Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease
Abstract Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients with Parkinson’s disease (PD). The adaptive DBS approach (aDBS) modulates stimulation, based on the power in the beta range ([12–30] Hz) of STN local field potentials, aiming to follow the pat...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | npj Parkinson's Disease |
| Online Access: | https://doi.org/10.1038/s41531-025-01011-1 |
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| author | Salvatore Falciglia Laura Caffi Claudio Baiata Chiara Palmisano Ioannis Ugo Isaias Alberto Mazzoni |
| author_facet | Salvatore Falciglia Laura Caffi Claudio Baiata Chiara Palmisano Ioannis Ugo Isaias Alberto Mazzoni |
| author_sort | Salvatore Falciglia |
| collection | DOAJ |
| description | Abstract Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients with Parkinson’s disease (PD). The adaptive DBS approach (aDBS) modulates stimulation, based on the power in the beta range ([12–30] Hz) of STN local field potentials, aiming to follow the patient’s clinical state. Control of aDBS relies on identifying the correct thresholds of pathological beta power. Currently, in-person reprogramming sessions, due to changes in beta power distribution over time, are needed to ensure clinical efficacy. Here we present LAURA, a Transformer-based framework predicting the nonlinear evolution of subthalamic beta power up to 6 days in advance, based on the analysis of chronic recordings. High prediction accuracy (>90%) was achieved in four PD patients with chronic DBS over months of recordings, independently of stimulation parameters. Our study paves the way for remote monitoring strategies and the implementation of new algorithms for personalized auto-tuning aDBS devices. |
| format | Article |
| id | doaj-art-e3b51aa99fbc40e6a6d833709127bfa1 |
| institution | Kabale University |
| issn | 2373-8057 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Parkinson's Disease |
| spelling | doaj-art-e3b51aa99fbc40e6a6d833709127bfa12025-08-20T04:01:56ZengNature Portfolionpj Parkinson's Disease2373-80572025-07-0111111210.1038/s41531-025-01011-1Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s diseaseSalvatore Falciglia0Laura Caffi1Claudio Baiata2Chiara Palmisano3Ioannis Ugo Isaias4Alberto Mazzoni5The BioRobotics Institute, Scuola Superiore Sant’AnnaThe BioRobotics Institute, Scuola Superiore Sant’Anna Pezzoli Foundation for Parkinson’s DiseaseUniversity Hospital Wuerzburg and Julius Maximilian, University of WuerzburgUniversity Hospital Wuerzburg and Julius Maximilian, University of WuerzburgThe BioRobotics Institute, Scuola Superiore Sant’AnnaAbstract Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients with Parkinson’s disease (PD). The adaptive DBS approach (aDBS) modulates stimulation, based on the power in the beta range ([12–30] Hz) of STN local field potentials, aiming to follow the patient’s clinical state. Control of aDBS relies on identifying the correct thresholds of pathological beta power. Currently, in-person reprogramming sessions, due to changes in beta power distribution over time, are needed to ensure clinical efficacy. Here we present LAURA, a Transformer-based framework predicting the nonlinear evolution of subthalamic beta power up to 6 days in advance, based on the analysis of chronic recordings. High prediction accuracy (>90%) was achieved in four PD patients with chronic DBS over months of recordings, independently of stimulation parameters. Our study paves the way for remote monitoring strategies and the implementation of new algorithms for personalized auto-tuning aDBS devices.https://doi.org/10.1038/s41531-025-01011-1 |
| spellingShingle | Salvatore Falciglia Laura Caffi Claudio Baiata Chiara Palmisano Ioannis Ugo Isaias Alberto Mazzoni Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease npj Parkinson's Disease |
| title | Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease |
| title_full | Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease |
| title_fullStr | Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease |
| title_full_unstemmed | Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease |
| title_short | Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease |
| title_sort | transformer based long term predictor of subthalamic beta activity in parkinson s disease |
| url | https://doi.org/10.1038/s41531-025-01011-1 |
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