Stimulus and cognitive factors in cortical entrainment to speech

Understanding speech is a difficult computational problem yet the human brain does it with ease. Entrainment of oscillatory neural activity to acoustic features of speech is an example of dynamic coupling between cortical activity and sensory inputs. The phenomenon may be a bottom-up, sensory-driven neurophysiological mechanism that supports speech processing. However, cognitive top-down factors such as linguistic knowledge and attentional focus affect speech perception, especially in challenging real-world environments. It is unclear how these top-down influences affect cortical entrainment to speech. We used electroencephalography to measure cortical entrainment to speech under conditions of acoustic and cognitive interference. By manipulating the bottom-up, sensory features in the acoustic scene we found evidence of top-down influences of attentional selection and linguistic processing on speech-entrained activity

Analysis of patterns of neural activity in response to auditory stimuli

vi, 49 leaves ; 29 cmIt is usually easy to understand speech, but when several people are talking at once it becomes difficult. The brain must select one speech stream and ignore distracting streams. This thesis tested a theory about the neural and computational mechanisms of attentional selection. The theory is that oscillating signals in brain networks phase-lock with amplitude fluctuations in speech. By doing this, brain-wide networks acquire information from the selected speech, but ignore other speech signals on the basis of their non-preferred dynamics. Two predictions were supported: first, attentional selection boosted the power of neuroelectric signals that were phase-locked with attended speech, but not ignored speech. Second, this phase selectivity was associated with better perception for the attended speech. We also describe a novel analysis of neuroelectric responses in complex auditory scenes, and suggest a new model of auditory distraction that is consistent with some unexpected results

The acoustical and perceptual features of snore-related sounds in patients with obstructive sleep apnea sleeping with the dynamic mandibular advancement system MATRx plus®

Purpose: The effect of snoring on the bed partner can be studied through the evaluation of in situ sound records by the bed partner or unspecialized raters as a proxy of real-life snoring perception. The aim was to characterize perceptual snore events through acoustical features in patients with obstructive sleep apnea (OSA) with an advanced mandibular position. Methods: Thirty-minute sound samples of 29 patients with OSA were retrieved from overnight, in-home recordings of a study to validate the MATRx plus® dynamic mandibular advancement system. Three unspecialized raters identified sound events and classified them as noise, snore, or breathing. The raters provided ratings for classification certainty and annoyance. Data were analyzed with respect to respiratory phases, and annoyance. Results: When subdividing perceptual events based on respiratory phase, the logarithm-transformed Mean Power, Spectral Centroid, and Snore Factor differed significantly between event types, although not substantially for the spectral centroid. The variability within event type was high and distributions suggested the presence of subpopulations. The general linear model (GLM) showed a significant patient effect. Inspiration segments occurred in 65% of snore events, expiration segments in 54%. The annoyance correlated with the logarithm of mean power (r = 0.48) and the Snore Factor (0.46). Conclusion: Perceptual sound events identified by non-experts contain a non-negligible mixture of expiration and inspiration phases making the characterization through acoustical features complex. The present study reveals that subpopulations may exist, and patient-specific features need to be introduced

Perceptual snoring as a basis for a psychoacoustical modeling and clinical patient profiling

Purpose The perceptual burden and social nuisance for mainly the co-sleeper can affect the relationship between snorer and bedpartner. Mandibular advancement devices (MAD) are commonly recommended to treat sleep-related breathing such as snoring or sleep apnea. There is no consensus about the definition of snoring particularly with MAD, which is essential for assessing the effectiveness of treatment. We aimed to stablish a notion of perceptual snoring with MAD in place. Methods Sound samples, each 30 min long, were recorded during in-home, overnight, automatic mandibular repositioning titration studies in a population of 29 patients with obstructive sleep apnea syndrome (OSAS) from a clinical trial carried out to validate the MATRx plus. Three unspecialized and calibrated raters identified sound events and classified them as noise, snore, or breathing as well as providing scores for classification certainty and annoyance. Data were analyzed with respect to expiration-inspiration, duration, annoyance, and classification certainty. Results A Fleiss' kappa (>0.80) and correlation duration of events (>0.90) between raters were observed. Prevalence of all breath sounds: snore 55.6% (N = 6398), breathing sounds 31.7% (N = 3652), and noise 9.3% (N = 1072). Inspiration occurs in 88.3% of events, 96.8% contained at least on expiration phase. Snore and breath events had similar duration, respectively 2.58s (sd 1.43) and 2.41s (sd 1.22). Annoyance is lowest for breathing events (8.00 sd 0.98) and highest for snore events (4.90 sd 1.92) on a VAS from zero to ten. Conclusion Perceptual sound events can be a basis for analysis in a psychosocial context. Perceived snoring occurs during both expiration as well as inspiration. Substantial amount of snoring remains despite repositioning of the mandible aimed at the reduction of AHI-ODI

Correction: Dynamics of distraction: competition among auditory streams modulates gain and disrupts inter-trial phase coherence in the human electroencephalogram

This is an open-access article distributed under the terms of the Creative Commons Attribution LIcenseYe

A Bayesian computational basis for auditory selective attention using head rotation and the interaural time-difference cue

<div><p>The process of resolving mixtures of several sounds into their separate individual streams is known as auditory scene analysis and it remains a challenging task for computational systems. It is well-known that animals use binaural differences in arrival time and intensity at the two ears to find the arrival angle of sounds in the azimuthal plane, and this localization function has sometimes been considered sufficient to enable the un-mixing of complex scenes. However, the ability of such systems to resolve distinct sound sources in both space and frequency remains limited. The neural computations for detecting interaural time difference (ITD) have been well studied and have served as the inspiration for computational auditory scene analysis systems, however a crucial limitation of ITD models is that they produce ambiguous or “phantom” images in the scene. This has been thought to limit their usefulness at frequencies above about 1khz in humans. We present a simple Bayesian model and an implementation on a robot that uses ITD information recursively. The model makes use of head rotations to show that ITD information is sufficient to unambiguously resolve sound sources in both space and frequency. Contrary to commonly held assumptions about sound localization, we show that the ITD cue used with high-frequency sound can provide accurate and unambiguous localization and resolution of competing sounds. Our findings suggest that an “active hearing” approach could be useful in robotic systems that operate in natural, noisy settings. We also suggest that neurophysiological models of sound localization in animals could benefit from revision to include the influence of top-down memory and sensorimotor integration across head rotations.</p></div

Resolution of two talkers separated by 45°.

<p>(A) Spectral-spatial map of acoustic scene containing a female and male speaker at 0° and 45° after 9 rotations. White dashed lines indicate the true location of sources. (B) Spatial map of the acoustic scene shows two distinct peaks corresponding to the two talkers. Filled regions under peaks indicate the extent of the beam patterns used to estimate spectra in panel C. (C) Plots of the difference between the average spectrum of the two talkers (Left) and the difference between the activity in the spectral-spatial map at the peaks shown in panel B near 45° (S_B2) and 0° (S_B1). (D) Correlation between difference in the spectra of the target acoustic streams and the difference between the spectra of the two most prominent spatial peaks (blue) and the total localization error between targets and peaks (red) over successive rotations.</p

Resolution of broadband noise and a pure tone.

<p>(A) Spectral-spatial map of acoustic scene containing broadband noise at 0° and a 2400 Hz tone at 11° after 9 rotations. White dashed lines indicate the true location of sources. (B) Spatial map of the acoustic scene shows two distinct peaks corresponding to the noise and tone, respectively. Filled regions under peaks indicate the extent of the beam patterns used to estimate spectra in panel C. (C) Plots of the difference between the average spectrum of the tone (S_T2) and broadband noise (S_T1) (Left) and the difference between the activity in the spectral-spatial map at the peaks shown in panel B near 11° (S_B2) and 0° (S_B1). (D) Correlation between difference in the spectra of the target acoustic streams and the difference between the spectra of the two most prominent spatial peaks (blue) and the total localization error between targets and peaks (red) over successive rotations.</p

Modelled beamformer response to pure tones at varying azimuth angles in egocentric space.

<p>Response to a modelled sound source located at 0° in allocentric space from a set of narrow-band beamformers oriented at various angles in egocentric space obtained from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186104#pone.0186104.e001" target="_blank">Eq 1</a>. At low frequencies, peak activation occurs over broad arcs; multiplying evidence distributions across successive rotations results in a reduced localization uncertainty. At high frequencies multiple peaks are eliminated by multiplying across rotations effectively resolving ambiguity.</p