I study how we hear structures in sounds and sound sequences and learn regularities in the acoustic environment. Auditory perception is a dynamic process through which stable perceptual patterns are formed and learned in time. My approach is to model the auditory system as a dynamical system interacting with the sound environment and explain auditory perception as dynamic pattern formation occurring in the system. My current research projects show that the nonlinear dynamics of neural networks may underlie the perception of musical structures as well as more general auditory functions such as pitch perception and auditory scene analysis.
My research is strongly interdisciplinary, drawing theories and methodologies from psychology, neuroscience, physics, music theory and others. Research areas include music cognition, music information retrieval, computational neuroscience, dynamical systems, auditory modeling and music analysis.
- Perceptual organization of tonal melody
- Neurodynamics of harmony and tonality
- Nonlinear oscillator model of complex rhythm perception
- Dynamical model of auditory scene analysis
- Analysis of gradient frequency neural networks (GrFNNs)