Simulating the transverse non-patterning problem

doi:10.1016/S0925-2312(02)00507-6

2002-06-01

PRE

Xiangbao Wu *

William B. Levy

DOI：10.1016/S0925-2312(02)00507-6

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摘要

En 中文

The hippocampus is needed to store memories that are reconfigurable. We have previously shown that a hippocampal-like computational model solves the transverse patterning (TP) problem and transitive inference problems. Here, we show that the same model with the same parameters which solve the TP problem and transitive inference problems reproduces another interesting problem-transverse non-patterning (TNP) problem investigated by Alvarado and Rudy (J. Exp, Psychol,: Anim. Behav. Process 18 (1992) 145). By turning TNP into a problem of sequence learning (stimuli-decision-outcome), a sequence teaming, hippocampal-like neural network finds that the TNP problem is unlearnable with the progressive learning paradigm. This unlearnability is what Alvarado and Rudy observed, Thus, both rats and the model team TP, but fail to team TNP. (C) 2002 Elsevier Science B.V. All rights reserved.

Keyword:

recurrent networks

sequence learning

transverse patterning

transverse non-patterning

hippocampus