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Principal Investigator
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Address
Technical University of Munich
School
of Life Sciences
85354 Freising
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Phone
+49-69-850033-3600
Email
gjorgjieva@tum.de
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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:
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Using information
theoretic and
statistical inference
approaches to understand
the diversity of sensory
population responses
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Connecting single cell
properties to network
dynamics in the
developing mammalian
cortex
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Exploring the
interaction of synaptic
plasticity rules during
network homeostasis
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Examining the
relationship between
neural circuits for
locomotion
in Drosophila and different
behavioral strategies
used during exploration
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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.
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Related Publications
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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.
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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.
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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.
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J. Gjorgjieva, H.
Sompolinsky and M. Meister
(2014). Benefits of Pathway
Splitting in Sensory Coding.
J Neurosci 34:12127-12144.
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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).
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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.
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