Learning and Memory

How are memoires formed? How are memories retrieved and translated into behavioral decisions? We investigate these questions in the honeybee. In close collaboration with our experimental partners we analyze behavioral and neurophysiological data and we formulate computational and abstract models of learning and memory formation. In the NeuroCopter project we test insect-inspired spiking neural network models with plasticity as central control units of autonomous robots.


This project is funded by the German Ministry of Education and Research within the Bernstein Focus Neuronal Basis of Learning: Insect inspired robots - The role of memory in decision making.


Prof. Dr. Randolf Menzel, Freie Universität Berlin

Prof. Dr. Dorothea Eisenhardt, Freie Universität Berlin

Dr. Martin Strube-Bloss, Universität Würzburg

Dr. Paul Szyska, Universität Konstanz

Related Publications

  • Schmuker M, Pfeil T, Nawrot MP (2014) A neuromorphic network for generic multivariate data classification. PNAS, published ahead of print Jan 27, 2014. [abstract] [PDF]
  • Helgadottir LI, Haenicke J, Landgraf T, Rojas R, Nawrot MP (2013) Conditioned behavior in a robot controlled by a spiking neural network. 6th International IEEE EMBS Conference on Neural Engineering, San Diege, USA, Nov 5-8, p. 891 - 894, doi: 10.1109/NER.2013.6696078  [Preprint] [video]
  • Pamir E, Chakroborty NK, Stollhoff N, Gehring KB, Antemann V, Morgenstern L, Felsenberg J, Eisenhardt D, Menzel R, Nawrot MP (2011) Average group behavior does not represent individual behavior in classical conditioning of the honeybee. Learning and Memory 18: 733-741 [PDF]
  • Strube-Bloss M *, Nawrot MP *, Menzel R (2011) Mushroom Body Output Neurons Encode Odor-Reward Associations. Journal of Neuroscience 31(8):3129-3140 [abstract] [PDF] [supplement]
  • Häusler C, Nawrot MP and Schmuker M (2011): A spiking neuron classifier network with a deep architecture inspired by the olfactory system of the honeybee. Proceedings of the 5th International IEEE EMBS Conference on Neural Engineering, Cancun, Mexico, April 27 - May 1, 2011:198-202 [PDF]
  • Schmuker M, Weidert M and Menzel R (2008) A network model for learing-induced changes in odor representation in the antennal lobe, in Proceedings of the second french conference on Computational Neuroscience, Marseille, Laurent U. Perrinet and Emmanuel Dauc. (ed.). [PDF]