Learning Personal Representations from fMRI by Predicting Neurofeedback Performance

Jhonathan Osin, Lior Wolf*, Guy Gurevitch, Jackob Nimrod Keynan, Tom Fruchtman-Steinbok, Ayelet Or-Borichev, Talma Hendler

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


We present a deep neural network method that enables learning of a personal representation from samples acquired while subjects are performing a self neuro-feedback task, guided by functional MRI (fMRI). The neurofeedback task (watch vs. regulate) provides the subjects with continuous feedback, contingent on the down-regulation of their Amygdala signal. The representation is learned by a self-supervised recurrent neural network that predicts the Amygdala activity in the next fMRI frame given recent fMRI frames and is conditioned on the learned individual representation. We show that our personal representation, learned solely using fMRI images, improves the next-frame prediction considerably and, more importantly, yields superior performance in linear prediction of psychiatric traits, compared to performing such predictions based on clinical data and personality tests. Our code is attached as supplementary and the data would be shared subject to ethical approvals.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings
EditorsAnne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783030597276
StatePublished - 2020
Event23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
Duration: 4 Oct 20208 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12267 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020


FundersFunder number
7th Framework Programme
US Department of DefenseW81XWH-11–2–0008
U.S. Department of DefenseW81XWH-11
Horizon 2020 Framework Programme725974
Seventh Framework Programme602186
European Research Council
Horizon 2020


    • Amygdala-neurofeedback
    • Imaging based diagnosis
    • Psychiatry
    • Recurrent neural networks
    • fMRI


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