Reconsidering the Imaging Evidence Used to Implicate Prediction Error as the Driving Force behind Learning.
Published version
Peer-reviewed
Repository URI
Repository DOI
Change log
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
1664-1078
Volume Title
8
Publisher
Frontiers Media SA
Publisher DOI
Sponsorship
MRC (unknown)
Medical Research Council (MC_UU_00005/8)
Medical Research Council (MC_U105579226)
Medical Research Council (MC_UU_00005/8)
Medical Research Council (MC_U105579226)