Selfreparing neural networks: A model for recovery from brain damage

被引：0

作者：

Murre, JMJ ^{[1
]}

Griffioen, R

Robertson, IH

机构：

[1] Univ Amsterdam, Roetersstr 15, NL-1018 WB Amsterdam, Netherlands

[2] Univ Maastricht, Maastricht, Netherlands

[3] Univ Ireland Trinity Coll, Dublin, Ireland

来源：

KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS | 2003年 / 2774卷

关键词：

D O I：

10.1007/978-3-540-45226-3_158

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1164 / 1171

页数：8

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