Dale's law, stability and nonlinearity are sufficient constraints to ignite transient and self-sustained neural dynamics
- 1Institute of Science and Technology Austria (ISTA)
Abstract
The motor cortex orchestrates a rich and flexible repertoire of network dynamics for rhythmic and goal-directed movements. Computational studies have begun to illuminate the mechanistic origins of this repertoire, but a comprehensive model that can explain the emergence of both transient and self-sustained dynamics is still missing. Here, we show that three simple ingredients: Dalean connectivity, stability, and nonlinear neural responses, suffice to reverse-engineer networks that produce transient, steady-state, and self-sustained periodic activity. A single dynamical principle underlies this repertoire: the interaction of non-normal amplification, inherent to Dalean networks, with neuronal nonlinearity, so to ignite and sustain multi-stable, controllable dynamics. Our approach yields entire families of connectivity matrices that require no hand-tuning or learning of weights. Without fitting them to data, these networks reproduce the population-level signatures of motor cortex, implying that the richness of cortical dynamics need not be sculpted by learning, but may emerge from simple biological ingredients.
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BibTeX
@misc{condruz2026dales,
title = {{Dale's law, stability and nonlinearity are sufficient constraints to ignite transient and self-sustained neural dynamics}},
author = {N. Condruz and I. Bulygin and C. Chintaluri and T. P. Vogels},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.14.751508},
url = {https://www.biorxiv.org/content/10.64898/2026.09.14.751508v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Dale's law, stability and nonlinearity are sufficient constraints to ignite transient and self-sustained neural dynamics
AU - N. Condruz
AU - I. Bulygin
AU - C. Chintaluri
AU - T. P. Vogels
PY - 2026
DA - 2026/09/14
PB - bioRxiv
DO - 10.64898/2026.09.14.751508
UR - https://www.biorxiv.org/content/10.64898/2026.09.14.751508v1
AB - The motor cortex orchestrates a rich and flexible repertoire of network dynamics for rhythmic and goal-directed movements. Computational studies have begun to illuminate the mechanistic origins of this repertoire, but a comprehensive model that can explain the emergence of both transient and self-sustained dynamics is still missing. Here, we show that three simple ingredients: Dalean connectivity, stability, and nonlinear neural responses, suffice to reverse-engineer networks that produce transient, steady-state, and self-sustained periodic activity. A single dynamical principle underlies this repertoire: the interaction of non-normal amplification, inherent to Dalean networks, with neuronal nonlinearity, so to ignite and sustain multi-stable, controllable dynamics. Our approach yields entire families of connectivity matrices that require no hand-tuning or learning of weights. Without fitting them to data, these networks reproduce the population-level signatures of motor cortex, implying that the richness of cortical dynamics need not be sculpted by learning, but may emerge from simple biological ingredients.
ER -