New Ideas for Brain Modelling 5
  This paper describes a process for combining patterns and features, to guide
a search process and make predictions. It is based on the functionality that a
human brain might have, which is a highly distributed network of simple
neuronal components that can apply some level of matching and cross-referencing
over retrieved patterns. The process uses memory in a dynamic way and it is
directed through the pattern matching. The paper firstly describes the
mechanisms for neuronal search, memory and prediction. The paper then presents
a formal language for defining cognitive processes, that is, pattern-based
sequences and transitions. The language can define an outer framework for
concept sets that are linked to perform the cognitive act. The language also
has a mathematical basis, allowing for the rule construction to be consistent.
Now, both static memory and dynamic process hierarchies can be built as tree
structures. The new information can also be used to further integrate the
cognitive model and the ensemble-hierarchy structure becomes an essential part.
A theory about linking can suggest that nodes in different regions link
together when generally they represent the same thing.
