Non-linear biological responses to environmental noise affect population extinction risk

Non-linearities are commonly observed in the responses of organisms to environment. They potentially modify the qualitative and quantitative properties of population dynamics. We studied how non-linear responses to environment, or "noise filters", influence population variability and extinction risk by introducing coloured noise to the growth rate in the Hassell single-species model. The consequences of noise filtering were analysed by comparing the model dynamics with linearly filtered and non-linearly filtered noise that have the same mean. Three biologically plausible filters we used: saturating, unimodal optimum type, and sigmoid responses.
Filtering can either decrease or increase population variability when compared to linear noise response. The effect of noise filtering on variability is most pronounced with stable population dynamics and the outcome depends on the filter type, population growth rate, and noise colour.
Non-linear noise filtering predominantly increases extinction risks when population growth rate is low (R<5). As an exception, saturating filter has a window of decreased risk at very low growth rate and reddened environment. In the unstable range of the dynamics (15These results suggest that accounting for the non-linear responses to environment should be considered when estimating extinction risks and population variability. Moreover, the non-linear responses make noise colour a more important factor in these analyses.     

Improved processing of the steady-state evoked potential

Two related procedures for estimating the parameters of steady-state evoked potentials (SSEPs) are introduced. The first procedure involves an initial stage of digital bandpass filtering followed by a Discrete Fourier Transform analysis. In the second method, a high resolution method based on parametric modelling is applied to the filtered data. The digital pre-filter consists of a non-phase shifting Chebychev bandpass filter. The parametric modelling method considers the evoked-response-plus-noise distribution to consist of a set of exponentially damped sinusoids. The frequency, amplitude, phase and damping factors of these components are estimated by calculating the mean of the forward and backward prediction filters and linear regression.We compared the signal-to-noise ratio (SNR) of the new procedures to the conventional Discrete Fourier Transform method for Monte Carlo simulations utilizing known sinusoids buried in white noise, known sinusoids buried in human EEG noise and for a sample of visual evoked potential data. Both of the new methods produce substantially more accurate and less variable estimates of test sinusoid amplitude. For VEP recording, the EEG background noise level is reduced by 5–6 dB over that obtained with the DFT. The new methods also provide approximately 5 dB better SNR than the DFT for detection of sinusoids based on the Rayleigh statistic. The parametric modelling approach is particularly suited for the analysis of very short data records including cycle-by-cycle analysis of the SSEP.     

DIGITAL FILTERS IN AUDITORY PHYSIOLOGY

ABSTRACT

In auditory research, the manipulation of signals by filtering with analog electronic filters plays an important role. Recently, digital filters that compute signal modifications in realtime became available. They can mimic all functions of analog filters, and additionally make possible new experimental concepts.

This tutorial paper introduces the concept of digital filters by using analogies from acoustics. Even complex acoustical environments can be simulated with digital filters, as they allow the programming of almost arbitrary frequency and phase responses.     

Scalp potentials following sudden coherence and discoherence of binaural noise and change in the inter-aural time difference: a specific binaural evoked potential or a “mismatch” response?

When uncorrelated random noise signals presented to the two ears suddenly become identical (coherent), a centrally located sound image is abruptly perceived and long latency scalp potentials are evoked. When the same signals are presented monaurally there is no perceived change and no potentials are evoked: hence the response must be purely a function of the binaural interaction.P70, N130 and P220 components were consistently recorded to both coherence and discoherence. N130 was usually largest at Fz and P220 at Cz. No potentials of shorter latency were identified, even after averaging 5000 or more sweeps. When the noise became coherent with an inter-aural time difference (δT) of ±0.5 msec (giving rise to an off-centre sound image), the responses were of slightly longer latency and showed no significant asymmetries between C3 and C4. In binaurally coherent noise, δT changes of ±0.5 or ±1.0 msec evoked similar responses which showed no significant asymmetries on the scalp. N130 was of longer latency when δT was changed from ±0.5 msec to zero, as compared with the converse change.In view of the similarity of all these responses it is considered unlikely that they were due to specific populations of binaurally responsive cortical neurones. The N130 and P220 components are thought to be non-specific potentials which are elicited by amy perceptible change in steady auditory stimulus conditions, due to a “mismatch” between the stimulus and the contents of a short-term auditory memory.     

Classification of brain-stem auditory evoked potentials by syntactic methods

A syntactic pattern recognition procedure for classification of brain-stem auditory evoked potential (BSAEP) is presented. A pre-processing stage of zero-phase bandpass filtering enhances the peaks and suppresses the noise. A finite-state grammar was designed to identify the peaks. Attributes of the peaks (latencies and amplitudes) that are identified are checked for their acceptability. A training run in 70 subjects of known diagnosis was perfomed finr-tune the system and build up necessary acceptance criteria. Peak latency differences are used for the classification rather than absolute peak latencies. Acceptance criteria for peak latency differences were empirically optimized. A data base of normal BSAEPs, created during the training run, was updated and used during the test run. Test of the classifier using 60 subjects yielded a classification accuracy of 83%. The classifier has acceptable accuracy and can be modified for other evoked potentials such as visual and somatosensory by establishing relevant attribute tables.     

Removal of power-line interference from the ECG: a review of the subtraction procedure

Background  

Modern biomedical amplifiers have a very high common mode rejection ratio. Nevertheless, recordings are often contaminated by residual power-line interference. Traditional analogue and digital filters are known to suppress ECG components near to the power-line frequency. Different types of digital notch filters are widely used despite their inherent contradiction: tolerable signal distortion needs a narrow frequency band, which leads to ineffective filtering in cases of larger frequency deviation of the interference. Adaptive filtering introduces unacceptable transient response time, especially after steep and large QRS complexes. Other available techniques such as Fourier transform do not work in real time. The subtraction procedure is found to cope better with this problem.     

Vibrissal inputs into the motor cortex of adult and developing rats

Field potentials (FP) and responses of single neurones to electrical stimulation of vibrissal pads have been recorded in motor cortex in the albino mature and developing rats. The FPs were characterized by 3-phasic shape and high stability in mature rats. The FPs evoked by contralateral stimuli have a range of onset latency of 4 to 24 ms (peak of distribution 8-11 ms); those to ipsilateral stimuli have a latency of 4 to 23 ms (peak of distribution 12-16 ms). Responses of single neurones were evoked with a latency of 9 to 20 ms. Usually, the FPs were evoked by both contralateral and ipsilateral stimulation, and in some tracks were effective only ipsilateral stimuli in the developing rats beginning from the 11th day of life. The FPs in such animals were less stable and more fatigable. During 2-4 weeks of life, FPs evoked by contralateral stimulation appeared with a latency of 15 to 46 ms; during the same period, a latency of single unit responses ranged between 20 to 33 ms. The FPs to ipsilateral stimuli appeared with a latency of 18 to 47 ms, a latency of single unit responses of 27 to 47 ms. The results indicate functional immaturity of vibrissal system up to the end of the first month of rat life.     

Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis

 In many applications of signal processing, especially in communications and biomedicine, preprocessing is necessary to remove noise from data recorded by multiple sensors. Typically, each sensor or electrode measures the noisy mixture of original source signals. In this paper a noise reduction technique using independent component analysis (ICA) and subspace filtering is presented. In this approach we apply subspace filtering not to the observed raw data but to a demixed version of these data obtained by ICA. Finite impulse response filters are employed whose vectors are parameters estimated based on signal subspace extraction. ICA allows us to filter independent components. After the noise is removed we reconstruct the enhanced independent components to obtain clean original signals; i.e., we project the data to sensor level. Simulations as well as real application results for EEG-signal noise elimination are included to show the validity and effectiveness of the proposed approach. Received: 6 November 2000 / Accepted in revised form: 12 November 2001     

Hybrid filtering to rescue stable oscillations from noise-induced chaos in continuous cultures of budding yeast

In large-scale fermentations with oscillating microbial cultures, noise is commonly present in the feed stream(s). As this can destabilize the oscillations and even generate chaotic behavior, noise filters are employed. Here three types of filters were compared by applying them to a noise-affected continuous culture of Saccharomyces cerevisiae with chaotic oscillations. The aim was to restore the original noise-free stable oscillations. An extended Kalman filter was found to be the least efficient, a neural filter was better and a combined hybrid filter was the best. In addition, better filtering of noise was achieved in the dilution rate than in the oxygen mass transfer coefficient. These results suggest the use of hybrid filters with the dilution rate as the manipulated variable for bioreactor control.     

Sampling, noise-reduction and amplitude estimation issues in surface electromyography.

This paper reviews data acquisition and signal processing issues relative to producing an amplitude estimate of surface EMG. The paper covers two principle areas. First, methods for reducing noise, artefact and interference in recorded EMG are described. Wherever possible noise should be reduced at the source via appropriate skin preparation, and the use of well designed active electrodes and signal recording instrumentation. Despite these efforts, some noise will always accompany the desired signal, thus signal processing techniques for noise reduction (e.g. band-pass filtering, adaptive noise cancellation filters and filters based on the wavelet transform) are discussed. Second, methods for estimating the amplitude of the EMG are reviewed. Most advanced, high-fidelity methods consist of six sequential stages: noise rejection/filtering, whitening, multiple-channel combination, amplitude demodulation, smoothing and relinearization. Theoretical and experimental research related to each of the above topics is reviewed and the current recommended practices are described.     

Seismic communication signals in the blind mole-rat (Spalax ehrenbergi ): electrophysiological and behavioral evidence for their processing by the auditory system

Based on morphological and behavioral findings we suggest that the seismic vibratory signals that blind mole-rats (Spalax ehrenbergi) use for intraspecific communication are picked up from the substrate by bone conduction and processed by the auditory system. An alternative hypothesis, raised by others, suggest that these signals are processed by the somatosensory system. We show here that brain stem and middle latency responses evoked by vibrations are similar to those evoked by high-intensity airborne clicks but are larger in their amplitudes, especially when the lower jaw is in close contact with the vibrating substrate. Bilateral deafening of the mole-rat or high-intensity masking noise almost completely eliminated these responses. Deafening also gradually reduced head-drumming behavior until its complete elimination about 4–6 weeks after surgery. Successive vibrations, at a rate of 0.5 vibrations/s, elicited prominent responses. At rates higher than 2 vibrations/s the amplitude of the brain stem response did not change, yet the middle latency response disappeared almost completely. It is concluded that the seismic signals that mole rats use for long distance communication are indeed processed primarily by the auditory system. Accepted: 11 May 1998     

The Electrophysiology of Electric Organs of Marine Electric Fishes : I. Properties of electroplaques of Torpedo nobiliana

Single electroplaques of Torpedo nobiliana have been studied with microelectrode recording. Direct evidence is presented that the only electrogenically reactive membrane of the cells is on the innervated surface and that this membrane is electrically inexcitable. Responses are not evoked by depolarizing currents applied to this membrane, but only by stimulating the innervating nerve fibers. The responses arise after a latency of 1 to 3 msec. This latency is not affected by large depolarizing or hyperpolarizing changes in membrane potential. Various properties that have been theoretically associated with electrically inexcitable responses have been also demonstrated to occur in the electroplaques. The neurally evoked response is not propagated actively in the membrane and may have different amplitudes and forms in closely adjacent regions. The maximal responses frequently are slightly larger than the recorded resting potential but the apparent small overshoot may be due to difficulty in recording the full resting potential. The responses are subject to electrochemical gradation and appear inverted in sign on applying strong outward currents across the innervated membrane. This membrane is cholinoceptive and shows marked desensitization. The membrane of the uninnervated surface has a very low resistance, a factor that aids maximum output of current during the discharge of the electric organ.     

Short latency somatosensory and spinal evoked potentials: Power spectra and comparison between high pass analog and digital filter

Medium nerve somatosensory evoked potentials (SSEPs) and intraoperative spinal evoked potentials were analyzed using different analog and zero phase shift digital high pass filter and by power spectrum. Additionally, high pass analog and digital filtering was performed on various sine, triangular and rectangular waves manufactured by a wave form generator. Recordings were also transformed to the 1st and 2nd time derivatives.The great abundance of spectral energy for scalp recorded median nerve SSEPs was below 125 c/sec but lower energy fast frequency components consistently extended to 500 c/sec. Power spectrum of the Erb's point compound nerve action potential revealed a wide band of spectral energy commencing at about 50–100 c/sec, peaking at about 250–270 c/sec and extending to nearly 1000 c/sec. This suggests that synchronous axonal activity generates predominantly faster frequencies above 100 c/sec.High pass analog filter confers phase non-linearity which results in various distortions including latency shift and a morphological change which may be visually similar to the 1st or 2nd time derivatives. High pass zero phase shift digital filter removes selected low frequencies without accompanying phase distortion. This accentuates fast peaks seen at open bandpass as well as transition points between baseline and component ascent or descent. Zero phase shift digital filter may also generate peaks that are not visualized at open pass but which reflect the sum of frequencies which were not removed by filtering. These peaks do not necessarily correspond to discrete singular neuroanatomical structures.Although peaks observed in high pass analog and digital filter appear similar and comparable, their underlying activity may be of different origin. This is because high pass analog filter projects a considerable amount of overlap from earlier onto later waves.For clinical correlation it is important that restricted bandpass analog or digitally filtered recordings be compared with open pass data. Only those peaks visualized in both open and restricted bandpass can be considered authentic. Examples of spinal and scalp SSEPs indicate that selective filtering may, under certain circumstances, distinguish axonal or lemniscal from synaptic generators.     

Production of reliability proven physiological data for use in automated monitoring and diagnostic systems

In recent years manufacturers of intensive care monitoring systems have introduced complex digital processing architectures that theoretically have enormous processing power. This power should allow the realization of many useful processing methodologies that up to now have only been research tools, e.g. the generation of reliable alarms, the implementation of predictive monitoring strategies and reliable diagnostic and treatment guidance to the clinical staff. However, before any of these methodologies can be successfully initiated, each must have accurate and relaible derived physiological data available to them, e.g. beat-by-beat heart rate and blood pressure. From the very nature of monitoring physiological quantities there will be much misinformation or ‘noise’ superimposed on the raw signal obtained from the patient. The major source of noise (as far as electocardiogram (ECG) monitoring is concerned) is internal to the body and is electromyographic noise. This results from the contraction of skeletal muscles producing action potentials of similar magnitude and frequency to that of the ECG. Fortunately, nursing staff are very good at ‘filtering out’ any misinformation before recording any data (on a ward chart for instance). However, in completely automated systems, if this noise is not detected and eliminated or compensated for at an early stage in the processing chain, misinformation will result with potentially serious consequences. The recognition and elimination of such noise cannot be readily achieved using standard filtering techniques without serious degradation of information. This paper discusses the potential of modern digital system architectures developed for ECG monitoring. It analyses the noise that occurs on this physiological variable and demonstrates a novel method of eliminating such noise.     

Some statistical aspects of digital Wiener filtering and detection of prescribed frequency components in time averaging of biological signals

A statistical analysis of digital a posteriori Wiener filtering as applied to time averaging techniques for biological signals is presented. The authors show that when ap.w.f. is applied to the average signal hardly any effect can be expected, where as when applied to the individual responses, ap.w.f. improves the signal to noise ratio. The applied analysis leads to a simple test to check whether a prescribed frequency component is present.     

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.     

Real time microprocessor-based 50 Hz notch filter for ECG

High performance analogue notch filters are difficult to realize in practice. Their real time digital counterparts, when implemented on an inexpensive microprocessor with no additional hardware, also have limitations of their own. To overcome these limitations, we have developed a new type of 50 Hz notch filter with its poles close to the zeros of the transfer function 1 + Z^−N. This new type of digital notch filter can be used for suppression of 50 Hz noise in the ECG. The filter is simple to design and easy to implement on most 8-bit microprocessors. It has a high execution speed, low analogue to digital noise, low recursive noise and good frequency response with no overshoot or ringing. It is capable of suppressing 50 Hz noise by at least 40 db. Its finite bandwidth of 4 Hz causes about 2% attenuation on the QRS peak, which is acceptable for almost all practical applications. One possible drawback is that multiple notches occur at higher frequencies. However, this has hardly any effect on the ECG because of the limited notch bandwidth.     

A new descriptor of the dual character of the input-output behaviour of the cochlea,with implications for signal-to-noise ratio estimation of brain-stem auditory potentials evoked by alternating polarity clicks

The signal-to-noise ratio based on a plus-minus average for residual noise estimation has been systematically computed for brain-stem auditory evoked potentials (BAEPs) evoked by alternating polarity clicks from threshold up to 100 dB nHL in subjects with normal cochlear function. The plus-minus averages have exhibited a systematic dual behaviour in close correspondence with the “L” and “H” portions of the latency-intensity functions: from threshold up to 50 dB SL (“L” segment) they faithfully reflect the post-averaging residual noise. From 50 dB SL upwards the plus-minus averages are contaminated by a signal identified as the differential potential between rarefaction and condensation responses. The plus-minus average is therefore an unreliable indicator of the post-averaging residual noise when alternating polarity clicks louder than 50 dB are used. These findings suggest that for intensities corresponding to the “L” (steep) part of the latency-intensity function, when inner hair cell excitation is dependent on active amplification by the outer hair cells, no difference exists between rarefaction and condensation responses. By contrast, once levels at which the inner hair cells can be directly stimulated are reached, responses to rarefaction and condensation clicks become different.     

On the Similarity of Functional Connectivity between Neurons Estimated across Timescales

A central objective in neuroscience is to understand how neurons interact. Such functional interactions have been estimated using signals recorded with different techniques and, consequently, different temporal resolutions. For example, spike data often have sub-millisecond resolution while some imaging techniques may have a resolution of many seconds. Here we use multi-electrode spike recordings to ask how similar functional connectivity inferred from slower timescale signals is to the one inferred from fast timescale signals. We find that functional connectivity is relatively robust to low-pass filtering—dropping by about 10% when low pass filtering at 10 hz and about 50% when low pass filtering down to about 1 Hz—and that estimates are robust to high levels of additive noise. Moreover, there is a weak correlation for physiological filters such as hemodynamic or Ca²⁺ impulse responses and filters based on local field potentials. We address the origin of these correlations using simulation techniques and find evidence that the similarity between functional connectivity estimated across timescales is due to processes that do not depend on fast pair-wise interactions alone. Rather, it appears that connectivity on multiple timescales or common-input related to stimuli or movement drives the observed correlations. Despite this qualification, our results suggest that techniques with intermediate temporal resolution may yield good estimates of the functional connections between individual neurons.     

WaveletQuant,an improved quantification software based on wavelet signal threshold de-noising for labeled quantitative proteomic analysis

Background  

Quantitative proteomics technologies have been developed to comprehensively identify and quantify proteins in two or more complex samples. Quantitative proteomics based on differential stable isotope labeling is one of the proteomics quantification technologies. Mass spectrometric data generated for peptide quantification are often noisy, and peak detection and definition require various smoothing filters to remove noise in order to achieve accurate peptide quantification. Many traditional smoothing filters, such as the moving average filter, Savitzky-Golay filter and Gaussian filter, have been used to reduce noise in MS peaks. However, limitations of these filtering approaches often result in inaccurate peptide quantification. Here we present the WaveletQuant program, based on wavelet theory, for better or alternative MS-based proteomic quantification.