🧭 Chan’s Curiosity Log — January 12, 2026

Daily reflections on new papers, theories, and open questions.

🧩 Paper: Multiscale emergence of directional traveling waves in random neuronal networks with nonreciprocal excitation–inhibition synaptic coupling

📄 Phys. Rev. E (2025)

1.1 Background

The brain coordinates distributed neural activity through rich spatiotemporal patterns.
Among these, traveling waves (TWs)—propagating oscillations of neural activity—have emerged as a fundamental mechanism for large-scale communication.
A particularly compelling aspect of TWs is their directionality, which exhibits behaviorally relevant structure: waves often propagate from parietal to anterior and posterior regions during rest and memory tasks, yet can reverse direction across different behavioral contexts.

1.2 Questions

Despite extensive experimental evidence, a unified modeling framework that seamlessly bridges the neuronal, local circuit, and cortical network scales remains elusive.

1.3 Key Idea

The central idea is that nonreciprocal excitation–inhibition (E–I) coupling, even within isolated local many-body systems, generically induces collective oscillations.
These local oscillatory dynamics can then organize into large-scale directional traveling waves.

1.4 Key Conclusions and Results

The authors identify a multi-pathway control mechanism that provides a unified framework for explaining a wide range of experimentally observed wave dynamics, including:

• Fixed-direction propagation, and
• Task-dependent wave reversal.

This mechanism naturally connects dynamics across multiple spatial scales.

1.5 Why It Is Interesting

My advisor once raised the question: “Is there any work showing that non-reciprocal neural networks can generate traveling wave structures?”
This paper provides a clear and concrete answer to that question.

1.6 Questions Worth Exploring

There is a striking analogy between this system and ecological models, where nonreciprocal coupling also gives rise to traveling wave phenomena.
Is there a deeper connection between these systems, and can this analogy be made more precise or even predictive?