Selfreparing Neural Networks: A Model for Recovery from Brain Damage

  • Jaap M. J. Murre
  • Robert Griffioen
  • I. H. Robertson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2774)


We introduce selfrepairing neural networks as a model for recovery from brain damage. Small lesions are repaired through reinstatement of the redundancy in the network’s connections. With mild lesions, this process can model autonomous recovery. Moderate lesions require patterned input. In this paper, we discuss implementations in three types of network of increasing biological plausibility. We also mention some results from random graph theory. Finally, we discuss the implications for rehabilitation theory.


Random Graph Brain Damage Retrograde Amnesia Hebbian Learning Moderate Lesion 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jaap M. J. Murre
    • 1
    • 2
  • Robert Griffioen
    • 1
  • I. H. Robertson
    • 3
  1. 1.University of AmsterdamAmsterdamThe Netherlands
  2. 2.University of MaastrichtThe Netherlands
  3. 3.Trinity CollegeIreland

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