Background Of White Noise Research Articles

Background white noise increases neuronal activity by reducing membrane fluctuations and slow-wave oscillations in auditory cortex.

The brain faces the challenging task of preserving a consistent portrayal of the external world in the face of disruptive sensory inputs. What alterations occur in sensory representation amidst noise, and how does brain activity adapt to it? Although it has previously been shown that background white noise (WN) decreases responses to salient sounds, a mechanistic understanding of the brain processes responsible for such changes is lacking. We investigated the effect of background WN on neuronal spiking activity, membrane potential, and network oscillations in the mouse central auditory system. We found that, in addition to increasing background spiking activity in the auditory cortex and thalamus, background WN decreases neural activity fluctuations, as reflected in the membrane potential of single neurons and the local field potential. Blocking acetylcholine signaling in the auditory cortex eliminated the WN-dependent increase in background activity as well as the shift in slow-wave oscillations. Together, our observations show that background WN is not filtered away along the auditory pathway, but rather drives sustained changes in cortical activity that can be reverted by blocking cholinergic inputs.

Effect of different scanning threshold triggers on the image quality of brain computed tomography angiography: a randomized controlled trial.

The scanning trigger threshold affects image quality. The aim of this study was to investigate the effect of different scanning trigger thresholds on brain computed tomography angiography (CTA) image quality. In this prospective study, 80 patients undergoing brain CTA examinations with dual-layer CT (DLCT) were randomly divided into group A and group B, with 40 patients in each group. In group A, the CT value of the internal carotid artery at the level of the fourth cervical vertebra was monitored, and the scan was initiated once the CT value reached 100 Hounsfield units (HU). In group B, the trigger threshold was set at 60 HU, with all other parameters kept consistent with those of group A. Finally, the image quality of the 50-keV virtual monoenergetic images (VMIs) was evaluated, including the CT values of the internal carotid artery (CTICA), middle cerebral artery (CTMCA), sinus confluence (CTSC), cerebral white matter (CTCWM), background noise (BN), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective scoring. All images met the diagnostic imaging requirements. Group B showed significantly lower values than did group A for CTICA (371.97±51.81 vs. 442.64±83.39 HU), CTMCA (345.80±50.72 vs. 405.87±82.81 HU), CTSC (90.44±21.30 vs. 138.87±37.37 HU), CTCWM (31.98±5.66 vs. 38.86±5.68 HU), SNR (108.64±21.05 vs. 126.79±30.87), and CNR (98.58±19.72 vs. 114.65±29.56) (all P values <0.05) but the value for BN was not significantly different (P>0.05). However, the subjective scores in group B were significantly higher than those in group A (χ2=19.013; P<0.05). For brain CTA imaging in DLCT (50 keV VMIs), lowering the scan trigger threshold to 60 HU helped to reduce venous artifacts and improve image quality (as evidenced by improved subjective scores) and also suggests the potential for a further reduction of the contrast dose.

Transimpedance amplifier for LGAD noise measurements: design and characterization

A wideband low-noise transimpedance amplifier (TIA) is designed for the measurement of the noise power spectral density (NPSD) of the current of low-gain avalanche diodes (LGADs). The design focuses on minimization of system background noise and maximization of operating bandwidth. The diffusive line effect of the high value resistor used in the feedback network has been analyzed, and a compensation of its effect has been implemented. With a transimpedance of 200 MΩ, a background white noise of 9.5 fA/√(Hz) and an input current dynamic range up to 20 nA are achieved. The useful bandwidth ranges from 1 kHz up to 3 MHz depending on the noise level to be measured. An effective method for calibrating the system and measuring its transfer function with high accuracy over the full bandwidth is described. The designed TIA enables an accurate characterization of LGADs noise, which is a crucial step for the technology qualification and for the prediction of the performance of these devices as radiation and particle detectors.

Recognition and classification of noise signals by dolphins under conditions of noise interference and spatial uncertainty of their simultaneous presentation

The ability of dolphin`s auditory system to recognize and classify noise signals according to certain invariant features under the influence of noise interference and spatial uncertainty of their simultaneous presentation was studied. The bottlenose dolphins trained to differentiate such signals had to solve this problem under conditions simulating real marine ones, when the perception of a useful signal occurs against the background of similar signals and noise interference. First, the noise signals were sequentially presented to the animal against the background of white masking noise. Further the dolphin had to identify a signal of a positive class from several simultaneously sounding sound sources. The efficiency of the animal was evaluated at several given levels of noise interference. In this case, the actual noise interference was both white noise and simultaneously sounding negative signals. It`s shown that the efficiency and noise immunity of dolphin`s auditory system depend on the degree of alternativeness of the spatial uncertainty of the simultaneous presentation of signals.

Характеристики оценки частоты последовательности сверхширокополосных сигналов с неизвестными длительностями

The work synthesizes a quasi-likelihood algorithm for estimating the frequency of a coherent sequence of ultra-wideband quasi-radio signals with unknown duration against a background of white Gaussian noise. When synthesizing the frequency estimation algorithm, instead of an unknown duration, some of its expected value is used. Analytical expressions are obtained for the statistical characteristics of the frequency estimate of a sequence of ultra-wideband quasi-radio signals depending on the pulse duration detuning parameter. In particular, the dependence of the variance of the frequency estimate of a sequence of ultra-wideband quasi-radio signals on the signal-to-noise ratio is obtained for different values of the duration detuning and the number of sequence pulses. It has been established that the frequency estimate bias does not depend on the number of pulses in the sequence, and for large values of the narrowband parameter there is no frequency estimate bias. It is shown that the duration detuning has a significant impact on the characteristics of the frequency estimate of a sequence of ultra-wideband quasi-radio signals, while at large values of the narrowband parameter the obtained expressions coincide with the known expressions for the variance and bias of the frequency estimates of a sequence of narrow-band radio signals.

Analysis of the effect of multiplicative noise on the conditions of signal resolution according to a statistical criterion

We analyzed the effect of multiplicative noise on signal resolution characteristics when a statistical criterion for processing is used in the receiving device. The receiver is optimal for resolving two signals in the sense of detecting against the background of additive white noise. It is shown that the complex envelope of the signal at the output of the analyzed receiver can be considered as a flat vector with correlated components having different variances. However, with fast multiplicative noise, the named components become uncorrelated, and their variances become equal. It is shown that the delay time resolution intervals and frequency shift resolution intervals with known statistical characteristics of signals, additive and multiplicative noise are uniquely determined by the probabilities of correct and false resolution. It is pointed out that the use of a statistical criterion allows us to determine quantitative values of resolution intervals in a fairly wide range of changes in the parameters of additive and multiplicative noise, significantly exceeding the Woodward criterion for example. Thus, the use of statistical criteria leads to an increase in the efficiency of radio systems.

Quasi-likelihood estimation of the arrival time of an ultra-wideband quasi-radio signal with unknown amplitude and initial phase

The problem of estimating the time of arrival of a signal is relevant in the fields of radio and hydrolocation, radio astronomy, remote observation and sensing, etc. The useful signal is often described by a quasi-deterministic function of time, which can be regular or discontinuous. In recent years, problems of processing ultra-wideband signals have been of significant interest. Among the many UWB signals, it is customary to distinguish a separate class of ultra-wideband quasi-radio signals, the structure of which is similar to the structure of narrowband radio signals, but the condition of relative narrowband for which may not be met. Algorithms for estimating the arrival time of regular ultra-wideband quasi-radio signals have been studied in the existing literature. In this case, the synthesis and analysis of an algorithm for quasi-plausible estimation of the arrival time of a discontinuous signal of finite duration and arbitrary shape is of practical interest. The purpose of the work is to synthesize and analyze a quasi-likelihood algorithm for estimating the time of arrival of a discontinuous ultra-wideband quasi-radio signal with an unknown amplitude and initial phase against a background of white Gaussian noise. In this work, closed asymptotically exact expressions for the bias and scattering of the estimate are obtained, which make it possible to study the effectiveness of the synthesized algorithm, as well as compare its effectiveness with special cases of signal models - narrowband and wideband radio and video signals. The results of the study make it possible to determine losses in the accuracy of estimation the signal arrival time due to a priori ignorance of the initial phase and shape of the modulating function of the signal. Depending on the required accuracy of estimate the time of arrival of an ultra-wideband quasi-radio signal, it is possible to optimize the parameters of the transmitted signals and determine the limits of applicability of the designed radio system.

Design and Analysis of a Contact Piezo Microphone for Recording Tracheal Breathing Sounds.

Analysis of tracheal breathing sounds (TBS) is a significant area of study in medical diagnostics and monitoring for respiratory diseases and obstructive sleep apnea (OSA). Recorded at the suprasternal notch, TBS can provide detailed insights into the respiratory system's functioning and health. This method has been particularly useful for non-invasive assessments and is used in various clinical settings, such as OSA, asthma, respiratory infectious diseases, lung function, and detection during either wakefulness or sleep. One of the challenges and limitations of TBS recording is the background noise, including speech sound, movement, and even non-tracheal breathing sounds propagating in the air. The breathing sounds captured from the nose or mouth can interfere with the tracheal breathing sounds, making it difficult to isolate the sounds necessary for accurate diagnostics. In this study, two surface microphones are proposed to accurately record TBS acquired solely from the trachea. The frequency response of each microphone is compared with a reference microphone. Additionally, this study evaluates the tracheal and lung breathing sounds of six participants recorded using the proposed microphones versus a commercial omnidirectional microphone, both in environments with and without background white noise. The proposed microphones demonstrated reduced susceptibility to background noise particularly in the frequency ranges (1800-2199) Hz and (2200-2599) Hz with maximum deviation of 2 dB and 2.1 dB, respectively, compared to 9 dB observed in the commercial microphone. The findings of this study have potential implications for improving the accuracy and reliability of respiratory diagnostics in clinical practice.

Detection of phase modulation disorder when processing a sequence of ultra-wideband quasi-radio signals against a background of white Gaussian noise

In conditions of a complex electromagnetic environment in communication and data transmission systems, a change in the type of modulation occurs when one or more signal parameters change abruptly, therefore the task of determining the type of signal modulation can be reduced to the task of detecting a disorder, that is, detecting the fact of a change in the type of modulation of the signal and estimation of the disorder time. The purpose of the work is to synthesize an algorithm for detecting phase modulation disorder when processing a sequence of ultra-wideband quasi-radio signals with unknown amplitude and initial phase against a background of white Gaussian noise and to analyze the effectiveness of the resulting algorithm based on the results of statistical modeling. The work synthesizes an algorithm for detecting a phase modulation disorder of a received sequence of ultra-wideband quasi-radio signals against a background of white Gaussian noise. To analyze the effectiveness of the resulting algorithm, statistical modeling of algorithm for detecting a phase modulation disorder is carried out. The dependences of the probability of detection of a disorder on the signal-to-noise ratio and the length of the sequence of received signals at a fixed moment of disorder are obtained. A comparison of the detection characteristics of phase modulation disorder of ultra-wideband quasi-radio signals and narrowband radio signals is made. It is shown that when a low-order phase modulation disorder is detected, the required values of the probability of detection are achieved at low signal-to-noise ratios, while with an increase in the modulation order and the use of its modifications, the efficiency indicators of the algorithm will deteriorate. The introduction of algorithms for detecting a disorder in radio engineering applications will allow optimizing synchronization algorithms and adaptation to interference conditions with a concomitant change in the type of modulation, as well as reducing the amount of transmitted service information in telecommunication systems.

Adaptive stochastic resonance under Poisson white noise background and its application for bolt looseness detection

Adaptive stochastic resonance under Poisson white noise background and its application for bolt looseness detection

Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering

Introduction. The use of non-equidistant pulse sequences as probing radar signals makes it possible to eliminate blind spots in speed and range. However, the implementation of multi-channel Doppler filtering (MDF) based on the classical fast Fourier transform (FFT) algorithm of non-equidistant signal samples in the signal detection problem is associated with energy losses. The use of modified FFT algorithms increases the efficiency of MDF against the background of white Gaussian noise, while reducing the efficiency of signal accumulation in the part of signal processing channels blocked by the narrow-band clutter. To eliminate this drawback, the authors previously proposed using combined classical and modified FFT algorithms. However, the use of the combined method does not lead to an optimal solution in terms of MDF efficiency.Aim. Optimization of weight processing of non-equidistant signals to improve the efficiency of MDF.Materials and methods. An MDF synthesis was carried out using optimization procedures, and the effectiveness of the algorithms was assessed using computer calculations.Results. The results show that the Kaiser Bessel window with a window parameter of 4.42 provides the highest signal-(clutter+noise) ratio improvement coefficient averaged over frequency channels equal to 30.06 dB and the highest probability of correct signal detection averaged over MDF channels equal to 0.5 at processing of non-equidistant pulse sequences. Optimization of the weight processing of MDF under the specified conditions increased the average efficiency characteristics used of up to 53.18 dB and 0.92, respectively.Conclusion. Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. However, these advantages are achieved at the cost of not using the FFT, i.e., implemented within the framework of the discrete Fourier transform (DFT) algorithm.

Effects of Different Types of Music on Students’ Study Efficiency

Music has been omnipresent in people’s daily lives; therefore, it is crucial to evaluate how it exerts influence as people depend more on it. Many studies suggest that listening to background music has a positive impact and raises study efficiency, while others suggest that it is counterproductive because it negatively impacts attention levels. These equivocal results occur because people focus on different tasks while testing the effect of background music. This paper explores various effects on students’ study efficiency of three genres of background music, classical music, white noise or environmental sounds, and lyrical pop music. Classical music had both beneficial and harmful impacts depending on different cognitive tasks. White noise, surprisingly, has some positive impact on students, especially for ADHD students. Lyrical music has a generally distracting effect on study tasks. Certainly, more research about how three types of music impact students is needed. Since music has become more and more entrenched in people’s life, this paper hopes to provide insight into how three types of music can be incorporated into tasks that helps performance and avoid using those that might hurt students’ performance.

Effects of urban traffic noise on the early growth and transcription of Arabidopsis thaliana

Man-made noise in cities has been recognized as one of the major contributors to a range of adverse health outcomes, including heart disease. Besides the detrimental effects on human health, noise can act as a potential threat to other organisms in the ecosystem. Despite the growing concern, the biological effects of noise pollution on plants, in particular, remain largely obscure. Therefore, this study aimed to investigate the impacts of urban traffic noise on the growth of Arabidopsis thaliana (A. thaliana). We hypothesized that traffic noise could stimulate plant growth (seed germination and seedling growth) since noise treatment has been reported to improve immunity and drought tolerance in A. thaliana (1, 2). Seeds in the experimental group were exposed to 48 hours of traffic noise recorded in a highly congested area of Seoul, while the control group was exposed to background white noise. Compared with background white noise, traffic noise exposure had no effects on seed germination but significantly increased the growth of seedlings by 39%. We further investigated the traffic noise-induced molecular changes in the A. thaliana seedlings by employing RNA sequencing. We detected aberrant expression of 690 genes in traffic noise-exposed seedlings. The differentially expressed genes were enriched for various biological pathways, such as stress response and auxin signaling. The observed molecular changes suggest profound impacts of traffic noise on the physiology of A. thaliana. The results of our research can help shed light on the fundamental principles underlying the noise-plant interaction as well as provide a further basis for conserving our ecosystem.

A Combined Noise Reduction Method for Floodgate Vibration Signals Based on Adaptive Singular Value Decomposition and Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

To address the issue of the vibration characteristic signals of floodgates being affected by background white noise and low-frequency water flow noise, a noise reduction method combining the improved adaptive singular value decomposition algorithm (ASVD) and the improved complete ensemble EMD with adaptive noise (ICEEMDAN) is proposed. Firstly, a Hankel matrix is constructed based on the collected discrete time signals. After performing SVD on the Hankel matrix, the ASVD algorithm is used to automatically select the effective singular values to filter out most of the background white noise and retain the useful frequency components with similar energy in the signal. Then, ICEEMDAN combined with the Spearman correlation coefficient method is used to further filter out residual white noise and low-frequency water flows. The noise reduction performance of this combined method is verified through simulation experiments. Filtered by the ASVD-ICEEMDAN method, the signal-to-noise ratio of the simulation signal (50% noise level) is increased from 4.417 to 16.237, and the root mean square error is reduced from 2.286 to 0.586. Based on the practically measured vibration signals of a floodgate at a large hydropower station, the result shows that the ASVD-ICEEMDAN method exhibits good noise reduction performance and feature information extraction abilities for floodgate vibration signals, and can provide support for operational mode analysis and damage identification of practical structures under complex interference conditions.

Effects of target-amplitude and background-contrast uncertainty predicted by a normalized template-matching observer.

When detecting targets under natural conditions, the visual system almost always faces multiple, simultaneous, dimensions of extrinsic uncertainty. This study focused on the simultaneous uncertainty about target amplitude and background contrast. These dimensions have a large effect on detection and vary greatly in natural scenes. We measured the human performance for detecting a sine-wave target in white noise and natural-scene backgrounds for two levels of prior probability of the target being present. We derived and tested the ideal observer for white-noise backgrounds, a special case of a template-matching observer that dynamically moves its criterion with the background contrast (the DTM observer) and two simpler models with a fixed criterion: the template-matching (TM) observer and the normalized template-matching (NTM) observer that normalizes template response by background contrast. Simulations show that, when the target prior is low, the performance of the NTM observer is near optimal and the TM observer is near chance, suggesting that manipulating the target prior is valuable for distinguishing among models. Surprisingly, we found that the NTM and DTM observers better explain human performance than the TM observer for both target priors in both background types. We argue that the visual system most likely exploits contrast normalization, rather than dynamic criterion adjustment, to deal with simultaneous background contrast and target amplitude uncertainty. Finally, our findings show that the data collected under high levels of uncertainty have a rich structure capable of discriminating between models, providing an alternative approach for studying high dimensions of uncertainty.

Association Between Bilingualism, Vocal Effort, and Background Noise With Voice Fundamental Frequency and LTAS Among Spanish-English Bilingual Teachers

As the world becomes increasingly interconnected, the demand for bilingual teachers has grown exponentially. However, the unique combination of being a bilingual occupational voice user establishes challenges that warrant careful examination. To investigate the association between bilingualism, vocal effort, and background noise with fundamental frequency and long-term spectrum average among Spanish-English bilingual teachers. Exploratory cross-sectional correlational study with the participation of eight Spanish-English proficient bilingual teachers (native Spanish speakers) who were teaching online classes during the quarantines established to mitigate the propagation of COVID-19. Participants were asked to read two standardized texts (one in English and one in Spanish) under two background noise conditions (with and without background white noise). There was a significant interaction between language and vocal effort considering that the association of vocal effort with fo was different for Spanish and English. There was also a significant main effect of background noise on fo. There were significant differences in voice spectral characteristics between productions in Spanish and English and between productions with and without background noise. The alpha ratio was significantly higher in productions in English and with background noise compared with productions in Spanish without background noise. The mid to high spectral energy ratio (1-5K/5-8K) was significantly lower in productions in English and with higher perceived vocal effort compared with productions in Spanish and with lower scores on the Borg Scale. Our findings introduce a need perspective by emphasizing the impact of speaking a second language on the work-relatedness of voice disorders among teachers. These findings stress the necessity to factor in language and environmental conditions for the comprehensive evaluation and management of work-related voice disorders.

A comparison of background noise reduction algorithms for improving acoustic beamforming output

This work presents a comparison of different background noise reduction algorithms available in literature at a range of signal-to-noise ratios (SNRs) for improving the conventional beamforming (CB) source maps. The algorithms include the classical background noise removal (BNR), eigenvalue identification organization and subtraction (EIOS), subspace-based background subtraction (SBS), and ensemble empirical mode decomposition (EEMD), amongst others. To assess the performance of different algorithms, three test-cases were considered: (1) localizing a loudspeaker placed in an anechoic environment in the presence of background white-noise, (2) diagnosing machine-tool noise source(s) during machining, i.e., when the workpiece and tool piece are in contact and (3) localizing airfoil trailing-edge (TE) noise sources in the presence of background tunnel noise. The analysis showed that the suitability of an algorithm depends upon the given situation – for the loudspeaker source, all algorithms deliver comparable results while for machine-tool application, the relatively simple BNR algorithm delivered the desired improvements in CB maps. For the experimental airfoil TE noise test-case, the EIOS and EEMD algorithms demonstrated substantial enhancements as compared to other methods. This investigation, therefore, suggests that for a given application, it is desirable to customize the background noise reduction algorithm to obtain optimal results.

Orbitofrontal cortex conveys stimulus and task information to the auditory cortex

Auditory cortical neurons modify their response profiles in response to numerous external factors. During task performance, changes in primary auditory cortex (A1) responses are thought to be driven by top-down inputs from the orbitofrontal cortex (OFC), which may lead to response modification on a trial-by-trial basis. While OFC neurons respond to auditory stimuli and project to A1, the function of OFC projections to A1 during auditory tasks is unknown. Here, we observed the activity of putative OFC terminals in A1 in mice by using invivo two-photon calcium imaging of OFC terminals under passive conditions and during a tone detection task. We found that behavioral activity modulates but is not necessary to evoke OFC terminal responses in A1. OFC terminals in A1 form distinct populations that exclusively respond to either the tone, reward, or error. Using tones against a background of white noise, we found that OFC terminal activity was modulated by the signal-to-noise ratio (SNR) in both the passive and active conditions and that OFC terminal activity varied with SNR, and thus task difficulty in the active condition. Therefore, OFC projections in A1 are heterogeneous in their modulation of auditory encoding and likely contribute to auditory processing under various auditory conditions.

Оценка длительности сверхширокополосного квазирадиосигнала при неуверенности в его наличии

We synthesize a quasi-likelihood algorithm for estimation of the duration of an arbitrary shape ultra-wideband quasi-radio signal with unknown amplitude and initial phase, which observed against the background of additive Gaussian white noise. Among the ultra-wideband signals, a separate class is distinguished – ultra-wideband quasi-radio signals, which structure is similar to narrowband radio signals, but the condition of relative narrowband is not satisfied. We suggest that its duration can be equal to several periods or a fraction of the period of a harmonic oscillation. We consider the model of a signal which may be absent in the received realization, while the structure of the receiver does not take into account the disappearance of the signal. Statistical characteristics of the synthesized duration estimates are conditional bias and dispersions. The obtained results can be used for estimation of the decrease in efficiency in evaluation of the duration of a signal, when such a signal may disappear in the received realization.

Does Task-Irrelevant Brightness Modulation Affect Auditory Contrast Processing? Exploring the Interplay Between Temporal Synchrony and Stimulus Salience

Abstract Stimulus factors such as timing, spatial location, and stimulus effectiveness affect whether and how information across the senses is integrated. Extending recent work highlighting interactions between stimulus factors, here we investigated the influence of visual information on auditory processing, complementing previous studies on the influence of auditory information on visual processing. We hypothesized that task-irrelevant and spatially non-informative visual information would enhance auditory contrast processing, when visual information was at an optimal salience level and changed synchronously with the sound. We asked human observers to indicate the location of an amplitude-modulated white-noise sound, while its loudness against a constant white-noise background varied across trials. To test for the influence of task-irrelevant visual information, we modulated screen brightness smoothly (Experiment 1) or transiently (Experiment 2) in phase or out of phase with the amplitude modulation of the target sound. In addition, to test for the interaction between temporal synchrony and stimulus salience, maximum brightness varied systematically across trials. Auditory contrast thresholds were compared across conditions. Results showed that task-irrelevant visual information did not alter auditory contrast thresholds regardless of the nature of modulation of brightness, contrary to our expectations. Nonetheless, task-irrelevant visual information modulated in phase with the target sound reduced auditory contrast thresholds if we accounted for individual differences in the optimal salience required for the largest multisensory effects. Our results are discussed in light of several stimulus factors that might be critical in modulating multisensory enhancement.