Event Abstract

A spiking neuronal network model of fast associative learning in the honeybee

  • 1 Freie Universität Berlin, Institute of Biology, Germany
  • 2 Bernstein Center for Computational Neuroscience Berlin, Germany

Numerous experimental studies on classical conditioning in the honeybee (Apis mellifera) have provided insights into the physiological processes of olfactory learning and memory formation. On the basis of these findings, several theoretical studies have proposed different model hypotheses for sensory processing and learning in the insect brain. However, the actual dynamics of associative learning as evident from behavior in individual animals is typically neglected. For the honeybee, recent analyses suggest that individual animals learn to associate between odor and sugar reward within a single trial (Pamir et al. 2011).
Here we present a spiking neuronal network model which processes sensory stimuli defined by classical conditioning protocols of the proboscis extension response in the honeybee. We compare and implement different hypotheses on physiological mechanisms that support fast associative learning in their ability to reproduce both behavioral and physiological constraints as observed in experiments. The behavioral constraints of our model are defined by the learning performance of individual animals during absolute, differential, backward and trace conditioning. Physiological constraints comprise several recordings of neuronal activity from different processing stages along the sensory-to-motor pathway.


This work was supported by the BMBF through grant 01GQ0941 within the Bernstein Focus Neuronal Basis of Learning (BFNL). E.P was funded by the DFG within the Research Training Group Sensory Computation in Neural Systems (GRK 1589).
Author contribution: J.H. and E.P. contributed equally to this study.


Pamir, E., Chakroborty, N. K., Stollhoff, N., Gehring, K. B., Antemann, V., Morgenstern,
L.,Felsenberg, J., et al. (2011). Average group behavior does not represent individual behavior in classical conditioning of the honeybee. Learning & memory (Cold Spring Harbor, N.Y.), 18(11), 733-41.

Keywords: Classical Conditioning, Honeybee, insect, Learning, Olfaction, plasticity, spiking neuronal networks

Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012.

Presentation Type: Poster

Topic: Learning, plasticity, memory

Citation: Haenicke J, Pamir E and Nawrot MP (2012). A spiking neuronal network model of fast associative learning in the honeybee. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00149

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Received: 11 May 2012; Published Online: 12 Sep 2012.

* Correspondence: Mr. Joachim Haenicke, Freie Universität Berlin, Institute of Biology, Berlin, Berlin, 14195, Germany, joachim.haenicke@fu-berlin.de