Research Report Laboratory Dr. M. Neumann

Universität Freiburg
Institut für Biologie III
Schänzlestrasse 1
D-79104 Freiburg i. Br.

Basic Principles of Information Processing in the Human Brain

Team: Manfred Neumann, Masako Scheufens.

The global goal of the research is to understand the essential mechanisms of information processing in the human brain. In view of this, the basic idea is the following:

The main feature of cognitive information processing is that predicates are decided.

For the performance of decisions the only available information is the information transmitted from the sense organs to the brain. Cognitive Systems do not have external predicate definitions nor external decision criterions. Both must, through the cognitive system, be generated by self organization.

One can show, that from this follows:

  1. The only possible decision criterion is the testing of equivalence.

  2. Properties and predicates respectively can be defined only by using equivalence relations.

This concept of the brain as an "equivalence relations analyser" should be valid, without any exception, for all properties and all predicates respectively of arbitrary real or abstract objects. To claim this, leads to a problem:

Every perception content is imbedded into a three-dimensional space and into a one-dimensional time. But the topological property of dimensionality, and therefore one of the basic properties of perception contents cannot as yet be characterized by relations.

The work, therefore, was concentrated on the deduction of a relational dimension concept. Formally the concept deduced is in close relationship with vertex coloration of graphs.

The relational dimension concept has conclusions which can be verified by experiments:

If, for example, spatial information is processed by using equivalence classes, then one would expect that four cortical regions are involved. If spatial information is processed by using the vector space structure, then only three cortical regions should take part in the processing.

One can expect further conclusions from the analysis of feature maps. Therefore it should be attempted to confirm the results obtained by analysing feature maps and by computer simulations of network models.


  • Manfred Spitzer and Manfred Neumann: Noise in Models of Neurological and Psychiatric Disorders, Int. Journ. of Neural Systems, 7, 355-361 (1996).