Synopsis

Pseudovortices Aid in Modeling the Synchronization Behavior of Neurons

• Physics 16, s109
The dynamics of a collection of coupled neurons resemble that of vortices in a commonly studied two-dimensional lattice model, a finding that could help in understanding brain function and dysfunction.
onimate/stock.adobe.com

Ticking clocks and flashing fireflies that start out of sync will fall into sync, a tendency that has been observed for centuries. A discovery two decades ago therefore came as a surprise: the dynamics of identical coupled oscillators can also be asynchronous. The ability to fall in and out of sync, a behavior dubbed a chimera state, is generic to identical coupled oscillators and requires only that the coupling is nonlocal. Now Yasuhiro Yamada and Kensuke Inaba of NTT Basic Research Laboratories in Japan show that this behavior can be analyzed using a lattice model (the XY model) developed to understand antiferromagnetism [1]. Besides a pleasing correspondence, Yamada and Inaba say that their finding offers a path to study the partial synchronization of neurons that underlie brain function and dysfunction.

The chimera states of a system are typically analyzed by looking at how the relative phases of the coupled oscillators fall in and out of sync. But that approach struggles to describe the system when the system contains distantly separated pockets of synchrony or when there are nontrivial configurations of the oscillators, such as twisted or spiral waves. It also requires knowledge of the network’s structure and the oscillators’ equations of motion.

In seeking an alternative approach, Yamada and Inaba turned to a two-dimensional lattice model used to tackle phase transitions in 2D condensed-matter systems. A crucial ingredient in that model is a topological defect called a vortex. Yamada and Inaba found that they could embody the asynchronous dynamics of pairs of oscillators by formulating the problem in terms of an analogous quantity that they call pseudovorticity, whose absence indicates synchrony and whose presence indicates asynchrony. Their calculations show that their pseudo-vorticity-containing lattice model can successfully recover the chimera state behavior of a simulated neural network made up of 200 model oscillators of a type commonly used to study brain activity.

–Charles Day

Charles Day is a Senior Editor for Physics Magazine.

References

  1. Y. Yamada and K. Inaba, “Detecting partial synchrony in a complex oscillatory network using pseudovortices,” Phys. Rev. E 108, 024307 (2023).

Subject Areas

Complex SystemsAstrophysics

Related Articles

Nobel Prize: Neutrinos from Far, Far Away
Particles and Fields

Nobel Prize: Neutrinos from Far, Far Away

Neutrino astronomy and the effort to build a cubic-kilometer-sized detector at the South Pole are recognized by the 2026 Nobel Prize in Physics. Read More »

Quantum States Cannot Hide Their Origin
Complex Systems

Quantum States Cannot Hide Their Origin

Theorists find a persistent signature of a chaotic quantum system’s initial state, implying a memory effect—called a quantum birthmark—that resists thermodynamic equilibration. Read More »

Lab-Based Plasmas Shed Light on Stellar Mystery
Plasma Physics

Lab-Based Plasmas Shed Light on Stellar Mystery

Using high-power lasers to drive highly magnetized plasmas, researchers have probed the stellar processes that control coronal mass ejections. Read More »

More Articles