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Although no two brains are alike, they can display a comparable pattern of neural activity when exposed to similar sensory input. Scientists at the Max Planck Institute for Dynamics and Self-Organization in Göttingen have now developed a mathematical method to design networks from neural cells which exhibit a predefined pattern dynamics. The researchers hope that their method will assist them in getting closer to understanding which of the possible network configurations was privileged by evolution - and why (Physica D: Nonlinear Phenomena, December, 2006).

The nerve cells of the brain are inter-connected to a complex network. All brain activities are the result of the "firing" of nerve cells, when they send electrical pulses - like a Morse code - to other cells of the brain. This process depends on the exact dynamics of the neuronal activity. When the brain receives sensory input, calculates or remembers, it processes information encoded in a series of neuronal impulses in different nerve cells. Although no two people have the same brain, they can still share the same thought. Thus, only to a certain extent is the dynamics of neuronal activity dependent on the structure of neuronal networks. For networks far simpler than that of the human brain this idea also applies: different structures can display the same functionality. Raoul-Martin Memmesheimer and Marc Timme, researchers at the Max Planck Institute for Dynamics and Self-Organization and the Bernstein Center for Computational Neuroscience Göttingen, have developed a mathematical method to describe the set of all networks that exhibit a given dynamics. With this, they provide researchers with a tool which can be used to investigate the correlation between structure and function of a neuronal network.

A common approach in scientific research is to investigate the structure of a system in order to then draw conclusions about its function. Memmesheimer and Timme now took the reverse perspective.
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Source:Max-Planck-Gesellschaft

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