Stochastic facilitation in heteroclinic communication channels

Biological neural systems encode and transmit information as patterns of activity tracing complex trajectories in high-dimensional state spaces, inspiring alternative paradigms processing. Heteroclinic networks, naturally emerging artificial systems, are networks saddles space that provide a transparent approach to generate via controlled switches among interconnected saddles. External signals induce specific switching sequences, thus dynamically encoding inputs trajectories. Recent works have focused either on computational aspects heteroclinic i.e., Computing, or their stochastic properties under noise. Yet, how well such may remains an open question. Here, we investigate the transmission studying them communication channels. Choosing tractable but representative system exhibiting network, mutual rate (MIR) between input resulting sequences states level noise varies. Intriguingly, MIR does not decrease monotonically with increasing Intermediate levels indeed maximize capacity by promoting increased yet exploration underlying network states. Complementing standard resonance, these results highlight constructive effect facilitation (i.e., noise-enhanced transfer) channels possibly more general dynamical space.