Testing mathematical laws of behavior in the honey bee

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Two mathematical laws of behavior derived from work on vertebrate ­animals were tested in honey bees in my research. One law concerned the ubiquitous phenomenon of generalization in learning. An animal obtaining a reward for a response to one stimulus will often make that response to similar but discriminably different stimuli. Under a suitably ideal characterization, generalization gradients ought to come out exponential in shape (Shepard RN, Science 237:1317–1323, 1987). In spatial generalization in honey bees, this prediction was upheld in a number of different studies. A second law concerned the weighting of different and conflicting evidence. A piece of evidence is supposed to be weighted by its recency, with more recent evidence given higher weight (Devenport L, Hill T, Wilson M, Ogden E, J Exp Psychol Anim Behav Process 23:450–460, 1997). With the passage of time since the last evidence was obtained, overall profitability of a ‘patch’ rather than recency of profits should dominate. Tests with honey bees failed to uphold this law, instead finding circadian modulation of preferences, with ‘patch’ preference highest at the circadian time at which reward was obtained on the previous (training) day. I attempted a speculative reformulation in terms of modulation of preferences according to different oscillators.
Original languageEnglish
Title of host publicationHoneybee neurobiology and behavior
Subtitle of host publicationa tribute to Randolf Menzel
EditorsC. Giovanni Galizia, Dorothea Eisenhardt, Martin Giurfa
Place of PublicationDordrecht ; London
PublisherSpringer, Springer Nature
Pages457-470
Number of pages14
ISBN (Print)9789400720985
DOIs
Publication statusPublished - 2012

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    Cheng, K. (2012). Testing mathematical laws of behavior in the honey bee. In C. G. Galizia, D. Eisenhardt, & M. Giurfa (Eds.), Honeybee neurobiology and behavior: a tribute to Randolf Menzel (pp. 457-470). Dordrecht ; London: Springer, Springer Nature. https://doi.org/10.1007/978-94-007-2099-2_34