Human Auditory cortical processing of changes in interaural correlation

Sensitivity to the similarity of the acoustic waveforms at the two ears, and specifically to changes in similarity, is crucial to auditory scene analysis and extraction of objects from background. Here, we use the high temporal resolution of magnetoencephalography to investigate the dynamics of cortical processing of changes in interaural correlation, a measure of interaural similarity, and compare them with behavior. Stimuli are interaurally correlated or uncorrelated wideband noise, immediately followed by the same noise with intermediate degrees of interaural correlation. Behaviorally, listeners' sensitivity to changes in interaural correlation is asymmetrical. Listeners are faster and better at detecting transitions from correlated noise than transitions from uncorrelated noise. The cortical response to the change in correlation is characterized by an activation sequence starting from ∼50 ms after change. The strength of this response parallels behavioral performance: auditory cortical mechanisms are much less sensitive to transitions from uncorrelated noise than from correlated noise. In each case, sensitivity increases with interaural correlation difference. Brain responses to transitions from uncorrelated noise lag those from correlated noise by ∼80 ms, which may be the neural correlate of the observed behavioral response time differences. Importantly, we demonstrate differences in location and time course of neural processing: transitions from correlated noise are processed by a distinct neural population, and with greater speed, than transitions from uncorrelated noise

Cortical responses to natural speech reflect probabilistic phonotactics

Humans comprehend speech despite the various challenges of real-world environments, such as loud noise and mispronunciation. Our auditory system is robust to these thanks to the integration of the upcoming sensory input with prior knowledge and expectations built on language-specific regularities. One such regularity regards the permissible phoneme sequences, which determine the likelihood that a word belongs to a given language (phonotactic probability; “blick” is more likely to be an English word than “bnick”). Previous research suggested that violations of these rules modulate brain evoked responses such as the N400 and the late positive complex. Yet several fundamental questions remain unresolved, especially regarding the neural encoding and integration strategy of phonotactic information. Here, we used linear modelling approaches to assess the influence of phonotactic probabilities on the brain responses to narrative speech measured with non-invasive EEG. We found that the relationship between continuous speech and EEG responses is best described when the speech descriptor includes phonotactic probabilities. This provides us with a methodology to isolate and measure the brain responses to phonotactics using natural speech at the individual subject-level. Furthermore, such low-frequency signals showed the strongest speech-EEG interactions at latencies of 100-400 ms, supporting a pre-lexical role of phonotactic information

Human Time-Frequency Acuity Beats the Fourier Uncertainty Principle

The time-frequency uncertainty principle states that the product of the temporal and frequency extents of a signal cannot be smaller than $1/(4\pi)$. We study human ability to simultaneously judge the frequency and the timing of a sound. Our subjects often exceeded the uncertainty limit, sometimes by more than tenfold, mostly through remarkable timing acuity. Our results establish a lower bound for the nonlinearity and complexity of the algorithms employed by our brains in parsing transient sounds, rule out simple "linear filter" models of early auditory processing, and highlight timing acuity as a central feature in auditory object processing.Comment: 4 pages, 2 figures; Accepted at PR

A Comparison of Regularization Methods in Forward and Backward Models for Auditory Attention Decoding

The decoding of selective auditory attention from noninvasive electroencephalogram (EEG) data is of interest in brain computer interface and auditory perception research. The current state-of-the-art approaches for decoding the attentional selection of listeners are based on linear mappings between features of sound streams and EEG responses (forward model), or vice versa (backward model). It has been shown that when the envelope of attended speech and EEG responses are used to derive such mapping functions, the model estimates can be used to discriminate between attended and unattended talkers. However, the predictive/reconstructive performance of the models is dependent on how the model parameters are estimated. There exist a number of model estimation methods that have been published, along with a variety of datasets. It is currently unclear if any of these methods perform better than others, as they have not yet been compared side by side on a single standardized dataset in a controlled fashion. Here, we present a comparative study of the ability of different estimation methods to classify attended speakers from multi-channel EEG data. The performance of the model estimation methods is evaluated using different performance metrics on a set of labeled EEG data from 18 subjects listening to mixtures of two speech streams. We find that when forward models predict the EEG from the attended audio, regularized models do not improve regression or classification accuracies. When backward models decode the attended speech from the EEG, regularization provides higher regression and classification accuracies

Auditory evoked fields measured non-invasively with small-animal MEG reveal rapid repetition suppression in the guinea pig

In animal models, single-neuron response properties such as stimulus-specific adaptation (SSA) have been described as possible precursors to the mismatch negativity (MMN), a human brain response to stimulus change. Here, we attempt to bridge the gap between human and animal studies by characterising responses to changes in the frequency of repeated tone series in the anaesthetised guinea pig using small-animal magnetoencephalography (MEG). We show that: (1) auditory evoked fields (AEFs) qualitatively similar to those observed in human MEG studies can be detected non-invasively in rodents using small-animal MEG; (2) guinea-pig AEF amplitudes reduce rapidly with tone repetition, and this AEF reduction is largely complete by the second tone in a repeated series; and (3) differences between responses to the first (deviant) and later (standard) tones after a frequency transition resemble those previously observed in awake humans using a similar stimulus paradigm

The Intelligent Music Editor: Towards an Automated Platform for Music Analysis and Editing

Abstract. Digital music editing is a standard process in music production for correcting mistakes and enhancing quality, but this is tedious and time-consuming. The Intelligent Music Editor, or IMED, automates routine music editing tasks using advanced techniques for music transcription (especially score alignment), and signal processing. The IMED starts with multiple recorded tracks and a detailed score that specifies all of the notes to be played. A transcription algorithm locates notes in the recording and identifies their pitch. A scheduling model tracks instantaneous tempo of the recorded performance and determines adjusted timings for output tracks. A time-domain pitch modification/time stretching algorithm performs pitch correction and time adjustment. An empirical evaluation on a multi-track recording illustrates the proposed algorithms achieve an onset detection accuracy of 87 % and a detailed subjective evaluation shows that the IMED improves pitch and timing accuracy while retaining the expressive nuance of the original recording

The spike train statistics for consonant and dissonant musical accords

The simple system composed of three neural-like noisy elements is considered. Two of them (sensory neurons or sensors) are stimulated by noise and periodic signals with different ratio of frequencies, and the third one (interneuron) receives the output of these two sensors and noise. We propose the analytical approach to analysis of Interspike Intervals (ISI) statistics of the spike train generated by the interneuron. The ISI distributions of the sensory neurons are considered to be known. The frequencies of the input sinusoidal signals are in ratios, which are usual for music. We show that in the case of small integer ratios (musical consonance) the input pair of sinusoids results in the ISI distribution appropriate for more regular output spike train than in a case of large integer ratios (musical dissonance) of input frequencies. These effects are explained from the viewpoint of the proposed theory.Comment: 22 pages, 6 figure

Pattern formation in directional solidification under shear flow. I: Linear stability analysis and basic patterns

An asymptotic interface equation for directional solidification near the absolute stabiliy limit is extended by a nonlocal term describing a shear flow parallel to the interface. In the long-wave limit considered, the flow acts destabilizing on a planar interface. Moreover, linear stability analysis suggests that the morphology diagram is modified by the flow near the onset of the Mullins-Sekerka instability. Via numerical analysis, the bifurcation structure of the system is shown to change. Besides the known hexagonal cells, structures consisting of stripes arise. Due to its symmetry-breaking properties, the flow term induces a lateral drift of the whole pattern, once the instability has become active. The drift velocity is measured numerically and described analytically in the framework of a linear analysis. At large flow strength, the linear description breaks down, which is accompanied by a transition to flow-dominated morphologies, described in a companion paper. Small and intermediate flows lead to increased order in the lattice structure of the pattern, facilitating the elimination of defects. Locally oscillating structures appear closer to the instability threshold with flow than without.Comment: 20 pages, Latex, accepted for Physical Review