New ideas for brain modelling 5

Kieran Greer; Kieran Greer

doi:10.3934/biophy.2021003

AIMS Biophysics

2021, Volume 8, Issue 1: 41-56. doi: 10.3934/biophy.2021003

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Research article Special Issues

New ideas for brain modelling 5

Kieran Greer ^,

Distributed Computing Systems, Belfast, UK

Received: 13 October 2020 Accepted: 04 December 2020 Published: 10 December 2020

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.
- cognitive model,
- behaviour,
- formal description,
- prediction,
- search
Citation: Kieran Greer. New ideas for brain modelling 5[J]. AIMS Biophysics, 2021, 8(1): 41-56. doi: 10.3934/biophy.2021003

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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.

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