scholarly journals Neurocognitive dynamics of near-threshold voice signal detection and affective voice evaluation

2020 ◽  
Vol 6 (50) ◽  
pp. eabb3884
Author(s):  
Huw Swanborough ◽  
Matthias Staib ◽  
Sascha Frühholz
Keyword(s):  
Signal Detection ◽  
Fundamental Problem ◽  
Dynamic Properties ◽  
Signal To Noise Ratio ◽  
Affective Meaning ◽  
Communication Signals ◽  
Threshold Detection ◽  
Voice Signal ◽  
Detection Point ◽  
Near Threshold

Communication and voice signal detection in noisy environments are universal tasks for many species. The fundamental problem of detecting voice signals in noise (VIN) is underinvestigated especially in its temporal dynamic properties. We investigated VIN as a dynamic signal-to-noise ratio (SNR) problem to determine the neurocognitive dynamics of subthreshold evidence accrual and near-threshold voice signal detection. Experiment 1 showed that dynamic VIN, including a varying SNR and subthreshold sensory evidence accrual, is superior to similar conditions with nondynamic SNRs or with acoustically matched sounds. Furthermore, voice signals with affective meaning have a detection advantage during VIN. Experiment 2 demonstrated that VIN is driven by an effective neural integration in an auditory cortical-limbic network at and beyond the near-threshold detection point, which is preceded by activity in subcortical auditory nuclei. This demonstrates the superior recognition advantage of communication signals in dynamic noise contexts, especially when carrying socio-affective meaning.

scholarly journals Emission-Line Asymmetries and the Kinematics of the Narrow-Line Region in AGNs

1989 ◽  
Vol 134 ◽  
pp. 347-348
Author(s):  
Richard A. Shaw ◽  
Michael M. De Robertis
Keyword(s):  
Emission Line ◽  
Fundamental Problem ◽  
Signal To Noise Ratio ◽  
Critical Density ◽  
High Signal ◽  
Symmetric Model ◽  
Narrow Line ◽  
Line Region ◽  
Wide Range ◽  
Narrow Line Region

We have obtained high signal-to-noise ratio CCD spectra at ≤ 150 km/s resolution for 6 high-ionization Seyfert galaxies. We analyzed the profiles of the emission-lines over a wide range in both ionization potential (IP) and critical density (Ncr) in order to study the fundamental problem of cloud motion in the narrow-line region (NLR). Using the known correlations between FWHM and IP and/or Ncr for these galaxies, and assuming that the blueward profile asymmetries result from the combined effects of radially infalling or outflowing clouds and extinction within or between them, we deconvolve these effects by analyzing the correlation between emission-line asymmetries and both IP and Ncr. We find fair to good correlations in the sense that lines with high IP and Ncr also tend to have high asymmetry, while lines with low IP and Ncr have low but usually non-zero asymmetry. Simulated emission-line profiles generated with a spherically-symmetric model of a NLR suggest that the extinction arises primarily within radially infalling clouds.

Weak Signal Detection System Based on Lock-in Amplifier Technology

2013 ◽  
Vol 389 ◽  
pp. 489-493
Author(s):  
Yong Lv ◽  
Chun Hui Niu ◽  
Yue Qiang Li ◽  
Qing Shan Chen ◽  
Xiao Ying Li ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Phase Sensitive ◽  
Lock In

In order to detect the weak signal deeply buried in the noise, a weak signal detection system based on lock-in amplifier is proposed. The system includes the preamplifier circuit, active low pass filter circuit, AC amplifying circuit and phase sensitive demodulation circuit. Test results show that it can greatly increase the signal-to-noise ratio (SNR) up to 12.7db.

Study on Threshold Detection of Micro-Seismic Signal Based on Constraint Judgment

2011 ◽  
Vol 255-260 ◽  
pp. 2898-2903
Author(s):  
Chang Peng Ji ◽  
Mo Gao ◽  
Jie Yang
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Probability Of Detection ◽  
Identification Accuracy ◽  
Signal To Noise ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Improvement Effect ◽  
The Mathematical Model ◽  
Double Threshold

Double threshold detection based on constraint judgment is proposed for micro-seismic signal detection. The improvement effect on Probability of False Alarm and influence on Probability of Detection are quantitatively analyzed with constraint judgment. The mathematical models of total PFA and PD of double threshold detection based on constraint judgment are built, and the validity of the mathematical model is verified by simulation tests and experiments. The results show that the signal-to-noise ratio under scheduled PFA and PD Call be decreased by introducing constraint judgment to double threshold detection, and improve the identification accuracy of micro-seismic signal.

scholarly journals An Extraction Method of Weak Low-Frequency Magnetic Communication Signals Based on Multisensor

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Chao Huang ◽  
Xin Xu ◽  
Dunge Liu ◽  
Wanhua Zhu ◽  
Xiaojuan Zhang ◽  
...  
Keyword(s):  
Blind Source Separation ◽  
Extraction Method ◽  
Field Experiments ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
Low Frequency ◽  
Signal Extraction ◽  
Magnetic Noise ◽  
Communication Signals ◽  
Low Snr

It is a technical challenge to effectively remove the influence of magnetic noise from the vicinity of the receiving sensors on low-frequency magnetic communication. The traditional denoising methods are difficult to extract high-quality original signals under the condition of low SNR (the signal-to-noise ratio). In this paper, we analyze the numerical characteristics of the low-frequency magnetic field and propose the algorithms of the fast optimization of blind source separation (FOBSS) and the frequency-domain correlation extraction (FDCE). FOBSS is based on blind source separation (BSS). Signal extraction of low SNR can be implemented through FOBSS and FDCE. This signal extraction method is verified in multiple field experiments which can remove the magnetic noise by about 25 dB or more.

The Comparison between Chaos Algorithm and Music Algorithm Applied in Weak Signal Detection

2013 ◽  
Vol 427-429 ◽  
pp. 1552-1556
Author(s):  
Chen Zhang ◽  
Zhen Bin Gao ◽  
Jing Chun Li ◽  
Biao Huang
Keyword(s):  
Signal Detection ◽  
Array Signal Processing ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Music Algorithm ◽  
Verilog Hdl ◽  
Simulation Experiments ◽  
Chaos Algorithm ◽  
Core Part

Chaos algorithm is essential in weak signal detection because of its sensibility to weak signals and immunity to noise. This paper applies subspace algorithm which originates from array signal processing to weak signal detection field because of its lower signal to noise ratio. Firstly, the article introduces the principles of two algorithms, then analyses simulation experiments results of real signal data. After that, a conclusion for two algorithms comparison by estimation of computation cost, complexity of implementation and hardware resources occupied is drawn. At the end, the writer designs a duffing chaos module which is the core part of chaotic detection with verilog-hdl.

scholarly journals Spike Sorting of Muscle Spindle Afferent Nerve Activity Recorded with Thin-Film Intrafascicular Electrodes

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
Milan Djilas ◽  
Christine Azevedo-Coste ◽  
David Guiraud ◽  
Ken Yoshida
Keyword(s):  
Thin Film ◽  
Muscle Spindle ◽  
Signal To Noise Ratio ◽  
Muscle Length ◽  
Detection Scheme ◽  
Threshold Detection ◽  
Complex Wavelets ◽  
Intrafascicular Electrodes ◽  
Stimulation System

Afferent muscle spindle activity in response to passive muscle stretch was recorded in vivo using thin-film longitudinal intrafascicular electrodes. A neural spike detection and classification scheme was developed for the purpose of separating activity of primary and secondary muscle spindle afferents. The algorithm is based on the multiscale continuous wavelet transform using complex wavelets. The detection scheme outperforms the commonly used threshold detection, especially with recordings having low signal-to-noise ratio. Results of classification of units indicate that the developed classifier is able to isolate activity having linear relationship with muscle length, which is a step towards online model-based estimation of muscle length that can be used in a closed-loop functional electrical stimulation system with natural sensory feedback.

Electrical noise modulates perception of electrical pulses in humans: sensation enhancement via stochastic resonance

2014 ◽  
Vol 111 (6) ◽  
pp. 1238-1248 ◽  
Author(s):  
Fivos Iliopoulos ◽  
Till Nierhaus ◽  
Arno Villringer
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Signal Detection ◽  
Stochastic Resonance ◽  
Detection Threshold ◽  
Left Index Finger ◽  
Electrical Noise ◽  
Low Pass ◽  
The Central Nervous System ◽  
Near Threshold

Although noise is usually considered to be harmful for signal detection and information transmission, stochastic resonance (SR) describes the counterintuitive phenomenon of noise enhancing the detection and transmission of weak input signals. In mammalian sensory systems, SR-related phenomena may arise both in the peripheral and the central nervous system. Here, we investigate behavioral SR effects of subliminal electrical noise stimulation on the perception of somatosensory stimuli in humans. We compare the likelihood to detect near-threshold pulses of different intensities applied on the left index finger during presence vs. absence of subliminal noise on the same or an adjacent finger. We show that (low-pass) noise can enhance signal detection when applied on the same finger. This enhancement is strong for near-threshold pulses below the 50% detection threshold and becomes stronger when near-threshold pulses are applied as brief trains. The effect reverses at pulse intensities above threshold, especially when noise is replaced by subliminal sinusoidal stimulation, arguing for a peripheral direct current addition. Unfiltered noise applied on longer pulses enhances detection of all pulse intensities. Noise applied to an adjacent finger has two opposing effects: an inhibiting effect (presumably due to lateral inhibition) and an enhancing effect (most likely due to SR in the central nervous system). In summary, we demonstrate that subliminal noise can significantly modulate detection performance of near-threshold stimuli. Our results indicate SR effects in the peripheral and central nervous system.

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