{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T17:07:35Z","timestamp":1793207255283,"version":"4.5.0"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:00:00Z","timestamp":1767916800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:00:00Z","timestamp":1770336000000},"content-version":"vor","delay-in-days":28,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Postdoctoral Fellowship Program of CPSF","award":["GZC20231742"],"award-info":[{"award-number":["GZC20231742"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82371267, 81830033, 81671104, 82401713 and 82301655"],"award-info":[{"award-number":["82371267, 81830033, 81671104, 82401713 and 82301655"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82371267, 81830033, 81671104, 82401713 and 82301655"],"award-info":[{"award-number":["82371267, 81830033, 81671104, 82401713 and 82301655"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005088","name":"Beijing Municipal Health Commission","doi-asserted-by":"publisher","award":["11000025T000003319495-4"],"award-info":[{"award-number":["11000025T000003319495-4"]}],"id":[{"id":"10.13039\/501100005088","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Nature Science Foundation of Beijing","award":["24L60078"],"award-info":[{"award-number":["24L60078"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Parkinsons Dis."],"DOI":"10.1038\/s41531-025-01252-0","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T09:47:30Z","timestamp":1767952050000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Video-based machine learning models for predicting deep brain stimulation outcomes in Parkinson\u2019s disease patients"],"prefix":"10.1038","volume":"12","author":[{"given":"Tianxue","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zixiao","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichen","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boya","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanwen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifei","family":"Gan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Houyou","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehua","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoting","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rujin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianze","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengda","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hutao","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianguo","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anchao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"key":"1252_CR1","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1001\/jama.2019.22360","volume":"323","author":"MJ Armstrong","year":"2020","unstructured":"Armstrong, M. J. & Okun, M. S. Diagnosis and treatment of Parkinson disease: A review. JAMA 323, 548\u2013560 (2020).","journal-title":"JAMA"},{"key":"1252_CR2","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1016\/S0140-6736(14)60683-8","volume":"384","author":"PDMC Group","year":"2014","unstructured":"Group, P. D. M. C. et al. Long-term effectiveness of dopamine agonists and monoamine oxidase B inhibitors compared with levodopa as initial treatment for Parkinson\u2019s disease (PD MED): A large, open-label, pragmatic randomised trial. Lancet 384, 1196\u20131205 (2014).","journal-title":"Lancet"},{"key":"1252_CR3","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1038\/s41582-019-0145-9","volume":"15","author":"P Limousin","year":"2019","unstructured":"Limousin, P. & Foltynie, T. Long-term outcomes of deep brain stimulation in Parkinson disease. Nat. Rev. Neurol. 15, 234\u2013242 (2019).","journal-title":"Nat. Rev. Neurol."},{"key":"1252_CR4","doi-asserted-by":"publisher","first-page":"1666","DOI":"10.1002\/mds.26029","volume":"29","author":"KT Stroupe","year":"2014","unstructured":"Stroupe, K. T. et al. Cost of deep brain stimulation for the treatment of Parkinson\u2019s disease by surgical stimulation sites. Mov. Disord. 29, 1666\u20131674 (2014).","journal-title":"Mov. Disord."},{"key":"1252_CR5","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1002\/ana.25994","volume":"89","author":"F Cavallieri","year":"2021","unstructured":"Cavallieri, F. et al. Predictors of long-term outcome of subthalamic stimulation in Parkinson disease. Ann. Neurol. 89, 587\u2013597 (2021).","journal-title":"Ann. Neurol."},{"key":"1252_CR6","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1002\/mdc3.13379","volume":"9","author":"Z Lin","year":"2022","unstructured":"Lin, Z., Zhang, C., Li, D. & Sun, B. Preoperative levodopa response and deep brain stimulation effects on motor outcomes in Parkinson\u2019s disease: A systematic review. Mov. Disord. Clin. Pract. 9, 140\u2013155 (2022).","journal-title":"Mov. Disord. Clin. Pract."},{"key":"1252_CR7","doi-asserted-by":"publisher","first-page":"3135","DOI":"10.1007\/s00415-020-09810-7","volume":"268","author":"G Saranza","year":"2021","unstructured":"Saranza, G. & Lang, A. E. Levodopa challenge test: Indications, protocol, and guide. J. Neurol. 268, 3135\u20133143 (2021).","journal-title":"J. Neurol."},{"key":"1252_CR8","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1002\/mds.22340","volume":"23","author":"CG Goetz","year":"2008","unstructured":"Goetz, C. G. et al. Movement Disorder Society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Mov. Disord. 23, 2129\u20132170 (2008).","journal-title":"Mov. Disord."},{"key":"1252_CR9","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1002\/mds.20640","volume":"20","author":"B Post","year":"2005","unstructured":"Post, B., Merkus, M. P., de Bie, R. M., de Haan, R. J. & Speelman, J. D. Unified Parkinson\u2019s disease rating scale motor examination: Are ratings of nurses, residents in neurology, and movement disorders specialists interchangeable?. Mov. Disord. 20, 1577\u20131584 (2005).","journal-title":"Mov. Disord."},{"key":"1252_CR10","doi-asserted-by":"publisher","first-page":"1382","DOI":"10.1111\/j.1365-2648.2010.05313.x","volume":"66","author":"JL Palmer","year":"2010","unstructured":"Palmer, J. L. et al. Unified Parkinson\u2019s disease rating scale-motor exam: inter-rater reliability of advanced practice nurse and neurologist assessments. J. Adv. Nurs. 66, 1382\u20131387 (2010).","journal-title":"J. Adv. Nurs."},{"key":"1252_CR11","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1002\/mdc3.13825","volume":"10","author":"R Wolke","year":"2023","unstructured":"Wolke, R. et al. The role of levodopa challenge in predicting the outcome of subthalamic deep brain stimulation. Mov. Disord. Clin. Pract. 10, 1181\u20131191 (2023).","journal-title":"Mov. Disord. Clin. Pract."},{"key":"1252_CR12","doi-asserted-by":"publisher","first-page":"575","DOI":"10.3233\/JPD-225101","volume":"13","author":"VJ Geraedts","year":"2023","unstructured":"Geraedts, V. J. et al. Predicting motor outcome and quality of life after subthalamic deep brain stimulation for Parkinson\u2019s disease: The role of standard screening measures and wearable-data. J. Parkinsons Dis. 13, 575\u2013588 (2023).","journal-title":"J. Parkinsons Dis."},{"key":"1252_CR13","doi-asserted-by":"publisher","first-page":"1281","DOI":"10.1038\/s41593-018-0209-y","volume":"21","author":"A Mathis","year":"2018","unstructured":"Mathis, A. et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21, 1281\u20131289 (2018).","journal-title":"Nat. Neurosci."},{"key":"1252_CR14","doi-asserted-by":"publisher","unstructured":"Graving, J. M. et al. DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning. Elife 8. https:\/\/doi.org\/10.7554\/eLife.47994 (2019).","DOI":"10.7554\/eLife.47994"},{"key":"1252_CR15","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1038\/s41746-019-0166-1","volume":"2","author":"K Huckvale","year":"2019","unstructured":"Huckvale, K., Venkatesh, S. & Christensen, H. Toward clinical digital phenotyping: A timely opportunity to consider purpose, quality, and safety. NPJ Digit Med 2, 88 (2019).","journal-title":"NPJ Digit Med"},{"key":"1252_CR16","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1038\/s41746-022-00568-y","volume":"5","author":"AS Chandrabhatla","year":"2022","unstructured":"Chandrabhatla, A. S., Pomeraniec, I. J. & Ksendzovsky, A. Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson\u2019s disease motor symptoms. NPJ Digit Med. 5, 32 (2022).","journal-title":"NPJ Digit Med"},{"key":"1252_CR17","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1038\/s41531-023-00494-0","volume":"9","author":"H Alfalahi","year":"2023","unstructured":"Alfalahi, H., Dias, S. B., Khandoker, A. H., Chaudhuri, K. R. & Hadjileontiadis, L. J. A scoping review of neurodegenerative manifestations in explainable digital phenotyping. NPJ Parkinsons Dis. 9, 49 (2023).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR18","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1038\/s41531-024-00742-x","volume":"10","author":"D Deng","year":"2024","unstructured":"Deng, D. et al. Interpretable video-based tracking and quantification of parkinsonism clinical motor states. NPJ Parkinsons Dis. 10, 122 (2024).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR19","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41746-024-01022-x","volume":"7","author":"YY Yang","year":"2024","unstructured":"Yang, Y. Y. et al. FastEval Parkinsonism: an instant deep learning-assisted video-based online system for Parkinsonian motor symptom evaluation. NPJ Digit Med. 7, 31 (2024).","journal-title":"NPJ Digit Med."},{"key":"1252_CR20","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1038\/s41531-025-00999-w","volume":"11","author":"F Lange","year":"2025","unstructured":"Lange, F. et al. Computer vision uncovers three fundamental dimensions of levodopa-responsive motor improvement in Parkinson\u2019s disease. NPJ Parkinsons Dis. 11, 140 (2025).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR21","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1038\/s41531-025-00876-6","volume":"11","author":"G Acevedo","year":"2025","unstructured":"Acevedo, G. et al. VisionMD: an open-source tool for video-based analysis of motor function in movement disorders. NPJ Parkinsons Dis. 11, 27 (2025).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR22","doi-asserted-by":"publisher","first-page":"107104","DOI":"10.1016\/j.parkreldis.2024.107104","volume":"127","author":"DL Guarin","year":"2024","unstructured":"Guarin, D. L., Wong, J. K., McFarland, N. R., Ramirez-Zamora, A. & Vaillancourt, D. E. What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson\u2019s disease from videos. Parkinsonism Relat. Disord. 127, 107104 (2024).","journal-title":"Parkinsonism Relat. Disord."},{"key":"1252_CR23","doi-asserted-by":"publisher","first-page":"S83","DOI":"10.3233\/JPD-202402","volume":"11","author":"KG Sibley","year":"2021","unstructured":"Sibley, K. G., Girges, C., Hoque, E. & Foltynie, T. Video-based analyses of Parkinson\u2019s disease severity: A brief review. J. Parkinsons Dis. 11, S83\u2013S93 (2021).","journal-title":"J. Parkinsons Dis."},{"key":"1252_CR24","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1177\/1877718X241312605","volume":"15","author":"J Xu","year":"2025","unstructured":"Xu, J. et al. Improving reliability of movement assessment in Parkinson\u2019s disease using computer vision-based automated severity estimation. J. Parkinsons Dis. 15, 349\u2013360 (2025).","journal-title":"J. Parkinsons Dis."},{"key":"1252_CR25","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","volume":"2","author":"SM Lundberg","year":"2020","unstructured":"Lundberg, S. M. et al. From local explanations to global understanding with explainable AI for trees. Nat. Mach. Intell. 2, 56\u201367 (2020).","journal-title":"Nat. Mach. Intell."},{"key":"1252_CR26","doi-asserted-by":"publisher","first-page":"S290","DOI":"10.1002\/mds.20962","volume":"21","author":"G Kleiner-Fisman","year":"2006","unstructured":"Kleiner-Fisman, G. et al. Subthalamic nucleus deep brain stimulation: summary and meta-analysis of outcomes. Mov. Disord. 21, S290\u2013S304 (2006).","journal-title":"Mov. Disord."},{"key":"1252_CR27","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1002\/mds.20914","volume":"21","author":"A Schrag","year":"2006","unstructured":"Schrag, A., Sampaio, C., Counsell, N. & Poewe, W. Minimal clinically important change on the unified Parkinson\u2019s disease rating scale. Mov. Disord. 21, 1200\u20131207 (2006).","journal-title":"Mov. Disord."},{"key":"1252_CR28","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1002\/mds.22735","volume":"25","author":"E Moro","year":"2010","unstructured":"Moro, E. et al. Long-term results of a multicenter study on subthalamic and pallidal stimulation in Parkinson\u2019s disease. Mov. Disord. 25, 578\u2013586 (2010).","journal-title":"Mov. Disord."},{"key":"1252_CR29","first-page":"100187","volume":"8","author":"C Adams","year":"2023","unstructured":"Adams, C. et al. Updated Parkinson\u2019s disease motor subtypes classification and correlation to cerebrospinal homovanillic acid and 5-hydroxyindoleacetic acid levels. Clin. Park Relat. Disord. 8, 100187 (2023).","journal-title":"Clin. Park Relat. Disord."},{"key":"1252_CR30","doi-asserted-by":"publisher","first-page":"2077","DOI":"10.1056\/NEJMoa0907083","volume":"362","author":"KA Follett","year":"2010","unstructured":"Follett, K. A. et al. Pallidal versus subthalamic deep-brain stimulation for Parkinson\u2019s disease. N. Engl. J. Med. 362, 2077\u20132091 (2010).","journal-title":"N. Engl. J. Med."},{"key":"1252_CR31","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1109\/JBHI.2019.2898332","volume":"24","author":"S Aghanavesi","year":"2020","unstructured":"Aghanavesi, S., Bergquist, F., Nyholm, D., Senek, M. & Memedi, M. Motion sensor-based assessment of Parkinson\u2019s disease motor symptoms during leg agility tests: Results from levodopa challenge. IEEE J. Biomed. Health Inf. 24, 111\u2013119 (2020).","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"1252_CR32","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1038\/s41746-022-00674-x","volume":"5","author":"V Ramesh","year":"2022","unstructured":"Ramesh, V. & Bilal, E. Detecting motor symptom fluctuations in Parkinson\u2019s disease with generative adversarial networks. NPJ Digit Med. 5, 138 (2022).","journal-title":"NPJ Digit Med."},{"key":"1252_CR33","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1186\/s12984-024-01362-5","volume":"21","author":"J Mifsud","year":"2024","unstructured":"Mifsud, J. et al. Detecting the symptoms of Parkinson\u2019s disease with non-standard video. J. Neuroeng. Rehabil. 21, 72 (2024).","journal-title":"J. Neuroeng. Rehabil."},{"key":"1252_CR34","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1038\/s41746-024-01253-y","volume":"7","author":"E Ferrea","year":"2024","unstructured":"Ferrea, E., Negahbani, F., Cebi, I., Weiss, D. & Gharabaghi, A. Machine learning explains response variability of deep brain stimulation on Parkinson\u2019s disease quality of life. NPJ Digit Med. 7, 269 (2024).","journal-title":"NPJ Digit Med."},{"key":"1252_CR35","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1038\/s41531-021-00223-5","volume":"7","author":"ML Lachenmayer","year":"2021","unstructured":"Lachenmayer, M. L. et al. Subthalamic and pallidal deep brain stimulation for Parkinson\u2019s disease-meta-analysis of outcomes. NPJ Parkinsons Dis. 7, 77 (2021).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR36","doi-asserted-by":"publisher","first-page":"5951","DOI":"10.1007\/s00521-019-04082-3","volume":"32","author":"B Pes","year":"2020","unstructured":"Pes, B. Ensemble feature selection for high-dimensional data: a stability analysis across multiple domains. Neural Comput. Appl. 32, 5951\u20135973 (2020).","journal-title":"Neural Comput. Appl."},{"key":"1252_CR37","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1177\/0013164418817803","volume":"79","author":"KM Marcoulides","year":"2019","unstructured":"Marcoulides, K. M. & Raykov, T. Evaluation of variance inflation factors in regression models using latent variable modeling methods. Educ. Psychol. Meas. 79, 874\u2013882 (2019).","journal-title":"Educ. Psychol. Meas."},{"key":"1252_CR38","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1038\/nrneurol.2014.252","volume":"11","author":"A Fasano","year":"2015","unstructured":"Fasano, A., Aquino, C. C., Krauss, J. K., Honey, C. R. & Bloem, B. R. Axial disability and deep brain stimulation in patients with Parkinson disease. Nat. Rev. Neurol. 11, 98\u2013110 (2015).","journal-title":"Nat. Rev. Neurol."},{"key":"1252_CR39","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1186\/s12984-024-01452-4","volume":"21","author":"J He","year":"2024","unstructured":"He, J. et al. Instrumented timed up and go test and machine learning-based levodopa response evaluation: A pilot study. J. Neuroeng. Rehabil. 21, 163 (2024).","journal-title":"J. Neuroeng. Rehabil."},{"key":"1252_CR40","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1038\/s41746-024-01163-z","volume":"7","author":"W Zhang","year":"2024","unstructured":"Zhang, W. et al. Wearable sensor-based quantitative gait analysis in Parkinson\u2019s disease patients with different motor subtypes. NPJ Digit Med 7, 169 (2024).","journal-title":"NPJ Digit Med"},{"key":"1252_CR41","doi-asserted-by":"publisher","unstructured":"Khodakarami, H. et al. Prediction of the levodopa challenge test in Parkinson\u2019s disease using data from a wrist-worn sensor. Sensors (Basel) 19. https:\/\/doi.org\/10.3390\/s19235153 (2019).","DOI":"10.3390\/s19235153"},{"key":"1252_CR42","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1111\/cns.12807","volume":"24","author":"D Johansson","year":"2018","unstructured":"Johansson, D. et al. Individualization of levodopa treatment using a microtablet dispenser and ambulatory accelerometry. CNS Neurosci. Ther. 24, 439\u2013447 (2018).","journal-title":"CNS Neurosci. Ther."},{"key":"1252_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.clineuro.2021.106890","volume":"209","author":"I Guan","year":"2021","unstructured":"Guan, I. et al. Comparison of the Parkinson\u2019s KinetiGraph to off\/on levodopa response testing: Single center experience. Clin. Neurol. Neurosurg. 209, 106890 (2021).","journal-title":"Clin. Neurol. Neurosurg."},{"key":"1252_CR44","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.jns.2018.08.001","volume":"393","author":"C Miller-Patterson","year":"2018","unstructured":"Miller-Patterson, C. et al. Motor asymmetry over time in Parkinson\u2019s disease. J. Neurol. Sci. 393, 14\u201317 (2018).","journal-title":"J. Neurol. Sci."},{"key":"1252_CR45","doi-asserted-by":"publisher","first-page":"2504","DOI":"10.1002\/mds.23893","volume":"26","author":"AJ Espay","year":"2011","unstructured":"Espay, A. J. et al. Differential response of speed, amplitude, and rhythm to dopaminergic medications in Parkinson\u2019s disease. Mov. Disord. 26, 2504\u20132508 (2011).","journal-title":"Mov. Disord."},{"key":"1252_CR46","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.1002\/mds.22480","volume":"24","author":"AJ Espay","year":"2009","unstructured":"Espay, A. J. et al. Impairments of speed and amplitude of movement in Parkinson\u2019s disease: a pilot study. Mov. Disord. 24, 1001\u20131008 (2009).","journal-title":"Mov. Disord."},{"key":"1252_CR47","doi-asserted-by":"publisher","first-page":"4373","DOI":"10.1007\/s00415-024-12379-0","volume":"271","author":"J Seuthe","year":"2024","unstructured":"Seuthe, J. et al. Gait asymmetry and symptom laterality in Parkinson\u2019s disease: two of a kind?. J. Neurol. 271, 4373\u20134382 (2024).","journal-title":"J. Neurol."},{"key":"1252_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2021.110414","volume":"122","author":"RM Kanko","year":"2021","unstructured":"Kanko, R. M. et al. Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system. J. Biomech. 122, 110414 (2021).","journal-title":"J. Biomech."},{"key":"1252_CR49","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1002\/ana.24974","volume":"82","author":"A Horn","year":"2017","unstructured":"Horn, A. et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann. Neurol. 82, 67\u201378 (2017).","journal-title":"Ann. Neurol."},{"key":"1252_CR50","doi-asserted-by":"publisher","first-page":"3592","DOI":"10.1093\/brain\/awz285","volume":"142","author":"JN Petry-Schmelzer","year":"2019","unstructured":"Petry-Schmelzer, J. N. et al. Non-motor outcomes depend on location of neurostimulation in Parkinson\u2019s disease. Brain 142, 3592\u20133604 (2019).","journal-title":"Brain"},{"key":"1252_CR51","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1093\/brain\/awaa394","volume":"144","author":"YM Kehnemouyi","year":"2021","unstructured":"Kehnemouyi, Y. M. et al. Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia. Brain 144, 473\u2013486 (2021).","journal-title":"Brain"},{"key":"1252_CR52","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41531-022-00301-2","volume":"8","author":"LK Feldmann","year":"2022","unstructured":"Feldmann, L. K. et al. Toward therapeutic electrophysiology: Beta-band suppression as a biomarker in chronic local field potential recordings. NPJ Parkinsons Dis. 8, 44 (2022).","journal-title":"NPJ Parkinsons Dis."},{"key":"1252_CR53","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","volume":"30","author":"RB Postuma","year":"2015","unstructured":"Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson\u2019s disease. Mov. Disord. 30, 1591\u20131601 (2015).","journal-title":"Mov. Disord."},{"key":"1252_CR54","doi-asserted-by":"publisher","first-page":"119862","DOI":"10.1016\/j.neuroimage.2023.119862","volume":"268","author":"C Neudorfer","year":"2023","unstructured":"Neudorfer, C. et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 268, 119862 (2023).","journal-title":"Neuroimage"},{"key":"1252_CR55","first-page":"40","volume":"2018","author":"NS Escanilla","year":"2018","unstructured":"Escanilla, N. S. et al. Recursive feature elimination by sensitivity testing. Proc. Int Conf. Mach. Learn Appl 2018, 40\u201347 (2018).","journal-title":"Proc. Int Conf. Mach. Learn Appl"}],"container-title":["npj Parkinson's Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41531-025-01252-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41531-025-01252-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41531-025-01252-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T14:03:30Z","timestamp":1770386610000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41531-025-01252-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,9]]},"references-count":55,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1252"],"URL":"https:\/\/doi.org\/10.1038\/s41531-025-01252-0","relation":{},"ISSN":["2373-8057"],"issn-type":[{"value":"2373-8057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,9]]},"assertion":[{"value":"7 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Author B.Y.D. was employed by NERVTEX Co. Ltd, Shanghai, China. All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"40"}}