FIAS Scientific Report 2010 - Frankfurt Institute for Advanced Studies ...

2. Project “SECO”
FP7-2008-216593
Co-PI C. v.d. Malsburg
Period 01.03.2008-28.02.2012
Amount subproject FIAS: Euro 425.306
Collaborators: Urs Bergmann, Christoph von der Malsburg, Junmei Zhu, Alexander Schmid, Tomas Fernandes
This project is funded under the European program “Bio-ICT convergence”. The project’s full title is “Self-
Constructing Computing Systems”. The aim of the integrated project is to model the ontogenetic growth of
neural circuits under genetic control. The FIAS subproject has two aims. The first is to model the pre-natal and
post-natal self-organization of the specific circuit patterns that have been used as the basis of the FIAS invariant
object recognition system developed in the DAISY project. The essential aims of this part of the project have
been achieved in simple form within the reporting year. The second aim is the development of methodology
for the semi-numerical analysis of sets of differential equations describing self-organizing systems, applied
especially to network self-organization. Some applications to ontogenesis and to visual function have been
published.
Related publications in 2010:
1) Urs Bergmann and C. von der Malsburg, A Bilinear Model for Consistent Topographic Representations,
International Conference on Artificial Neural Networks (ICANN), 2010.
2) Junmei Zhu, Urs Bergmann and C. von der Malsburg, Self-Organization of Steerable Topographic Mappings
as Basis for Translation Invariance, International Conference on Artificial Neural Networks (ICANN),
2010.
3) Urs Bergmann and C. von der Malsburg, Self-Organization of Topographic Bilinear Networks for Invariant
Recognition, Neural Computation. In second review, 2011.
4) Junmei Zhu, Self-organization of two interacting winner-take-all systems, In Proceedings International Joint
Conference on Neural Networks (IJCNN), 2010.
3. Project “PLICON”: Plasticity and Learning in Cortical Networks
Collaborators: Dana Ballard 3 , Guido Marco Cicchini 2 , Arthur Franz 1 , Mary Hayhoe 3 Manu Punnen John 1 ,
Prashant Joshi 1 , Africa P 1 , Constantin Rothkopf 1 , Cristina Savin 1 , Lisa Scocchia 1 , Paul Schrater 4 Brian
Sullivan 3 , Jochen Triesch 1 , Thomas Weisswange 1
1 FIAS, 2 University of Florence, and Institute of Neuroscience, National Research Council, Italy, 3 University of Texas
Austin, 4 University of Minnesota
The brain is a very plastic organ. A plethora of plasticity mechanisms are constantly adapting its structure
and optimize its function, allowing us to learn and adapt to changing environments. Many of these individual
plasticity mechanisms have been carefully characterized in experimental studies and their properties have been
described theoretically. However, there is little understanding of how the various mechanisms are interacting
in the brain and what emergent properties result from these interactions at the network level. This project
15