New ideas for brain modelling 5

Abstract

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 (Cognitive Process 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 act. The language also has a mathematical basis, allowing for the rule construction to be consistent. The CPL is novel in some ways. Firstly, it uses 3 entities for each statement, where the object source is also required. This roots the act and allows for cross-referencing that can create a behaviour script automatically. It also allows natural cycles to be derived from the script that can define the brain-like processes. Now, both static memory and dynamic process hierarchies can be built as tree structures. A theory about linking can suggest that nodes in different regions link together when generally they represent the same thing.

Keywords

• cognitive model
• behaviour
• formal description
• prediction
• search