In-channel cancellation: A model of early auditory processing.

A model of early auditory processing is proposed in which each peripheral channel is processed by a delay-and-subtract cancellation filter, tuned independently for each channel with a criterion of minimum power. For a channel dominated by a pure tone or a resolved partial of a complex tone, the optimal delay is its period. For a channel responding to harmonically related partials, the optimal delay is their common fundamental period. Each peripheral channel is thus split into two subchannels-one that is cancellation-filtered and the other that is not. Perception can involve either or both, depending on the task. The model is illustrated by applying it to the masking asymmetry between pure tones and narrowband noise: a noise target masked by a tone is more easily detectable than a tone target masked by noise. The model is one of a wider class of models, monaural or binaural, that cancel irrelevant stimulus dimensions to attain invariance to competing sources. Similar to occlusion in the visual domain, cancellation yields sensory evidence that is incomplete, thus requiring Bayesian inference of an internal model of the world along the lines of Helmholtz's doctrine of unconscious inference.

Why is the perceptual octave stretched? An account based on mismatched time constants within the auditory brainstem.

This paper suggests an explanation for listeners' greater tolerance to positive than negative mistuning of the higher tone within an octave pair. It hypothesizes a neural circuit tuned to cancel the lower tone that also cancels the higher tone if that tone is in tune. Imperfect cancellation is the cue to mistuning of the octave. The circuit involves two neural pathways, one delayed with respect to the other, that feed a coincidence-sensitive neuron via excitatory and inhibitory synapses. A mismatch between the time constants of these two synapses results in an asymmetry in sensitivity to mismatch. Specifically, if the time constant of the delayed pathway is greater than that of the direct pathway, there is a greater tolerance to positive mistuning than to negative mistuning. The model is directly applicable to the harmonic octave (concurrent tones) but extending it to the melodic octave (successive tones) requires additional assumptions that are discussed. The paper reviews evidence from auditory psychophysics and physiology in favor-or against-this explanation.

The Spectral Extent of Phasic Suppression of Loudness and Distortion-Product Otoacoustic Emissions by Infrasound and Low-Frequency Tones.

We investigated the effect of a biasing tone close to 5, 15, or 30 Hz on the response to higher-frequency probe tones, behaviorally, and by measuring distortion-product otoacoustic emissions (DPOAEs). The amplitude of the biasing tone was adjusted for criterion suppression of cubic DPOAE elicited by probe tones presented between 0.7 and 8 kHz, or criterion loudness suppression of a train of tone-pip probes in the range 0.125-8 kHz. For DPOAEs, the biasing-tone level for criterion suppression increased with probe-tone frequency by 8-9 dB/octave, consistent with an apex-to-base gradient of biasing-tone-induced basilar membrane displacement, as we verified by computational simulation. In contrast, the biasing-tone level for criterion loudness suppression increased with probe frequency by only 1-3 dB/octave, reminiscent of previously published data on low-side suppression of auditory nerve responses to characteristic frequency tones. These slopes were independent of biasing-tone frequency, but the biasing-tone sensation level required for criterion suppression was ~ 10 dB lower for the two infrasound biasing tones than for the 30-Hz biasing tone. On average, biasing-tone sensation levels as low as 5 dB were sufficient to modulate the perception of higher frequency sounds. Our results are relevant for recent debates on perceptual effects of environmental noise with very low-frequency content and might offer insight into the mechanism underlying low-side suppression.

Harmonic Cancellation-A Fundamental of Auditory Scene Analysis.

This paper reviews the hypothesis of harmonic cancellation according to which an interfering sound is suppressed or canceled on the basis of its harmonicity (or periodicity in the time domain) for the purpose of Auditory Scene Analysis. It defines the concept, discusses theoretical arguments in its favor, and reviews experimental results that support it, or not. If correct, the hypothesis may draw on time-domain processing of temporally accurate neural representations within the brainstem, as required also by the classic equalization-cancellation model of binaural unmasking. The hypothesis predicts that a target sound corrupted by interference will be easier to hear if the interference is harmonic than inharmonic, all else being equal. This prediction is borne out in a number of behavioral studies, but not all. The paper reviews those results, with the aim to understand the inconsistencies and come up with a reliable conclusion for, or against, the hypothesis of harmonic cancellation within the auditory system.

Neurophysiological Indices of Audiovisual Speech Processing Reveal a Hierarchy of Multisensory Integration Effects.

Seeing a speaker's face benefits speech comprehension, especially in challenging listening conditions. This perceptual benefit is thought to stem from the neural integration of visual and auditory speech at multiple stages of processing, whereby movement of a speaker's face provides temporal cues to auditory cortex, and articulatory information from the speaker's mouth can aid recognizing specific linguistic units (e.g., phonemes, syllables). However, it remains unclear how the integration of these cues varies as a function of listening conditions. Here, we sought to provide insight on these questions by examining EEG responses in humans (males and females) to natural audiovisual (AV), audio, and visual speech in quiet and in noise. We represented our speech stimuli in terms of their spectrograms and their phonetic features and then quantified the strength of the encoding of those features in the EEG using canonical correlation analysis (CCA). The encoding of both spectrotemporal and phonetic features was shown to be more robust in AV speech responses than what would have been expected from the summation of the audio and visual speech responses, suggesting that multisensory integration occurs at both spectrotemporal and phonetic stages of speech processing. We also found evidence to suggest that the integration effects may change with listening conditions; however, this was an exploratory analysis and future work will be required to examine this effect using a within-subject design. These findings demonstrate that integration of audio and visual speech occurs at multiple stages along the speech processing hierarchy.SIGNIFICANCE STATEMENT During conversation, visual cues impact our perception of speech. Integration of auditory and visual speech is thought to occur at multiple stages of speech processing and vary flexibly depending on the listening conditions. Here, we examine audiovisual (AV) integration at two stages of speech processing using the speech spectrogram and a phonetic representation, and test how AV integration adapts to degraded listening conditions. We find significant integration at both of these stages regardless of listening conditions. These findings reveal neural indices of multisensory interactions at different stages of processing and provide support for the multistage integration framework.

Auditory stimulus-response modeling with a match-mismatch task.

Objective.An auditory stimulus can be related to the brain response that it evokes by a stimulus-response model fit to the data. This offers insight into perceptual processes within the brain and is also of potential use for devices such as brain computer interfaces (BCIs). The quality of the model can be quantified by measuring the fit with a regression problem, or by applying it to a classification task and measuring its performance.Approach.Here we focus on amatch-mismatch(MM) task that entails deciding whether a segment of brain signal matches, via a model, the auditory stimulus that evoked it.Main results. Using these metrics, we describe a range of models of increasing complexity that we compare to methods in the literature, showing state-of-the-art performance. We document in detail one particular implementation, calibrated on a publicly-available database, that can serve as a robust reference to evaluate future developments.Significance.The MM task allows stimulus-response models to be evaluated in the limit of very high model accuracy, making it an attractive alternative to the more commonly used task of auditory attention detection. The MM task does not require class labels, so it is immune to mislabeling, and it is applicable to data recorded in listening scenarios with only one sound source, thus it is cheap to obtain large quantities of training and testing data. Performance metrics from this task, associated with regression accuracy, provide complementary insights into the relation between stimulus and response, as well as information about discriminatory power directly applicable to BCI applications.

Cortical encoding of melodic expectations in human temporal cortex.

Humans engagement in music rests on underlying elements such as the listeners' cultural background and interest in music. These factors modulate how listeners anticipate musical events, a process inducing instantaneous neural responses as the music confronts these expectations. Measuring such neural correlates would represent a direct window into high-level brain processing. Here we recorded cortical signals as participants listened to Bach melodies. We assessed the relative contributions of acoustic versus melodic components of the music to the neural signal. Melodic features included information on pitch progressions and their tempo, which were extracted from a predictive model of musical structure based on Markov chains. We related the music to brain activity with temporal response functions demonstrating, for the first time, distinct cortical encoding of pitch and note-onset expectations during naturalistic music listening. This encoding was most pronounced at response latencies up to 350 ms, and in both planum temporale and Heschl's gyrus.

ZapLine: A simple and effective method to remove power line artifacts.

Power line artifacts are the bane of animal and human electrophysiology. A number of methods are available to help attenuate or eliminate them, but each has its own set of drawbacks. In this brief note I present a simple method that combines the advantages of spectral and spatial filtering, while minimizing their downsides. A perfect-reconstruction filterbank is used to split the data into two parts, one noise-free and the other contaminated by line artifact. The artifact-contaminated stream is processed by a spatial filter to project out line components, and added to the noise-free part to obtain clean data. This method is applicable to multichannel data such as electroencephalography (EEG), magnetoencephalography (MEG), or multichannel local field potentials (LFP). I briefly review past methods, pointing out their drawbacks, describe the new method, and evaluate the outcome using synthetic and real data.

Filters: When, Why, and How (Not) to Use Them.

Filters are commonly used to reduce noise and improve data quality. Filter theory is part of a scientist's training, yet the impact of filters on interpreting data is not always fully appreciated. This paper reviews the issue and explains what a filter is, what problems are to be expected when using them, how to choose the right filter, and how to avoid filtering by using alternative tools. Time-frequency analysis shares some of the same problems that filters have, particularly in the case of wavelet transforms. We recommend reporting filter characteristics with sufficient details, including a plot of the impulse or step response as an inset.

Low-frequency cortical responses to natural speech reflect probabilistic phonotactics.

Humans comprehend speech despite the various challenges such as mispronunciation and noisy environments. Our auditory system is robust to these thanks to the integration of the 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 demonstrated that violations of these rules modulate brain-evoked responses. However, several fundamental questions remain unresolved, especially regarding the neural encoding and integration strategy of phonotactics in naturalistic conditions, when there are no (or few) violations. Here, we used linear modelling 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 stimulus descriptor includes phonotactic probabilities. This indicates that low-frequency cortical signals (<9 Hz) reflect the integration of phonotactic information during natural speech perception, providing us with a measure of phonotactic processing at the individual subject-level. Furthermore, phonotactics-related signals showed the strongest speech-EEG interactions at latencies of 100-500 ms, supporting a pre-lexical role of phonotactic information.