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Formal Aspects of Computing

, 21:513 | Cite as

Process algebraic modelling of attentional capture and human electrophysiology in interactive systems

  • Li SuEmail author
  • Howard Bowman
  • Philip Barnard
  • Brad Wyble
Open Access
Original Article

Abstract

Previous research has developed a formal methods-based (cognitive-level) model of the Interacting Cognitive Subsystems central engine, with which we have simulated attentional capture in the context of Barnard’s key-distractor Attentional Blink task. This model captures core aspects of the allocation of human attention over time and as such should be applicable across a range of practical settings when human attentional limitations come into play. In addition, this model simulates human electrophysiological data, such as electroencephalogram recordings, which can be compared to real electrophysiological data recorded from human participants. We have used this model to evaluate the performance trade-offs that would arise from varying key parameters and applying either a constructive or a reactive approach to improving interactive systems in a stimulus rich environment. A strength of formal methods is that they are abstract and the resulting specifications of the operator are general purpose, ensuring that our findings are broadly applicable. Thus, we argue that new modelling techniques from computer science can also be employed in computational modelling of the mind. These would complement existing techniques, being specifically targeted at psychological level modelling, in which it is advantageous to directly represent the distribution of control.

Keywords

Formal methods HCI Stimulus rich reactive interfaces Attentional blink EEG Interacting cognitive subsystems 

Notes

Acknowledgements

We are indebted to anonymous reviewers for their comments on the previous version of this manuscript. We also thank Patrick Craston, Srivas Chennu and Dell Green for their contribution to the collection and analysis of the EEG data. The UK Engineering and Physical Sciences Research Council supported this research (grant number GR/S15075/01). The participation of Philip Barnard in this project was supported by the Medical Research Council under project code U.1055.02.003.00001.01.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Copyright information

© The Author(s) 2008

Authors and Affiliations

  • Li Su
    • 1
    • 4
    Email author
  • Howard Bowman
    • 1
  • Philip Barnard
    • 2
  • Brad Wyble
    • 3
  1. 1.Centre for Cognitive Neuroscience and Cognitive SystemsUniversity of KentCanterburyUK
  2. 2.MRC Cognition and Brain Sciences UnitCambridgeUK
  3. 3.Department of Brain and Cognitive SciencesMassachusetts Institute of TechnologyCambridgeUSA
  4. 4.Section of Cognitive Neuropsychiatry, Department of Psychological MedicineInstitute of Psychiatry at King’s College LondonLondonUK

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