Neural Basis and Computational Strategies for Auditory Processing

Our senses are our window to the world, and hearing is the window through which we perceive the world of sound. While seemingly effortless, the process of hearing involves complex transformations by which the auditory system consolidates acoustic information from the environment into perceptual and cognitive experiences. Studies of auditory processing try to elucidate the mechanisms underlying the function of the auditory system, and infer computational strategies that are valuable both clinically and intellectually…


1 Introduction
1.1 From sound to meaning
1.1.1 The magic of our auditory system
1.1.2 Challenges of audition
1.2 Thesis outline
2 Auditory system primer
2.1 Nature of sound
2.2 Auditory pathways
2.2.1 Auditory periphery
2.2.2 Central pathways
2.3 Neural receptive fields
3 Cortical timing paradox
3.1 Exploring cortical dynamics
3.1.1 The stimulus space
3.1.2 Cortical response properties
3.1.3 Temporal resolution of cortical information
3.2 Modelling cortical responses
3.2.1 Defining a piecewise linear model
3.2.2 Cortical functions with dual operating-point
3.2.3 Cortical receptive fields
3.3 Neural mechanisms
3.3.1 Synaptic dynamics
3.3.2 Cortical circuitry
3.3.3 Emergence of cortical STRFs
3.4 Functional significance
4 Speech Intelligibility
4.1 Measures of intelligibility
4.2 Intelligibility of communication channels
4.2.1 STMIR procedure
4.2.2 Modulation Transfer Functions in noise
4.3 Intelligibility for noisy speech
4.3.1 STMIT procedure
4.3.2 Human psychoacoustic testing
4.4 Nonlinear speech distortions
4.5 Conclusion
5 Auditory scene analysis
5.1 Perceptual principles
5.1.1 Gestalt principles
5.1.2 Acoustic correlates
5.1.3 Top-down effects
5.2 Literature review of CASA techniques
5.3 Adaptive ASA architecture
5.3.1 Unsupervised learning
5.3.2 Adaptive competitive learning
5.3.3 Model architecture
5.4 Implementation of the model
5.4.1 Pre-processing stage
5.4.2 Multi-scale representation
5.4.3 Cortical filtering
5.4.4 Adaptive learning
5.5 Results
5.5.1 Streaming effects
5.5.2 Speech segregation
5.6 Summary and Discussion
6 Conclusion
6.1 Thesis overview
6.2 Future prospects
A Derivation of predictive learning
A.1 Optimizing the learning function
A.2 Difference to state-space equation

Author: Elhilali, Mounya

Source: University of Maryland

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