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  1. Article ; Online: Commentary: Congress of Neurological Surgeons Systematic Review and Evidence-Based Guidelines for Deep Brain Stimulations for Obsessive Compulsive Disorder: Update of the 2014 Guidelines.

    Henderson, Jaimie M

    Neurosurgery

    2021  Volume 88, Issue 6, Page(s) E550–E551

    MeSH term(s) Deep Brain Stimulation ; Humans ; Neurosurgeons ; Obsessive-Compulsive Disorder/therapy
    Language English
    Publishing date 2021-02-23
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 135446-2
    ISSN 1524-4040 ; 0148-396X
    ISSN (online) 1524-4040
    ISSN 0148-396X
    DOI 10.1093/neuros/nyab035
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1424: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 539: Show issues

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  2. Book: Neuroaugmentation for chronic pain

    Henderson, Jaimie M.

    (Neurosurgery clinics of North America ; 14,3)

    2003  

    Author's details Jaimie M. Henderson, guest ed
    Series title Neurosurgery clinics of North America ; 14,3
    Collection
    Language English
    Size X S., S. 327 - 468 : Ill.
    Publisher Saunders
    Publishing place Philadelphia u.a.
    Publishing country United States
    Document type Book
    HBZ-ID HT013760186
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    Se 1200 -14,3- verfügbar in Königswinter Königswinter

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  3. Article: Report on the Joint Workshop on the Relations between Health Inequalities, Ageing and Multimorbidity, Iceland, May 3-4, 2023.

    Vandenbroucke, Jan P / Sørensen, Henrik Toft / Rehkopf, David H / Gradus, Jaimie L / Mackenbach, Johan P / Glymour, M Maria / Galea, Sandro / Henderson, Victor W

    Clinical epidemiology

    2024  Volume 16, Page(s) 9–22

    Abstract: ... for Population Health Sciences, Stanford University, CA., USProfessor Jaimie Gradus, Department of Epidemiology ... Department of Public Health, Erasmus University Rotterdam, HollandProfessor, Chair M Maria Glymour ... USProfessor Victor W. Henderson, Departments of Epidemiology & Population Health and of Neurology ...

    Abstract This paper is a summary of key presentations from a workshop in Iceland on May 3-4, 2023 arranged by Aarhus University and with participation of the below-mentioned scientists. Below you will find the key messages from the presentations made by: Professor Jan Vandenbroucke, Department of Clinical Epidemiology, Aarhus University, Emeritus Professor, Leiden University; Honorary Professor, London School of Hygiene & Tropical Medicine, UKProfessor, Chair Henrik Toft Sørensen, Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, DenmarkProfessor David H. Rehkopf, Director, the Stanford Center for Population Health Sciences, Stanford University, CA., USProfessor Jaimie Gradus, Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Johan Mackenbach, Emeritus Professor, Department of Public Health, Erasmus University Rotterdam, HollandProfessor, Chair M Maria Glymour, Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, Massachusetts, USProfessor, Dean Sandro Galea, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Victor W. Henderson, Departments of Epidemiology & Population Health and of Neurology & Neurological Sciences, Stanford University, Stanford, CA, US; Department of Clinical Epidemiology, Aarhus University, Aarhus, DK.
    Language English
    Publishing date 2024-01-16
    Publishing country New Zealand
    Document type Journal Article
    ZDB-ID 2494772-6
    ISSN 1179-1349
    ISSN 1179-1349
    DOI 10.2147/CLEP.S443152
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Subject and Family Perspectives from the Central Thalamic Deep Brain Stimulation for Traumatic Brain Injury Study: Part I.

    Fins, Joseph J / Wright, Megan S / Henderson, Jaimie M / Schiff, Nicholas D

    Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees

    2022  Volume 31, Issue 4, Page(s) 419–443

    Abstract: This is the first article in a two-part series describing subject and family perspectives from the central thalamic deep brain stimulation for the treatment of traumatic brain injury using the Medtronic PC + ...

    Abstract This is the first article in a two-part series describing subject and family perspectives from the central thalamic deep brain stimulation for the treatment of traumatic brain injury using the Medtronic PC +
    MeSH term(s) Humans ; Quality of Life ; Deep Brain Stimulation ; Brain Injuries, Traumatic/therapy ; Brain Injuries, Traumatic/psychology ; Brain Injuries ; Family/psychology
    Language English
    Publishing date 2022-09-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1146581-5
    ISSN 1469-2147 ; 0963-1801
    ISSN (online) 1469-2147
    ISSN 0963-1801
    DOI 10.1017/S0963180122000226
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3650: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: Brain control of bimanual movement enabled by recurrent neural networks.

    Deo, Darrel R / Willett, Francis R / Avansino, Donald T / Hochberg, Leigh R / Henderson, Jaimie M / Shenoy, Krishna V

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 1598

    Abstract: Brain-computer interfaces have so far focused largely on enabling the control of a single effector, for example a single computer cursor or robotic arm. Restoring multi-effector motion could unlock greater functionality for people with paralysis (e.g., ... ...

    Abstract Brain-computer interfaces have so far focused largely on enabling the control of a single effector, for example a single computer cursor or robotic arm. Restoring multi-effector motion could unlock greater functionality for people with paralysis (e.g., bimanual movement). However, it may prove challenging to decode the simultaneous motion of multiple effectors, as we recently found that a compositional neural code links movements across all limbs and that neural tuning changes nonlinearly during dual-effector motion. Here, we demonstrate the feasibility of high-quality bimanual control of two cursors via neural network (NN) decoders. Through simulations, we show that NNs leverage a neural 'laterality' dimension to distinguish between left and right-hand movements as neural tuning to both hands become increasingly correlated. In training recurrent neural networks (RNNs) for two-cursor control, we developed a method that alters the temporal structure of the training data by dilating/compressing it in time and re-ordering it, which we show helps RNNs successfully generalize to the online setting. With this method, we demonstrate that a person with paralysis can control two computer cursors simultaneously. Our results suggest that neural network decoders may be advantageous for multi-effector decoding, provided they are designed to transfer to the online setting.
    MeSH term(s) Humans ; Neural Networks, Computer ; Movement ; Functional Laterality ; Hand ; Paralysis ; Brain-Computer Interfaces ; Brain
    Language English
    Publishing date 2024-01-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-51617-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Subject and Family Perspectives from the Central Thalamic Deep Brain Stimulation Trial for Traumatic Brain Injury: Part II.

    Fins, Joseph J / Wright, Megan S / Shulman, Kaiulani S / Henderson, Jaimie M / Schiff, Nicholas D

    Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees

    2023  , Page(s) 1–24

    Abstract: This is the second paper in a two-part series describing subject and family perspectives from the CENTURY-S (CENtral Thalamic Deep Brain Stimulation for the Treatment of Traumatic Brain InjURY-Safety) first-in-human invasive neurological device trial to ... ...

    Abstract This is the second paper in a two-part series describing subject and family perspectives from the CENTURY-S (CENtral Thalamic Deep Brain Stimulation for the Treatment of Traumatic Brain InjURY-Safety) first-in-human invasive neurological device trial to achieve cognitive restoration in moderate to severe traumatic brain injury (msTBI). To participate, subjects were independently assessed to formally establish decision-making capacity to provide voluntary informed consent. Here, we report on post-operative interviews conducted after a successful trial of thalamic stimulation. All five msTBI subjects met a pre-selected primary endpoint of at least a 10% improvement in completion time on Trail-Making-Test Part B, a marker of executive function. We describe narrative responses of subjects and family members, refracted against that success. Interviews following surgery and the stimulation trial revealed the challenge of adaptation to improvements in cognitive function and emotional regulation as well as altered (and restored) relationships and family dynamics. These improvements exposed barriers to social reintegration made relevant by recoveries once thought inconceivable. The study's success sparked concerns about post-trial access to implanted devices, financing of device maintenance, battery replacement, and on-going care. Most subjects and families identified the need for supportive counseling to adapt to the new trajectory of their lives.
    Language English
    Publishing date 2023-10-18
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1146581-5
    ISSN 1469-2147 ; 0963-1801
    ISSN (online) 1469-2147
    ISSN 0963-1801
    DOI 10.1017/S0963180123000518
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3650: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article: Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces.

    Pun, Tsam Kiu / Khoshnevis, Mona / Hosman, Thomas / Wilson, Guy H / Kapitonava, Anastasia / Kamdar, Foram / Henderson, Jaimie M / Simeral, John D / Vargas-Irwin, Carlos E / Harrison, Matthew T / Hochberg, Leigh R

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, ... ...

    Abstract Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method to measure instability in neural data without needing to label user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson
    Language English
    Publishing date 2024-03-04
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.02.29.582733
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Translating deep learning to neuroprosthetic control.

    Deo, Darrel R / Willett, Francis R / Avansino, Donald T / Hochberg, Leigh R / Henderson, Jaimie M / Shenoy, Krishna V

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Advances in deep learning have given rise to neural network models of the relationship between movement and brain activity that appear to far outperform prior approaches. Brain-computer interfaces (BCIs) that enable people with paralysis to control ... ...

    Abstract Advances in deep learning have given rise to neural network models of the relationship between movement and brain activity that appear to far outperform prior approaches. Brain-computer interfaces (BCIs) that enable people with paralysis to control external devices, such as robotic arms or computer cursors, might stand to benefit greatly from these advances. We tested recurrent neural networks (RNNs) on a challenging nonlinear BCI problem: decoding continuous bimanual movement of two computer cursors. Surprisingly, we found that although RNNs appeared to perform well in offline settings, they did so by overfitting to the temporal structure of the training data and failed to generalize to real-time neuroprosthetic control. In response, we developed a method that alters the temporal structure of the training data by dilating/compressing it in time and re-ordering it, which we show helps RNNs successfully generalize to the online setting. With this method, we demonstrate that a person with paralysis can control two computer cursors simultaneously, far outperforming standard linear methods. Our results provide evidence that preventing models from overfitting to temporal structure in training data may, in principle, aid in translating deep learning advances to the BCI setting, unlocking improved performance for challenging applications.
    Language English
    Publishing date 2023-04-21
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.04.21.537581
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: A real-time, high-performance brain-computer interface for finger decoding and quadcopter control.

    Willsey, Matthew S / Shah, Nishal P / Avansino, Donald T / Hahn, Nick V / Jamiolkowski, Ryan M / Kamdar, Foram B / Hochberg, Leigh R / Willett, Francis R / Henderson, Jaimie M

    bioRxiv : the preprint server for biology

    2024  

    Abstract: People with paralysis express unmet needs for peer support, leisure activities, and sporting activities. Many within the general population rely on social media and massively multiplayer video games to address these needs. We developed a high-performance ...

    Abstract People with paralysis express unmet needs for peer support, leisure activities, and sporting activities. Many within the general population rely on social media and massively multiplayer video games to address these needs. We developed a high-performance finger brain-computer-interface system allowing continuous control of 3 independent finger groups with 2D thumb movements. The system was tested in a human research participant over sequential trials requiring fingers to reach and hold on targets, with an average acquisition rate of 76 targets/minute and completion time of 1.58 ± 0.06 seconds. Performance compared favorably to previous animal studies, despite a 2-fold increase in the decoded degrees-of-freedom (DOF). Finger positions were then used for 4-DOF velocity control of a virtual quadcopter, demonstrating functionality over both fixed and random obstacle courses. This approach shows promise for controlling multiple-DOF end-effectors, such as robotic fingers or digital interfaces for work, entertainment, and socialization.
    Language English
    Publishing date 2024-02-08
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.02.06.578107
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: An Individualized Tractography Pipeline for the Nucleus Basalis of Meynert Lateral Tract.

    Crockett, Rachel A / Wilkins, Kevin B / Zeineh, Michael M / McNab, Jennifer A / Henderson, Jaimie M / Buch, Vivek P / Brontë-Stewart, Helen M

    medRxiv : the preprint server for health sciences

    2023  

    Abstract: Background: At the center of the cortical cholinergic network, the nucleus basalis of Meynert (NBM) is crucial for the cognitive domains most vulnerable in PD. Preclinical evidence has demonstrated the positive impact of NBM deep brain stimulation (DBS) ...

    Abstract Background: At the center of the cortical cholinergic network, the nucleus basalis of Meynert (NBM) is crucial for the cognitive domains most vulnerable in PD. Preclinical evidence has demonstrated the positive impact of NBM deep brain stimulation (DBS) on cognition but early human trials have had mixed results. It is possible that DBS of the lateral NBM efferent white matter fiber bundle may be more effective at improving cognitive-motor function. However, precise tractography modelling is required to identify the optimal target for neurosurgical planning. Individualized tractography approaches have been shown to be highly effective for accurately identifying DBS targets but have yet to be developed for the NBM.
    Methods: Using structural and diffusion weighted imaging, we developed a tractography pipeline for precise individualized identification of the lateral NBM target tract. Using dice similarity coefficients, the reliability of the tractography outputs was assessed across three cohorts to investigate: 1) whether this manual pipeline is more reliable than an existing automated pipeline currently used in the literature; 2) the inter- and intra-rater reliability of our pipeline in research scans of patients with PD; and 3) the reliability and practicality of this pipeline in clinical scans of DBS patients.
    Results: The individualized manual pipeline was found to be significantly more reliable than the existing automated pipeline for both the segmentation of the NBM region itself (p<0.001) and the reconstruction of the target lateral tract (p=0.002). There was also no significant difference between the reliability of two different raters in the PD cohort (p=0.25), which showed high inter- (mean Dice coefficient >0.6) and intra-rater (mean Dice coefficient >0.7) reliability across runs. Finally, the pipeline was shown to be highly reliable within the clinical scans (mean Dice coefficient = 0.77). However, accurate reconstruction was only evident in 7/10 tracts.
    Conclusion: We have developed a reliable tractography pipeline for the identification and analysis of the NBM lateral tract in research and clinical grade imaging of healthy young adult and PD patient scans.
    Language English
    Publishing date 2023-09-01
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.08.31.23294922
    Database MEDical Literature Analysis and Retrieval System OnLINE

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