Reinforcement Expectation in the Honey Bee (Apis mellifera): Can Downshifts in Reinforcement Show Conditioned Inhibition?

Abstract

ABSTRACTWhen animals learn the association of a Conditioned Stimulus with an Unconditioned Stimulus, later presentation of the CS invokes a representation of the US. When the expected US fails to occur, theoretical accounts predict that conditioned inhibition can accrue to any other stimuli that are associated with this change in the US. Empirical work with mammals has confirmed the existence of conditioned inhibition. But the way it is manifested, the conditions that produce it, and determining whether it is the opposite of excitatory conditioning, are important considerations. Invertebrates can make valuable contributions to this literature because of the well-established conditioning protocols and access to the central nervous system for studying neural underpinnings of behavior. Nevertheless, while conditioned inhibition has been reported, it has yet to be thoroughly investigated in invertebrates. Here we evaluate the role of the unconditioned stimulus (US) in producing conditioned inhibition by using Proboscis Extension Response conditioning of the honey bee (Apis mellifera). Specifically, using variations of a ‘feature-negative’ experimental design, we employ downshifts in US intensity relative to US intensity used during initial excitatory conditioning, to show that an odorant in an odor-odor mixture can become a conditioned inhibitor. We argue that some alternative interpretations to conditioned inhibition are unlikely. However, we show variation across individuals in how strongly they show Conditioned Inhibition, with some individuals possibly revealing a different means of learning about changes in reinforcement. We discuss how resolution of these differences is needed to fully understand whether and how Conditioned Inhibition is manifested in the honey bee, and whether it can be extended to investigate how it is encoded in the CNS. It is also important for extension to other insect models. In particular, work like this will be important as more is revealed of the complexity of the insect brain from connectome projects.