2 - Representation of sensory information in self-organizing feature maps, and the relation of these maps to distributed memory networks

Summary

Is there enough motivation for a solid-state physics approach to the brain?

One of the salient features of the brain networks is that anatomical sections of a few millimetres width, taken from different parts of the cortex, look roughly similar by their texture. This observation might motivate a theoretical approach in which principles of solid-state physics are applied to the analysis of the collective states of neural networks. Such a step, however, should be made with extreme care. I am first trying to point out a few characteristics of the neural tissue which are similar to those of, or distinguish it from non-living solids.

Similarities. There is a dense feedback connectivity between neighbouring neural units, which corresponds to interaction forces between atoms or molecules in solids.

Generation and propagation of brain waves seem to support a continuous-medium view of the tissue.

Differences. In addition to local, random feedback there exist plenty of directed connectivities, ‘projections’, between different neural areas. As a whole, the brain is a complex self-controlling system in which global feedback control actions often override the local ‘collective’ effects.

Although the geometric structure of the neural tissue looks uniform, there exist plenty of specific biochemical and physiological differences between cells and connections. For instance, there exist some 40 different types of neural connection, distinguished by the particular chemical transmitter substances involved in signal transmission, and these chemicals vary from one part of the brain to another.