Cusped singularities organize mixed-mode oscillations in mutually inhibitory slow-fast systems
New math reveals how inhibitory circuits produce mixed oscillatory rhythms...
A new mathematical framework published on arXiv (2605.03606) by Morten Gram Pedersen establishes that cusped singularities—special folded points on critical manifolds—serve as universal organizers for mixed-mode oscillations (MMOs) in coupled slow-fast systems with mutual inhibition. The paper shows that these geometric structures produce small-amplitude oscillations (SAOs) via geometric singular perturbation theory and blow-up methods, which then combine with a return mechanism to create the alternating large-and-small amplitude patterns characteristic of MMOs.
Pedersen validates the theory in two distinct neuronal models: the Curtu rate model of mutually inhibitory neural populations and coupled Morris-Lecar neurons with synaptic inhibition. In both cases, pushing the system equilibrium near the cusped singularity triggers SAOs as the system passes the cusp and approaches a full-system saddle-focus linked to a singular Hopf bifurcation. Large-amplitude oscillations emerge as the system spirals away, producing alternating patterns distinct from standard saddle-node-induced MMOs. This work provides a generic, biologically relevant mechanism for complex oscillatory dynamics in inhibitory neural networks, with implications for understanding brain rhythms, seizure activity, and neural computation.
- Cusped singularities (folded points on critical manifolds) are shown to be universal organizers for mixed-mode oscillations in mutually inhibitory slow-fast systems
- Validated in two neuronal models: Curtu rate model for inhibitory populations and coupled Morris-Lecar neurons with synaptic inhibition
- The mechanism links small-amplitude oscillations near the cusp to a singular Hopf bifurcation, producing alternating large-amplitude patterns distinct from standard MMOs
Why It Matters
Provides a geometric foundation for complex neural rhythms, potentially explaining brain oscillations and seizure dynamics.