Signals of resilience to ocean change: high thermal tolerance of early stage Antarctic sea urchins (Sterechinus neumayeri) reared under present-day and future pCO2 and temperature

We tested the hypothesis that development of the Antarctic urchin Sterechinus neumayeri under future ocean conditions of warming and acidification would incur physiological costs, reducing the tolerance of a secondary stressor. The aim of this study is twofold: (1) quantify current austral spring temperature and pH near sea urchin habitat at Cape Evans in McMurdo Sound, Antarctica and (2) spawn S. neumayeri in the laboratory and raise early developmental stages (EDSs) under ambient (-0.7 °C; 400 µatm pCO2) and future (+2.6 °C; 650 and 1,000 µatm pCO2) ocean conditions and expose four EDSs (blastula, gastrula, prism, and 4-arm echinopluteus) to a one hour acute heat stress and assess survivorship. Results of field data from 2011 to 2012 show extremely stable inter-annual pH conditions ranging from 7.99 to 8.08, suggesting that future ocean acidification will drastically alter the pH-seascape for S. neumayeri. In the laboratory, S. neumayeri EDSs appear to be tolerant of temperatures and pCO2 levels above their current habitat conditions. EDSs survived acute heat exposures >20 °C above habitat temperatures of -1.9 °C. No pCO2 effect was observed for EDSs reared at -0.7 °C. When reared at +2.6 °C, small but significant pCO2 effects were observed at the blastula and prism stage, suggesting that multiple stressors are more detrimental than single stressors. While surprisingly tolerant overall, blastulae were the most sensitive stage to ocean warming and acidification. We conclude that S. neumayeri may be unexpectedly physiologically tolerant of future ocean conditions.

Abundance patterns and isotopic signals of morphotypes of Globigerinoides ruber

The chemical composition of shells of the planktonic foraminifer Globigerinoides ruber (white) is frequently used to determine past sea surface conditions. Recently, it has been shown that arbitrarily defined morphotypes within this species exhibit different chemical and isotopic signatures. Here, we investigate the occurrence through time and in space of morphological types of G. ruber (white) in late Quaternary and Holocene sediments of the central and the eastern Mediterranean Sea. In 115 samples representing two distinct time intervals (MIS 1-2 and MIS 9-12) at ODP Site 964 and the piston core GeoTü-SL96, we have defined three morphological types within this species and determined their relative abundances and stable isotopic composition. A quantitative analysis of morphological variation within G. ruber (white) in four samples revealed that the subjectively defined morphotypes occupy separate segments of a continuous and homogenous morphospace. We further show that the abundance of the morphotypes changes significantly between glacials and interglacials and that the three morphotypes of G. ruber show significant offsets in their stable isotopic composition. These offsets are consistent within glacial and interglacial stages but their sign is systematically reversed between the two Sites. Since the isotopic shifts among the three G. ruber morphotypes are systematic and often exceed 1per mil, their understanding is essential for the interpretation of all G. ruber-based proxy records for the paleoceanographic development of the Mediterranean during the late Quaternary.

A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.

Quantitative evaluation of artifact removal in real magnetoencephalogram signals with blind source separation

The magnetoencephalogram (MEG) is contaminated with undesired signals, which are called artifacts. Some of the most important ones are the cardiac and the ocular artifacts (CA and OA, respectively), and the power line noise (PLN). Blind source separation (BSS) has been used to reduce the influence of the artifacts in the data. There is a plethora of BSS-based artifact removal approaches, but few comparative analyses. In this study, MEG background activity from 26 subjects was processed with five widespread BSS (AMUSE, SOBI, JADE, extended Infomax, and FastICA) and one constrained BSS (cBSS) techniques. Then, the ability of several combinations of BSS algorithm, epoch length, and artifact detection metric to automatically reduce the CA, OA, and PLN were quantified with objective criteria. The results pinpointed to cBSS as a very suitable approach to remove the CA. Additionally, a combination of AMUSE or SOBI and artifact detection metrics based on entropy or power criteria decreased the OA. Finally, the PLN was reduced by means of a spectral metric. These findings confirm the utility of BSS to help in the artifact removal for MEG background activity.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

Brain rhythms alterations and their effect in functional networks: A simultaneous EEG/fMRI study in Fixation-off epilepsy

Fixation-off sensitivity (FOS) denotes the forms of EEG abnormalities, which are elicited by elimination of central vision or fixation. The phenomenon seems to depend on variables that modulate the alpha rhythm, however, the cerebral mechanisms underlying FOS remain unclear [1]. The scarce previous fMRI findings related to FOS have shown activation in extrastriate cortex [2] and also in frontal areas [3][4]. On the other hand, simultaneous EEG-fMRI technique has been used to assess the relationship between spontaneous power fluctuations of electrical rhythms and associated fMRI signal modulations. These studies have identified that lateral frontoparietal networks show a negative correlation with alpha band in healthy subjects. This neuroanatomical pattern is related to attentional processes and cognitive resources. Moreover, a sub-beta band (17-23 Hz) has been identified with posterior cingulate, temporoparietal junction and dorso-medial prefrontal cortex activations, which correspond to the DMN [5][6].

Effects of binaural stimulation in attention and EEG

When two pure tones of slightly different frequency are presented separately to each ear, the listener perceives a third single tone with amplitude variations at a frequency that equals the difference between the two tones, this perceptual illusion is known as binaural auditory beat. There are anecdotal reports that suggest that the binaural beat can entrain EEG activity and may affect the arousal levels, although few studies have been published. There is a need for double-blind, well-designed studies in order to establish a solid foundation for these sounds, as most of the documented benefits come from self-reported cases that could be affected by placebo effect. As BB’s are a cheap technology (it even exists a free open source programmable bin aural-beat generator on the internet named Gnaural), any achievement in this area could be of public interest. The aim in our research was to explore the potential of BB’s in a particular field: tasks that require focus and concentration. In order to detect changes in the brain waves that could relate to any particular improvement, EEG recordings of a small sample of individuals were also obtained. In this study we compare the effect of different binaural stimulation in 7 EEG frequency ranges, 78 participants were exposed to 20 min binaural beat stimulation. The effects were obtained both qualitative with cognitive test and quantitative with EEG analysis. Results suggest no significant statistical improvement in 20 min stimulation.

Analysis and design of multirate synchronous sampling schemes for sparse multiband signals

We consider the problem of developing efficient sampling schemes for multiband sparse signals. Previous results on multicoset sampling implementations that lead to universal sampling patterns (which guarantee perfect reconstruction), are based on a set of appropriate interleaved analog to digital converters, all of them operating at the same sampling frequency. In this paper we propose an alternative multirate synchronous implementation of multicoset codes, that is, all the analog to digital converters in the sampling scheme operate at different sampling frequencies, without need of introducing any delay. The interleaving is achieved through the usage of different rates, whose sum is significantly lower than the Nyquist rate of the multiband signal. To obtain universal patterns the sampling matrix is formulated and analyzed. Appropriate choices of the parameters, that is the block length and the sampling rates, are also proposed.

Design of universal multicoset sampling patterns for compressed sensing of multiband sparse signals

Many problems in digital communications involve wideband radio signals. As the most recent example, the impressive advances in Cognitive Radio systems make even more necessary the development of sampling schemes for wideband radio signals with spectral holes. This is equivalent to considering a sparse multiband signal in the framework of Compressive Sampling theory. Starting from previous results on multicoset sampling and recent advances in compressive sampling, we analyze the matrix involved in the corresponding reconstruction equation and define a new method for the design of universal multicoset codes, that is, codes guaranteeing perfect reconstruction of the sparse multiband signal.

Quantum optical signals in telecommunication networks

Introducción a una red óptica metropolitana cuántica donde señales cuánticas y convencionales son multiplexadas en longitud de onda utilizando bandas separadas del espectro óptico. El enrutado se realiza con componentes pasivos para no perturbar los qubits. Se estudian dos redes: red de acceso WDM-PON y red metropolitana completa con backbone DWDM y redes de acceso WDM-PON.

Signals and Systems Students trainer.

Higher education students demand fast feedback about their assignments and the opportunity to repeat them in case they do in a wrong way. Here a computer based trainer for Signals and Systems students is presented. An application, that automatically generates and assesses thousands of numerically different versions of several Signals and Systems problems have been developed. This applet guides the students to find the solution and automatically assesses and grades the students proposed solution. The students can use the application to practice in solving several types of Signals and Systems basic problems. After selecting the problem type, the student introduces a seed and the application generates a numerical version of the selected problem. Then the application presents a sequence of questions that the students must solve and the application automatically assess their answers. After solving a given problem, the students can repeat the same numerical variation of the problem by introducing the same seed to the application. In this way, they can review their solution with the help of the hints given by the application for wrong solutions. This application can also be used as an automatic assessment tool by the instructor. When the assessment is made in a controlled environment (examination classroom or laboratory) the instructor can use the same seed for all students. Otherwise, different seeds can be assigned to different students and in this way they solve different numerical variation of the proposed problem, so cheating becomes an arduous task. Given a problem type, the mathematical or conceptual difficulty of the problem can vary depending on the numerical values of the parameters of the problem. The application permits to easily select groups of seeds that yield to numerical variations with similar mathematical or conceptual difficulty. This represents an advantage over a randomised task assignment where students are asked to solve tasks with different difficulty.

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Effect of binaural stimulation on attention and EEG

When two pure tones of slightly different frequency are presented separately to each ear, the listener perceives a third single tone with amplitude variations at a frequency that equals the difference between the two tones; this perceptual illusion is known as the binaural auditory beat (BB). There are anecdotal reports that suggest that the binaural beat can entrain EEG activity and may affect the arousal levels, although few studies have been published. There is a need for double-blind, well-designed studies in order to establish a solid foundation for these sounds, as most of the documented benefits come from self-reported cases that could be affected by placebo effect. As BBs are a cheap technology (it even exists a free open source programmable binaural- beat generator on the Internet named Gnaural), any achievement in this area could be of public interest. The aim in our research was to explore the potential of BBs in a particular field: tasks that require focus and concentration. In order to detect changes in the brain waves that could relate to any particular improvement, EEG recordings of a small sample of individuals were also obtained. In this study we compare the effect of different binaural stimulation in 7 EEG frequency ranges. 78 participants were exposed to 20-min binaural beat stimulation. The effects were obtained both quali- tative with cognitive test and quantitative with EEG analysis. Results suggest no significant statistical improvement in 20-min stimulation.