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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Hum. Neurosci. | doi: 10.3389/fnhum.2019.00289

Predicting ventral striatal activation during reward anticipation from functional connectivity at rest

 Asako Mori1, 2, 3,  Manfred Klöbl2, Go Okada1,  Murray B. Reed2,  Masahiro Takamura1, Paul Michenthaler2, Koki Takagaki4, Patricia A. Handschuh2,  Satoshi Yokoyama1,  Matej Murgas2,  Naho Ichikawa1, Gregor Gryglewski2, Chiyo Shibasaki1, Marie Spies2,  Atsuo Yoshino1,  Andreas Hahn5,  Yasumasa Okamoto1,  Rupert Lanzenberger5,  Shigeto YAMAWAKI1* and  Siegfried Kasper2*
  • 1Department of Psychiatry and Neurosciences, Hiroshima University, Japan
  • 2Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
  • 3Department of Neuropsychiatry, Faculty of Medicine, The University of Tokyo Hospital, Japan
  • 4Health Service Center, Hiroshima University, Japan
  • 5Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria

Reward anticipation is essential for directing behavior towards positively valenced stimuli, creating motivational salience. Task-related activation of the ventral striatum has long been used as a target for understanding reward function. However, some subjects may not be able to perform the respective tasks because of their complexity or subjects’ physical or mental disabilities. Moreover, task implementations may differ, which results in limited comparability. Hence, developing a task-free method for evaluating neural gain circuits is essential. Research has shown that fluctuations in neuronal activity at rest denoted individual differences in the brain functional networks. Here, we proposed novel models to predict the activation of the ventral striatum during gain anticipation, using the fMRI data of 45 healthy subjects acquired during a monetary incentive delay task and under rest. In-sample validation and held-out data were used to estimate the generalizability of the models. It was possible to predict three measures of reward activation (sensitivity, average, maximum) from resting-state functional connectivity (Pearson’s r = 0.38 – 0.54 in validation data). Especially high contributions to the models were observed from the default mode network. These findings highlight the potential of using functional connectivity at rest as a task-free alternative for predicting activation in the ventral striatum, offering a possibility to estimate reward response in the broader sampling of subject populations.

Keywords: Ventral striatum (VS), MRI - Magnetic resonance imaging, Rest, monetary incentive delay task, prediction

Received: 24 Apr 2019; Accepted: 12 Aug 2019.

Copyright: © 2019 Mori, Klöbl, Okada, Reed, Takamura, Michenthaler, Takagaki, Handschuh, Yokoyama, Murgas, Ichikawa, Gryglewski, Shibasaki, Spies, Yoshino, Hahn, Okamoto, Lanzenberger, YAMAWAKI and Kasper. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. Shigeto YAMAWAKI, Hiroshima University, Department of Psychiatry and Neurosciences, Higashihiroshima, Japan,
Prof. Siegfried Kasper, Medical University of Vienna, Department of Psychiatry and Psychotherapy, Vienna, 1090, Vienna, Austria,