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SignificanceNetworks of neurons need to reliably encode and replay patterns and sequences of activity. In the brain, sequences of spatially coding neurons are replayed in both the forward and reverse direction in time with respect to their order in recent experience. As of yet there is no network-level or biophysical mechanism known that can produce both modes of replay within the same network. Here we propose that resonance, a property of neurons, paired with subthreshold oscillations in neural input facilitate network-level learning of fixed and sequential activity patterns and lead to both forward and reverse replay.

A repetitive gait cycle is an archetypical component within the behavioral repertoire of many animals including humans. It originates from mechanical feedback within proprioceptors to adjust the motor program during locomotion and thus leads to a periodic orbit in a low-dimensional space. Here, we investigate the mechanics, molecules, and neurons responsible for proprioception in Caenorhabditis elegans to gain insight into how mechanosensation shapes the orbital trajectory to a well-defined limit cycle. We used genome editing, force spectroscopy, and multiscale modeling and found that alternating tension and compression with the spectrin network of a single proprioceptor encodes body posture and informs TRP-4/NOMPC and TWK-16/TREK2 homologs of mechanosensitive ion channels during locomotion. In contrast to a widely accepted model of proprioceptive "stretch" reception, we found that proprioceptors activated locally under compressive stresses in-vivo and in-vitro and propose that this property leads to compartmentalized activity within long axons delimited by curvaturedependent mechanical stresses.

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