Signal-to-noise ratio of the MEG signal after preprocessing

Background Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. New method The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio between the mean signal amplitude (evoked field) and the standard error of the mean over trials. Results Recordings from 26 subjects obtained during and event-related visual paradigm with an Elekta MEG scanner were employed. Two methods were considered as first-step noise reduction: Signal Space Separation and temporal Signal Space Separation, which decompose the signal into components with origin inside and outside the head. Both algorithm increased the SNR by approximately 100%. Epoch-based methods, aimed at identifying and rejecting epochs containing eye blinks, muscular artifacts and sensor jumps provided an SNR improvement of 5–10%. Decomposition methods evaluated were independent component analysis (ICA) and second-order blind identification (SOBI). The increase in SNR was of about 36% with ICA and 33% with SOBI. Comparison with existing methods No previous systematic evaluation of the effect of the typical preprocessing steps in the SNR of the MEG signal has been performed. Conclusions The application of either SSS or tSSS is mandatory in Elekta systems. No significant differences were found between the two. While epoch-based methods have been routinely applied the less often considered decomposition methods were clearly superior and therefore their use seems advisable.

Background noise and its influence on the brain waves related to attention

In this work, we present a study whose objective is to prove the influence of background noise produced inside university facilities on the brain waves related to attention processes. Recordings of background noise were carried out in study areas inside university facilities. Volunteers were asked to perform an attention test without any background noise but also while being exposed to the sound recordings, and their cerebral activity was recorded through electroencephalography (EEG). After the application of the test in both conditions, changes in the frequency bands related to attention processes (beta 13-30 Hz and theta 4-7 Hz) were studied. The results of this study show that when the students were performing the test while being exposed to background noise, both beta and theta frequency bands decreased statistically significantly. Because attentional improvement is related to increases of the beta and theta waves, we believe that those decreases are directly related to a lack of attention caused by the exposure to background noise. Nevertheless, the results do not allow us to conclude that background noise produced inside university facilities has an influence on the attentional processes.

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Noise-induced attractor annihilation in the delayed feedback logistic map

We study dynamics of the bistable logistic map with delayed feedback, under the influence of white Gaussian noise and periodic modulation applied to the variable. This system may serve as a model to describe population dynamics under finite resources in noisy environment with seasonal fluctuations. While a very small amount of noise has no effect on the global structure of the coexisting attractors in phase space, an intermediate noise totally eliminates one of the attractors. Slow periodic modulation enhances the attractor annihilation.

Evaluation of noise environments during daily activities of university students

Noise conditions specifically in areas inside university facilities and its impact on the quality of life of university students aretopics that have received little attention. In this paper, a study of the noise conditions in which university students of various institutions in Madrid carry out their daily studies. A representative number of measurements were carried out using noise dosemeters and dataloggers in order to evaluate the levels of noise, noise dose and exposure to noise during study period and extracurricular activities. The results obtained in these measurements were compared with the recommendations given by current environmental noise regulations.This paper was complemented with a survey to get to know how students perceive the exposure to noise inuniversity environments.

Optimal Impulsive Collision Avoidance

The problem of optimal impulsive collision avoidance between two colliding objects in 3-dimensional elliptical Keplerian orbits is investigated with the purpose of establishing the optimal impulse direction and orbit location that give rise to the maximum miss distance following the maneuver. Closed-form analytical expressions are provided that predicts such distance and can be employed to perform a full optimization analysis. After verifying the accuracy of the expression for any orbital eccentricity and encounter geometry the optimum maneuver direction is derived as a function of the arc length separation between the maneuver point and the predicted collision point. The provided formulas can be used for high accuracy instantaneous estimation of the outcome of a generic impulsive collision avoidance maneuver and its optimization

Arrays de sensores interferométricos recirculantes de fibra óptica

Two discrete interferometric sensors' arrays have been analysed from time división multiplexing of recirculating crossed loop structures based on singlemode optical fiber. Intensity impulsive responses for both arrays have been obtained and compared under different design considerations, calculating Ihe system coupling constants, signial to interference noise ratio, input pulse repetition rate and duty cycle for each case. First experimental results are shown in this paper and very simple temperature and pressure sensing applicalions are suggested from here.

A novel method for measuring the dynamic fracture-initiation toughness under impulsive loadings

The design and development of a new method for performing fracture toughness tests under impulsive loadings using explosives is presented. The experimental set-up was complemented with pressure transducers and strain gauges in order to measure, respectively, the blast wave that reached the specimen and the loading history. Fracture toughness tests on a 7017-T73 aluminium alloy were carried out by using this device under impulsive loadings. Previous studies reported that such aluminium alloy had very little strain rate sensitivity, which made it an ideal candidate for comparison at different loading rates. The fracture-initiation toughness values of the 7017-T73 aluminium alloy obtained at impulsive loadings did not exhibit a significant variation from the cases studied at lower loading rates. Therefore, the method and device developed for measuring the dynamic fracture-initiation toughness under impulsive loadings was considered suitable for such a purpose

Aeroacoustic noise prediction in high speed trains due to attached and detached flow

This paper aims to set out the influence of the flow field around high speed trains in open field. To achieve this parametric analysis of the sound pressure inside the train was performed. Three vibroacoustic models of a characteristic train section are used to predict the noise inside the train in open field by using finite element method FEM, boundary element method (BEM) and statistical energy analysis (SEA) depending on the frequency range of analysis. The turbulent boundary layer excitation is implemented as the only airborne noise source, in order to focus on the study of the attached and detached flow in the surface of the train. The power spectral densities of the pressure fluctuation in the train surface proposed by [Cockburn and Roberson 1974, Rennison et al. 2009] are applied on the exterior surface of the structural subsystems in the vibroacoustic models. An increase in the sound pressure level up to10 dB can be appreciated due to the detachment of the flow around the train. These results highlight the importance to determine the detached regions prediction, making critical the airborne noise due to turbulent boundary layer.

Análisis de la precisión en la medida del tiempo de reverberación y de los parámetros asociados

El trabajo fin de master “Análisis de la precisión en la medida del tiempo de reverberación y de los parámetros asociados” tiene como objetivo primordial la evaluación de los parámetros y métodos utilizados para la obtención de estos, a través del tiempo de reverberación, tanto de forma global, conjunto de todos los métodos, como cada uno de ellos por separado. Un objetivo secundario es la evaluación de la incertidumbre en función del método de medición usado. Para realizarlo, se van a aprovechar las mediciones realizadas para llevar a cabo el proyecto fin de carrera [1], donde se medía el tiempo de reverberación en dos recintos diferentes usando el método del ruido interrumpido y el método de la respuesta impulsiva integrada con señales distintas. Las señales que han sido utilizadas han sido señales impulsivas de explosión de globos, disparo de pistola, claquetas y, a través de procesado digital, señales periódicas pseudoaleatorias MLS y barridos de tonos puros. La evaluación que se realizará a cada parámetro ha sido extraída de la norma UNE 89002 [2], [3]y [4]. Se determinará si existen valores aberrantes tanto por el método de Grubbs como el de Cochran, e interesará conocer la veracidad, precisión, repetibilidad y reproducibilidad de los resultados obtenidos. Los parámetros que han sido estudiados y evaluados son el tiempo de reverberación con caída de 10 dB, (T10), con caída de 15 dB (T15), con caída de 20 dB (T20), con caída de 30 dB (T30), el tiempo de la caída temprana (EDT), el tiempo final (Ts), claridad (C20, C30, C50 y C80) y definición (D50 y D80). Dependiendo de si el parámetro hace referencia al recinto o si varía en función de la relación entre la posición de fuente y micrófono, su estudio estará sujeto a un procedimiento diferente de evaluación. ABSTRACT. The master thesis called “Analysis of the accuracy in measuring the reverberation time and the associated parameters” has as the main aim the assessment of parameters and methods used to obtain these through reverberation time, both working overall, set of all methods, as each of them separately. A secondary objective is to evaluate the uncertainty depending on the measurement method used. To do this, measurements of [1] will be used, where they were carried on in two different spaces using the interrupted noise method and the method of impulse response integrated with several signals. The signals that have been used are impulsive signals such as balloon burst, gunshot, slates and, through digital processing, periodic pseudorandom signal MLS and swept pure tone. The assessment that will be made to each parameter has been extracted from the UNE 89002 [2], [3] and [4]. It will determine whether there are aberrant values both through Grubbs method and Cochran method, to say so, if a value is inconsistent with the rest of the set. In addition, it is interesting to know the truthfulness, accuracy, repeatability and reproducibility of results obtained from the first part of this rule. The parameters that are going to be evaluated are reverberation time with 10 dB decay, (T10), with 15 dB decay (T15), with 20 dB decay (T20), with 30 dB decay (T30), the Early Decay Time (EDT), the final time (Ts), clarity (C20, C30, C50 y C80) and definition (D50 y D80). Depending on whether the parameter refers to the space or if it varies depending on the relationship between source and microphone positions, the study will be related to a different evaluation procedure.

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).

Neuronal calcium sparks and intracellular calcium “noise”

Intracellular calcium ions are involved in many forms of cellular function. To accommodate so many control functions, a complex spatiotemporal organization of calcium signaling has developed. In both excitable and nonexcitable cells, calcium signaling was found to fluctuate. Sudden localized increases in the intracellular calcium concentration—or calcium sparks—were found in heart, striated and smooth muscle, Xenopus Laevis oocytes, and HeLa and P12 cells. In the nervous system, intracellular calcium ions were found important in key processes such as transmitter release, repetitive firing, and gene expression. Hence, we examined whether calcium sparks also exist in neurons. Using confocal laser-scanning microscopy and fluorescent probes, we found that calcium sparks exist in two types of neuronal preparations: the presynaptic boutons of the lizard neuromuscular junction and rat hippocampal neurons in cell culture. Control experiments exclude the possibility that these calcium sparks originate from instrumental or biological artifacts. Calcium sparks seem to be just the tip of the iceberg of a more general phenomenon of intracellular calcium “noise.” We speculate that calcium sparks and calcium noise may be of key importance in calcium signaling in the nervous system.

Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting

To investigate the nature of plasticity in the adult visual system, perceptual learning was measured in a peripheral orientation discrimination task with systematically varying amounts of external (environmental) noise. The signal contrasts required to achieve threshold were reduced by a factor or two or more after training at all levels of external noise. The strong quantitative regularities revealed by this novel paradigm ruled out changes in multiplicative internal noise, changes in transducer nonlinearites, and simple attentional tradeoffs. Instead, the regularities specify the mechanisms of perceptual learning at the behavioral level as a combination of external noise exclusion and stimulus enhancement via additive internal noise reduction. The findings also constrain the neural architecture of perceptual learning. Plasticity in the weights between basic visual channels and decision is sufficient to account for perceptual learning without requiring the retuning of visual mechanisms.

Noise in neurons is message dependent

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise is not independent of the message. However, we also show the existence of error-correcting topologies, which can achieve better timing reliability than their components.