The Mechanism Of Motor Sequence Generation Across Different Timescales In C. Elegans

Animal behaviors are complex and hierarchical spatiotemporal patterns.In the popular model organism Caenorhabditis elegans,behavior sequences are composed of rhythmic motor sequences.On a long timescale,behavioral sequences emerge from ordered and flexible transitions between different behavioral states,such as forward movements,reversals and turn.On a short timescale,different parts of a worm body coordinate rhythmic bending squences in spacetime.Here we use the nematode Caenorhabditis elegans to investigate the neural circuit mechanisms and algorithms that underlie motor sequence generation in both long and short timescales.We combined a range of approaches,including behavior tracking of freely moving animals;optogenetics mainipulation of descending interneurons and other neurons;opto-ablation of interneurons and motoeneurons;and calcium imaging to study the dynamics of B motorneurons and SAA interneurons.We found that(1)Mid-body B motor-neurons generate rhythmic activity and constitute distributed CPGs(central pattern generator).(2)Gap junctions between AVB interneurons and B motorneurons affect the activity of mid-body CPGs and facilitate bending wave propagation.(3)Gap junctions between neighboring B motorneurons and between AVB interneurons and B motorneurons help propagate regulatory signals in B motorneurons.(4)Proprioception is responsible for propagating undulatory waves and coupling of distributed CPGs.(5)Finally,the putative proprioceptive neurons SAA localized at the worm head play a dual role in shaping the dynamics of motor sequences acorss different timescales.SAA suppress spontaneous reversals and prolong forward runs through cholinergic inhibition onto RIM interneurons;the same neurons also stablize and regularize rhythmic bending activity by interacting with head motor neurons during forward movements.Our findings dissect motor control circuit of C.elegans forward movement and reveal circuit principles for organizing behaviors across different timescales.