Abstract:

Insomnia has high incidence in modern society. The resting-state functional magnetic resonance (rs-fMRI) becomes one of the main imaging methods for the neuroimaging studies of insomnia, with its convenience and non-intrusive during data recording. Recent rs-fMRI studies showed that patients with insomnia had abnormalities in the prefrontal lobe, the temporal lobe, anterior cingulate gyrus and insula. Large-scale brain network is a brain structure that contains multiple brain regions and has relatively unique cognitive function. Based on the perspective of large-scale brain networks, patients with insomnia had abnormal activities and connectivities within the default network, the salience network, the cognitive control network and the negative affect network. More important, growing evidence presented an altered connectivities pattern among these four large-scale brain networks. Based on the symptoms, therapy, and the patterns of the large-scale brain networks, we proposed a "precision treatment" approach for insomnia. Future researches could integrate the big data with multimodal neuroimaging technology to verify the findings of rs-fMRI. Moreover, longitudinal and sequential design of insomnia can further benefit for the understanding of the neural mechanisms of insomnia.

Key words: insomnia, rs-fMRI, large-scale brain network, subtype of insomnia, precision treatment