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Computational cognitive modelling of action awareness: prior and retrospective

Overview of attention for article published in Brain Informatics, March 2015
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Title
Computational cognitive modelling of action awareness: prior and retrospective
Published in
Brain Informatics, March 2015
DOI 10.1007/s40708-015-0013-3
Pubmed ID
Authors

Dilhan J. Thilakarathne, Jan Treur

Abstract

This paper presents a computational cognitive model for action awareness focusing on action preparation and performance by considering its cognitive effects and affects from both prior and retrospective form relative to the action execution. How action selection and execution contribute to the awareness or vice versa is a research question, and from the findings of brain imaging and recording techniques more information has become available on this. Some evidence leads to a hypothesis that awareness of action selection is not directly causing the action execution (or behaviour) but comes afterwards as an effect of unconscious processes of action preparation. In contrast, another hypothesis claims that both predictive and inferential processes related to the action preparation and execution may contribute to the conscious awareness of the action, and furthermore, this awareness of an action is a dynamic combination of both prior awareness (through predictive motor control processes) and retrospective awareness (through inferential sense-making processes) relative to the action execution. The proposed model integrates the findings of both conscious and unconscious explanations for both action awareness and ownership and acts as a generic computational cognitive model to explain agent behaviour through the interplay between conscious and unconscious processes. Validation of the proposed model is achieved through simulations on suitable scenarios which are covered with actions that are prepared without being conscious at any point in time, and also with the actions that agent develops prior awareness and/or retrospective awareness. Having selected an interrelated set of scenarios, a systematic approach is used to find a suitable but generic parameter value set which is used throughout all the simulations that highlights the strength of the design of this cognitive model.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 22%
Student > Bachelor 4 22%
Student > Master 4 22%
Researcher 2 11%
Student > Doctoral Student 1 6%
Other 0 0%
Unknown 3 17%
Readers by discipline Count As %
Psychology 8 44%
Business, Management and Accounting 2 11%
Nursing and Health Professions 1 6%
Arts and Humanities 1 6%
Computer Science 1 6%
Other 1 6%
Unknown 4 22%