[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127994-en":3,"doc-seo-127994-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127994,962084928904,"Asher","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Altered brainstem–cortex activation and interaction in migraine patients - somatosensory evoked EEG responses with machine learning","Neural signatures of abnormal sensory processing in migraine are investigated through an electroencephalography (EEG) protocol designed to measure brainstem and cortical responses to sensory stimulation. Weighted minimum norm estimates quantify activation amplitude and effective connectivity, while spectral Granger causality characterizes interactions. Machine learning classification models use evoked brainstem–cortex features plus psychometric scores to determine migraine presence and subtype. Analysis of somatosensory responses from 342 participants evaluates reliability and generalisability for chronic and episodic migraine.","Hsiao et al. The Journal of Headache and Pain (2024) 25:185  \n[https://doi.org/10.1186/s10194-024-01892-2](https://doi.org/10.1186/s10194-024-01892-2)  \nThe Journal of Headache and Pain  \n RESEARCH Open Access  \nAltered brainstem–cortex activation and interaction in migraine patients:  \nsomatosensory evoked EEG responses with machine learning  \nFu-Jung Hsiao 1*, Wei-Ta Chen 1,3,5, Hung-Yu Liu2,3, Yu-Te Wu1, Yen-Feng Wang2,3, Li-Ling Hope Pan 1, Kuan-Lin Lai2,3, Shih-Pin Chen 1,3, Gianluca Coppola4 and Shuu-Jiun Wang1,2,3  \nAbstract  \nBackground To gain a comprehensive understanding of the altered sensory processing in patients with migraine, in this study, we developed an electroencephalography (EEG) protocol for examining brainstem and cortical responses to sensory stimulation. Furthermore, machine learning techniques were employed to identify neural signatures from evoked brainstem–cortex activation and their interactions, facilitating the identification of the presence and subtype of migraine.  \nMethods This study analysed 1,000-epoch-averaged somatosensory evoked responses from 342 participants, comprising 113 healthy controls (HCs), 106 patients with chronic migraine (CM), and 123 patients with episodic migraine (EM) . Activation amplitude and effective connectivity were obtained using weighted minimum norm estimates with spectral Granger causality analysis. This study used support vector machine algorithms to develop classification models; multimodal data (amplitude, connectivity, and scores of psychometric assessments) were applied to assess the reliability and generalisability of the identification results from the classification models.  \nResults The findings revealed that patients with migraine exhibited reduced amplitudes for responses in both the brainstem and cortical regions and increased effective connectivity between these regions in the gamma and highgamma frequency bands. The classification model with characteristic features performed well in distinguishing patients with CM from HCs, achieving an accuracy of 81 . 8% and an area under the curve (AUC) of 0.86 during training and an accuracy of 76 . 2% and an AUC of 0.89 during independent testing. Similarly, the model effectively identified patients with EM, with an accuracy of 77 . 5% and an AUC of 0.84 during training and an accuracy of 87% and an AUCof 0.88 during independent testing. Additionally, the model successfully differentiated patients with CM from patients with EM, with an accuracy of 70 . 5% and an AUC of 0.73 during training and an accuracy of 72. 7% and an AUC of 0.74 during independent testing.  \nConclusion Altered brainstem-cortex activation and interaction are characteristic of the abnormal sensory processing in migraine. Combining evoked activity analysis with machine learning offers a reliable and generalisable tool for identifying patients with migraine and for assessing the severity of their condition. Thus, this approach is an effective and rapid diagnostic tool for clinicians.  \n*Correspondence:  \nFu-Jung Hsiao  \n[fujunghsiao@gmail.com](fujunghsiao@gmail.com)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is no","cbCaivc3JC9e2RwZ","https://ap.wps.com/l/cbCaivc3JC9e2RwZ","pdf",8298614,3,1,17,"English","en",105,"# Abstract\n## Background\n## Methods\n## Results\n## Conclusion\n# Introduction\n## Migraine burden and progression\n## Sensory processing alterations in migraine","[{\"question\":\"What was the goal of the EEG protocol in this study?\",\"answer\":\"To examine brainstem and cortical responses to sensory stimulation and better understand altered sensory processing in migraine patients.\"},{\"question\":\"How were brainstem–cortex activation and interaction quantified?\",\"answer\":\"Activation amplitude and effective connectivity were estimated using weighted minimum norm estimates, and interactions were assessed with spectral Granger causality.\"},{\"question\":\"Which machine learning approach was used to identify migraine subtypes?\",\"answer\":\"Support vector machine algorithms were trained using amplitude, connectivity, and psychometric scores to classify chronic migraine, episodic migraine, and controls.\"}]","Altered brainstem–cortex activation and interaction in migraine patients - somatosensory evoked EEG responses with machine learning | PDF",1785943719,43,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"altered-brainstemcortex-activation-and-interaction-in-migraine-patients-somatosensory-evoked-eeg-responses-with-machine-learning","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":20},"https://docshare.wps.com/document/research-report/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/altered-brainstemcortex-activation-and-interaction-in-migraine-patients-somatosensory-evoked-eeg-responses-with-machine-learning/127994/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-26","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What was the goal of the EEG protocol in this study?","Question",{"text":76,"@type":77},"To examine brainstem and cortical responses to sensory stimulation and better understand altered sensory processing in migraine patients.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How were brainstem–cortex activation and interaction quantified?",{"text":81,"@type":77},"Activation amplitude and effective connectivity were estimated using weighted minimum norm estimates, and interactions were assessed with spectral Granger causality.",{"name":83,"@type":74,"acceptedAnswer":84},"Which machine learning approach was used to identify migraine subtypes?",{"text":85,"@type":77},"Support vector machine algorithms were trained using amplitude, connectivity, and psychometric scores to classify chronic migraine, episodic migraine, and controls.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]