A neuroimaging comparative study of changes in a cellist's brain when playing contemporary and Baroque styles.

The emergence of different styles of Contemporary concert music in the 20th century led to a marked modification of the foundations built on previous styles. This work investigates whether these modifications, which include procedures and technical resources different to those used in the interpretation of previous musical styles, require different encephalic controls to those used in tonal music and if the experience of the musician in these styles influences them. Functional magnetic resonance images of encephalic regions from 13 professional cellists while interpreting Baroque and Contemporary excerpts inside an MRI scanner were acquired. Activation and connectivity encephalic maps show common cortical motor and sensorial regions (Precentral, Postcentral and Supramarginal Gyri) in both interpretation styles, but with different hemispheric intensity levels. However, certain auditory and motor regions only activate during Baroque. Connectivity maps show some exclusive seed-regions; thus, the Heschl's and Superior Frontal Gyri, Planum-Temporal and Caudate appear as prominent seeds when playing Baroque, whereas when playing Contemporary, the main seeds appear in the Cerebellar-Vermis, Insular cortex and Parietal Operculum. The discrepancies found are attributed to different cognitive, sensory and motor demands underlying the musical interpretation of each style, as well as to the musicians' learning of and training in these styles.

Bulk and grain boundary Li-diffusion in dense LiMn2O4 pellets by means of isotope exchange and ToF-SIMS analysis.

Lithium diffusion in LiMn2O4 pellets is studied by means of isotope exchange and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). A 6Li-enriched film deposited by Pulsed Laser Deposition (PLD) on a dense LiMn2O4 pellet with natural abundance of lithium isotopes is used to study the tracer diffusion of lithium. The measured profiles are analyzed by numerical models describing the 6Li tracer diffusion from the film into the pellet. Experiments in the Harrison type B regime of diffusion kinetics allow for the distinction and simultaneous determination of bulk and grain boundary diffusion coefficients. Changing the experimental conditions to reach Harrison type A behavior yields effective diffusion coefficients for lithium tracer diffusion in LiMn2O4. Activation energies for bulk and grain boundary diffusion were obtained from experiments at different temperatures. Our values are critically compared to previous studies.

Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians.

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

Interaction of single- and double-stranded DNA with multilayer MXene by fluorescence spectroscopy and molecular dynamics simulations.

The integration of nucleic acids with nanomaterials has attracted great attention from various research communities in search of new nanoscale tools for a range of applications, from electronics to biomedical uses. MXenes are a new class of multielement 2D materials baring exciting properties mostly directed to energy-related fields. These advanced materials are now beginning to enter the biomedical field given their biocompatibility, hydrophilicity and near-infrared absorption. Herein, we elucidate the interaction of MXene Ti3C2T x with fluorophore-tagged DNA by fluorescence measurements and molecular dynamics simulations. The system showed potential for biosensing with unequivocal detection at picomole levels and single-base discrimination. We found that this material possesses a kinetically unique entrapment/release behavior, with potential implications in time-controlled biomolecule delivery. Our findings present MXenes as platforms for binding nucleic acids, contributing to their potential for hybridization-based biosensing and related bio-applications.

Autonomic mediation in the interdependences between cardiocortical activity time variations and between cardiorespiratory activity time variations in the lizard, Gallotia galloti.

Multivariate nonlinear analysis methods were applied to variability time series extracted from electrocardiographic, electrocorticographic and respiratory activities of Gallotia galloti lizards, to study interdependences between cardio-cortical activity time variations, and between cardio-respiratory activity time variations. Autonomic nervous system involvement in the mediation of such interdependences was investigated through pharmacological blockade. Cardiac variability was evaluated from the R-R intervals of the electrocardiogram (RRIv). Cortical (CORTv) and respiratory (RESPv) activity time variations were evaluated from power-data signals derived from both electrocorticogram and respiratory signal segments obtained within each R-R interval, respectively. A nonlinear index N to measure interdependence between the signals, and a surrogate data test to measure the significance and nature of the interdependences were used. A nonlinear dependence of RRIv vs. CORTv and of RRIv vs. RESPv was found. Both dependences seem to be unconnected with the functioning of both alpha(1)-adrenoceptor and cholinoceptor systems, but appear to be mediated by beta-adrenoceptor mechanisms. A linear dependence of CORTv vs. RRIv and of RESPv vs. RRIv was also found. Both dependences seem to be unconnected with the operation of alpha(1)-adrenoceptor, beta-adrenoceptor and cholinoceptor systems. It is suggested that both the cardiocortical and cardiorespiratory synchronizations studied seem to be mediated by beta-adrenoceptor mechanisms.

The blessing of Dimensionality: Feature Selection outperforms functional connectivity-based feature transformation to classify ADHD subjects from EEG patterns of phase synchronisation.

Functional connectivity (FC) characterizes brain activity from a multivariate set of N brain signals by means of an NxN matrix A, whose elements estimate the dependence within each possible pair of signals. Such matrix can be used as a feature vector for (un)supervised subject classification. Yet if N is large, A is highly dimensional. Little is known on the effect that different strategies to reduce its dimensionality may have on its classification ability. Here, we apply different machine learning algorithms to classify 33 children (age [6-14 years]) into two groups (healthy controls and Attention Deficit Hyperactivity Disorder patients) using EEG FC patterns obtained from two phase synchronisation indices. We found that the classification is highly successful (around 95%) if the whole matrix A is taken into account, and the relevant features are selected using machine learning methods. However, if FC algorithms are applied instead to transform A into a lower dimensionality matrix, the classification rate drops to less than 80%. We conclude that, for the purpose of pattern classification, the relevant features should be selected among the elements of A by using appropriate machine learning algorithms.

Topography of EEG complexity in human neonates: effect of the postmenstrual age and the sleep state.

The topography of the EEG of human neonates is studied in terms of its power spectral density and its estimated complexity as a function of both the postmenstrual age (PMA) and the sleep state. The monopolar EEGs of three groups of seven neonates (preterm, term and older term) were recorded during active (AS) and quiet sleep (QS) from electrodes Fp1, Fp2, T3, T4, C3, C4, O1 and O2. The existence of changes between groups and sleep states in the power of delta, theta, alpha and beta bands and in the dimensional complexity of these electrodes was tested. Additionally, the nonlinearity of the EEG in each electrode and situation was analyzed. The results of the spectral measures show an increment of the power in the low frequency bands from AS to QS and with the PMA, which can be mainly traced on central and temporal electrodes. This change is shown as well by the dimensional complexity, which also presents the greatest differences in the central derivations. Moreover, the signals show evidence of nonlinearity in almost all the groups and situations, although a dynamic change from nonlinear to linear character is apparent in the central electrodes with increased PMA. As a result, it is concluded that nonlinear analysis methods provide a clear portrait of the integrated brain activity that complements the information of spectral analysis in the characterization of the brain development and the sleep states in neonates.

The variability of EEG functional connectivity of young ADHD subjects in different resting states.

OBJECTIVE: To assess ADHD from global measures of EEG functional connectivity and their temporal variability in different resting states. METHODS: EEGs from sixteen cortical regions were recorded at rest during eyes-closed (EC) and eyes-open (EO) in 10 male combined-type ADHD subjects and 12 healthy male controls. The mean global connectivity (CM) of each region and its temporal variability (CV) were estimated from a number of EEG segments recorded in both states. Connectivity indices between regions were calculated using the magnitude squared coherence (Coh) in the delta(δ)/theta(θ)/alpha(α)/beta(ß) frequency bands and the nonlinear index (L) of generalized synchronization. RESULTS: The CM did not present between-group differences in any region or state. However, the CV exhibited state-independent differences between both groups (ADHD>controls) mainly in frontal and parieto-occipital regions for all indices except Coh(α). Within group, only the CV-Coh(θ) of the centro-temporal region increased significantly for the ADHD subjects from EC to EO (p<0.001) and was greater than controls in EO (p<0.001). CONCLUSIONS: The CV of index-L and of Coh(θ) seem to be the best state-independent and -dependent measurements, respectively, to discriminate ADHDs from control subjects using resting state EEG data. SIGNIFICANCE: The underlying neural dysfunctions producing the ADHD seem better reflected by the CV measurements.

Comparing generalized and phase synchronization in cardiovascular and cardiorespiratory signals.

We made use of multivariate nonlinear analysis methods to study the interdependence between the cardiac interval variability and both the respiratory activity and the systolic pressure in rats. The study was carried out in basal conditions and after the application of different drugs affecting the cardiovascular system. The results showed that there are changes both in the extent and in the directionality of such interdependences because of the drugs. The inhibition of the NO and the parasympathetic blockade changed the cardiovascular coordination, with the latter one also modifying the interdependence between the cardiac interval and the respiratory signal. This suggests that the nonlinear approach might be very helpful to explore the interaction between subsystems of the cardiovascular control system.

Electroencephalography signatures of attention-deficit/hyperactivity disorder: clinical utility.

The techniques and the most important results on the use of electroencephalography (EEG) to extract different measures are reviewed in this work, which can be clinically useful to study subjects with attention-deficit/hyperactivity disorder (ADHD). First, we discuss briefly and in simple terms the EEG analysis and processing techniques most used in the context of ADHD. We review techniques that both analyze individual EEG channels (univariate measures) and study the statistical interdependence between different EEG channels (multivariate measures), the so-called functional brain connectivity. Among the former ones, we review the classical indices of absolute and relative spectral power and estimations of the complexity of the channels, such as the approximate entropy and the Lempel-Ziv complexity. Among the latter ones, we focus on the magnitude square coherence and on different measures based on the concept of generalized synchronization and its estimation in the state space. Second, from a historical point of view, we present the most important results achieved with these techniques and their clinical utility (sensitivity, specificity, and accuracy) to diagnose ADHD. Finally, we propose future research lines based on these results.

Applications of fractal and non-linear time series analysis to the study of short-term cardiovascular control.

The short-term cardiovascular control system is reviewed from the analysis of the heart rate, respiration and blood pressure beat-to-beat variability signals. The present state of the art concerning fractal and non-linear techniques as applied to the cardiovascular system and the differences between both approaches are highlighted. We present results obtained in mammals from statistics, such as the fractal exponent, the correlation dimension or the maximal Lyapunov exponent and discuss the convenience of these indexes for characterizing the irregularity present in the signals. Finally, the interdependence between the systems involved in the cardiovascular control is addressed. Recent results obtained from interdependence indexes between the cardio, respiratory and vascular signals are discussed and their convenience in physiological studies and clinical applications are stressed.

Non-linear asymmetric interdependencies in the electroencephalogram of healthy term neonates during sleep.

The multichannel electroencephalograph (EEG) of six healthy term neonates was recorded during awake as well as during active and quiet sleep. The existence and nature of the interdependencies among the different brain areas were studied by means of a multivariate variant of the surrogate data method. Such interdependencies were then quantified by using the coherence function and a newly developed non-linear index. The results showed that during quiet sleep these interdependencies were mostly non-linear, asymmetric and greater than those found during both awake and active sleep. We conclude that the index might be useful to define patterns of EEG interdependencies in healthy neonates, thereby allowing the early detection of brain dysfunctions.

Evidence of state-dependent interhemispheric relationships in lizard EEG during the awake state.

The electroencephalogram (EEG) from both hemispheres of eight Canary lizards Gallotia galloti was registered at 25 degrees C and 35 degrees C during awake state with open eyes (OE) and closed eyes. The possible interdependence between the recorded EEGs was assessed by means of newly developed methods of multivariate nonlinear time-series analysis. The interdependence turned out to be significant and greater for the OE state at both temperatures, although it was of linear type in most of the cases. We conclude that the methods can be successfully applied to study the interdependence between noisy, low-amplitude EEGs.

Performance analysis of univariate and multivariate EEG measurements in the diagnosis of ADHD.

OBJECTIVE: To investigate the performance of univariate and multivariate EEG measurements in diagnosing ADHD subjects in a broad age range. METHODS: EEG from eight cortical regions were recorded at rest during eyes open and eyes closed in 22 male ADHD subjects of combined type and 21 healthy male controls (age range 4-15 years). Univariate and interdependence measurements calculated from the frequency domain and from the reconstructed state spaces of EEG signals were computed, and their performance in discriminating ADHD from healthy subjects was analyzed. RESULTS: Significant between-group differences in univariate measures were age-dependent. However, certain interdependence inter-hemispheric measures during eyes closed showed significant, age-independent between-groups differences. Among them, coherence in the beta band between inter-occipital regions and between left/occipital-right/central regions provided an overall accuracy classification rate of 74.4%. Even greater accuracy (86.7%) was obtained by an interdependence index of generalized synchronization between left/occipital-right/central regions and left/central-right/temporal regions. CONCLUSIONS: EEG beta coherence and especially the degree of generalized synchronization between a few inter-hemispheric regions during resting state with eyes closed allow a high accuracy classification rate of ADHD subjects. SIGNIFICANCE: Changes in inter-hemispheric EEG functional brain connectivity at rest are useful for ADHD diagnosis in a broad age range.

Assessment of electroencephalographic functional connectivity in term and preterm neonates.

OBJECTIVE: To study how functional connectivity of neonate EEG during sleep is assessed by different interdependence indices and to analyze its dependence on conceptional (CA), gestational (GA) and/or chronological age (CRA). METHODS: EEG data from eight cortical regions were recorded during active (AS) and quiet sleep (QS) in three groups of seven neonates each: preterm (PT; GA: 33-34 weeks; CA: 39-40 weeks), junior-term (JT; GA: 38-39 weeks; CA: 39-40 weeks) and senior-term neonates (ST; GA: 38-39 weeks; CA: 44-45 weeks). EEG functional connectivity was assessed by means of the coherence function (its magnitude (MSC) and its imaginary part (IMC)) and a measure of phase synchronization called phase lag index (PLI). RESULTS: Inter-hemispheric connectivity: (a) during AS in the beta band, the MSC of the ST group was greater than that of the PT group for the temporal region; (b) during QS in the delta band, both PLI and IMC of the ST group were different to those of the PT group for the frontopolar and central regions, whereas ST-JT differences were only found for PLI. Intra-hemispheric connectivity: (a) during AS in the beta band the MSC of the ST group was greater than that of the PT group for the left frontopolar-centrotemporal and right occipital-centrotemporal regions; (b) during QS in the beta band, both IMC and PLI were different for the JT group than for the PT and the ST groups for the right and left occipital-centrotemporal regions. CONCLUSIONS: EEG inter- and intra-hemispheric functional connectivity in neonates during sleep changes with the CA and CRA in delta and beta bands. SIGNIFICANCE: The neonate's brain development during the first weeks of life can be traced from changes in the characteristics of EEG functional connectivity.

Nonlinearity and fractality in the variability of cardiac period in the lizard, Gallotia galloti: effects of autonomic blockade.

Both nonlinear and fractal properties of beat-to-beat R-R interval variability signal (RRV) of freely moving lizards (Gallotia galloti) were studied in baseline and under autonomic nervous system blockade. Nonlinear techniques allowed us to study the complexity, chaotic behavior, nonlinearity, stationarity, and regularity over time of RRV. Scaling behavior of RRV was studied by means of fractal techniques. The autonomic nervous system blockers used were atropine, propranolol, prazosin, and yohimbine. The nature of RRV was linear in baseline and under beta-, alpha(1)- and alpha(2)-adrenoceptor blockades. Atropine changed the linear nature of RRV to nonlinear and increased its stationarity, regularity and fractality. Propranolol increased the complexity and chaotic behavior, and decreased the stationarity, regularity, and fractality of RRV. Both prazosin and yohimbine did not change any of the nonlinear and fractal properties of RRV. It is suggested that 1) the use of both nonlinear and fractal analysis is an appropriate approach for studying cardiac period variability in reptiles; 2) the cholinergic activity, which seems to make the alpha(1)-, alpha(2)- and beta-adrenergic activity interaction unnecessary, determines the linear behavior in basal RRV; 3) fractality, as well as both RRV regularity and stationarity over time, may result from the balance between cholinergic and beta-adrenergic activities opposing actions; 4) beta-adrenergic activity may buffer both the complexity and chaotic behavior of RRV, and 5) neither the alpha(1)- nor the alpha(2)-adrenergic activity seem to be involved in the mediation of either nonlinear or fractal components of RRV.

Maturational changes in the interdependencies between cortical brain areas of neonates during sleep.

This work aims at assessing the maturational changes in the interdependence between the activities of different cortical areas in neonates during active sleep (AS) and quiet sleep (QS). Eight electroencephalography (EEG) channels were recorded in 3 groups of neonates of increasing postmenstrual age. The average linear (AVL) and average nonlinear (AVN) interdependencies of each electrode region with the remaining ones were calculated using the coherence function and a recently developed index of nonlinear coupling between 2 signals in their state spaces, respectively. In theta band, AVL increased with neonate's age for central and temporal regions during QS. In beta band, AVL increased for most cortical regions during QS and a parallel decrease of AVL with neonate's age was found during AS. For all regions, beta AVL was greater in AS than in QS in preterm neonates but the reverse happened in older term neonates. Contrarily to AVL, AVN decreased with age during QS for most cortical regions. Surrogate data test showed that the interdependencies were nonlinear in preterm and younger term neonates but in older term both linear and nonlinear interdependencies coexisted. It is concluded that neonatal maturation is associated with changes in the magnitude and character of the EEG interdependencies during sleep.

Time-related interdependence between low-frequency cortical electrical activity and respiratory activity in lizard, Gallotia galloti.

Electroencephalograms of medial cortex and electromyograms of intercostal muscles (EMG-icm) were simultaneously recorded in the lizard, Gallotia galloti, during two daily time periods (at daytime, DTP: 1200-1600 h; by night, NTP: 0000-0400 h), to investigate whether a relationship exists between the respiratory and cortical electrical activity of reptiles, and, if so, how this relationship changes during the night rest period. Testing was carried out by studying interdependence between cortical electrical and respiratory activities, by means of linear and nonlinear signal analysis techniques. Both physiological activities were evaluated through simultaneous power signals, derived from the power of the low-frequency band of the electroencephalogram (pEEG-LF), and from the power of the EMG-icm (pEMG-icm), respectively. During both DTP and NTP, there was a significant coherence between both signals in the main frequency band of pEMG-icm. During both DTP and NTP, the nonlinear index N measured significant linear asymmetric interdependence between pEEG-LF and pEMG-icm. The N value obtained between pEEG-LF vs. pEMG-icm was greater than the one between pEMG-icm vs. pEEG-LF. This means that the system that generates the pEEG-LF is more complex than the one that generates the pEMG-icm, and suggests that the temporal variability of power in the low-frequency cortical electrical activity is driven by the power of the respiratory activity.

Heterosis in the hybridisation between the monoecious and dioecious subspecies ofEcballium elaterium (L.) Richard.

By means of a statistical analysis carried out on a number of samples grown in balanced incomplete blocks, respectively corresponding to filial generations which (pure, hybrid or backcross) can be discerned in the hybridisation between the monoecious and dioecious subspecies of the Mediterranean wild cucurbitaceaeEcballium elaterium (L.) Richard, the possible presence of a group of polygenes which modify or regulate the durability of the life of the plants has been investigated, studying especially the most frequent and the most characteristic observable effect of polygenes, the heterosis or hybrid vigour. Experimental results indicates that there is heterosis with respect to the survival of the individual plant. The occurrence of the phenomenon of heterosis is experimental evidence of the presence of a system of polygenes which has influence upon this particular quality of the plant (survival). Every one of these polygenes in the genotype of a subspecies has alleles somehow different from those of another (ofE. elaterium).

System of pleiotropic polygenes in the Cucurbitacea Ecballium elaterium (L.) Rich. related to durability and size of plant.

The statistical association between the characters "life durability of plant" and "size of plant" observed in a set of samples - cultivated forming a system of randomly balanced incomplete blocks - and corresponding to filial generations (pure, hybrid or backcross) from hybridization between the monoecious subspecies and the dioecious subspecies of the Cucurbitacea Ecballium elaterium (L.) Rich, respectively, is in concordance with the hypothesis that the system of polygenes governing the life durability of the plant in this species and the system of polygenes governing the size of the plants belong to the same system of polygenes. This system of pleiotropic polygenes governs the size and life durability of the plants at the same time.