Specific Research Projects  Thought Patterns of  Cross-Disciplinary Relevance


When confronted with a novel situation, a rather rich process of categorizations and classifications is triggered in human cognition. It can probably be described as occurring on several layers in parallel.


One way of “cutting the cake” may be to distinguish between four levels: a most fundamental level where it is determined with which “kind of reality” we are confronted, a second layer where basic concepts are invoked (and tested for their applicability), a third layer on which entire thought patterns come into play – and finally a fourth layer on which the actual thinking operations in a more narrow sense take place.

In this architecture thought patterns play the crucial role in setting the stage for what and how we can actually think. The hypothesis is that all complex thinking operations are based on thought patterns. In sophisticated thinking processes these thought patterns can be made explicit and can be modified or replaced. But the “thesaurus of available thought patterns” – and the ability to de- and recompose  them – plays a quintessential role in advanced thinking and coping with novelty.

Thought patterns usually have their sources within a particular discipline, but underneath there is a general concept which is the characteristic of the thought patterns and which allows for a generalization and transformation to other systems. Thought patterns include paradigms, scientific methods and heuristics.  

A few examples of TCRs from different disciplines are:

  • from physics: the dynamics of structural stability (exemplified in the paradigm of the harmonic oscillator), the dynamics of structural change (many aspects of which can be studied in the framework of the logistic mapping), self-organized criticality (systems with a dynamics which drives these systems into a critical state), small-world graphs (connectivities of systems components which are optimal for adaptation)
  • from evolutionary biology: generation of variations and selection mechanisms, neutrality networks (improved adaptability by the generation of variations with the same phenotype), splitting of representation levels (like pheno- and geno-type splitting)
  • from cognitive sciences: optimal cognitive distance (focusing on the relevant variables), the “problem as a friend” (what makes some problems so resistant)