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Prior neuroimaging studies in patients with migraine based on functional magnetic resonance imaging have found regional as well as network\u2010level alterations in brain function. Here, we expand on prior studies by establishing whole\u2010brain functional connectivity patterns in patients with migraine using dimensionality reduction techniques. We studied functional brain connectivity in 50 patients with episodic migraine and sex\u2010 and age\u2010matched healthy controls. Using dimensionality reduction techniques that project high\u2010dimensional functional connectivity onto low\u2010dimensional representations (i.e., eigenvectors), we found significant between\u2010group differences in the eigenvectors between patients with migraine and healthy controls, particularly in the sensory\/motor and limbic cortices. Furthermore, we assessed between\u2010group differences in subcortical connectivity with subcortical weighted manifolds defined by subcortico\u2010cortical connectivity multiplied by cortical eigenvectors and revealed significant alterations in the amygdala. Finally, leveraging supervised machine learning, we moderately predicted headache frequency using cortical and subcortical functional connectivity features, again indicating that sensory and limbic regions play a particularly important role in predicting migraine frequency. Our study confirmed that migraine is a hierarchical disease of the brain that shows alterations along the sensory\u2010limbic axis, and therefore, the functional connectivity in these areas could be a useful marker to investigate migraine symptomatology.<\/jats:p>","DOI":"10.1002\/hbm.26204","type":"journal-article","created":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T18:40:54Z","timestamp":1673980854000},"page":"2224-2233","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Whole\u2010brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine"],"prefix":"10.1002","volume":"44","author":[{"given":"Chae Hyeon","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Statistics Inha University  Incheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5681-8918","authenticated-orcid":false,"given":"Hyunjin","family":"Park","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering Sungkyunkwan University  Suwon Republic of Korea"},{"name":"Center for Neuroscience Imaging Research Institute for Basic Science  Suwon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mi Ji","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Neurology, Seoul National University Hospital Seoul National University College of Medicine  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7096-337X","authenticated-orcid":false,"given":"Bo\u2010yong","family":"Park","sequence":"additional","affiliation":[{"name":"Center for Neuroscience Imaging Research Institute for Basic Science  Suwon Republic of Korea"},{"name":"Department of Data Science Inha University  Incheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,1,17]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0137020"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000002261"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40122-021-00240-5"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.09.025"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0b013e3182a6cb32"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11910-004-0022-8"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"e_1_2_9_10_1","first-page":"2079","article-title":"On over\u2010fitting in model selection and subsequent selection bias in performance evaluation","volume":"11","author":"Cawley G. 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