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Reconsidering the Imaging Evidence Used to Implicate Prediction Error as the Driving Force behind Learning.

Published version
Peer-reviewed

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Authors

Čevora, Jiří 
Henson, Richard N 

Abstract

In this paper, we review the evidence that learning is driven by signaling of Prediction Error [PE] by some neurons. We model associative learning in artificial neural networks using Hebbian (non-PE) learning algorithms to investigate whether the data used to implicate PE in learning can arise without actual PE computation. We conclude that the metabolic demands of synaptic change during Hebbian learning would produce a PE-correlated component in functional magnetic resonance imaging (fMRI), which suggests that the research used to imply PE in learning is currently inconclusive.

Description

Keywords

Hebbian learning, associative learning, learning, neuroimaging, prediction error

Journal Title

Front Psychol

Conference Name

Journal ISSN

1664-1078
1664-1078

Volume Title

8

Publisher

Frontiers Media SA
Sponsorship
MRC (unknown)
Medical Research Council (MC_UU_00005/8)
Medical Research Council (MC_U105579226)