ECoG high gamma activity reveals distinct cortical representations of lyrics passages, harmonic and timbre-related changes in a rock song

Listening to music moves our minds and moods, stirring interest in its neural underpinnings. A multitude of compositional features drives the appeal of natural music. How such original music, where a composer's opus is not manipulated for experimental purposes, engages a listener's brain has not been studied until recently. Here, we report an in-depth analysis of two electrocorticographic (ECoG) data sets obtained over the left hemisphere in ten patients during presentation of either a rock song or a read-out narrative. First, the time courses of five acoustic features (intensity, presence/absence of vocals with lyrics, spectral centroid, harmonic change, and pulse clarity) were extracted from the audio tracks and found to be correlated with each other to varying degrees. In a second step, we uncovered the specific impact of each musical feature on ECoG high-gamma power (70–170 Hz) by calculating partial correlations to remove the influence of the other four features. In the music condition, the onset and offset of vocal lyrics in ongoing instrumental music was consistently identified within the group as the dominant driver for ECoG high-gamma power changes over temporal auditory areas, while concurrently subject-individual activation spots were identified for sound intensity, timbral, and harmonic features. The distinct cortical activations to vocal speech-related content embedded in instrumental music directly demonstrate that song integrated in instrumental music represents a distinct dimension in complex music. In contrast, in the speech condition, the full sound envelope was reflected in the high gamma response rather than the onset or offset of the vocal lyrics. This demonstrates how the contributions of stimulus features that modulate the brain response differ across the two examples of a full-length natural stimulus, which suggests a context-dependent feature selection in the processing of complex auditory stimuli

Representation of statistical sound properties in human auditory cortex

The work carried out in this doctoral thesis investigated the representation of statistical sound properties in human auditory cortex. It addressed four key aspects in auditory neuroscience: the representation of different analysis time windows in auditory cortex; mechanisms for the analysis and segregation of auditory objects; information-theoretic constraints on pitch sequence processing; and the analysis of local and global pitch patterns. The majority of the studies employed a parametric design in which the statistical properties of a single acoustic parameter were altered along a continuum, while keeping other sound properties fixed. The thesis is divided into four parts. Part I (Chapter 1) examines principles of anatomical and functional organisation that constrain the problems addressed. Part II (Chapter 2) introduces approaches to digital stimulus design, principles of functional magnetic resonance imaging (fMRI), and the analysis of fMRI data. Part III (Chapters 3-6) reports five experimental studies. Study 1 controlled the spectrotemporal correlation in complex acoustic spectra and showed that activity in auditory association cortex increases as a function of spectrotemporal correlation. Study 2 demonstrated a functional hierarchy of the representation of auditory object boundaries and object salience. Studies 3 and 4 investigated cortical mechanisms for encoding entropy in pitch sequences and showed that the planum temporale acts as a computational hub, requiring more computational resources for sequences with high entropy than for those with high redundancy. Study 5 provided evidence for a hierarchical organisation of local and global pitch pattern processing in neurologically normal participants. Finally, Part IV (Chapter 7) concludes with a general discussion of the results and future perspectives

Approaches to the cortical analysis of auditory objects

We describe work that addresses the cortical basis for the analysis of auditory objects using ‘generic’ sounds that do not correspond to any particular events or sources (like vowels or voices) that have semantic association. The experiments involve the manipulation of synthetic sounds to produce systematic changes of stimulus features, such as spectral envelope. Conventional analyses of normal functional imaging data demonstrate that the analysis of spectral envelope and perceived timbral change involves a network consisting of planum temporale (PT) bilaterally and the right superior temporal sulcus (STS). Further analysis of imaging data using dynamic causal modelling (DCM) and Bayesian model selection was carried out in the right hemisphere areas to determine the effective connectivity between these auditory areas. Specifically, the objective was to determine if the analysis of spectral envelope in the network is done in a serial fashion (that is from HG to PT to STS) or parallel fashion (that is PT and STS receives input from HG simultaneously). Two families of models, serial and parallel (16 in total) that represent different hypotheses about the connectivity between HG, PT and STS were selected. The models within a family differ with respect to the pathway that is modulated by the analysis of spectral envelope. After the models are identified, Bayesian model selection procedure is then used to select the ‘optimal’ model from the specified models. The data strongly support a particular serial model containing modulation of the HG to PT effective connectivity during spectral envelope variation. Parallel work in neurological subjects addresses the effect of lesions to different parts of this network. We have recently studied in detail subjects with ‘dystimbria’: an alteration in the perceived quality of auditory objects distinct from pitch or loudness change. The subjects have lesions of the normal network described above with normal perception of pitch strength but abnormal perception of the analysis of spectral envelope change

A Visionary Approach to Listening: Determining The Role Of Vision In Auditory Scene Analysis

To recognize and understand the auditory environment, the listener must first separate sounds that arise from different sources and capture each event. This process is known as auditory scene analysis. The aim of this thesis is to investigate whether and how visual information can influence auditory scene analysis. The thesis consists of four chapters. Firstly, I reviewed the literature to give a clear framework about the impact of visual information on the analysis of complex acoustic environments. In chapter II, I examined psychophysically whether temporal coherence between auditory and visual stimuli was sufficient to promote auditory stream segregation in a mixture. I have found that listeners were better able to report brief deviants in an amplitude modulated target stream when a visual stimulus changed in size in a temporally coherent manner than when the visual stream was coherent with the non-target auditory stream. This work demonstrates that temporal coherence between auditory and visual features can influence the way people analyse an auditory scene. In chapter III, the integration of auditory and visual features in auditory cortex was examined by recording neuronal responses in awake and anaesthetised ferret auditory cortex in response to the modified stimuli used in Chapter II. I demonstrated that temporal coherence between auditory and visual stimuli enhances the neural representation of a sound and influences which sound a neuron represents in a sound mixture. Visual stimuli elicited reliable changes in the phase of the local field potential which provides mechanistic insight into this finding. Together these findings provide evidence that early cross modal integration underlies the behavioural effects in chapter II. Finally, in chapter IV, I investigated whether training can influence the ability of listeners to utilize visual cues for auditory stream analysis and showed that this ability improved by training listeners to detect auditory-visual temporal coherence

DISSOCIABLE MECHANISMS OF CONCURRENT SPEECH IDENTIFICATION IN NOISE AT CORTICAL AND SUBCORTICAL LEVELS.

When two vowels with different fundamental frequencies (F0s) are presented concurrently, listeners often hear two voices producing different vowels on different pitches. Parsing of this simultaneous speech can also be affected by the signal-to-noise ratio (SNR) in the auditory scene. The extraction and interaction of F0 and SNR cues may occur at multiple levels of the auditory system. The major aims of this dissertation are to elucidate the neural mechanisms and time course of concurrent speech perception in clean and in degraded listening conditions and its behavioral correlates. In two complementary experiments, electrical brain activity (EEG) was recorded at cortical (EEG Study #1) and subcortical (FFR Study #2) levels while participants heard double-vowel stimuli whose fundamental frequencies (F0s) differed by zero and four semitones (STs) presented in either clean or noise degraded (+5 dB SNR) conditions. Behaviorally, listeners were more accurate in identifying both vowels for larger F0 separations (i.e., 4ST; with pitch cues), and this F0-benefit was more pronounced at more favorable SNRs. Time-frequency analysis of cortical EEG oscillations (i.e., brain rhythms) revealed a dynamic time course for concurrent speech processing that depended on both extrinsic (SNR) and intrinsic (pitch) acoustic factors. Early high frequency activity reflected pre-perceptual encoding of acoustic features (~200 ms) and the quality (i.e., SNR) of the speech signal (~250-350ms), whereas later-evolving low-frequency rhythms (~400-500ms) reflected post-perceptual, cognitive operations that covaried with listening effort and task demands. Analysis of subcortical responses indicated that while FFRs provided a high-fidelity representation of double vowel stimuli and the spectro-temporal nonlinear properties of the peripheral auditory system. FFR activity largely reflected the neural encoding of stimulus features (exogenous coding) rather than perceptual outcomes, but timbre (F1) could predict the speed in noise conditions. Taken together, results of this dissertation suggest that subcortical auditory processing reflects mostly exogenous (acoustic) feature encoding in stark contrast to cortical activity, which reflects perceptual and cognitive aspects of concurrent speech perception. By studying multiple brain indices underlying an identical task, these studies provide a more comprehensive window into the hierarchy of brain mechanisms and time-course of concurrent speech processing

Why would Musical Training Benefit the Neural Encoding of Speech? The OPERA Hypothesis

Mounting evidence suggests that musical training benefits the neural encoding of speech. This paper offers a hypothesis specifying why such benefits occur. The “OPERA” hypothesis proposes that such benefits are driven by adaptive plasticity in speech-processing networks, and that this plasticity occurs when five conditions are met. These are: (1) Overlap: there is anatomical overlap in the brain networks that process an acoustic feature used in both music and speech (e.g., waveform periodicity, amplitude envelope), (2) Precision: music places higher demands on these shared networks than does speech, in terms of the precision of processing, (3) Emotion: the musical activities that engage this network elicit strong positive emotion, (4) Repetition: the musical activities that engage this network are frequently repeated, and (5) Attention: the musical activities that engage this network are associated with focused attention. According to the OPERA hypothesis, when these conditions are met neural plasticity drives the networks in question to function with higher precision than needed for ordinary speech communication. Yet since speech shares these networks with music, speech processing benefits. The OPERA hypothesis is used to account for the observed superior subcortical encoding of speech in musically trained individuals, and to suggest mechanisms by which musical training might improve linguistic reading abilities

Intelligibility benefit for familiar voices is not accompanied by better discrimination of fundamental frequency or vocal tract length

Speech is more intelligible when it is spoken by familiar than unfamiliar people. If this benefit arises because key voice characteristics like perceptual correlates of fundamental frequency or vocal tract length (VTL) are more accurately represented for familiar voices, listeners may be able to discriminate smaller manipulations to such characteristics for familiar than unfamiliar voices. We measured participants’ (N = 17) thresholds for discriminating pitch (correlate of fundamental frequency, or glottal pulse rate) and formant spacing (correlate of VTL; ‘VTL-timbre’) for voices that were familiar (participants’ friends) and unfamiliar (other participants’ friends). As expected, familiar voices were more intelligible. However, discrimination thresholds were no smaller for the same familiar voices. The size of the intelligibility benefit for a familiar over an unfamiliar voice did not relate to the difference in discrimination thresholds for the same voices. Also, the familiar-voice intelligibility benefit was just as large following perceptible manipulations to pitch and VTL-timbre. These results are more consistent with cognitive accounts of speech perception than traditional accounts that predict better discrimination

A Linear Hybrid Sound Generation of Musical Instruments using Temporal and Spectral Shape Features

The generation of a hybrid musical instrument sound using morphing has always been an area of great interest to the music world. The proposed method exploits the temporal and spectral shape features of the sound for this purpose. For an effective morphing the temporal and spectral features are found as they can capture the most perceptually salient dimensions of timbre perception, namely, the attack time and the distribution of spectral energy. A wide variety of sound synthesis algorithms is currently available. Sound synthesis methods have become more computationally efficient. Wave table synthesis is widely adopted by digital sampling instruments or samplers. The Over Lap Add method (OLA) refers to a family of algorithms that produce a signal by properly assembling a number of signal segments. In granular synthesis sound is considered as a sequence with overlaps of elementary acoustic elements called grains. The simplest morph is a cross-fade of amplitudes in the time domain which can be obtained through cross synthesis. A hybrid sound is generated with all these methods to find out which method gives the most linear morph. The result will be evaluated as an error measure which is the difference between the calculated and interpolated features. The extraction of morph in a perceptually pleasant manner is the ultimate requirement of the work. DOI: 10.17762/ijritcc2321-8169.16045

Music and the brain: disorders of musical listening

The study of the brain bases for normal musical listening has advanced greatly in the last 30 years. The evidence from basic and clinical neuroscience suggests that listening to music involves many cognitive components with distinct brain substrates. Using patient cases reported in the literature, we develop an approach for understanding disordered musical listening that is based on the systematic assessment of the perceptual and cognitive analysis of music and its emotional effect. This approach can be applied both to acquired and congenital deficits of musical listening, and to aberrant listening in patients with musical hallucinations. Both the bases for normal musical listening and the clinical assessment of disorders now have a solid grounding in systems neuroscience

Neurophysiological Influence of Musical Training on Speech Perception

Does musical training affect our perception of speech? For example, does learning to play a musical instrument modify the neural circuitry for auditory processing in a way that improves one's ability to perceive speech more clearly in noisy environments? If so, can speech perception in individuals with hearing loss (HL), who struggle in noisy situations, benefit from musical training? While music and speech exhibit some specialization in neural processing, there is evidence suggesting that skills acquired through musical training for specific acoustical processes may transfer to, and thereby improve, speech perception. The neurophysiological mechanisms underlying the influence of musical training on speech processing and the extent of this influence remains a rich area to be explored. A prerequisite for such transfer is the facilitation of greater neurophysiological overlap between speech and music processing following musical training. This review first establishes a neurophysiological link between musical training and speech perception, and subsequently provides further hypotheses on the neurophysiological implications of musical training on speech perception in adverse acoustical environments and in individuals with HL