Skip to main content Accessibility help
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 2
  • Print publication year: 2011
  • Online publication date: February 2011

5 - Salience sensitive control, temporal attention and stimulus-rich reactive interfaces


This chapter reviews the results of the Salience Project, a cross-disciplinary research project focused on understanding how humans direct attention to salient stimuli. The first objective of the project was theoretical: that is, to understand behaviourally and electrophysiologically how humans direct attention through time to semantically and emotionally salient visual stimuli. Accordingly, we describe the glance-look model of the attentional blink. Notably, this model incorporates two levels of meaning, both of which are based upon latent semantic analysis, and, in addition, it incorporates an explicit body-state subsystem in which emotional experience manifests. Our second major objective has been to apply the same glance-look model to performance analysis of human–computer interaction. Specifically, we have considered a class of system which we call stimulus-rich reactive interfaces (SRRIs). Such systems are characterized by demanding (typically) visual environments, in which multiple stimuli compete for the user's attention, and a variety of physiological measures are employed to assess the user's cognitive state. In this context, we have particularly focused on electroencephalogram (EEG) feedback of stimulus perception. Moreover, we demonstrate how the glance-look model can be used to assess the performance of a variety of such reactive computer interfaces. Thus, the chapter contributes to the study of attentional support and adaptive interfaces associated with digital environments.


Humans are very good at prioritizing competing processing demands. In particular, perception of a salient environmental event can interrupt ongoing processing, causing attention, and accompanying processing resources, to be redirected to the new event.

Anderson, A. K. 2005. Affective influences on the attentional dynamics supporting awareness, Journal of Experimental Psychology: General 134: 258–81
Anderson, A. K., and Phelps, E. A. 2001. Lesions of the human amygdala impair enhanced perception of emotionally salient events, Nature 411: 305–9
Barnard, P. J. 1999. Interacting cognitive subsystems: Modelling working memory phenomena within a multi-processor architecture, in A. Miyake and P. Shah (eds.), Models of Working Memory: Mechanisms of Active Maintenance and Executive Control. Cambridge, UK: Cambridge University Press: 298–339
Barnard, P. J., and Bowman, H. 2004. Rendering information processing models of cognition and affect computationally explicit: Distributed executive control and the deployment of attention, Cognitive Science Quarterly 3: 297–328
Barnard, P. J., Ramponi, C., Battye, G., and Mackintosh, B. 2005. Anxiety and the deployment of visual attention over time, Visual Cognition 12: 181–211
Barnard, P. J., Scott, S., Taylor, J., May, J., and Knightley, W. 2004. Paying attention to meaning, Psychological Science 15: 179–86
Bechara, A., Tranel, D., and Damasio, H. 2000. Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions, Brain 123(11): 2189–202
Bowman, H., Su, L., and Barnard, P. J. 2006. Semantic Modulation of Temporal Attention: Distributed Control and Levels of Abstraction in Computational Modelling (Technical Report 9-06): Computing Laboratory, University of Kent at Canterbury
Bowman, H., and Wyble, B. 2007. The simultaneous type, serial token model of temporal attention and working memory, Psychological Review 114: 38–70
Cherry, E. C. 1953. Some experiments on the recognition of speech, with one and with two ears, Journal of Acoustical Society of America 25: 975–9
Chun, M. M., and Potter, M. C. 1995. A two-stage model for multiple target detection in rapid serial visual presentation, Journal of Experimental Psychology: Human Perception and Performance 21: 109–27
Corbetta, M., Patel, G., and Shulman, G. L. 2008. The reorienting system of the human brain: From environment to theory of mind, Neuron 58: 306–24
Corbetta, M., and Shulman, G. L. 2002. Control of goal-directed and stimulus-driven attention in the brain, Nature Reviews 3: 201–15
Craston, P., Wyble, B., Chennu, S., and Bowman, H. 2009. The attentional blink reveals serial working memory encoding: Evidence from virtual and human event-related potentials, Journal of Cognitive Neuroscience 21: 550–66
Damasio, A. 1994. Descartes' Error. New York: G. P. Putnam
Diaper, D., and Stanton, N. (eds.) 2004. The Handbook of Task Analysis for Human–Computer Interaction. Mahwah, NJ: Lawrence Erlbaum Associates
Donchin, E. 1981. Presidential address, 1980. Surprise!…Surprise? Psychophysiology 18: 493–513
Holmes, A., and Richard, A. 1999. Attentional bias to threat related material in anxiety: A resource allocation or a practice effect? Poster presentation at September conference, Cognitive Section of the British Psychological Society
Landauer, T. K., and Dumais, S. T. 1997. A solution to Plato's problem: The latent semantic analysis theory of the acquisition, induction and representation of knowledge, Psychological Review 104: 211–40
Landauer, T. K., Foltz, P. W., and Laham, D. 1998. An introduction to latent semantic analysis, Discourse Processes 25: 259–84
Landauer, T. K., McNamara, D. S., and Dennis, S. (eds.) 2007. Handbook of Latent Semantic Analysis. Mahwah, NJ: Lawrence Erlbaum Associates
MacLeod, C., Mathews, A., and Tata, P. 1986. Attentional bias in emotional disorders, Journal of Abnormal Psychology 95: 15–20
McKenna, F. P., and Sharma, D. 2004. Reversing the emotional Stroop effect reveals that it is not what it seems: The role of fast and slow components, Journal of Experimental Psychology: Learning, Memory and Cognition 30: 382–92
McNichol, D. 1972. A Primer of Signal Detection Theory. London: George Allen & Unwin
Most, S. B., Smith, S. D., Cooter, A. B., Levy, B. N., and Zald, D. H. 2007. The naked truth: Positive, arousing distractors impair rapid target perception, Cognition and Emotion 21: 964–81
Oatley, K., and Johnson-Laird, P. 1987. Towards a cognitive theory of emotion, Cognition and Emotion 1: 29–50
O'Reilly, R. C., and Munakata, Y. 2000. Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. Cambridge, MA: MIT Press
Pashler, H. 1994. Dual-task interference in simple tasks: Data and theory, Psychological Bulletin 116: 220–44
Picard, R. W. 1998. Affective Computing. Cambridge, MA: MIT Press
Raymond, J. E., Shapiro, K. L., and Arnell, K. M. 1992. Temporary suppression of visual processing in an RSVP task: An attentional blink, Journal of Experimental Psychology: Human Perception and Performance 18: 849–60
Schraagen, J. M., Chipman, S. F., and Shalin, V. L. (eds.) 2000. Cognitive Task Analysis. Mahwah, NJ: Lawrence Erlbaum Associates
Snodgrass, J. G., and Corwin, J. 1988. Pragmatics of measuring recognition memory: Applications to dementia and amnesia, Journal of Experimental Psychology: General 117: 34–50
Spielberger, C. D. 1972. Anxiety: Current Trends in Theory and Research: I. New York: Academic Press
Spielberger, C. D. 1983. Manual for the State-Trait Anxiety Inventory (STAI). Palo Alto, CA: Consulting Psychologists Press
Squires, N. K., Squires, K. C., and Hillyard, S. A. 1975. Two varieties of long latency positive waves evoked by unpredictable auditory stimuli in man, Electroencephalography and Clinical Neurophysiology 38: 387–401
Su, L., Bowman, H., and Barnard, P. J. 2007. Attentional capture by meaning: A multi-level modelling study, in Proceedings of 29th Annual Meeting of the Cognitive Science Society. Nashville, TN
Su, L., Bowman, H., and Barnard, P. J. 2008. Performance of reactive interfaces in stimulus rich environments, applying formal methods and cognitive frameworks, Electronic Notes in Theoretical Computer Science 208: 95–111
Su, L., Bowman, H., and Barnard, P. J. and Wyble, B. 2009. Process algebraic modelling of attentional capture and human electrophysiology in reactive systems, Formal Aspects of Computing 21(6): 513–39
Tanenbaum, A. S. 2002. Computer Networks. Upper Saddle River, NJ: Prentice Hall
Teasdale, J. D., and Barnard, P. J. 1993. Affect, Cognition and Change: Re-modelling Depressive Thought. Hove: Lawrence Erlbaum Associates
Vogel, E. K., Luck, S. J., and Shapiro, K. L. 1998. Electrophysiological evidence for a postperceptual locus of suppression during the attentional blink, Journal of Experimental Psychology: Human Perception and Performance 24: 1656–74
Walker, J. H., Sproull, L., and Subramasi, R. 1994. Using a human face in an interface, in Proceedings CHI'94 ACM: 85–91
Wang, M., Madhyastha, T., Chan, N. H., Papadimitriou, S., and Faloutsos, C. 2002. Data mining meets performance evaluation: Fast algorithms for modeling bursty traffic, in Proceedings of the 18th International Conference on Data Engineering, San Jose, CA
Wyble, B., Bowman, H., and Potter, M. 2009. Categorically defined targets trigger spatiotemporal attention, Journal of Experimental Psychology: Human Perception and Performance 35(2): 324–37
Wyble, B., Craston, P., and Bowman, H. 2006. Electrophysiological Feedback in Adaptive Human–Computer Interfaces (Technical Report 8-06): Computing Laboratory, University of Kent at Canterbury