Emergent Traveling Waves in Neural Circuits

Abstract Artificial neural networks achieve striking performance but do not capture a prominent neural property. Cortical activity is organized by structured spatiotemporal dynamics, traveling waves (TW), which have been implicated in a wide range of functions. Existing computational models often rely on hand-crafted connectivity and imposed dynamics, offering insight into their impact but less into how the waves naturally emerge in biological circuits. Here, we found that TWs emerge in models under biologically plausible constraints (spatially organized, directionally biased connectivity). Under an empirical neural manifold constraint, these wiring principles naturally emerge to support traveling wave dynamics in the recurrent model. We further show that wave propagation provides a robust mechanism for maintaining working memory in the presence of visual distractors. We compared these model predictions to non-human primate prefrontal cortex recordings, revealing a similar mechanism. Together, these results advance our understanding of traveling waves as a substrate for cognition and offer a framework for mechanistic accounts of cortical computation.