Circuit mechanisms of learning and firstname.lastname@example.org
The Zlatic lab aims to understand the relationship between the structure of the nervous system and its function and to discover the basic principles by which neural circuits implement fundamental computations. A major focus of our research is the circuit implementation of learning and decision-making. For the nervous system to select appropriate responses to multiple, often conflicting cues present in the environment it must be able to 1) learn which sensory cues are associated with rewards and punishments; 2) compute the “predicted value” of each action based on the learnt information; 3) select one action and suppress other physically incompatible competing actions; 4) update memories when predicted and actual outcomes differ to improve future decision-making.
We aim to discover the circuit motifs that implement these four functions, the comprehensive set of structural changes in the brain that are involved in storing specific memories, and the genes required in specific neurons for these computations. We use the tractable genetic model system, the Drosophila melanogaster larva which has the same ground-plan as the adult Drosophila and other insects, but contains fewer (ca. 12,000) and smaller neurons. In this system we can i) image the entire nervous system at synaptic resolution with electron microscopy, and map complete circuits with synaptic resolution, ii) record individual neurons with patch-clamp, iii) image the activity of all neurons at once in intact animals (through the transparent cuticle) with light-sheet microscopy, iv) constrain models of circuit function with comprehensive structural and functional connectivity maps, and iv) use powerful genetic tools to selectively manipulate individual neurons to test models’ predictions and elucidate the functional roles of specific circuit motifs.
EM Reconstruction of the Learning Center (Mushroom Body)
Automated high-throughput behavior detection
- Eschbach C., Fushiki A., Winding M., Schneider-Mizell C. M., Shao M., Arruda B., Eichler K., Valdes-Aleman J., Thum A. S., Gerber B., Fetter R. D., Truman W. J., Litwin-Kumar A., Cardona A. and Zlatic M. (2019)
Multilevel recurrent architecture for adaptive regulation of learning in the insect brain
- Eichler K., Li F., Kumar A. L., Andrade I., Schneider-Mizell C., Saumweber T., Huser A., Gerber, B., Fetter R. D., Truman J. W., Abbott L. F., Thum A., Zlatic, M. and Cardona A. (2017)
The complete connectome of a learning and memory centre in an insect brain
Nature 548(7666): 175-182.
- Jovanic, T. S.-M., C.M.; Shao, M.; Masson, J.B.; Denisov, G.; Fetter, R.D.; Truman, J.W.; Cardona, A. and Zlatic, M. (2016)
Competitive disinhibition in early sensory processing mediates behavioral choice and seqeunces in Drosophila
Cell 167(3): 858-870.
- Ohyama, T. et al. (2015)
A multilevel multimodal circuit enhances action selection in Drosophila
Nature 520: 633-639.
- Vogelstein, J. T. et al. (2014)
Discovery of brainwide neural-behavioral maps via multiscale unsupervised structure learning
Science 344: 386-392.
- Elise Croteau-Chonka
- Claire Eschbach
- Nan Hu
- François Laurent
- David Nguyen
- Nadine Randel
- Andrey Stoychev
- Lalanti Venkatasubramanian
- Michael Winding
- Marta Zlatic