Open AccessAttenuated alpha–gamma coupling in emotional dual pathways with right‐Amygdala predicting ineffective antidepressant response
Author(s) -
Dai Zhongpeng,
Pei Cong,
Zhang Siqi,
Tian Shui,
Chen Zhilu,
Zhou Hongliang,
Lu Qing,
Yao Zhijian
Publication year - 2022
Publication title -
cns neuroscience and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 69
eISSN - 1755-5949
pISSN - 1755-5930
DOI - 10.1111/cns.13787
Subject(s) - amygdala , antidepressant , magnetoencephalography , psychology , major depressive disorder , neuroscience , functional magnetic resonance imaging , audiology , medicine , electroencephalography , hippocampus
Abstract Aims The diversity of treatment outcomes for major depressive disorder (MDD) remains uncertain in neuropathology. The current study aimed at exploring electrophysiological biomarkers associated with treatment response. Methods The present study recruited 130 subjects including 100 MDD patients and 30 healthy controls. All subjects participated in a sad expression recognition task while their magnetoencephalography data were recorded. Patients who had a reduction of at least 50% in disorder severity at endpoint (>2 weeks) were considered as responders. Within‐frequency power and phase‐amplitude coupling were measured for the brain regions involved in the emotional visual information processing pathways. Results The significant alpha–gamma decoupling from the right thalamus to the right amygdala in unconscious processing and from right orbital frontal cortices to the right amygdala in conscious processing was found in non‐responders relative to responders and healthy controls. These kinds of dysregulation could also predict the potential treatment response. Conclusion The attenuated alpha–gamma coupling in dual pathways indicated increased sensitivity to the negative emotional information and reduced moderated effect of the amygdala, which might cause insensitivity to antidepressant treatment and could be regarded as potential neural mechanisms for treatment response prediction.