Fixed point compositionality via low-rank gluing rules in inhibition-dominated threshold-linear networks
The study investigates how structural modularity supports functional compositionality in inhibition-dominated threshold-linear networks (TLNs). By introducing 'low-rank gluings,' the research proves that global fixed points are constrained to be combinations of local fixed points. This provides a mathematical recipe for engineering complex, predictable dynamics from simple network components.