2026/06/25 by Anonymous, Pau Pomés, Bastian Pietras +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Chaos control and synchronization #Neural Networks Stability and Synchronization #Nonlinear Dynamics and Pattern Formation #nlin.AO #q-bio.NC
paper · pdf · doi:10.1103/gppc-1j4z
published as Phys. Rev. Res. 8, 033124 (2026)
openalex publication_date 2026/06/25 · openalex created_date 2026/06/26 · arxiv created 2026/07/29 · arxiv updated 2026/07/31 · openalex updated_date 2026/08/01
Collective oscillations in neuronal systems often arise from interactions between excitatory and inhibitory populations rather than from recurrent coupling within a single ensemble. Motivated by the coexistence of strongly and partially synchronized regimes in such systems, we study the Kuramoto-Sakaguchi model on a bipartite network. Despite its minimal structure, the model exhibits rich collective dynamics, including both continuous and discontinuous transitions from full synchrony to partial synchrony (PS). In the PS regime, global oscillations fail to entrain one of the two populations, whose oscillators display quasiperiodic dynamics with an average frequency that can significantly deviate from that of the global field, as observed in neuronal networks. We show that this PS state constitutes an example of self-organized quasiperiodicity, arising here in the bimodal Kuramoto-Sakaguchi model despite its purely linear global coupling.