The biosphere contains many scale-free networks. Prominent examples are provided by the functional networks within the human brain. Scientists at the Max Planck Institute of Colloids and Interfaces have discovered that activity patterns in such biomimetic networks have unusual dynamic properties, which are controlled by a few, highly connected nodes. As a result, ordered activity patterns are very robust against random perturbations but rather sensitive to selective perturbations. Disordered patterns, on the other hand, decay very fast and relax towards an ordered pattern even if the network becomes infinitely large. In addition, these scale-free networks can also be used to store and retrieve a large number of fixed patterns (PNAS, Advanced Online Publication, 8 July 2005).

The human brain consists of about 100 billion nerve cells or neurons that are interconnected to form a huge network. Each neuron can be active by producing an action potential. If we were able to make a snapshot of the whole neural network, we would see, at any moment in time, a certain pattern of active and inactive neurons. If we combined many such snapshots into a movie, we would find that this activity pattern changes continuously with time, (see Figure 1). This pattern evolution represents the global dynamics of the neural network. At present, one cannot observe such activity patterns on the level of single neurons, but modern imaging techniques enable us to monitor coarse-grained patterns with a reduced spatial resolution. Using functional magnetic resonance imaging, for example, scientists can obtain activity patterns of about 100,000 neuron clusters, each of which contains about one million neurons.

The neuron clusters form another, coarse-grained network. Each cluster corresponds to a node of this network, and each node can be characterized
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Contact: Prof. Dr. Reinhard Lipowsky
reinhard.lipowsky@mpikg.mpg.de
49-331-567-9600
Max-Planck-Gesellschaft
12-Jul-2005