Research

RESEARCH INTEREST

I study human perception, action and cognition by dynamical systems analysis and modeling. My modeling work explores the dynamical aspects of music perception and performance, such as the interaction of melodic tones in pitch memory, the multistability of rhythmic patterns, and the dynamic coordination in musical performance. With Edward Large, I developed a modeling framework that captures oscillatory dynamics of neural networks in a simple, elegant mathematical form. A series of extensive mathematical analysis revealed the general properties of oscillatory neural networks, which explain the principles underlying complex human behaviors and neural processes, such as music perception and production, auditory neural processing, and rhythmic movement coordination.

Harding, E. E., Kim, J. C., Demos, A. P., Roman, I. R., Tichko, P., Palmer, C., & Large, E. W. (2025). Musical neurodynamics. Nature Reviews Neuroscience, 26, 293–307. [link]

I also lead research and development at Oscillo Biosciences, a startup I co-founded with Edward Large. Our first commercial product was Synchrony LEDs, a music-activated LED controller powered by our oscillatory network technology. We are currently developing a therapeutic intervention for Alzheimer’s disease and mild cognitive impairment, called Synchrony Gamma, which combines the power of music listening with music-synchronized light stimulation.

Tichko, P., Kim, J. C., Large, E., & Loui, P. (2022). Integrating music‐based interventions with Gamma‐frequency stimulation: Implications for healthy ageing. European Journal of Neuroscience, 55(11–12), 3303–3323. [pdf]

RESEARCH PROJECTS

Coordinative Dynamics of Rhythmic Movements

• Phasing performance in percussive ensembles

• Acquisition and retention of multifrequency bimanual coordination

• Embodied Dynamics of Music (EDM)

Dynamics of Music Perception and Cognition

• Perceptual organization of tonal melody

• Neurodynamics of harmony and tonality

• Nonlinear oscillator model of complex rhythm perception

• Dynamical model of auditory scene analysis

Modeling Framework for Oscillatory Systems & Rhythmic Behaviors

• Analysis of Gradient Frequency Neural Networks (GrFNNs)

• Canonical modeling framework for multifrequency coordination and learning