New Ideas for Brain Modelling 5

TL;DR

This paper introduces a novel cognitive modeling framework inspired by human brain functions, combining pattern matching, memory, and formal language to simulate dynamic, hierarchical, and interconnected neural processes.

Contribution

It presents a formal language and hierarchical structures for modeling cognitive processes based on pattern matching and distributed neural networks.

Findings

Developed a formal language for defining cognitive sequences

Built hierarchical tree structures for memory and processes

Proposed linking mechanisms for interconnected nodes

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 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.