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The Journal of Neuroscience, November 19, 2008, 28(47):12539-12545; doi:10.1523/JNEUROSCI.2925-08.2008
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Behavioral/Systems/Cognitive
Trial-by-Trial Fluctuations in the Event-Related Electroencephalogram Reflect Dynamic Changes in the Degree of Surprise
Rogier B. Mars,1,3,4 Stefan Debener,5 Thomas E. Gladwin,6,7 Lee M. Harrison,2 Patrick Haggard,3,8 John C. Rothwell,1 andSven Bestmann1,2,3 1Sobell Department of Motor Neuroscience and Movement Disorders and 2Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom, 3Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, United Kingdom, 4Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom, 5Medical Research Council Institute of Hearing Research, Royal South Hants Hospital, Southampton SO14 0YG, United Kingdom, 6Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht 3508 GA, The Netherlands, 7Department of Psychiatry, Stuivenberg Hospital, Antwerpen B-2-60, Belgium, and 8Department of Psychology, University College London, London WC1E 6BT, United Kingdom
Correspondence should be addressed to Rogier B. Mars, Department of Experimental Psychology, University of Oxford, Tinbergen Building, South Parks Road, Oxford OX1 3UD, UK. Email: rogier.mars{at}psy.ox.ac.uk
The P300 component of the human event-related brain potential has often been linked to the processing of rare, surprising events. However, the formal computational processes underlying the generation of the P300 are not well known. Here, we formulate a simple model of trial-by-trial learning of stimulus probabilities based on Information Theory. Specifically, we modeled the surprise associated with the occurrence of a visual stimulus to provide a formal quantification of the "subjective probability" associated with an event. Subjects performed a choice reaction time task, while we recorded their brain responses using electroencephalography (EEG). In each of 12 blocks, the probabilities of stimulus occurrence were changed, thereby creating sequences of trials with low, medium, and high predictability. Trial-by-trial variations in the P300 component were best explained by a model of stimulus-bound surprise. This model accounted for the data better than a categorical model that parametrically encoded the stimulus identity, or an alternative model of surprise based on the Kullback–Leibler divergence. The present data demonstrate that trial-by-trial changes in P300 can be explained by predictions made by an ideal observer keeping track of the probabilities of possible events. This provides evidence for theories proposing a direct link between the P300 component and the processing of surprising events. Furthermore, this study demonstrates how model-based analyses can be used to explain significant proportions of the trial-by-trial changes in human event-related EEG responses.
Key words: P300; single-trial EEG; information theory; surprise; attention; independent component analysis
Received June 25, 2008; accepted Sept. 8, 2008.
Correspondence should be addressed to Rogier B. Mars, Department of Experimental Psychology, University of Oxford, Tinbergen Building, South Parks Road, Oxford OX1 3UD, UK. Email: rogier.mars{at}psy.ox.ac.uk
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