A sea slug's decision to approach or avoid potential prey has been simulated in a virtual environment called Cyberslug. In the future the software, described in a paper published in eNeuro, may provide a foundation for the development of more realistic artificial intelligence systems.
Sea slugs in the genus Pleurobranchaea readily learn to prefer easy prey while avoiding others that protect themselves from predators with a stinging defense, unless forced to eat them by intense hunger. Rhanor Gillette and colleagues were able to reproduce these choices in Cyberslug using data from previous studies of Pleurobranchaea brain and behavior. By simulating the relationships between the virtual predator's hunger level and learning ability, the researchers demonstrated how both attributes are required to regulate consumption of the appropriate amount and type of prey. The research suggests that this simple model is poised for improvements and additions that could enable the simulation of complex decision-making, as in addiction and social behavior.
Article: Implementing goal-directed foraging decisions of a simpler nervous system in simulation
University of Illinois at Urbana-Champaign, USA
eNeuro, the Society for Neuroscience's new open-access journal launched in 2014, publishes rigorous neuroscience research with double-blind peer review that masks the identity of both the authors and reviewers, minimizing the potential for implicit biases. eNeuro is distinguished by a broader scope and balanced perspective achieved by publishing negative results, failure to replicate or replication studies. New research, computational neuroscience, theories and methods are also published.
About The Society for Neuroscience
The Society for Neuroscience is the world's largest organization of scientists and physicians devoted to understanding the brain and nervous system. The nonprofit organization, founded in 1969, now has nearly 37,000 members in more than 90 countries and over 130 chapters worldwide.