The individual response to treatment with the transcutaneous auricular vagus nerve stimulation ( taVNS ) in primary insomnia varies greatly, while there is lack of objective markers for patient’s treatment outcome. In this work, we demonstrated that the baseline functional connectivity combined with machine learning algorithms can predict response to treatment with taVNS in primary insomnia. The functional connectivity values within and between brain networks such as the default mode network, affective network, visual network, and cerebellar network maybe potential objective markers of patient’s treatment outcome.
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