higher agreement exists between HEP and SDG approaches

Effectiveness of sodium acetate treatment on the mechanical properties and morphology of natural fiber-reinforced composites

This paper aims to investigate the ability of an eco-friendly and cheap treatment based on sodium acetate solutions to improve the mechanical properties of flax fiber-reinforced composites. Flax fibers were treated for 5 days (i.e., 120 h) at 25◦C with mildly alkaline solutions at 5%, 10% and 20% weight content of the sodium salt. Quasi-static tensile and flexural tests, Charpy impact tests and dynamical mechanical thermal (DMTA) tests were carried out to evaluate the mechanical properties of the resulting composites. Fourier transform infrared analysis (FTIR) was used to evaluate the chemical modification on the fibers surface due to the proposed treatment, whereas scanning electron microscope (SEM) and helium pycnometry were used to get useful information about the morphology of composites. It was found that the treatment with 5% solution of sodium acetate leads to the best mechanical performance and morphology of flax fiber-reinforced composites. SEM analysis confirmed these findings highlighting that composites reinforced with flax fibers treated in 5% sodium acetate solution show an improved morphology compared to the untreated ones. On the contrary, detrimental effects on the morphology as well as on the mechanical performance of composites were achieved by increasing the salt concentration of the treating solution

A novel approach for security function graph configuration and deployment

Network virtualization increased the versatility in enforcing security protection, by easing the development of new security function implementations. However, the drawback of this opportunity is that a security provider, in charge of configuring and deploying a security function graph, has to choose the best virtual security functions among a pool so large that makes manual decisions unfeasible. In light of this problem, the paper proposes a novel approach for synthesizing virtual security services by introducing the functionality abstraction. This new level of abstraction allows to work in the virtual level without considering the different function implementations, with the objective to postpone the function selection jointly with the deployment, after the configuration of the virtual graph. This novelty enables to optimize the function selection when the pool of available functions is very large. A framework supporting this approach has been implemented and it showed adequate scalability for the requirements of modern virtual networks

Physical and mechanical properties of sustainable hydraulic mortar based on marble slurry with waste glass

This paper aims to propose and characterize a sustainable hydraulic mortar entirely obtained by the reuse of waste materials, with marble slurry coming from quarries in the northwestern Sicily and glass powder coming from a waste collection plant in Marsala (Province of Trapani). The first was used as raw material to produce the mortar binder by a kilning and slaking process, while the second was used as a pozzolanic additive. The chemical and morphological characterization of the marble slurry was done by XRD, FTIR, STA and SEM analyses. Glass powder was analyzed through particle size distribution measurements, XRD and standard pozzolanic tests. Hydraulic mortars constituted by slaked lime from kilned marble slurry and waste glass powder (LGS) were prepared beside commercial Natural Hydraulic Lime (NHL) based mortars (NGS) and air-hardening lime (LSS)-based mortars. Mechanical and absorption properties of the mortars were investigated as a function of the grain size of the glass powder by means of three-point bending and compressive strength tests, capillary uptake, helium pycnometry and simultaneous thermal analysis. The results demonstrated that the formulation LGS exhibits significantly improved mechanical and absorption properties compared to air-hardening mortars (LSS). It confirms the possibility of producing a more sustainable hydraulic mortar exclusively from waste materials for civil engineering

Independent and interactive effects of thermal stress and mental fatigue on manual dexterity

Many occupations and sports require high levels of manual dexterity under thermal stress and mental fatigue. Yet, multistressor studies remain scarce. We quantified the interactive effects of thermal stress and mental fatigue on manual dexterity. Seven males (21.1 \ub1 1.3 yr) underwent six separate 60-min trials characterized by a combination of three air temperatures (hot, 37C; neutral, 21C; cold, 7C) and two mental fatigue states (MF, mental fatigue induced by a 35-min cognitive battery; no-MF, no mental fatigue). Participants performed complex (O'Connor test) and simple (hand-tool test) manual tasks pre- and posttrial to determine stressor-induced performance changes. We monitored participants' rectal temperature and hand skin temperature (Thand) continuously and assessed the reaction time (handclick test) and subjective mental fatigue (5-point scale). Thermal stress (P < 0.0001), but not mental fatigue (P = 0.290), modulated Thand (heat, +3.3C [95% CI: +0.2, +6.5]; cold, 7.5C [10.7, 4.4]). Mental fatigue (P = 0.021), but not thermal stress (P = 0.646), slowed the reaction time (10%) and increased subjective fatigue. Thermal stress and mental fatigue had an interactive effect on the complex manual task (P = 0.040), with cold-no-MF decreasing the performance by 22% [39, 5], whereas neutral-MF, cold-MF, and heat-MF by 36% [53, 19], 34% [52, 17], and 36% [53, 19], respectively. Only mental fatigue decreased the performance in the simple manual task (30% [43, 16] across all thermal conditions; P = 0.002). Cold stress-induced impairments in complex manipulation increase with mental fatigue; yet combined stressors' effects are no greater than those of mental fatigue alone, which also impairs simple manipulation. Mental fatigue poses a greater challenge to manual dexterity than thermal stress

Functional assessment of bidirectional cortical and peripheral neural control on heartbeat dynamics: A brain-heart study on thermal stress

The study of functional Brain-Heart Interplay (BHI) from non-invasive recordings has gained much interest in recent years. Previous endeavors aimed at understanding how the two dynamical systems exchange information, providing novel holistic biomarkers and important insights on essential cognitive aspects and neural system functioning. However, the interplay between cardiac sympathovagal and cortical oscillations still has much room for further investigation. In this study, we introduce a new computational framework for a functional BHI assessment, namely the Sympatho-Vagal Synthetic Data Generation Model, combining cortical (electroencephalography, EEG) and peripheral (cardiac sympathovagal) neural dynamics. The causal, bidirectional neural control on heartbeat dynamics was quantified on data gathered from 26 human volunteers undergoing a cold-pressor test. Results show that thermal stress induces heart-to-brain functional interplay sustained by EEG oscillations in the delta and gamma bands, primarily originating from sympathetic activity, whereas brain-to-heart interplay originates over central brain regions through sympathovagal control. The proposed methodology provides a viable computational tool for the functional assessment of the causal interplay between cortical and cardiac neural control