Delta Components Research Articles

Mindfulness meditation alters neural oscillations independently of arousal

Neuroscience has identified that mindfulness meditation induces a state of relaxed alertness, characterised by changes in theta and alpha oscillations and reduced sympathetic arousal, although the underlying mechanisms remain unclear. This study aims to address this gap by examining changes in neural oscillations and arousal during mindfulness meditation using both traditional and data-driven methods. Fifty-two healthy young adults underwent electroencephalography (EEG) and skin conductance level (SCL) recordings during resting baseline and mindfulness meditation conditions, both conducted with eyes closed. The EEG data revealed a significant decrease in traditional alpha (8–13 Hz) amplitude during mindfulness meditation compared to rest. However, no significant differences were observed between conditions in traditional delta, theta, beta, or gamma amplitudes. Frequency Principal Components Analysis (fPCA) was employed as a data-driven approach, identifying six components consistent across conditions. A complex delta-theta-alpha component significantly increased during mindfulness meditation. In contrast, low alpha (~9.5 Hz) and low alpha-beta (~11 Hz) components decreased significantly during mindfulness meditation. No significant differences were observed between conditions in the delta, high alpha, and high alpha-beta components. Additionally, there were no significant differences in SCL between conditions, nor were there correlations between traditional alpha or fPCA components and SCL. These findings support the conceptualisation of mindfulness meditation as a state of relaxed alertness, characterised by changes in neural oscillations likely associated with attention and awareness. However, the observed changes do not appear to be driven by arousal.

When the lava meets the sea: emplacement of the 2–4 ka San Bartolo lava flow field, Stromboli volcano (Italy)

When a lava flow enters a body of water, either a lake, sea, river or ocean, explosive interaction may arise. However, when it is an 'a'ā lava flow entering water, a more complex interaction occurs, that is very poorly described and documented in literature. In this paper, we analysed the 2–4 ka San Bartolo lava flow field emplaced on the north flank of Stromboli volcano, Italy. The lava flow field extends from ~ 650 m a.s.l. where the eruptive fissure is located, with two lava channels being apparent on the steep down to the coast. Along the coast the lava flow field expands to form a lava delta ~ 1 km wide characterised by 16 lava ‘Flow’ units. We performed a field survey to characterise the features of lava entering the sea and the associated formation of different components and magnetic measurements to infer the flow fabrics and emplacement process of the lava flow system. We measured the density, porosity and connectivity of several specimens to analyse the effect of lava-water interaction on the content in vesicles and their connectivity and conducted a macroscopic componentry analysis (clast count) at selected sites to infer the character of the eroded offshore segment of the lava flow field and its component flow units. The collected data allowed us to define the main components of a lava delta fed by 'a'ā lava flows, with its channels, littoral units, ramps, lava tubes, and inflated pāhoehoe flows controlled by the arterial 'a'ā flow fronts. The spatial organisation of these components allowed us to build a three-step descriptive model for 'a'ā entering a water. The initial stage corresponds to the entry of channel-fed 'a'ā lava flow into the sea which fragments to form metric blocks of 'a'ā lava. Continued lava supply to the foreshore causes flow units to stall while spreading over this substrate. Subsequent 'a'ā lava flow units ramp up behind the stalled flow front barrier. Lava tubes extending through the stalled flow barrier feed the seaward extension of a bench made of several pāhoehoe flow units.

Haemodynamic Responses to Spontaneous Neural Activity on the Electroencephalogram in Preterm Infants.

Delta brushes are spontaneous neural activities observed in preterm electroencephalograms (EEGs) and are thought to reflect the activities of subplate neurons in the developing brain. We investigated the haemodynamic responses associated with delta brushes in five preterm infants at two time points (at 33 or 34, and 36weeks of postmenstrual age), using simultaneous EEG-functional near-infrared spectroscopy (NIRS). An automated detection algorithm was developed to identify the brush components of delta brushes in the bipolar EEG envelope; we placed eight EEG electrodes. An eight-channel NIRS device was placed around the head of each infant to measure changes in oxy- and deoxy-haemoglobin (Hb) concentrations. Haemodynamic grand averages were calculated for local brushes in each NIRS channel. We classified the responses into five patterns based on changes in oxy- and deoxy-Hb signals (positive in-phase/anti-phase, negative in-phase/anti-phase, and unclassified) and evaluated the relationship between the locations of NIRS measurements and those of brushes, as well as the haemodynamic response patterns and infant age at the time of recording. In all the 10 recordings, we found that positive responses (oxy-Hb increases) predominated, not only in the corresponding areas but also in remote areas. Particularly, notable responses were observed in the bilateral temporal areas. Among the positive responses, the proportion exhibiting an anti-phase pattern was 12% at 33 to 34weeks of postmenstrual age and 54% at 36weeks of postmenstrual age. Our unexpected finding of remarkable temporal responses to localised neuronal activity supports the hypothesis that the insula is the most strongly interconnected hub in the developing brain.

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions.

Sleep deprivation, a widespread phenomenon that affects one-third of normal American adults, induces adverse changes in physical and cognitive performance, which in turn increases the occurrence of accidents. Sleep deprivation is known to increase resting blood pressure and decrease muscle sympathetic nerve activity. Monitoring changes in the interplay between the central and autonomic sympathetic nervous system can be a potential indicator of human's readiness to perform tasks that involve a certain level of cognitive load (e.g., driving). The electroencephalogram (EEG) is the standard to assess the brain's activity. The electrodermal activity (EDA) is a reflection of the general state of arousal regulated by the activation of the sympathetic nervous system through sweat gland stimulation. In this work, we calculated the mutual information between EDA and EEG recordings in order to consider linear and non-linear interactions and provide an insight of the relationship between brain activity and peripheral autonomic sympathetic activity. We analyzed EEG and EDA data from ten participants performing four cognitive tasks every two hours during 24 h (12 trials). We decomposed EEG data into delta, theta, alpha, beta, and gamma spectral components, and EDA into tonic and phasic components. The results demonstrate high values of mutual information between the EDA and delta component of EEG, mainly in working memory tasks. Additionally, we found an increase in the theta component of EEG in the presence of fatigue caused by sleep deprivation, the alpha component in tasks demanding inhibition and attention, and the delta component in working memory tasks. In terms of the location of brain activity, most of the tasks report high mutual information in frontal regions in the initial trials, with a trend to decrease and become uniform for all the nine analyzed EEG channels as a consequence of the sleep deprivation effect. Our results evidence the interplay between central and sympathetic nervous activity and can be used to mitigate the consequences of sleep deprivation.

Adaptive Governance of River Deltas Under Accelerating Environmental Change.

Many deltas are increasingly threatened by environmental change, including climate change-induced sea-level rise, land subsidence and reduced sediment delivery. Dealing with these challenges is a pressing necessity because deltas are home to many people and are important centres for economic and agricultural development. Successfully adapting to climate change requires a social-ecological system (SES) perspective, emphasising that social and ecological components of deltas are intertwined. Various modes of governance have been suggested to deal with uncertainty associated with environmental change in SESs, such as adaptive governance. Adaptive governance underlines the need for governance systems to be flexible enough to adapt to variable degrees of uncertainty in SESs. In this paper, we analyse the Dutch Delta Programme (DDP) and the Mekong Delta Plan (MDP) to explore their strengths and limitations relating to nine principles for adaptive governance proposed by DeCaro and others. We evaluate the suitability of this framework for the Rhine and Mekong deltas and contribute to the current understanding of delta governance in light of climate change. Most of the principles outlined by DeCaro and others are present in the DDP and MDP. However, adaptive governance is context dependent. The Rhine and Mekong deltas display different obstacles to adaptive governance, some of which are not sufficiently emphasised in this academic adaptive governance framework. Instead of relying on one framework as a blueprint for adaptive governance, using principles from different frameworks depending on the case may be the best approach for addressing environmental challenges in deltas.

Comparative analysis of background EEG activity based on MRI findings in neonatal hypoxic-ischemic encephalopathy: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study

BackgroundIt is important to assess the degree of brain injury and predict long-term outcomes in neonates diagnosed with hypoxic-ischemic encephalopathy (HIE). However, routine studies, including magnetic resonance imaging (MRI) and conventional encephalography (EEG) or amplitude-integrated EEG (aEEG), have their own limitations in terms of availability and accuracy of evaluation. Recently, quantitative EEG (qEEG) has been shown to improve the predictive reliability of neonatal HIE and has been further refined with brain mapping techniques.MethodsWe investigated background EEG activities in 29 neonates with HIE who experienced therapeutic hypothermia, via qEEG using a distributed source model. MRI images were evaluated and classified into two groups (normal-to-mild injury vs moderate-to-severe injury), based on a scoring system. Non-parametric statistical analysis using standardized low-resolution brain electromagnetic tomography was performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between the two groups.ResultsElectrical neuronal activities were significantly lower in the moderate-to-severe injury group compared with the normal-to-mild injury group. Background EEG activities in moderate-to-severe HIE were most significantly reduced in the temporal and parietal lobes. Quantitative EEG also revealed a decrease in background activity at all frequency bands, with a maximum in decrease in the delta component. The maximum difference in current density was found in the inferior parietal lobule of the right parietal lobe for the delta frequency band.ConclusionsOur study demonstrated quantitative and topographical changes in EEG in moderate-to-severe neonatal HIE. They also suggest possible implementation and evaluation of conventional EEG and aEEG in neonatal HIE. The findings have implications as biomarkers in the assessment of neonatal HIE.

EEG and ECG Power Spectrum Analysis of Sedative Effects on Propofol-Anesthetized Rats with Electroacupuncture.

Background In previous studies, electroacupuncture (EA) with 2/15 Hz has been shown to enhance the sedative effects in general anesthesia patients. Central lateral thalamic stimulation of 50 Hz showed an arousal effect in macaques. Therefore, it is worth studying the sedative effect of EA at peripheral acupoints with different frequencies, especially the frequency of around 50 Hz. Methods Rats were anesthetized under the constant infusion of propofol and EA at Zusanli (ST36) and Neiguan (PC6) locations. Electroencephalography (EEG) and heart rate were continuously recorded before and after the intervention by EA in the C group (control), LEA group (low-frequency group, 2/15 Hz diffuse/dense wave EA stimulation), and HEA group (high-frequency group, 50 Hz stimulation). Results In the LEA group, a significant increase in the power of the delta component with a decrease in the alpha component (p < 0.05) was observed after EA stimulation. In the HEA group, significant increases in the powers of alpha and beta components of EEG (p < 0.05) and a decrease in the delta component of EEG were observed (p < 0.05). The phenomenon is also shown in full-frequency waves. In addition, a significant decrease in the low-frequency/high-frequency ratio parameter was observed in the LEA group. Conclusions EA at bilateral ST36 and PC6 can enhance the sedative effects of propofol anesthesia in low-frequency stimulation but lighten the sedative effects in high-frequency (50 Hz) stimulation. The sympathetic-vagal balance was affected due to low-frequency EA.

Locked-in and living delta pathways in the Anthropocene

Delta systems are fundamental to the persistence of large human populations, food systems and ecosystem processes. Structural changes in natural and social components of deltas, emerging from past land-use changes, have led deltas to become locked-in loosing the ability to transform back into living deltas, and making them more at risk. We propose a framework to assess whether deltas become locked-in by changes in natural or social infrastructure, by examining the dynamic coupling between population and land-use development over 300 years for 48 deltas globally. We find that 46% of the deltas are defined as living, where population, irrigation, and cropland are correlated. Of the 54% locked-in deltas, 21% show changes in natural infrastructure to cropland (n = 6) or irrigation (n = 4), and 33% (n = 16) show changes in social infrastructure. Most locked-in deltas are in Europe but also in other continents due to decoupled development of population and cropland. While, locked-in deltas due to changes in natural infrastructure have highest average risks, those with changes in social infrastructure and the living deltas have highest risks from future relative sea level rise. These results show that deltas have varying natural and social components derived from a 300 years historical perspective, which are not taken into account in risk assessments for global deltas.

Health risk assessment of toxicants in Meriç River Delta Wetland, Thrace Region, Turkey

In the current research, water quality of Meric River Delta was evaluated using some toxic element risk assessment indices. Samples were collected from 24 locations and nickel (Ni), chromium (Cr), arsenic (As), zinc (Zn), lead (Pb), copper (Cu) and cadmium (Cd) accumulations in delta components were read using an ICP-MS. Water quality index (WQI), heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and degree of contamination index (Cdeg) were applied to detected data for assessing the water quality. Also, the toxic element concentrations in water were assessed in terms of public health using some health risk assessment methods including hazard index (HI), hazard quotient (HQ) and cancer risk (CR). According to the results of WQI, HPI, HEI and Cdeg, Ni and As were recorded as most dangerous toxicants among the investigated elements and Gala Lake was recorded as most effected delta component. According to the results HQs and CR, As was recorded as the most dangerous toxicant among the investigated elements and Gala Lake and Ergene River were recorded as the most effected delta components.

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds

Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.

Data-driven derivation of natural EEG frequency components: An optimised example assessing resting EEG in healthy ageing

BackgroundThe majority of electroencephalographic (EEG) investigations in normal ageing have determined EEG spectra from epochs recorded in the eyes-closed (EC) and/or eyes-open (EO) resting states, and summed amplitudes or power estimates within somewhat-arbitrary and/or inconsistently defined traditional frequency band limits. New methodNatural frequency components were sought using a data-driven frequency Principal Components Analysis (f-PCA) approach, optimised to reduce between-condition and between-group misallocation of variance. Frequency component correspondence was screened using the Congruence Coefficient and topographic correlations for potential matches on Condition and/or Group. The amplitudes of corresponding natural components were then explored as a function of these independent variables. ResultsSeparate f-PCAs with Young and Older adults’ EC and EO data each yielded between six and nine components that peaked across the traditional delta to beta band ranges. Across these, two components were matched on Group and Condition, while a further six were matched on Condition (within-groups), and four on Group (within-conditions). Comparison with Existing MethodsMultiple frequency components were found within the traditional bands, and provided a wider perspective in terms of additional natural component details. In addition to novel insights, the well-documented age-related spectral reductions were seen in the common delta component, and in one EC (but no EO) alpha component. ConclusionsThis combination of optimised f-PCA approach and component screening procedure has wide potential in the EEG field beyond the ageing topic explored here, being applicable across an extensive range of studies using EEG oscillations to explore aspects of cognitive processing and individual differences.

T and B Cell Immune Responses to Influenza Viruses in Pigs.

Influenza viruses are an ongoing threat to humans and are endemic in pigs, causing considerable economic losses to farmers. Pigs are also a source of new viruses potentially capable of initiating human pandemics. Many tools including monoclonal antibodies, recombinant cytokines and chemokines, gene probes, tetramers, and inbred pigs allow refined analysis of immune responses against influenza. Recent advances in understanding of the pig innate system indicate that it shares many features with that of humans, although there is a larger gamma delta component. The fine specificity and mechanisms of cross-protective T cell immunity have yet to be fully defined, although it is clear that the local immune response is important. The repertoire of pig antibody response to influenza has not been thoroughly explored. Here we review current understanding of adaptive immune responses against influenza in pigs and the use of the pig as a model to study human disease.

Feedback-Related Electroencephalogram Oscillations of Athletes With High and Low Sports Anxiety.

We investigated the relationship between performance-related anxiety and the neural response to error feedback that was delivered during the execution of a time estimation task. Using the Sport Anxiety Scale (SAS-2), we selected university athletes high and low in sports anxiety. Participants executed a time estimation task where they were instructed to estimate 1 s by pressing a button after a sound cue. They performed this task while their performance was being evaluated by an experimenter (evaluation condition) and also while alone (in a no-evaluation condition). We tested whether feedback-related brain activities may increase in amplitude in the evaluation condition compared to the control condition – especially for athletes who report high performance-related anxiety. We focused on oscillations of sub-delta, delta, and theta frequency bands phase-locked to the feedback onset. Time-frequency analyses revealed that the magnitude of both the sub-delta component (0.3–1.2 Hz) and the theta component (4–8 Hz) were larger in incorrect than correct trials. In addition, the theta component was smaller for athletes high in sports anxiety than for athletes low in sports anxiety. The delta component was overall larger for correct than incorrect feedback. Further, athletes high in sports anxiety exhibited a larger delta component (1.5–3.5 Hz) for correct feedback in the evaluation condition than in the no-evaluation condition. Our results suggest that evaluation by others may increase the delta oscillation associated with correct feedback processing – especially among athletes high in sports anxiety.

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, Fst and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.

Asymmetric Effects of Subaerial and Subaqueous Basement Slopes on Self‐Similar Morphology of Prograding Deltas

AbstractDeltas form over basements of various slope configurations. While the morphodynamics of prograding deltas over single‐slope basements have been studied previously, our understanding of delta progradation over segmented basements is still limited. Here we use experimental and analytical approaches to investigate the deltaic morphologies developing over two‐slope basements with unequal subaerial and subaqueous slopes. For each case considered, the scaled profiles of the evolving delta collapse to a single profile for constant water and sediment influxes, allowing us to use the analytical self‐similar profiles to investigate the individual effects of subaerial/subaqueous slopes. Individually varying the subaerial/subaqueous slopes exerts asymmetric effects on the morphologies. Increasing the subaerial slope advances the entire delta; increasing the subaqueous slope advances the upstream boundary of the topset yet causes the downstream boundary to retreat. The delta front exhibits a first‐retreat‐then‐advance migrating trend with increasing subaqueous slope. A decrease in subaerial topset length is always accompanied by an increase in subaqueous volume fraction, no matter which segment is steepened. Applications are presented for estimating shoreline retreat caused by steepening of basement slopes, and estimating subaqueous volume and delta front using the observed topset length. The results may have implications for real‐world delta systems subjected to upstream tectonic uplift and/or downstream subsidence. Both scenarios would exhibit reduced topset lengths, which are indicative of the accompanied increases in subaqueous volume and signal tectonic uplift and/or subsidence that are at play. We highlight herein the importance of geometric controls on partitioning of sediment between subaerial and subaqueous delta components.

Cortical Auditory-Evoked Responses in Preterm Neonates: Revisited by Spectral and Temporal Analyses.

Characteristic preterm EEG patterns of "Delta-brushes" (DBs) have been reported in the temporal cortex following auditory stimuli, but their spatio-temporal dynamics remains elusive. Using 32-electrode EEG recordings and co-registration of electrodes' position to 3D-MRI of age-matched neonates, we explored the cortical auditory-evoked responses (AERs) after 'click' stimuli in 30 healthy neonates aged 30-38 post-menstrual weeks (PMW). (1) We visually identified auditory-evoked DBs within AERs in all the babies between 30 and 33 PMW and a decreasing response rate afterwards. (2) The AERs showed an increase in EEG power from delta to gamma frequency bands over the middle and posterior temporal regions with higher values in quiet sleep and on the right. (3) Time-frequency and averaging analyses showed that the delta component of DBs, which negatively peaked around 550 and 750 ms over the middle and posterior temporal regions, respectively, was superimposed with fast (alpha-gamma) oscillations and corresponded to the late part of the cortical auditory-evoked potential (CAEP), a feature missed when using classical CAEP processing. As evoked DBs rate and AERs delta to alpha frequency power decreased until full term, auditory-evoked DBs are thus associated with the prenatal development of auditory processing and may suggest an early emerging hemispheric specialization.

CARACTERISTICS OF TIME AND FREQUENCY EEG PATTERN IN CHILDREN AND ADOLESCENTS LIVING IN THE NORTH IN DIFFERENT AGE PERIODS

Features of CNS development have been investigated in children and adolescents living under the severe ecological conditions in the North of Russia. The original method for estimating a time structure of the EEG frequency components interrelations was used to study the dynamics of maturation of bioelectrical brain activity pattern and age-related changes of the interplay between the main EEG rhythms. It was found that the statistical structure of the interaction of the frequency components of EEG is undergoing a significant restructuring with age and has certain topography and gender differences. The period from 7 to 18 years of age is marked by decrease the probability of interaction of wave components of the main EEG frequency bands with components of delta and theta bands while simultaneously increasing interaction with the components of beta and alpha2 frequency bands. The dynamics of studied indices EEG manifested in the parietal, temporal and occipital regions of the cerebral cortex to the greatest extent. The largest sex-related differences in the EEG parameters occur in puberty. Functional core of the wave components interaction that maintain the structure of the frequency-temporal EEG pattern is formed to 16-18 years in girls in alpha2-beta1 range, while in boys - in alpha1-alpha2 range. Intensity of age-related rearrangements of the EEG pattern reflects the gradual maturation of electrogenesis in different brain structures and has individual features due to both genetic and environmental factors. Obtained quantitative indicators of formation with age of dynamic relationships between basic EEG rhythms permit to reveal children with disturbed or delayed development of the central nervous system.

Feature selection for robust automatic speech recognition: a temporal offset approach

Automatic speech recognition relies on extracting features at fixed intervals. In order to enhance these features with dynamical (delta) components, discrete derivatives are usually computed and added as features. However, derivative operations tend to be susceptible to noise. Our proposed method alleviates this problem by replacing these derivatives with nearby features selected on a per-frequency basis. In particular, we noted that, at low frequency, consecutive samples are highly correlated and more information can be gathered by looking at features farther away in time. We thus propose a strategy to perform this frequency-based selection and evaluate it on the Aurora 2 continuous-digits and connected-digits tasks using MFCC, PLPCC and LPCC standard features. The results of our experimentations show that our strategy achieved an average relative improvement of $$32.10\,\%$$32.10% in accuracy, with most gains in very noisy environments where the traditional delta features have low recognition rates.

Multistable perception in children: Prefrontal delta oscillations in the developing brain

The prefrontal cortex (PFC) is considered to be the primary source of attentional control during elementary visual processing as exemplified in perceptual ambiguity. Assuming that multistable perception activates a fronto-parietal network, we contrast the results of mature and developing cognitive systems to deduce the developmental status of underlying structures from behavioral performances and functional EEG parameters. We analyzed the topographical distribution, amplitude characteristics and inter-trial variability of a reversal-related delta response that accompanies perceptual switches between the two alternative percepts of an ambiguous motion pattern. Fourteen ten-year old children and an adult control group indicated changes of perceived motion directions by a button-press. EEG was recorded from frontal, central, parietal, and occipital locations of both hemispheres. Behavioral data shows a considerably lower reversal rate within the children sample, suggesting that the related mechanisms are not yet operating on an adult level. In contrast to findings in adults, the involved delta component emerges as part of an unspecific posterior activation, suggesting that a cortical specialization process has not been accomplished yet. On frontal locations the ten-year old children fail to yield a stable component. The synchronized fronto-parietal activity in adults may constitute the result of a specialization process that determined connection patterns and functionally tuned the involved areas. This implies a deficit in timing and temporal sequencing of neuronal activity in children, mainly attributable to a less functional differentiated PFC that has not been fully integrated yet into the cognitive ensemble.

Neutron-rich $^{208}$Pb nucleus with delta excitation under compression

The spherical Hartree-Fock approximation is applied to a no-core shell model with a realistic effective baryon-baryon interaction. The ground state properties of a heavy spherical neutron-rich doubly magic 208Pb nucleus under compression are investigated. It is found that the nucleus becomes more bound with the occurrence of Delta resonances. The creation of Delta increases as the compression is continuous. There is a considerable reduction in the compressibility when the Delta degree of freedom is activated. It is found that the Delta particle is the basic component of the 208Pb nucleus besides nucleons at the ground state without any compression. When the nucleus is compressed to about 4.31 times the ordinary density, the Delta component is sharply increased to about 14.4% of all baryons in the system. It is found that there is a radial density distribution for Delta at the ground state of 208Pb nucleus without any compression. The single particle energy levels are calculated and their behaviors are examined under compression too. A good agreement was obtained between the results of the effective Hamiltonian and the phenomenological shell model for the low lying single-particle spectra.