The evolution of neuromodulation for chronic stroke: From neuroplasticity mechanisms to brain-computer interfaces

被引:8
|
作者
Saway, Brian F. [1 ]
Palmer, Charles [2 ]
Hughes, Christopher [3 ]
Triano, Matthew [1 ]
Suresh, Rishishankar E. [4 ]
Gilmore, Jordon [5 ]
George, Mark [2 ,8 ]
Kautz, Steven A. [6 ,8 ]
Rowland, Nathan C. [1 ,7 ]
机构
[1] Med Univ South Carolina, Dept Neurosurg, Charleston, SC 29425 USA
[2] Med Univ South Carolina, Dept Psychiat, Charleston, SC 29425 USA
[3] Univ Pittsburgh, Dept Bioengn, Pittsburgh, PA 15260 USA
[4] Med Univ South Carolina, Coll Med, Charleston, SC 29425 USA
[5] Clemson Univ, Dept Bioengn, Clemson, SC 29634 USA
[6] Med Univ South Carolina, Dept Hlth Sci & Res, Charleston, SC 29425 USA
[7] Med Univ South Carolina, MUSC Inst Neurosci Discovery MIND, Charleston, SC 29425 USA
[8] Ralph H Johnson VA Hlth Care Syst, Charleston 29425, SC USA
关键词
Chronic stroke; Motor recovery; Vagus nerve stimulation; Deep brain stimulation; Brain-computer interface; VAGUS NERVE-STIMULATION; LOCUS-COERULEUS; ELECTRICAL-STIMULATION; NEURAL ACTIVITY; MOTOR FUNCTION; REHABILITATION; RECOVERY; CORTEX; EEG; COMMUNICATION;
D O I
10.1016/j.neurot.2024.e00337
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Stroke is one of the most common and debilitating neurological conditions worldwide. Those who survive experience motor, sensory, speech, vision, and/or cognitive deficits that severely limit remaining quality of life. While rehabilitation programs can help improve patients' symptoms, recovery is often limited, and patients frequently continue to experience impairments in functional status. In this review, invasive neuromodulation techniques to augment the effects of conventional rehabilitation methods are described, including vagus nerve stimulation (VNS), deep brain stimulation (DBS) and brain-computer interfaces (BCIs). In addition, the evidence base for each of these techniques, pivotal trials, and future directions are explored. Finally, emerging technologies such as functional near-infrared spectroscopy (fNIRS) and the shift to artificial intelligence-enabled implants and wearables are examined. While the field of implantable devices for chronic stroke recovery is still in a nascent stage, the data reviewed are suggestive of immense potential for reducing the impact and impairment from this globally prevalent disorder.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Investigating the synergistic neuromodulation effect of bilateral rTMS and VR brain-computer interfaces training in chronic stroke patients
    Afonso, Monica
    Sanchez-Cuesta, Francisco
    Gonzalez-Zamorano, Yeray
    Romero, Juan Pablo
    Vourvopoulos, Athanasios
    JOURNAL OF NEURAL ENGINEERING, 2024, 21 (05)
  • [2] Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface
    Mrachacz-Kersting, Natalie
    Jiang, Ning
    Stevenson, Andrew James Thomas
    Niazi, Imran Khan
    Kostic, Vladimir
    Pavlovic, Aleksandra
    Radovanovic, Sasa
    Djuric-Jovicic, Milica
    Agosta, Federica
    Dremstrup, Kim
    Farina, Dario
    JOURNAL OF NEUROPHYSIOLOGY, 2016, 115 (03) : 1410 - 1421
  • [3] Brain-computer interfaces in the completely locked-in state and chronic stroke
    Chaudhary, U.
    Birbaumer, N.
    Ramos-Murguialday, A.
    BRAIN-COMPUTER INTERFACES: LAB EXPERIMENTS TO REAL-WORLD APPLICATIONS, 2016, 228 : 131 - 161
  • [4] Editorial: Artificial intelligence in brain-computer interfaces and neuroimaging for neuromodulation and neurofeedback
    Ponce, Hiram
    Martinez-Villasenor, Lourdes
    Chen, Yinong
    FRONTIERS IN NEUROSCIENCE, 2022, 16
  • [5] Exploring the Use of Brain-Computer Interfaces in Stroke Neurorehabilitation
    Yang, Siyu
    Li, Ruobing
    Li, Hongtao
    Xu, Ke
    Shi, Yuqing
    Wang, Qingyong
    Yang, Tiansong
    Sun, Xiaowei
    BIOMED RESEARCH INTERNATIONAL, 2021, 2021
  • [6] Engineering new treatments for stroke with brain-computer interfaces
    Leuthardt, Eric C.
    FUTURE NEUROLOGY, 2009, 4 (02) : 133 - 136
  • [7] Brain-computer interfaces
    Sajda, Paul
    Mueller, Klaus-Robert
    Shenoy, Krishna V.
    IEEE SIGNAL PROCESSING MAGAZINE, 2008, 25 (01) : 16 - 17
  • [8] Towards an Autonomous Brain-Computer Interface for Chronic Stroke Neuromodulation: The Importance of Gamma Power in Movement Classification
    Suresh, Rishi
    Salazar, Claudia
    Triano, Matthew
    Rowland, Nathan Christopher
    NEUROSURGERY, 2025, 71 : 212 - 212
  • [9] Brain-Computer Integration: A Framework for the Design of Brain-Computer Interfaces from an Integrations Perspective
    Semertzidis, Nathan
    Zambetta, Fabio
    Mueller, Florian Floyd
    ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, 2023, 30 (06)
  • [10] FROM COCHLEAR IMPLANTS TO BRAIN-COMPUTER INTERFACES
    Tadeusiewicz, Ryszard
    Rotter, Pawel
    BIO-ALGORITHMS AND MED-SYSTEMS, 2012, 8 (03) : 267 - 286