Information theory, novelty and hippocampal responses: unpredicted or unpredictable?

  • Authors:

  • Bryan A. Strange;Andrew Duggins;William Penny;Raymond J. Dolan;Karl J. Friston

  • Affiliations:

  • Wellcome Department of Imaging Neuroscience, Functional Imaging Laboratory, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK and Institute of Cognitive Neuroscience, 17 Queen Square, L ...;Wellcome Department of Imaging Neuroscience, Functional Imaging Laboratory, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK;Wellcome Department of Imaging Neuroscience, Functional Imaging Laboratory, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK;Wellcome Department of Imaging Neuroscience, Functional Imaging Laboratory, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK;Wellcome Department of Imaging Neuroscience, Functional Imaging Laboratory, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK

  • Venue:
  • Neural Networks
  • Year:
  • 2005

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Abstract

Shannon's information theory provides a principled framework for the quantitative analysis of brain responses during the encoding and representation of event streams. In particular, entropy measures the expected uncertainty of events in a given context. This contextual uncertainty or unpredictability may, itself, be important for balancing [bottom-up] sensory information and [top-down] prior expectations during perceptual synthesis. Using event-related functional magnetic resonance imaging (fMRI), we found that the anterior hippocampus is sensitive to the entropy of a visual stimulus stream. In contrast, activity in an extensive bilateral cortico-thalamic network was dictated by the surprise or information associated with each particular stimulus. In short, we show that the probabilistic structure or context in which events occur is an important predictor of hippocampal activity.