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Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants
Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized frame...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543023/ https://www.ncbi.nlm.nih.gov/pubmed/37790428 http://dx.doi.org/10.21203/rs.3.rs-3212709/v1 |
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author | Merk, Timon Köhler, Richard Peterson, Victoria Lyra, Laura Vanhoecke, Jonathan Chikermane, Meera Binns, Thomas Li, Ningfei Walton, Ashley Bush, Alan Sisterson, Nathan Busch, Johannes Lofredi, Roxanne Habets, Jeroen Huebl, Julius Zhu, Guanyu Yin, Zixiao Zhao, Baotian Merkl, Angela Bajbouj, Malek Krause, Patricia Faust, Katharina Schneider, Gerd-Helge Horn, Andreas Zhang, Jianguo Kühn, Andrea Richardson, R. Mark Neumann, Wolf-Julian |
author_facet | Merk, Timon Köhler, Richard Peterson, Victoria Lyra, Laura Vanhoecke, Jonathan Chikermane, Meera Binns, Thomas Li, Ningfei Walton, Ashley Bush, Alan Sisterson, Nathan Busch, Johannes Lofredi, Roxanne Habets, Jeroen Huebl, Julius Zhu, Guanyu Yin, Zixiao Zhao, Baotian Merkl, Angela Bajbouj, Malek Krause, Patricia Faust, Katharina Schneider, Gerd-Helge Horn, Andreas Zhang, Jianguo Kühn, Andrea Richardson, R. Mark Neumann, Wolf-Julian |
author_sort | Merk, Timon |
collection | PubMed |
description | Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson’s disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients. |
format | Online Article Text |
id | pubmed-10543023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-105430232023-10-03 Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants Merk, Timon Köhler, Richard Peterson, Victoria Lyra, Laura Vanhoecke, Jonathan Chikermane, Meera Binns, Thomas Li, Ningfei Walton, Ashley Bush, Alan Sisterson, Nathan Busch, Johannes Lofredi, Roxanne Habets, Jeroen Huebl, Julius Zhu, Guanyu Yin, Zixiao Zhao, Baotian Merkl, Angela Bajbouj, Malek Krause, Patricia Faust, Katharina Schneider, Gerd-Helge Horn, Andreas Zhang, Jianguo Kühn, Andrea Richardson, R. Mark Neumann, Wolf-Julian Res Sq Article Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson’s disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients. American Journal Experts 2023-09-20 /pmc/articles/PMC10543023/ /pubmed/37790428 http://dx.doi.org/10.21203/rs.3.rs-3212709/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Merk, Timon Köhler, Richard Peterson, Victoria Lyra, Laura Vanhoecke, Jonathan Chikermane, Meera Binns, Thomas Li, Ningfei Walton, Ashley Bush, Alan Sisterson, Nathan Busch, Johannes Lofredi, Roxanne Habets, Jeroen Huebl, Julius Zhu, Guanyu Yin, Zixiao Zhao, Baotian Merkl, Angela Bajbouj, Malek Krause, Patricia Faust, Katharina Schneider, Gerd-Helge Horn, Andreas Zhang, Jianguo Kühn, Andrea Richardson, R. Mark Neumann, Wolf-Julian Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title | Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title_full | Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title_fullStr | Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title_full_unstemmed | Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title_short | Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
title_sort | invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543023/ https://www.ncbi.nlm.nih.gov/pubmed/37790428 http://dx.doi.org/10.21203/rs.3.rs-3212709/v1 |
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