Bio-systems

We conclude with the description of a research line which we consider promising for the future. It concerns the realization that the modeling methods of theoretical physics can be exploited to describe the universal behaviour of very complex biological systems. In view of the importance of multidisciplinary developments, crossing the borders with the life sciences poses a important challenge. In this context Nienhuis intends to apply such tools from statistical physics to problems of growth and morphology in living systems. Within the framework of neuro-sciences, Van Leeuwen working on neural networks will participate in the Research Center for Neuro-sciences (RCN). This center is part of the 'Wetenschap en Technologie Centrum Watergraafsmeer (WTCW)'. The aim of this center is to bring together and coordinate research activities from biology, medicine, psychology, theoretical physics, mathematics and computational sciences.

One of the remarkable properties of neural networks, whether they are artificial, animal or human, is their ability to learn. There is a great deal of evidence that learning can be effected, in biological neural networks such as the brain, by an adjustment of the impact of one neuron on another. In more technical terms, by changes of the strengths of the synapses connecting the neurons. In order to understand the functioning of the brain at a multi-cellular level, it is necessary to unfold the rules that reign this process of adaptation at mono-cellular level. It is at this point that theoretical physics comes in: general physical principles of functioning of a neural network as a whole suggest biological rules for the adaptation of the individual synapses. The predictions thus found will be confronted with the results obtained by experiments.