[Comp-neuro] PhD or PostDoctoral Position in Computational Neuroscience of Learning and Memory at the University of Göttingen, Germany
tetzlaff at physik3.gwdg.de
Tue Mar 26 10:21:17 CET 2013
We have a PhD or PostDoc position for a project in Computational Neuroscience
of Learning and Memory at the Third Institute of Physics – Biophysics –
Georg-August University, Göttingen, Germany
Topic of project: The role of long-term depression during learning and memory
At the neuronal network level learning and memory formation are associated
with the ability to change synaptic efficiencies (Hebb, 1949). There is an
interesting imbalance. On the one side, most of the studies analyze the
connection between the increase of synaptic efficiencies (long-term
potentiation; LTP) and learning (e.g., Martin et al., 2000). On the other
side, the well-known mechanism of synaptic depression (long-term depression;
LTD) is in conjunction with learning mainly ignored. Only a few experiments
show that LTD is involved in learning and memory dynamics (Manahan-Vaughan and
Braunewell, 1999; Whitlock et al., 2006) and even fewer theoretical ideas
bring up possible functions of LTD (Willshaw and Dayan, 1990; Miller, 1996).
In this project we want to close this gap by augmenting a recent memory model
with long-term depression (LTD).
Our current memory model (Tetzlaff et al., 2011; 2012a) is based on a combined
adaptation rule of LTP and synaptic scaling (Turrigiano et al., 1998). The
combination enables neuronal networks to form local cell assemblies related to
“memories” (Tetzlaff et al., 2012b). The goal is to introduce LTD into this
model and analyze its functional role (e.g., for the competitive stabilization
of cell assemblies). Furthermore, as the reduction in spine size by LTD also
induces a shorter synaptic life span (Yasumatsu et al., 2008), the resulting
dynamics can be linked to the mechanisms of structural plasticity (Butz et
Start date: 01. 07. 2013 (or earlier), negotiable.
Requirements: Theoretical Background (Programming and mathematical analysis of
coupled differential equations), Background in Neuroscience.
Salary scale: German TV-L E13 (50% - 100%, depending on experience).
Our info: We are part of the Faculty of Physics at the University
of Göttingen and the BCCN Göttingen and cooperate closely, e.g., with the Max
Planck Institute for Dynamics and Self-Organization and the GGNB Göttingen.
References and further reading about project:
D.O. Hebb (1949). The organization of behavior. Wiley, New York.
S.J. Martin, P.D. Grimwood, and R.G.M. Morris (2000). Synaptic plasticity and
memory: an evaluation of the hypothesis. Annu. Rev. Neurosci., 23:649-711.
D. Manahan-Vaughan and K. Braunewell (1999). Novelty acquisition is associated
with induction of hippocampal long-term depression. Proc. Natl. Acad. Sci.
J.R. Whitlock, A.J. Heynen, M.G. Shuler, and M.F. Bear (2006). Learning
induces long-term potentiation in the hippocampus. Science, 313:1093-1097.
D.J. Willshaw and P. Dayan (1990). Optimal plasticity from matrix memories:
what goes up must come down. Neural Comput., 2:85:93.
K.D. Miller (1996). Synaptic economics: competition and cooperation in
synaptic plasticity. Neuron, 17:371-374.
C. Tetzlaff, C. Kolodziejski, M. Timme, and F. Wörgötter (2011). Synaptic
scaling in combination with many generic plasticity mechanisms stabilizes
circuit connectivity. Fron. Comput. Neurosci., 5:47.
C. Tetzlaff, C. Kolodziejski, M. Timme, and F. Wörgötter (2012a). Analysis of
synaptic scaling in combination with Hebbian plasticity in several simple
networks. Front. Comput. Neurosci., 6:36.
G.G. Turrigiano, K.R. Leslie, N.S. Desai, L.C. Rutherford, and S.B. Nelson
(1998). Activity-dependent scaling of quantal amplitude in neocortical
neurons. Nature, 391:892-896.
C. Tetzlaff, C. Kolodziejski, M. Timme, M. Tsodyks, and F. Wörgötter (2012b).
Memory formation, recall and forgetting in neuronal networks. Front. Comput.
Neurosci. Conference Abstract: Bernstein Conference 2012. doi:
N. Yasumatsu, M. Matsuzaki, T. Miyazaki, J. Noguchi, and H. Kasai (2008).
Principles of long-term dynamics of dendritic spines. J. Neurosci.,
M. Butz, F. Wörgötter, and A. Van Ooyen (2009). Activity-dependent structural
plasticity. Brain Res. Rev., 60:287-305.
Please send applications (PDF only) to, or request further information from:
Christian Tetzlaff (tetzlaff at physik3.gwdg.de) or
Florentin Wörgötter (worgott at physik3.gwdg.de)
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