LP → LQ - Estimates for the Fractional Acoustic Potentials and some Related Operators

Mathematics Subject Classification: 47B38, 31B10, 42B20, 42B15.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.

From otoacoustic emission to late auditory potentials P300: the inhibitory effect

This study verifies the effects of contralateral noise on otoacoustic emissions and auditory evoked potentials. Short, middle and late auditory evoked potentials as well as otoacoustic emissions with and without white noise were assessed. Twenty-five subjects, normal-hearing, both genders, aged 18 to 30 years, were tested. In general, latencies of the various auditory potentials were increased at noise conditions, whereas amplitudes were diminished at noise conditions for short, middle and late latency responses combined in the same subject. The amplitude of otoacoustic emission decreased significantly in the condition with contralateral noise in comparison to the condition without noise. Our results indicate that most subjects presented different responses between conditions (with and without noise) in all tests, thereby suggesting that the efferent system was acting at both caudal and rostral portions of the auditory system.

The effects of dexmedetomidine/remifentanil and midazolam/remifentanil on auditory-evoked potentials and electroencephalogram at light-to-moderate sedation levels in healthy subjects

Avoidance of excessively deep sedation levels is problematic in intensive care patients. Electrophysiologic monitoring may offer an approach to solving this problem. Since electroencephalogram (EEG) responses to different sedation regimens vary, we assessed electrophysiologic responses to two sedative drug regimens in 10 healthy volunteers. Dexmedetomidine/remifentanil (dex/remi group) and midazolam/remifentanil (mida/remi group) were infused 7 days apart. Each combination of medications was given at stepwise intervals to reach Ramsay scores (RS) 2, 3, and 4. Resting EEG, bispectral index (BIS), and the N100 amplitudes of long-latency auditory-evoked potentials (ERP) were recorded at each level of sedation. During dex/remi, resting EEG was characterized by a recurrent high-power low-frequency pattern which became more pronounced at deeper levels of sedation. BIS Index decreased uniformly in only the dex/remi group (from 94 +/- 3 at baseline to 58 +/- 14 at RS 4) compared to the mida/remi group (from 94 +/- 2 to 76 +/- 10; P = 0.029 between groups). The ERP amplitudes decreased from 5.3 +/- 1.3 at baseline to 0.4 +/- 1.1 at RS 4 (P = 0.003) in only the mida/remi group. We conclude that ERPs in volunteers sedated with dex/remi, in contrast to mida/remi, indicate a cortical response to acoustic stimuli, even when sedation reaches deeper levels. Consequently, ERP can monitor sedation with midazolam but not with dexmedetomidine. The reverse is true for BIS.

Acoustic Detection of Organic Enrichment in Sediments at a Salmon Farm Is Confirmed by Independent Groundtruthing Methods

Acoustic backscatter contrast in depositional sediments under salmon farm cages in the Bay of Fundy, Canada, was correlated with localized changes in (unknown) sediment geotechnical properties, as indicated by 4 independent measures of organic enrichment. Sediment total sulfides and redox potentials, enzyme hydrolyzable amino acids, sediment profile imaging and macrofaunal samples, taken at mid-cage positions, each rejected the null hypothesis that salmon cage footprints, defined acoustically as high backscatter areas, were indistinguishable from nearby reference areas. Acoustic backscatter imaging appears capable of mapping organic enrichment in depositional sediments caused by excessive inputs of salmon farm wastes associated with intensive aquaculture.

Acoustic overstimulation increases outer hair cell Ca2+ concentrations and causes dynamic contractions of the hearing organ

The dynamic responses of the hearing organ to acoustic overstimulation were investigated using the guinea pig isolated temporal bone preparation. The organ was loaded with the fluorescent Ca2+ indicator Fluo-3, and the cochlear electric responses to low-level tones were recorded through a microelectrode in the scala media. After overstimulation, the amplitude of the cochlear potentials decreased significantly. In some cases, rapid recovery was seen with the potentials returning to their initial amplitude. In 12 of 14 cases in which overstimulation gave a decrease in the cochlear responses, significant elevations of the cytoplasmic [Ca2+] in the outer hair cells were seen. [Ca2+] increases appeared immediately after terminating the overstimulation, with partial recovery taking place in the ensuing 30 min in some preparations. Such [Ca2+] changes were not seen in preparations that were stimulated at levels that did not cause an amplitude change in the cochlear potentials. The overstimulation also gave rise to a contraction, evident as a decrease of the width of the organ of Corti. The average contraction in 10 preparations was 9 μm (SE 2 μm). Partial or complete recovery was seen within 30–45 min after the overstimulation. The [Ca2+] changes and the contraction are likely to produce major functional alterations and consequently are suggested to be a factor contributing strongly to the loss of function seen after exposure to loud sounds.

Listening to nature : acoustic monitoring of the environment

The requirement to monitor the rapid pace of environmental change due to global warming and to human development is producing large volumes of data but placing much stress on the capacity of ecologists to store, analyse and visualise that data. To date, much of the data has been provided by low level sensors monitoring soil moisture, dissolved nutrients, light intensity, gas composition and the like. However, a significant part of an ecologist’s work is to obtain information about species diversity, distributions and relationships. This task typically requires the physical presence of an ecologist in the field, listening and watching for species of interest. It is an extremely difficult task to automate because of the higher order difficulties in bandwidth, data management and intelligent analysis if one wishes to emulate the highly trained eyes and ears of an ecologist. This paper is concerned with just one part of the bigger challenge of environmental monitoring – the acquisition and analysis of acoustic recordings of the environment. Our intention is to provide helpful tools to ecologists – tools that apply information technologies and computational technologies to all aspects of the acoustic environment. The on-line system which we are building in conjunction with ecologists offers an integrated approach to recording, data management and analysis. The ecologists we work with have different requirements and therefore we have adopted the toolbox approach, that is, we offer a number of different web services that can be concatenated according to need. In particular, one group of ecologists is concerned with identifying the presence or absence of species and their distributions in time and space. Another group, motivated by legislative requirements for measuring habitat condition, are interested in summary indices of environmental health. In both case, the key issues are scalability and automation.

Source location of acoustic emission waves for structural health monitoring of bridges

The process of structural health monitoring (SHM) involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures and acoustic emission (AE) is one technique that is finding an increasing use. Acoustic emission waves are the stress waves generated by the mechanical deformation of materials. AE waves produced inside a structure can be recorded by means of sensors attached on the surface. Analysis of these recorded signals can locate and assess the extent of damage. This paper describes preliminary studies on the application of AE technique for health monitoring of bridge structures. Crack initiation or structural damage will result in wave propagation in solid and this can take place in various forms. Propagation of these waves is likely to be affected by the dimensions, surface properties and shape of the specimen. This, in turn, will affect source localization. Various laboratory test results will be presented on source localization, using pencil lead break tests. The results from the tests can be expected to aid in enhancement of knowledge of acoustic emission process and development of effective bridge structure diagnostics system.

Virtual vignettes and pedagogical potentials : Insights into a virtual schooling service

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Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Towards an acoustic environmental observatory

The need for large scale environmental monitoring to manage environmental change is well established. Ecologists have long used acoustics as a means of monitoring the environment in their field work, and so the value of an acoustic environmental observatory is evident. However, the volume of data generated by such an observatory would quickly overwhelm even the most fervent scientist using traditional methods. In this paper we present our steps towards realising a complete acoustic environmental observatory - i.e. a cohesive set of hardware sensors, management utilities, and analytical tools required for large scale environmental monitoring. Concrete examples of these elements, which are in active use by ecological scientists, are also presented