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

Temporal dynamics of musical emotions examined through intersubject synchrony of brain activity

To study emotional reactions to music, it is important to consider the temporal dynamics of both affective responses and underlying brain activity. Here, we investigated emotions induced by music using functional magnetic resonance imaging (fMRI) with a data-driven approach based on intersubject correlations (ISC). This method allowed us to identify moments in the music that produced similar brain activity (i.e. synchrony) among listeners under relatively natural listening conditions. Continuous ratings of subjective pleasantness and arousal elicited by the music were also obtained for the music outside of the scanner. Our results reveal synchronous activations in left amygdala, left insula and right caudate nucleus that were associated with higher arousal, whereas positive valence ratings correlated with decreases in amygdala and caudate activity. Additional analyses showed that synchronous amygdala responses were driven by energy-related features in the music such as root mean square and dissonance, while synchrony in insula was additionally sensitive to acoustic event density. Intersubject synchrony also occurred in the left nucleus accumbens, a region critically implicated in reward processing. Our study demonstrates the feasibility and usefulness of an approach based on ISC to explore the temporal dynamics of music perception and emotion in naturalistic condition

Self-Supervised Pretraining and Transfer Learning on fMRI Data with Transformers

Transfer learning is a machine learning technique founded on the idea that knowledge acquired by a model during “pretraining” on a source task can be transferred to the learning of a target task. Successful transfer learning can result in improved performance, faster convergence, and reduced demand for data. This technique is particularly desirable for the task of brain decoding in the domain of functional magnetic resonance imaging (fMRI), wherein even the most modern machine learning methods can struggle to decode labelled features of brain images. This challenge is due to the highly complex underlying signal, physical and neurological differences between brains, low data collection throughput, and other factors. Transfer learning is exciting in its potential to mitigate these challenges, but with this application still in its infancy, we must begin on the ground floor. The goals of this thesis were to design, implement, and evaluate a framework for pretraining and transfer learning on arbitrary fMRI datasets, then demonstrate its performance with respect to the literature, and achieve substantive progress toward generalized pretrained models of the brain. The primary contribution is our novel framework which achieves these goals, called BEAT, which stands for Bi-directional Encoders for Auditory Tasks. The design and implementation of BEAT include adapting state-of-the-art deep learning architectures to sequences of fMRI data, as well as a novel self-supervised pretraining task called Next Thought Prediction and several novel supervised brain decoding tasks. To evaluate BEAT, we pretrained ii on Next Thought Prediction and performed transfer learning to the brain decoding tasks, which are specific to one of three fMRI datasets. To demonstrate significant benefits of transfer learning, BEAT decoded instrumental timbre from one of the fMRI datasets which standard methods failed to decode in addition to improved downstream performance. Toward generalized pretrained models of the brain, BEAT learned Next Thought Prediction on one fMRI dataset, and then successfully transferred that learning to a supervised brain decoding task on an entirely distinct dataset, with different participants and stimuli. To our knowledge this is the first instance of transfer learning across participants and stimuli–a necessity for whole-brain pretrained models

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

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

Music Perception in Dementia.

Despite much recent interest in music and dementia, music perception has not been widely studied across dementia syndromes using an information processing approach. Here we addressed this issue in a cohort of 30 patients representing major dementia syndromes of typical Alzheimer's disease (AD, n = 16), logopenic aphasia (LPA, an Alzheimer variant syndrome; n = 5), and progressive nonfluent aphasia (PNFA; n = 9) in relation to 19 healthy age-matched individuals. We designed a novel neuropsychological battery to assess perception of musical patterns in the dimensions of pitch and temporal information (requiring detection of notes that deviated from the established pattern based on local or global sequence features) and musical scene analysis (requiring detection of a familiar tune within polyphonic harmony). Performance on these tests was referenced to generic auditory (timbral) deviance detection and recognition of familiar tunes and adjusted for general auditory working memory performance. Relative to healthy controls, patients with AD and LPA had group-level deficits of global pitch (melody contour) processing while patients with PNFA as a group had deficits of local (interval) as well as global pitch processing. There was substantial individual variation within syndromic groups. Taking working memory performance into account, no specific deficits of musical temporal processing, timbre processing, musical scene analysis, or tune recognition were identified. The findings suggest that particular aspects of music perception such as pitch pattern analysis may open a window on the processing of information streams in major dementia syndromes. The potential selectivity of musical deficits for particular dementia syndromes and particular dimensions of processing warrants further systematic investigation

Perception and Processing of Pitch and Timbre in Human Cortex

University of Minnesota Ph.D. dissertation. 2018. Major: Psychology. Advisor: Andrew Oxenham. 1 computer file (PDF); 157 pages.Pitch and timbre are integral components of auditory perception, yet our understanding of how they interact with one another and how they are processed cortically is enigmatic. Through a series of behavioral studies, neuroimaging, and computational modeling, we investigated these attributes. First, we looked at how variations in one dimension affect our perception of the other. Next, we explored how pitch and timbre are processed in the human cortex, in both a passive listening context and in the presence of attention, using univariate and multivariate analyses. Lastly, we used encoding models to predict cortical responses to timbre using natural orchestral sounds. We found that pitch and timbre interact with each other perceptually, and that musicians and non-musicians are similarly affected by these interactions. Our fMRI studies revealed that, in both passive and active listening conditions, pitch and timbre are processed in largely overlapping regions. However, their patterns of activation are separable, suggesting their underlying circuitry within these regions is unique. Finally, we found that a five-feature, subjectively derived encoding model could predict a significant portion of the variance in the cortical responses to timbre, suggesting our processing of timbral dimensions may align with our perceptual categorizations of them. Taken together, these findings help clarify aspects of both our perception and processing of pitch and timbre

How touch and hearing influence visual processing in sensory substitution, synaesthesia and cross-modal correspondences

Sensory substitution devices (SSDs) systematically turn visual dimensions into patterns of tactile or auditory stimulation. After training, a user of these devices learns to translate these audio or tactile sensations back into a mental visual picture. Most previous SSDs translate greyscale images using intuitive cross-sensory mappings to help users learn the devices. However more recent SSDs have started to incorporate additional colour dimensions such as saturation and hue. Chapter two examines how previous SSDs have translated the complexities of colour into hearing or touch. The chapter explores if colour is useful for SSD users, how SSD and veridical colour perception differ and how optimal cross-sensory mappings might be considered. After long-term training, some blind users of SSDs report visual sensations from tactile or auditory stimulation. A related phenomena is that of synaesthesia, a condition where stimulation of one modality (i.e. touch) produces an automatic, consistent and vivid sensation in another modality (i.e. vision). Tactile-visual synaesthesia is an extremely rare variant that can shed light on how the tactile-visual system is altered when touch can elicit visual sensations. Chapter three reports a series of investigations on the tactile discrimination abilities and phenomenology of tactile-vision synaesthetes, alongside questionnaire data from synaesthetes unavailable for testing. Chapter four introduces a new SSD to test if the presentation of colour information in sensory substitution affects object and colour discrimination. Chapter five presents experiments on intuitive auditory-colour mappings across a wide variety of sounds. These findings are used to predict the reported colour hallucinations resulting from LSD use while listening to these sounds. Chapter six uses a new sensory substitution device designed to test the utility of these intuitive sound-colour links for visual processing. These findings are discussed with reference to how cross-sensory links, LSD and synaesthesia can inform optimal SSD design for visual processing