Prof. Dr. Julijana Gjorgjieva

Principal Investigator

Address

Technical University of Munich
School of Life Sciences
85354 Freising

Phone

+49-69-850033-3600

Email

gjorgjieva@tum.de

Homepage

http://cns.wzw.tum.de

Research topics

Efficient transmission of information across neural circuits requires an intricate balance between the intrinsic properties of single neurons and the synaptic connections between them. How are neurons and networks tuned to achieve this balance and enable the emergence of reliable computation? We are interested in two aspects of circuit organization: how it comes about from the interaction of single neuron properties and synaptic plasticity (as during learning and circuit development); and the organization principles that achieve it over the longer timescale of evolution.

Specific topics include:

Using information theoretic and statistical inference approaches to understand the diversity of sensory population responses
Connecting single cell properties to network dynamics in the developing mammalian cortex
Exploring the interaction of synaptic plasticity rules during network homeostasis
Examining the relationship between neural circuits for locomotion in Drosophila and different behavioral strategies used during exploration

Scientific approach

Our work is based on computational and mathematical approaches to understand how activity, generated spontaneously in the circuit, or by the external environment, shapes network organization and dynamics. We study the interaction of a diversity of mechanisms, including synaptic plasticity, intrinsic cellular properties, sensory noise, and biophysical constraints, on the generation of adult function and computation. Our work is supported by close experimental collaborations based on different animal models, from rodent to fruit fly, allowing direct access to individual neural circuit components.

Related Publications

J. Gjorgjieva, J. F. Evers, S. J. Eglen (2016). Homeostatic activity-dependent tuning of recurrent networks for robust propagation of activity. J Neurosci 36:3722-3734.
J. Gjorgjieva, G. Drion and E. Marder (2016). Computational implications of biophysical diversity and multiple timescales in neurons and synapses for circuit performance. Curr Opin Neurobiol 37:44-52.
J. Gjorgjieva, R. A. Mease, W. J. Moody and A. L. Fairhall (2014). Intrinsic neuronal properties govern information transmission in networks. PLoS Comp Biol 10(12): e1003962.
J. Gjorgjieva, H. Sompolinsky and M. Meister (2014). Benefits of Pathway Splitting in Sensory Coding. J Neurosci 34:12127-12144.
J. Gjorgjieva, J. Berni, J. F. Evers and S. J. Eglen (2013). Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling. Frontiers Comp Neurosci. 7(24).
J. Gjorgjieva, C. Clopath, J. Audet and J.-P. Pfister (2011). A triplet spike-timing-dependent plasticity model generalizes the Bienenstock-Cooper-Munro rule to higher-order spatiotemporal correlations. Proc Natl Acad Sci USA 108:19383-19388.