A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies

  • Anthony F. Morse
  • Robert Lowe
  • Tom Ziemke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5499)

Abstract

Anticipation and prediction have been identified as key functions of many brain areas facilitating recognition, perception, and planning. In this chapter we present a hierarchical neurocomputational model in which feedback, effectively predicting or anticipating task-relevant features, leads to sustained inattentional blindness. A psychological experiment on sustained inattentional blindness in human subjects is simulated to provide visual input to a hierarchy of Echo State Networks. Other parts of the model receive input relevant to tracking the attended object and also detecting the unexpected object, feedback from which is then used to simulate engagement in the task and compared to results obtained without feedback, simulating passive observation. We find a significant effect of anticipation enhancing performance at the task and simultaneously degrading detection of unexpected features, thereby modelling the sustained inattentional blindness effect. We therefore suggest that anticipatory / predictive mechanisms are responsible for sustained inattentional blindness.

Keywords

Enaction Anticipation Prediction Neurocomputation Reservoir Systems Association Sustained Inattentional Blindness Neural Modelling Cortical Hierarchies 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anthony F. Morse
    • 1
  • Robert Lowe
    • 1
  • Tom Ziemke
    • 1
  1. 1.COIN Lab, Informatics Research CentreUniversity of SkövdeSkövdeSweden

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