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The Use of the First Order System Transfer Function in the Analysis of Proboscis Extension Learning of Honey Bees, Apis mellifera L., Exposed to Pesticides

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Abstract

No attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to pesticides. We applied a standard transfer function in the form Y = B3*exp(− B2 * (X − 1)) + B4 * (1 − exp(− B2 * (X − 1))), where X is the trial number; Y is proportion of correct responses, B2 is the learning rate, B3 is readiness to learn and B4 is ability to learn. Reanalyzing previously published data on the effect of insect growth regulators tebufenozide and diflubenzuron on the classical conditioning of proboscis extension, the model revealed additional effects not detected with standard statistical tests of significance.

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References

  • Abramson CI (1994) A primer of invertebrate learning: the behavioral perspective. American Psychological Association, Washington DC

    Book  Google Scholar 

  • Abramson CI, Stepanov II (2007) The application of a mathematical model for the assessment of the memorization curve in drug addicts and alcoholics. J Drug Addict Educ Erad 3:239–262

    Google Scholar 

  • Abramson CI, Squire J, Sheridan A, Mulder PG Jr (2004) The effect of insecticides considered harmless to honey bees (Apis mellifera L.): proboscis conditioning studies using the insect growth regulators confirm®2F (tebufenozide) and dimilin® (diflubenzuron). Environ Entomol 33:378–388

    Article  CAS  Google Scholar 

  • Abramson CI, Singleton JB, Wilson MK, Wanderley PA, Ramalho FS, Michaluk LM (2006) The effect of an organic pesticide on mortality and learning in Africanized honey bees (Apis mellifera L.) in Brasil. Am J Environ Sci 2:37–44

    Google Scholar 

  • Abramson CI, Giray T, Mixson TA, Nolf SL, Wells H, Kence A, Kence M (2010) Proboscis conditioning experiments with honey bees (Apis mellifera caucasica) show butyric acid and deet not to be repellents. J Insect Sci 10:122 available online: insectscience.org/10.122

    Google Scholar 

  • Abramson CI, Sokolowski MBC, Wells H (2011) Issues in the study of proboscis conditioning. In: Columbus F (ed) Social insects: structure, function, and behavior. Nova Science Publishers, Hauppaug, pp 25–49

    Google Scholar 

  • Balaban PM, Stepanov II (1996) Innate and acquired behavior of mollusks. In: Abramson CI, Shuranova ZP, Burmistrov YM (eds) Russian contributions to invertebrate behavior. Praeger Publishers, Westport, pp 77–109

    Google Scholar 

  • Decourtye A, Pham-Delegue MH (2002) The proboscis extension response: assessing the sublethal effect of pesticides on the honey bee. In: Devillers J, Pham-Delegue MH (eds) Honey bees: estimating the environmental impact of chemicals. Taylor & Frances, London, pp 67–84

    Google Scholar 

  • El Hassani AK, Dacher M, Gauthier M, Armengaud C (2005) Effects of sublethal doses of finopril on the behavior of the honeybee (Apis mellifera L.). Pharmacol Biochem Behav 82:30–39

    Article  Google Scholar 

  • Grodins FS (1963) Control theory and biological systems. Columbia University Press, New York

    Google Scholar 

  • Han P, Niu C-Y, Lei C-L, Cui J-J, Desneux N (2010) Use of an innovative T-tube maze assay and the proboscis extension response assay to assess sublethel effects of GM products and pesticides on learning capacity on the honey bee Apis mellifera L. Ecotoxicology 19:1612–1619

    Article  CAS  Google Scholar 

  • Hartz SM, Ben-Shahar Y, Tyler M (2001) Logistic growth curve analysis in associative learning data. Anim Cogn 4:185–189

    Article  Google Scholar 

  • Milsum JH (1966) Biological control systems analysis. McGraw-Hill, New York

    Google Scholar 

  • Stegen S, Stepanov I, Cookfair D, Schwartz E, Hojnacki D, Weinstock-Guttman B, Benedict RHB (2010) Validity of the California verbal learning test-II in multiple sclerosis. Clin Neuropsychol 24:189–202

    Article  Google Scholar 

  • Stepanov II, Abramson CI (2005) A new mathematical model for assessment of memorization dynamics. Span J Psychol 8:142–156

    Google Scholar 

  • Stepanov II, Abramson CI (2008) The application of the first order system transfer function for fitting the 3-arm radial maze learning curve. J Math Psychol 52:309–319

    Article  Google Scholar 

  • Stepanov II, Abramson CI, Wolf OT, Convit A (2010) The application of the first order system transfer function for fitting the California verbal learning test learning curve. JINS 16:443–452

    Google Scholar 

  • Stepanov II, Abramson CI, Warschausky S (2011) Assessment of the learning curve from the California verbal learning test—children’s version with the first-order system transfer function. Child Neuropsychol 17:330–346

    Article  Google Scholar 

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Correspondence to Charles I. Abramson.

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Abramson, C.I., Stepanov, I.I. The Use of the First Order System Transfer Function in the Analysis of Proboscis Extension Learning of Honey Bees, Apis mellifera L., Exposed to Pesticides. Bull Environ Contam Toxicol 88, 559–562 (2012). https://doi.org/10.1007/s00128-011-0512-8

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  • DOI: https://doi.org/10.1007/s00128-011-0512-8

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