The role of the auditory periphery in comodulation detection difference and comodulation masking release

Natural sounds often exhibit correlated amplitude modulations at different frequency regions, so-called comodulation. Therefore, the ear might be especially adapted to these kinds of sounds. Two effects have been related to the sensitivity of the auditory system to common modulations across frequency: comodulation detection difference (CDD) and comodulation masking release (CMR). Research on these effects has been done on the psychophysical and on the neurophysiological level in humans and other animals. Until now, models have focused only on one of the effects. In the present study, a simple model based on data from neuronal recordings obtained during CDD experiments with starlings is discussed. This model demonstrates that simple peripheral processing in the ear can go a substantial way to explaining psychophysical signal detection thresholds in response to CDD and CMR stimuli. Moreover, it is largely analytically tractable. The model is based on peripheral processing and incorporates the basic steps frequency filtering, envelope extraction, and compression. Signal detection is performed based on changes in the mean compressed envelope of the filtered stimulus. Comparing the results of the model with data from the literature, the scope of this unifying approach to CDD and CMR is discussed.     

Effects of noise bandwidth and amplitude modulation on masking in frog auditory midbrain neurons

Natural auditory scenes such as frog choruses consist of multiple sound sources (i.e., individual vocalizing males) producing sounds that overlap extensively in time and spectrum, often in the presence of other biotic and abiotic background noise. Detection of a signal in such environments is challenging, but it is facilitated when the noise shares common amplitude modulations across a wide frequency range, due to a phenomenon called comodulation masking release (CMR). Here, we examined how properties of the background noise, such as its bandwidth and amplitude modulation, influence the detection threshold of a target sound (pulsed amplitude modulated tones) by single neurons in the frog auditory midbrain. We found that for both modulated and unmodulated masking noise, masking was generally stronger with increasing bandwidth, but it was weakened for the widest bandwidths. Masking was less for modulated noise than for unmodulated noise for all bandwidths. However, responses were heterogeneous, and only for a subpopulation of neurons the detection of the probe was facilitated when the bandwidth of the modulated masker was increased beyond a certain bandwidth - such neurons might contribute to CMR. We observed evidence that suggests that the dips in the noise amplitude are exploited by TS neurons, and observed strong responses to target signals occurring during such dips. However, the interactions between the probe and masker responses were nonlinear, and other mechanisms, e.g., selective suppression of the response to the noise, may also be involved in the masking release.     

Superposition of masking releases

We are constantly exposed to a mixture of sounds of which only few are important to consider. In order to improve detectability and to segregate important sounds from less important sounds, the auditory system uses different aspects of natural sound sources. Among these are (a) its specific location and (b) synchronous envelope fluctuations in different frequency regions. Such a comodulation of different frequency bands facilitates the detection of tones in noise, a phenomenon known as comodulation masking release (CMR). Physiological as well as psychoacoustical studies usually investigate only one of these strategies to segregate sounds. Here we present psychoacoustical data on CMR for various virtual locations of the signal by varying its interaural phase difference (IPD). The results indicate that the masking release in conditions with binaural (interaural phase differences) and across-frequency (synchronous envelope fluctuations, i.e. comodulation) cues present is equal to the sum of the masking releases for each of the cues separately. Data and model predictions with a simplified model of the auditory system indicate an independent and serial processing of binaural cues and monaural across-frequency cues, maximizing the benefits from the envelope comparison across frequency and the comparison of fine structure across ears.

Masking release for gap detection.

In random noise, masking is influenced almost entirely by noise components in a narrow band around the signal frequency. However, when the noise is not random, but has a modulation pattern which is coherent across frequency, noise components relatively remote from the signal frequency can actually produce a release from masking. This masking release has been called comodulation masking release (CMR). The present research investigated whether a similar release from masking occurs in the analysis of a suprathreshold signal. Specifically, the ability to detect the presence of a temporal gap was investigated in conditions which do and do not result in CMR for detection threshold. Similar conditions were investigated for the masking level difference (a binaural masking release phenomenon). The results indicated that suprathreshold masking release for gap detection occurred for both the masking-level difference (MLD) and for CMR. However, masking release for gap detection was generally smaller than that obtained for detection threshold. The largest gap detection masking release effects obtained corresponded to relatively low levels of stimulation, where gap detection was relatively poor.     

Signal detection theory,detectability and stochastic resonance effects

 Stochastic resonance is a phenomenon in which the performance of certain non-linear detectors can be enhanced by the addition of appropriate levels of random noise. Signal detection theory offers a powerful tool for analysing this type of system, through an ability to separate detection processes into reception and classification, with the former generally being linear and the latter always non-linear. Through appropriate measures of signal detectability it is possible to decide whether a local improvement in detection via stochastic resonance occurs due to the non-linear effects of the classification process. In this case, improvement of detection through the addition of noise can never improve detection beyond that of a corresponding adaptive system. Signal detection and stochastic resonance is investigated in several integrate-and-fire neuron models. It is demonstrated that the stochastic resonance observed in spiking models is caused by non-linear properties of the spike-generation process itself. The true detectability of the signal, as seen by the receiver part of the spiking neuron (the integrator part), decreases monotonically with input noise level for all signal and noise intensities. Received: 3 April 2001 / Accepted in revised form: 8 March 2002     

Paradoxical relationship between speed and accuracy in olfactory figure-background segregation

In natural settings, many stimuli impinge on our sensory organs simultaneously. Parsing these sensory stimuli into perceptual objects is a fundamental task faced by all sensory systems. Similar to other sensory modalities, increased odor backgrounds decrease the detectability of target odors by the olfactory system. The mechanisms by which background odors interfere with the detection and identification of target odors are unknown. Here we utilized the framework of the Drift Diffusion Model (DDM) to consider possible interference mechanisms in an odor detection task. We first considered pure effects of background odors on either signal or noise in the decision-making dynamics and showed that these produce different predictions about decision accuracy and speed. To test these predictions, we trained mice to detect target odors that are embedded in random background mixtures in a two-alternative choice task. In this task, the inter-trial interval was independent of behavioral reaction times to avoid motivating rapid responses. We found that increased backgrounds reduce mouse performance but paradoxically also decrease reaction times, suggesting that noise in the decision making process is increased by backgrounds. We further assessed the contributions of background effects on both noise and signal by fitting the DDM to the behavioral data. The models showed that background odors affect both the signal and the noise, but that the paradoxical relationship between trial difficulty and reaction time is caused by the added noise.     

Influence of amplitude modulated noise on the recognition of communication signals in the grasshopper Chorthippus biguttulus

The detection of acoustic communication signals in the presence of sinusoidally amplitude modulated noise was investigated in males of the grasshopper Chorthippus biguttulus. The auditory system of grasshoppers exhibits only poor spectral resolution. Hence, these animals are ideally suited to investigate noise tolerance in a system operating in the temporal domain. As a sensitive indicator for signal recognition the conspicuous phonotactic turning responses of males were recorded. The main result was that noise modulated at low frequencies (1.5-5 Hz) did not impair recognition compared to a unmodulated noise. With long stimuli even a moderate improvement of noise tolerance was observed, an effect that can probably be attributed to the existence of long troughs at low modulation frequencies during which the masking of the signal was reduced. Higher modulation frequencies (15-150 Hz), however, rendered detection and recognition increasingly difficult, due to a strong interference of the sound pulses of the masking noise with the syllable-pause structure of the species-specific signals. There are no indications for the operation of mechanisms analogous to comodulation masking release as found in vertebrates, nor for a spatial release from masking.     

Weak electric fields detectability in a noisy neural network

We investigate the detectability of weak electric field in a noisy neural network based on Izhikevich neuron model systematically. The neural network is composed of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex, and the axonal conduction delays between neurons are also considered. It is found that the noise intensity can modulate the detectability of weak electric field. Stochastic resonance (SR) phenomenon induced by white noise is observed when the weak electric field is added to the network. It is interesting that SR almost disappeared when the connections between neurons are cancelled, suggesting the amplification effects of the neural coupling on the synchronization of neuronal spiking. Furthermore, the network parameters, such as the connection probability, the synaptic coupling strength, the scale of neuron population and the neuron heterogeneity, can also affect the detectability of the weak electric field. Finally, the model sensitivity is studied in detail, and results show that the neural network model has an optimal region for the detectability of weak electric field signal.     

Modeling electromagnetic fields detectability in a HH-like neuronal system: stochastic resonance and window behavior

Noise has already been shown to play a constructive role in neuronal processing and reliability, according to stochastic resonance (SR). Here another issue is addressed, concerning noise role in the detectability of an exogenous signal, here representing an electromagnetic (EM) field. A Hodgkin–Huxley like neuronal model describing a myelinated nerve fiber is proposed and validated, excited with a suprathreshold stimulation. EM field is introduced as an additive voltage input and its detectability in neuronal response is evaluated in terms of the output signal-to-noise ratio. Noise intensities maximizing spiking activity coherence with the exogenous EM signal are clearly shown, indicating a stochastic resonant behavior, strictly connected to the model frequency sensitivity. In this study SR exhibits a window of occurrence in the values of field frequency and intensity, which is a kind of effect long reported in bioelectromagnetic experimental studies. The spatial distribution of the modeled structure also allows to investigate possible effects on action potentials saltatory propagation, which results to be reliable and robust over the presence of an exogenous EM field and biological noise. The proposed approach can be seen as assessing biophysical bases of medical applications funded on electric and magnetic stimulation where the role of noise as a cooperative factor has recently gained growing attention. This work investigates the role of noise as a cooperative factor for the detection of an exogenous electromagnetic field in a compartimental model of a myelinated nerve fiber. The occurrence of stochastic resonance is discussed in relation to neuronal frequency sensitivity.     

Improved methods for fitting sedimentation coefficient distributions derived by time-derivative techniques

Time-derivative approaches to analyzing sedimentation velocity data have proven to be highly successful and have now been used routinely for more than a decade. For samples containing a small number of noninteracting species, the sedimentation coefficient distribution function, g(s *), traditionally has been fitted by Gaussian functions to derive the concentration, sedimentation coefficient, and diffusion coefficient of each species. However, the accuracy obtained by that approach is limited, even for noise-free data, and becomes even more compromised as more scans are included in the analysis to improve the signal/noise ratio (because the time span of the data becomes too large). Two new methods are described to correct for the effects of long time spans: one approach that uses a Taylor series expansion to correct the theoretical function and a second approach that creates theoretical g(s *) curves from Lamm equation models of the boundaries. With this second approach, the accuracy of the fitted parameters is approximately 0.1% and becomes essentially independent of the time span; therefore, it is possible to obtain much higher signal/noise when needed. This second approach is also compared with other current methods of analyzing sedimentation velocity data.     

Water conditions influence the detectability of Crossodactylus gaudichaudii (Anura,Hylodidae) in streams of the Atlantic Forest

Stream-dwelling amphibians' occurrence, behaviour and reproductive success are strongly influenced by dynamic abiotic factors, for example, water flow and spray. These factors can disproportionately affect these frogs due to their dependency on specific favourable conditions for development and incapacity to disperse from unfavourable environments. We analysed the influence of environmental covariates on the detectability of Crossodactylus gaudichaudii, an amphibian species endemic to streams in the Brazilian Atlantic Forest. We conducted sampling in the streams of the Duas Bocas Biological Reserve, Brazil, and we measured air and water temperature, air humidity and pH of water on each sampling occasion. We estimated the effects of variables on the detectability of the species using single-season occupancy models. Our results indicated that the detectability of the species increases on occasions with higher water temperatures (24–26°C) and lower pH (5.0–5.5). We investigated the influence of these covariates only on the detectability of adult frogs, but it is likely that the physiochemical properties of stream water are more important to aquatic larvae, and hence, the probability of their detection. Given this, further studies should examine the relevance of covariates on the detectability of adult frogs as well as larvae.     

Tutorial. Surface EMG detection,conditioning and pre-processing: Best practices

This tutorial is aimed primarily to non-engineers, using or planning to use surface electromyography (sEMG) as an assessment tool for muscle evaluation in the prevention, monitoring, assessment and rehabilitation fields. The main purpose is to explain basic concepts related to: (a) signal detection (electrodes, electrode–skin interface, noise, ECG and power line interference), (b) basic signal properties, such as amplitude and bandwidth, (c) parameters of the front-end amplifier (input impedance, noise, CMRR, bandwidth, etc.), (d) techniques for interference and artifact reduction, (e) signal filtering, (f) sampling and (g) A/D conversion, These concepts are addressed and discussed, with examples.The second purpose is to outline best practices and provide general guidelines for proper signal detection, conditioning and A/D conversion, aimed to clinical operators and biomedical engineers. Issues related to the sEMG origin and to electrode size, interelectrode distance and location, have been discussed in a previous tutorial. Issues related to signal processing for information extraction will be discussed in a subsequent tutorial.     

Probability of detection of Flammulated Owls using nocturnal broadcast surveys

ABSTRACT Broadcasts of conspecific vocalizations are used to increase detection rates on surveys of secretive bird species, yet the assessment of detectability necessary to fully interpret such survey data is frequently lacking. We used radiotelemetry to evaluate the probability of detection of 17 radio‐tagged male Flammulated Owls (Otus flammeolus) using conspecific broadcast surveys in Idaho during 2005 and 2006. Probability of detection among the 11 paired, five unpaired, and one unknown pairing status owls was 100% during the pair‐bonding and incubation periods of the breeding season, after which it declined to less than 15% during the postfledging period. Paired males showed a different pattern than unpaired males. Following hatching of eggs, detectability of paired males declined gradually over a 6‐week period, whereas detectability of unpaired males dropped sharply for a 4‐week period before increasing during the postfledging period. We suggest that surveys for Flammulated Owls be conducted during the pair‐bonding and incubation periods when high detectability permits stronger inference concerning the presence or absence of owls based on broadcast survey detections.     

Comparison of audio recording system performance for detecting and monitoring songbirds

ABSTRACT Acoustic recording systems are being used more frequently to estimate habitat occupancy or relative abundance, and to monitor population trends over time. A potential concern with digital recording systems is that changes in technology could affect detectability of birds and cause bias in trend estimates based on counts of birds detected. We evaluated several currently available commercial recording systems ranging from low‐cost multipurpose digital recorders to custom‐designed wildlife recorders (US$250–$7000 price range) to examine possible differences among systems in species detection. We made recordings during Breeding Bird Surveys (BBS) counts using several units concurrently, and asked several expert birders to listen to the recordings in a factorial design. We found that birders detected, on average, 10% fewer species on some units compared to others, though there was high variance. Analysis of a subset of recordings, using spectrograms and repeated listening, suggested that ～90% of species on each BBS stop could be clearly detected on all units. The remaining species could be identified on at least one unit, but were hard or impossible to detect on others. We found that the recording unit with the lowest empirical signal‐to‐noise‐ratio (SNR) had the lowest number of birds detected on the BBS recordings, and that frequency‐specific SNR differed among units. Missed detections were likely related to variation in internal noise and frequency‐dependent sensitivity of the units, and were an issue for all systems regardless of price. We caution that researchers using recorders need to consider variation among recording systems in their study design, particularly for long‐term monitoring programs.     

Weak-Periodic Stochastic Resonance in a Parallel Array of Static Nonlinearities

This paper studies the output-input signal-to-noise ratio (SNR) gain of an uncoupled parallel array of static, yet arbitrary, nonlinear elements for transmitting a weak periodic signal in additive white noise. In the small-signal limit, an explicit expression for the SNR gain is derived. It serves to prove that the SNR gain is always a monotonically increasing function of the array size for any given nonlinearity and noisy environment. It also determines the SNR gain maximized by the locally optimal nonlinearity as the upper bound of the SNR gain achieved by an array of static nonlinear elements. With locally optimal nonlinearity, it is demonstrated that stochastic resonance cannot occur, i.e. adding internal noise into the array never improves the SNR gain. However, in an array of suboptimal but easily implemented threshold nonlinearities, we show the feasibility of situations where stochastic resonance occurs, and also the possibility of the SNR gain exceeding unity for a wide range of input noise distributions.     

Phototransduction in primate cones and blowfly photoreceptors: different mechanisms, different algorithms, similar response

Phototransduction in primate cones is compared with phototransduction in blowfly photoreceptor cells. Phototransduction in the two cell types utilizes not only different molecular mechanisms, but also different signal processing steps, producing range compression, contrast constancy, and an intensity-dependent integration time. The dominant processing step in the primate cone is a strongly compressive nonlinearity due to cGMP hydrolysis by phosphodiesterase. In the blowfly photoreceptor a considerable part of the range compression is performed by the nonlinear membrane of the cell. Despite these differences, both photoreceptor cell types are similarly effective in compressing the wide range of naturally occurring intensities, and in converting intensity variations into contrast variations. A direct comparison of the responses to a natural time series of intensities, simulated in the cone and measured in the blowfly photoreceptor, shows that the responses are quite similar.     

A stochastic approach to solving the problem of sensory system thresholds]

On the basis of an analysis of mathematical models realizing concept of discrete and signal detection probability of the threshold it is shown that utilization for describing the discrete model concepts of probability and the apparatus of Dirac delta functions and root-mean-square of noise distribution being reduced to zero in the continuous model the analytical expressions of the models are identical. The evidence obtained shows inner unity of the examined thresholds models and universal nature of the thresholds model of Swets, Tanner and Birdsall built on the basis of the statistical theory of signal detectability. It provides solution of one of the central problems of psychophysics--that of the threshold of the sensory systems.     

Simplified Paper Format for Detecting HIV Drug Resistance in Clinical Specimens by Oligonucleotide Ligation

Human immunodeficiency virus (HIV) is a chronic infection that can be managed by antiretroviral treatment (ART). However, periods of suboptimal viral suppression during lifelong ART can select for HIV drug resistant (DR) variants. Transmission of drug resistant virus can lessen or abrogate ART efficacy. Therefore, testing of individuals for drug resistance prior to initiation of treatment is recommended to ensure effective ART. Sensitive and inexpensive HIV genotyping methods are needed in low-resource settings where most HIV infections occur. The oligonucleotide ligation assay (OLA) is a sensitive point mutation assay for detection of drug resistance mutations in HIV pol. The current OLA involves four main steps from sample to analysis: (1) lysis and/or nucleic acid extraction, (2) amplification of HIV RNA or DNA, (3) ligation of oligonucleotide probes designed to detect single nucleotide mutations that confer HIV drug resistance, and (4) analysis via oligonucleotide surface capture, denaturation, and detection (CDD). The relative complexity of these steps has limited its adoption in resource-limited laboratories. Here we describe a simplification of the 2.5-hour plate-format CDD to a 45-minute paper-format CDD that eliminates the need for a plate reader. Analysis of mutations at four HIV-1 DR codons (K103N, Y181C, M184V, and G190A) in 26 blood specimens showed a strong correlation of the ratios of mutant signal to total signal between the paper CDD and the plate CDD. The assay described makes the OLA easier to perform in low resource laboratories.     

Human fetuses have nonlinear cardiac dynamics.

Approximate entropy (ApEn) is a statistic that quantifies regularity in time series data, and this parameter has several features that make it attractive for analyzing physiological systems. In this study, ApEn was used to detect nonlinearities in the heart rate (HR) patterns of 12 low-risk human fetuses between 38 and 40 wk of gestation. The fetal cardiac electrical signal was sampled at a rate of 1,024 Hz by using Ag-AgCl electrodes positioned across the mother's abdomen, and fetal R waves were extracted by using adaptive signal processing techniques. To test for nonlinearity, ApEn for the original HR time series was compared with ApEn for three dynamic models: temporally uncorrelated noise, linearly correlated noise, and linearly correlated noise with nonlinear distortion. Each model had the same mean and SD in HR as the original time series, and one model also preserved the Fourier power spectrum. We estimated that noise accounted for 17.2-44.5% of the total between-fetus variance in ApEn. Nevertheless, ApEn for the original time series data still differed significantly from ApEn for the three dynamic models for both group comparisons and individual fetuses. We concluded that the HR time series, in low-risk human fetuses, could not be modeled as temporally uncorrelated noise, linearly correlated noise, or static filtering of linearly correlated noise.