Dynamical Systems Modeling and Data Analysis Software
The Gradient Frequency Neural Network (GrFNN – pronounced “Griffin”) Toolbox, is a suite of Matlab programs for simulating and analyzing signal processing, plasticity, and pattern formation in the auditory system. GrFNNs can be used to simulate active cochlear responses, auditory brainstem physiology, auditory cortical physiology, pitch perception, tonality perception, dynamic attending and rhythm perception. Some models are available below. The current release is 1.2.1.
- Canonical Nonlinear Cochlea
This repository includes scripts for a canonical nonlinear cochlear model using the GrFNN Toolbox, based on coupling between the basilar membrane and outer hair cells of the organ of Corti. The model includes human middle ear filtering (Zilaney & Bruce, 2006) and the cochlear parameters have been chosen to replicate the tuning curves in macaques (Joris et al., 2011).
- Dynamical Auditory Brainstem
This repository contains scripts for simulating a dynamical model of the auditory periphery and brainstem using the GrFNN Toolbox. The first two layers simulate nonlinear cochlear filtering. The next layer represents the cochlear nucleus, which already exhibits many interesting nonlinear properties, including mode-locking. The fourth layer of simulates the inferior colliculus, believed to be an important area for the perception of pitch, as well as a potential generating site of the FFR (frequency-following response) in response to periodic stimuli.
- Pulse and Meter Perception in Complex Musical Rhythms
This repository includes scripts to run models of pulse and meter perception in musical rhythm using the GrFNN Toolbox. The model is one of the few consistent with neurophysiological evidence on the role of neural oscillation, and it explains a phenomenon (the “missing pulse”) that other computational models fail to explain.
Circular Statistics Toolbox
This is a toolbox for doing circular statistics with Matlab. It requires the Matlab Statistics Toolbox. Reference: P. Berens, CircStat: A Matlab Toolbox for Circular Statistics, Journal of Statistical Software, 31 (10), 2009.
Dynamic Score Matcher
The toolbox provides functions to a match a musical performance to its corresponding notation, or score. This program requires the MIDI Toolbox. The matcher utilizes dynamic programming techniques and runs in polynomial time. Reference: Large, E. W. (1993). Dynamic programming for the analysis of serial behaviors. Behavior Research Methods, Instruments, and Computers, 25 (2), 238-241.
Movies, Animations and Other Supplementary Materials
Large, E. W., Kim, J. C., Flaig, N., Bharucha, J., & Krumhansl, C. L. (2016). A neurodynamic account of musical tonality, Music Perception, 33 (3), 319-331.
Kim, J. C., & Large, E. W. (2015). Signal processing in periodically forced gradient frequency neural networks, Frontiers in Computational Neuroscience, 9:152.
Large, E. W. & Gray, P. (2015). Spontaneous tempo and entrainment in a bonobo (Pan paniscus), Journal of Comparative Psychology, 129 (4), 317-28.
Chapin, H., Jantzen, K. J., Kelso, J. A. S., Steinberg, F. & Large, E. W. (2010). Dynamic emotional and neural responses to music depend on performance expression and listener experience, PLoS ONE, 5 (12), e13812.