A Self-Priming Neural Chain Links Sequential Behaviors Across Timescales

Behavioral sequences are essential for survival, yet the neural mechanisms that link one action to the next remain incompletely understood. In classical chain models, sequential behaviors arise through feedforward propagation of activity across distinct neuronal populations or network modules. Here, we identify a distinct form of neural chain mechanism in which neurons active during a first behavior modulate themselves into a persistent state of elevated tonic firing that subsequently drives the second behavior from within the first circuit module. We term this process self-priming, reflecting the role of activity-dependent auto-modulation in enabling behavioral sequencing. We investigated this mechanism in the escape swim/crawl sequence of the marine mollusk Tritonia diomedea, in which rhythmic swimming is consistently followed by tens of minutes of rapid crawling. Serotonergic dorsal swim interneurons (DSIs), components of the swim central pattern generator, were previously known to exhibit elevated firing for tens of minutes after a swim motor program (SMP) and to drive crawling. We show here that their sustained post-SMP activity arises from self-induced increases in DSI excitability: their bursting during the SMP produces long-lasting depolarization and enhanced excitability within the DSI population. This persistent state drives prolonged elevated tonic firing which, in turn, drives escape crawling. Our findings demonstrate a self-priming neural chain mechanism in which activity during one behavior generates the internal drive for the next. Unlike previously described feedforward chain mechanisms, sequencing in this system does not depend on sequential recruitment of distinct neural substrates. Instead, the same neurons participate continuously across both behaviors while their activity-dependent change in state links the two actions into a coordinated sequence. This mechanism provides an elegant and generalizable solution for linking sequential actions across timescales.