Amygdala-Prefrontal Connectivity Analysis of Decoding Human Emotion

DOI

10.2991/bep-16.2017.10How to use a DOI?

Keywords

emotion illness; fMRI; functional connectivity; basolateral amygdala; centromedial amygdala

Abstract

Functional neuroimaging studies have found that emotion network in patients with some psychiatric and neurological diseases was abnormal. However, human emotion network is extremely complex and understanding of it still remains unclear. So, it's difficult to regulate and remodel emotion network directly. Here, we first estimated the critical connectivity from whole brain functional connectivity, whose seed regions were the structurally and functionally distinct nuclei of amygdala, the basolateral amygdala (BLA) and centromedial amygdala (CMA). And then the critical connectivity was extracted from whole brain functional connectivity using a machine learning method. The experimental results showed that the connectivity between left amygdala and various regions of the prefrontal gyrus, especially right medial superior frontal gyrus, performed better in the classification. Moreover, real time fMRI neurofeedback training also demonstrated that the critical connectivity provided a great contribution for emotion regulation. These findings may be useful support for the connectivity-based emotion regulation training and possibly applied to supplementary treatment of emotion illness.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wenjie HE
AU  - Haibing BU
AU  - Zhonglin LI
AU  - Bin YAN
AU  - Li TONG
AU  - Linyuan WANG
PY  - 2016/12
DA  - 2016/12
TI  - Amygdala-Prefrontal Connectivity Analysis of Decoding Human Emotion
BT  - Proceedings of the 2016 International Conference on Biological Engineering and Pharmacy (BEP 2016)
PB  - Atlantis Press
SP  - 45
EP  - 50
SN  - 2468-5747
UR  - https://doi.org/10.2991/bep-16.2017.10
DO  - 10.2991/bep-16.2017.10
ID  - HE2016/12
ER  -