Operant avoidance learning in crayfish, Orconectes rusticus: Computational ethology and the development of an automated learning paradigm.

Research in crustaceans offers a valuable perspective for studying the neural implementation of conserved behavioral phenomena, including motivation, escape, aggression, and drug-sensitive reward. The present work adds to this literature by demonstrating that crayfish successfully learn to respond to spatially contingent cues. An integrated video-tracking system automatically delivered a mild electric shock when a test animal entered or remained on a substrate paired with punishment. Following a few instances of shock delivery, crayfish quickly learned to avoid these areas. Comparable changes in substrate preference were not exhibited by yoked controls, but locomotion differed significantly from both pre-conditioning levels and from those of their masters receiving shock in a contingent fashion. The results of this work provide valuable insights into the principles governing avoidance learning in an invertebrate system and provide a behavioral template for exploring the neural changes during associative learning. Serving as a case study, this project introduces a new computer framework for the automated control of learning paradigms. Based on routines contained within the JavaGrinders library (free download at iEthology.com), it integrates real-time video tracking with robotic interfaces, and provides a suitable framework for implementing automated learning paradigms.