Abstract
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.
- ABM93 Spatiotemporal firing patterns in the frontal cortex of behaving monkeysJ Neurophysiol19937016291638Google ScholarCross Ref
- And93 Rules of the mind1993HillsdaleErlbaumGoogle Scholar
- And05 Affective influences on the attentional dynamics supporting awarenessJ Exp Psychol General2005134225828110.1037/0096-3445.134.2.258Google ScholarCross Ref
- BMM02 Process algebra with timing2002New YorkSpringer1021.68063Google ScholarDigital Library
- Bar99 Barnard PJ (1999) Interacting cognitive subsystems: modelling working memory phenomena within a multi-processor architecture, Models of Working Memory: Mechanisms of active maintenance and executive control, pp 298–339Google Scholar
- BST04 Paying attention to meaningPsychol Sci200415317918610.1111/j.0956-7976.2004.01503006.xGoogle ScholarCross Ref
- Bar03 Rendering information processing models of cognition and affect computationally explicit: distributed executive control and the deployment of attentionCogn Sci Q200333297328Google Scholar
- BRB05 Anxiety and the deployment of visual attention over timeVis Cogn200512118121110.1080/13506280444000139Google ScholarCross Ref
- BPS03 User adaptive BCIs: SSVEP and P300 based interfacesPsychnology200314331354Google Scholar
- Bol88 Introduction to the ISO specification language LOTOSComput Netw ISDN Syst1988149102529Google Scholar
- Bon99 Describing behavioural states using a system model of the primate brainAm J Primatol19994931533810.1002/(SICI)1098-2345(199912)49:4<315::AID-AJP3>3.0.CO;2-VGoogle Scholar
- BBD01 Analysis of a multimedia stream using stochastic process algebraComput J20014442302450993.6806810.1093/comjnl/44.4.230Google ScholarCross Ref
- Bow99 Analysing cognitive behaviour using LOTOS and MexitlFormal Aspects Comput19991113215910.1007/s001650050045Google ScholarDigital Library
- Bow06 Concurrency theory, calculi and automata for modelling untimed and timed concurrent systems2006BerlinSpringerGoogle Scholar
- Bow07 The simultaneous type, serial token model of temporal attention and working memoryPsychol Rev20071141387010.1037/0033-295X.114.1.38Google ScholarCross Ref
- Car98 On the self-regulation of behaviour1998CambridgeCambridge University PressGoogle Scholar
- Chu95 A two-stage model for multiple target detection in rapid serial visual presentationJ Exp Psychol Hum Percept Perform199521110912710.1037/0096-1523.21.1.109Google ScholarCross Ref
- Cil93 Cilliers PJ, Van Der Kouwe AJW (1993) A VEP-based computer interfcae for C2-Quadriplegics. Engineering in Medicine and Biology Society, 1993. In: Proceedings of the 15th Annual International Conference of the IEEE, vol 15(3), pp 1263–1624Google Scholar
- CFS96 A systematic methodology for cognitive modellingArtif Intell19968534410.1016/0004-3702(95)00112-3Google ScholarDigital Library
- CWC08 Craston P, Wyble B, Chennu S, Bowman H (2008) The attentional blink reveals serial working memory encoding: evidence from virtual and human event-related potentials. J Cogn Neurosci (in press)Google Scholar
- Don81 Presidential address, 1980Surprise!...Surprise?. Psychophysiology198118549351310.1111/j.1469-8986.1981.tb01815.xGoogle ScholarCross Ref
- DBD98 Syndetic modellingHum Comput Interact199813433739310.1207/s15327051hci1304_1Google ScholarDigital Library
- EFH83 Ehrig H, Fey W, Hansen H (1983) ACT ONE—an algebraic specification language with two levels of semantics, ADTGoogle Scholar
- EBJ96 Rethinking innateness: a connectionist perspective on development, a Bradford book1996CambridgeMIT PressGoogle Scholar
- Eri81 From words to meaning: a semantic illusionJ Verbal Learn Verbal Behav19812054055110.1016/S0022-5371(81)90165-1Google ScholarCross Ref
- Fod88 Connectionism and cognitive architecture: a critical analysisCognition19882837110.1016/0010-0277(88)90031-5Google ScholarDigital Library
- GLM02 An overview of CADP 2001EASST Newsl200241324Google Scholar
- GVZ01 System design of a CC-NUMA multiprocessor architecture using formal specification, model-checking, co-simulation, and test generationSpringer Int J Softw Tools Technol Transf (STTT)2001333143310991.68731Google ScholarCross Ref
- Gom98 Gomez ME, Santonja V (1998) Self-similiary in I/O workload: analysis and modeling. In: Workshop on Workload CharacterizationGoogle Scholar
- Gri05 Visual recognition: as soon as you know it is there, you know what it isPsychol Sci200516215216010.1111/j.0956-7976.2005.00796.xGoogle ScholarCross Ref
- Hoa85 Communicating sequential processes1985LondonPrentice-Hall0637.68007Google ScholarDigital Library
- KMM99 Insights into working memory from the perspective of the EPIC architecture for modelling skilled perceptual-motor and cognitive human performance, Models of Working Memory, Mechanisms of Active Maintenance and Executive Control1999New YorkCambridge University Press183223Google Scholar
- Lev79 A perceptual-motor processing model of emotionPerception of emotion in self and others, vol 51979New YorkPlenum146Google Scholar
- LHB00 A direct brain interface based on event-related potentialsIEEE Trans Rehabil Eng20008218018510.1109/86.847809Google ScholarCross Ref
- Mac63 The duration of the visual imageCan J Paychol19631716268Google Scholar
- MFP97 Associative priming by targets and distractors during rapid serial presentationJ Exp Psychol Hum Percept Perform1997231014103410.1037/0096-1523.23.4.1014Google ScholarCross Ref
- MKH03 Improving transfer rates in brain computer interfacing: a case studyAdv Neural Inform Process Syst20031511071114Google Scholar
- Met78 Basic principles of ROC analysisSemin Nuclear Med1978828329810.1016/S0001-2998(78)80014-2Google ScholarCross Ref
- Mey97 A computational theory of executive cognitive processes and multiple task performance: Part 1Basic mechanisms. Psychol Rev1997104365Google ScholarCross Ref
- Mil89 Communication and concurrency1989Hemel HempsteadPrentice-Hall0683.68008Google ScholarDigital Library
- New90 Unified theories of cognition1990CambridgeHarvard University PressGoogle ScholarDigital Library
- Rei00 Computational explorations in cognitive neuroscience: understanding the mind by simulating the brain, a Bradford book2000CambidgeMIT PressGoogle Scholar
- RSA92 Temporary suppression of visual processing in an RSVP Task: an attentional blinkJ Exp Psychol Hum Percept Perform199218384986010.1037/0096-1523.18.3.849Google ScholarCross Ref
- Rol01 A model of the interaction between mood and memoryNetw: Comput Neural Syst200112891090969.9201110.1080/713663216Google Scholar
- Rol98 Neural networks and brain function1998OxfordOxford University PressGoogle Scholar
- RMP86 Parallel distributed processing, explorations in the microstructure of cognition. Volume 1: Foundations and Volume 2: Psychological and Biological Models, a Bradford book1986CambridgeMIT PressGoogle Scholar
- SWH98 Signal timing across the Macaque visual systemJ Neurophysiopl199879632723278Google ScholarCross Ref
- SCS97 Personal names and the attentional blink: the cocktail party revisitedJ Exp Psychol Hum Percept Perform19972350451410.1037/0096-1523.23.2.504Google ScholarCross Ref
- Sha99 Shapiro KL, Luck SJ (1999) The attentional blink: a front-end mechanism for fleeting memories. In: Fleeting memories, cognition of brief visual stimuli, A Bradford book. MIT Press, Boston, pp 95–118Google Scholar
- Sno88 Pragmatics of measuring recognition memory: applications to dementia and amnesiaJ Exp Psychol Gen19881171345010.1037/0096-3445.117.1.34Google ScholarCross Ref
- SSH75 Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in manElectroencephalogr Clin Neurophysiol197538438740110.1016/0013-4694(75)90263-1Google ScholarCross Ref
- SBB07 Su L, Bowman H, Barnard PJ (2007) Attentional capture by meaning: a multi-level modelling study. In: Proceedings of the 29th Annual Cognitive Science Society. Cognitive Science Society, Austin, pp 1521–1526Google Scholar
- SBB08 Su L, Bowman H, Barnard PJ (2008) Performance of reactive interfaces in stimulus rich environments, applying formal methods and cognitive frameworks. In: The 2nd International Workshop on Formal Methods for Interactive Systems FMIS2007 (held in conjunction with HCI2007), Electronic Notes in Theoretical Computer Science, vol 208. Elsevier, Amsterdam, pp 95–111Google Scholar
- Tea93 Affect, cognition and change: re-modelling depressive thought1993HoveLawrence Erlbaum AssociatesGoogle Scholar
- Vid73 Toward direct brain-computer communicationAnn Rev Biophys Bioeng1973215718010.1146/annurev.bb.02.060173.001105Google ScholarCross Ref
- VLS98 Electrophysiological evidence for a postperceptual locus of suppression during the attentional blinkJ Exp Psychol Hum Percept Perform19982461656167410.1037/0096-1523.24.6.1656Google Scholar
- WMC02 Wang M, Madhyastha T, Chan NH, Papadimitriou S, Faloutsos C (2002) Data mining meets performance evaluation: fast algorithms for modeling bursty traffic. In: 18th International Conference on Data EngineeringGoogle Scholar
- Wyb05 Wyble B, Bowman H (2005) Computational and experimental evaluation of the attentional blink: testing the simultaneous type serial token model. In: Bara BG, Barsalou LW, Bucciarelli M (eds) CogSci 2005, XXVII Annual Conference of the Cognitive Science Society. Cognitive Science Society, Cognitive Science Society through Lawrence Erlbaum, Austin, pp 2371–2376Google Scholar
- WCB06 Wyble B, Craston P, Bowman H (2006) Electrophysiological feedback in adaptive human–computer interfaces, Technical Report 8-06, Computing Laboratory, University of Kent, Canterbury, UKGoogle Scholar
Index Terms
Process algebraic modelling of attentional capture and human electrophysiology in interactive systems
Recommendations
Difficulty of discrimination modulates attentional capture by regulating attentional focus
Attentional capture for distractors is enhanced by increasing the difficulty of discrimination between the standard and the target in the three-stimulus oddball paradigm. In this study, we investigated the cognitive mechanism of this modulation of ...
Neural Correlates of Attentional Capture in Visual Search
Much behavioral research has shown that the presence of a unique singleton distractor during a task of visual search will typically capture attention and thus disrupt target search. Here we examined the neural correlates of such attentional capture ...
Performance of Reactive Interfaces in Stimulus Rich Environments, Applying Formal Methods and Cognitive Frameworks
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. ...
Comments