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Using individual-level cortical segmentation to construct individual brain atlases can supplement the individual information covered by group-level cortical segmentation. Functional connectivity analyses at the individual level are helpful for obtaining clinically useful markers and predicting treatment response. Based on the functional connectivity of individualized regions of interest, a support vector regression model was trained to estimate the severity of motor symptoms for each subject, and a correlation analysis between the estimated scores and clinical symptom scores was performed. Forty-six PD patients aged 50\u201375\u00a0years were included from the Parkinson\u2019s Progression Markers Initiative database, and 63 PD patients were included from the Beijing Rehabilitation Hospital database. Only patients below Hoehn and Yahr stage III were included. The analysis showed that the severity of motor symptoms could be estimated by the individualized functional connectivity between the visual network and sensorimotor network in early-stage disease. The results reveal individual-level connectivity biomarkers related to motor symptoms and emphasize the importance of individual differences in the prediction of the treatment response of PD.<\/jats:p>","DOI":"10.1093\/cercor\/bhac503","type":"journal-article","created":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T03:26:48Z","timestamp":1673407608000},"page":"6282-6290","source":"Crossref","is-referenced-by-count":9,"title":["Individual-level functional connectomes predict the motor symptoms of Parkinson\u2019s disease"],"prefix":"10.1093","volume":"33","author":[{"given":"Zhongyan","family":"Shi","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology School of Life Science, , Beijing 100081 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Jiang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology School of Life Science, , Beijing 100081 , 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