Electroencephalography connectome changes in chronic insomnia disorder are correlated with neurochemical signatures

Author:

Yu Liyong1ORCID,Peng Wei2,Lin Wenting3,Luo Yucai1,Hu Daijie1,Zhao Guangli3,Xu Hao1,Dou Zeyang1,Zhang Qi2,Hong Xiaojuan1,Yu Siyi1ORCID

Affiliation:

1. School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine , Chengdu , China

2. Chongqing Hospital of Traditional Chinese Medicine , Chongqing , China

3. School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine , Chengdu , China

Abstract

Abstract Study Objectives This study aimed to investigate the alterations in resting-state electroencephalography (EEG) global brain connectivity (GBC) in patients with chronic insomnia disorder (CID) and to explore the correlation between macroscale connectomic variances and microscale neurotransmitter distributions. Methods We acquired 64-channel EEG from 35 female CID patients and 34 healthy females. EEG signals were source-localized using individual brain anatomy and orthogonalized to mitigate volume conduction. Correlation coefficients between band-limited source-space power envelopes of the DK 68 atlas were computed and averaged across regions to determine specific GBC values. A support vector machine (SVM) classifier utilizing GBC features was employed to differentiate CID patients from controls. We further used Neurosynth and a 3D atlas of neurotransmitter receptors/transporters to assess the cognitive functions and neurotransmitter landscape associated with CID cortical abnormality maps, respectively. Results CID patients exhibited elevated GBC within the medial prefrontal cortex and limbic cortex, particularly at the gamma carrier frequency, compared to controls (pFDR < .05). GBC patterns were found to effectively distinguish CID patients from controls with a precision of 90.8% in the SVM model. The cortical abnormality maps were significantly correlated with meta-analytic terms like “cognitive control” and “emotion regulation.” Notably, GBC patterns were associated with neurotransmitter profiles (pspin < .05), with neurotransmitter systems such as norepinephrine, dopamine, and serotonin making significant contributions. Conclusions This work characterizes the EEG connectomic profile of CID, facilitating the cost-effective clinical translation of EEG-derived markers. Additionally, the linkage between GBC patterns and neurotransmitter distribution offers promising avenues for developing targeted treatment strategies for CID.

Funder

National Natural Science Foundation of China

Sichuan Provincial Science and Technology Department

Chengdu University of Traditional Chinese Medicine Xinglin Scholar Discipline Talent Research and Improvement

Publisher

Oxford University Press (OUP)

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