sound-localization-equilibrium-dynamics

name	sound-localization-equilibrium-dynamics
description	Microsecond-precision sound localization emerges from slow equilibrium dynamics. ITD represented as stable equilibrium of neural population dynamics rather than classical Jeffress place-coding framework.
activation	sound localization, ITD, interaural time difference, equilibrium dynamics, neural population coding, auditory neuroscience, binaural perception, Jeffress model, computational auditory
tags	["neuroscience","auditory-system","sound-localization","neural-dynamics","population-coding","equilibrium","ITD","binaural-processing"]
arxiv_id	2607.03890
date	2026-07-04T00:00:00.000Z
authors	arXiv q-bio.NC
venue	arXiv

Microsecond-Precision Sound Localization Emerges from Slow Equilibrium Dynamics

Paper Summary

Title: Microsecond-precision sound localization emerges from slow equilibrium dynamics
arXiv: 2607.03890
Date: July 4, 2026
Category: q-bio.NC

Core Problem

Paradox: Precise sound localization relies on microsecond sensitivity to interaural time differences (ITDs), yet binaural perception exhibits sluggish tracking of dynamic acoustic cues. How can these properties coexist?

Classical view: Jeffress (1948) place-coding framework requires explicit delay lines or precisely timed inhibition to achieve microsecond precision.

Key Contribution

New Computational Principle

ITD is represented as a stable equilibrium of neural population dynamics rather than by classical place-coding:

• Excitatory and inhibitory interactions across frequency channels generate a population signal
• This signal drives a dynamical system toward an equilibrium corresponding to the estimated ITD
• Despite relying on relatively slow temporal dynamics, achieves microsecond-level precision

Mechanism

1. Cross-frequency interactions: E/I interactions across frequency channels
2. Population signal generation: Creates a dynamical landscape with stable equilibria
3. Equilibrium convergence: System evolves toward ITD-encoding equilibrium
4. Precision without speed: Microsecond precision emerges from equilibrium position, not temporal precision

Key Results

• Achieves microsecond-level ITD precision
• Reproduces key physiological observations:
  • Frequency-dependent best-delay distributions
  • No explicit delay lines required
  • No precisely timed inhibition needed
• Provides explanation for how precise ITD sensitivity arises from slow neural dynamics

Theoretical Framework

Dynamical Systems Approach

• Neural population state evolves on a landscape
• ITD corresponds to position of stable equilibrium
• System converges to equilibrium regardless of initial conditions
• Precision determined by equilibrium sharpness, not dynamics speed

Comparison to Jeffress Model