Generative adversarial networks for reconstructing natural images from brain activity

We explore a method for reconstructing visual stimuli from brain activity. Using large databases of natural images we trained a deep convolutional generative adversarial network capable of generating gray scale photos, similar to stimuli presented during two functional magnetic resonance imaging exp...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 181; pp. 775 - 785
Main Authors:	Seeliger, K., Güçlü, U., Ambrogioni, L., Güçlütürk, Y., van Gerven, M.A.J.
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.11.2018 Elsevier Limited
Subjects:	Adult Brain Brain - diagnostic imaging Brain - physiology Brain mapping Datasets fMRI Functional magnetic resonance imaging Functional Neuroimaging - methods Generative adversarial networks Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Models, Theoretical Neural Networks (Computer) Neuroimaging NMR Nuclear magnetic resonance Pattern Recognition, Visual - physiology Perceptions Reconstruction Vision Visual stimuli Reconstruction fMRI Generative adversarial networks Vision
ISSN:	1053-8119, 1095-9572, 1095-9572
Online Access:	Get full text
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