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Hong Y, Ryun S, Chung CK. Evoking artificial speech perception through invasive brain stimulation for brain-computer interfaces: current challenges and future perspectives. Front Neurosci 2024; 18:1428256. [PMID: 38988764 PMCID: PMC11234843 DOI: 10.3389/fnins.2024.1428256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 06/10/2024] [Indexed: 07/12/2024] Open
Abstract
Encoding artificial perceptions through brain stimulation, especially that of higher cognitive functions such as speech perception, is one of the most formidable challenges in brain-computer interfaces (BCI). Brain stimulation has been used for functional mapping in clinical practices for the last 70 years to treat various disorders affecting the nervous system, including epilepsy, Parkinson's disease, essential tremors, and dystonia. Recently, direct electrical stimulation has been used to evoke various forms of perception in humans, ranging from sensorimotor, auditory, and visual to speech cognition. Successfully evoking and fine-tuning artificial perceptions could revolutionize communication for individuals with speech disorders and significantly enhance the capabilities of brain-computer interface technologies. However, despite the extensive literature on encoding various perceptions and the rising popularity of speech BCIs, inducing artificial speech perception is still largely unexplored, and its potential has yet to be determined. In this paper, we examine the various stimulation techniques used to evoke complex percepts and the target brain areas for the input of speech-like information. Finally, we discuss strategies to address the challenges of speech encoding and discuss the prospects of these approaches.
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Affiliation(s)
- Yirye Hong
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Seokyun Ryun
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Chun Kee Chung
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Republic of Korea
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2
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Ji B, Sun F, Guo J, Zhou Y, You X, Fan Y, Wang L, Xu M, Zeng W, Liu J, Wang M, Hu H, Chang H. Brainmask: an ultrasoft and moist micro-electrocorticography electrode for accurate positioning and long-lasting recordings. MICROSYSTEMS & NANOENGINEERING 2023; 9:126. [PMID: 37829160 PMCID: PMC10564857 DOI: 10.1038/s41378-023-00597-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/11/2023] [Accepted: 09/02/2023] [Indexed: 10/14/2023]
Abstract
Bacterial cellulose (BC), a natural biomaterial synthesized by bacteria, has a unique structure of a cellulose nanofiber-weaved three-dimensional reticulated network. BC films can be ultrasoft with sufficient mechanical strength, strong water absorption and moisture retention and have been widely used in facial masks. These films have the potential to be applied to implantable neural interfaces due to their conformality and moisture, which are two critical issues for traditional polymer or silicone electrodes. In this work, we propose a micro-electrocorticography (micro-ECoG) electrode named "Brainmask", which comprises a BC film as the substrate and separated multichannel parylene-C microelectrodes bonded on the top surface. Brainmask can not only guarantee the precise position of microelectrode sites attached to any nonplanar epidural surface but also improve the long-lasting signal quality during acute implantation with an exposed cranial window for at least one hour, as well as the in vivo recording validated for one week. This novel ultrasoft and moist device stands as a next-generation neural interface regardless of complex surface or time of duration.
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Affiliation(s)
- Bowen Ji
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, 710072 China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
- Collaborative Innovation Center of Northwestern Polytechnical University, Shanghai, 201108 China
| | - Fanqi Sun
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, 710072 China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
- Collaborative Innovation Center of Northwestern Polytechnical University, Shanghai, 201108 China
| | - Jiecheng Guo
- Institute of Medical Research, Northwestern Polytechnical University, Xi’an, 710072 China
| | - Yuhao Zhou
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, 710072 China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
- Collaborative Innovation Center of Northwestern Polytechnical University, Shanghai, 201108 China
| | - Xiaoli You
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an, 710072 China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
- Collaborative Innovation Center of Northwestern Polytechnical University, Shanghai, 201108 China
| | - Ye Fan
- College of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018 China
| | - Longchun Wang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Mengfei Xu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Wen Zeng
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
| | - Jingquan Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Minghao Wang
- College of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018 China
| | - Huijing Hu
- Institute of Medical Research, Northwestern Polytechnical University, Xi’an, 710072 China
| | - Honglong Chang
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, 710072 China
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Lim J, Wang PT, Bashford L, Kellis S, Shaw SJ, Gong H, Armacost M, Heydari P, Do AH, Andersen RA, Liu CY, Nenadic Z. Suppression of cortical electrostimulation artifacts using pre-whitening and null projection. J Neural Eng 2023; 20:056018. [PMID: 37666246 DOI: 10.1088/1741-2552/acf68b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 09/04/2023] [Indexed: 09/06/2023]
Abstract
Objective.Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers. While front-end hardware techniques can alleviate this problem, residual artifacts generally persist and must be suppressed by back-end methods.Approach.We have developed a technique based on pre-whitening and null projection (PWNP) and tested its ability to suppress stimulation artifacts in electroencephalogram (EEG), electrocorticogram (ECoG) and microelectrode array (MEA) signals from five human subjects.Main results.In EEG signals contaminated by narrow-band stimulation artifacts, the PWNP method achieved average artifact suppression between 32 and 34 dB, as measured by an increase in signal-to-interference ratio. In ECoG and MEA signals contaminated by broadband stimulation artifacts, our method suppressed artifacts by 78%-80% and 85%, respectively, as measured by a reduction in interference index. When compared to independent component analysis, which is considered the state-of-the-art technique for artifact suppression, our method achieved superior results, while being significantly easier to implement.Significance.PWNP can potentially act as an efficient method of artifact suppression to enable simultaneous stimulation and recording in bi-directional BCIs to biomimetically restore motor function.
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Affiliation(s)
- Jeffrey Lim
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
| | - Po T Wang
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
| | - Luke Bashford
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
| | - Spencer Kellis
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
- Department of Neurological Surgery, Keck School of Medicine of University of Southern California (USC), Los Angeles, CA 90033, United States of America
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Susan J Shaw
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Hui Gong
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Michelle Armacost
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
| | - Payam Heydari
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
- Department of Electrical Engineering and Computer Science, UCI, Irvine, CA 92697, United States of America
| | - An H Do
- Department of Neurology, UCI, Irvine, CA 92697, United States of America
| | - Richard A Andersen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States of America
| | - Charles Y Liu
- Department of Neurological Surgery, Keck School of Medicine of University of Southern California (USC), Los Angeles, CA 90033, United States of America
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA 90033, United States of America
- Department of Neurosurgery, Rancho Los Amigos National Rehabilitation Center, Downey, CA 90242, United States of America
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America
- Department of Electrical Engineering and Computer Science, UCI, Irvine, CA 92697, United States of America
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Yoo KS. Motion prediction using brain waves based on artificial intelligence deep learning recurrent neural network. J Exerc Rehabil 2023; 19:219-227. [PMID: 37662525 PMCID: PMC10468292 DOI: 10.12965/jer.2346242.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 07/10/2023] [Indexed: 09/05/2023] Open
Abstract
Electroencephalogram (EEG) research has gained widespread use in various research domains due to its valuable insights into human body movements. In this study, we investigated the optimization of motion discrimination prediction by employing an artificial intelligence deep learning recurrent neural network (gated recurrent unit, GRU) on unique EEG data generated from specific movement types among EEG signals. The experiment involved participants categorized into five difficulty levels of postural control, targeting gymnasts in their twenties and college students majoring in physical education (n=10). Machine learning techniques were applied to extract brain-motor patterns from the collected EEG data, which consisted of 32 channels. The EEG data underwent spectrum analysis using fast Fourier transform conversion, and the GRU model network was utilized for machine learning on each EEG frequency domain, thereby improving the performance index of the learning operation process. Through the development of the GRU network algorithm, the performance index achieved up to a 15.92% improvement compared to the accuracy of existing models, resulting in motion recognition accuracy ranging from a minimum of 94.67% to a maximum of 99.15% between actual and predicted values. These optimization outcomes are attributed to the enhanced accuracy and cost function of the GRU network algorithm's hidden layers. By implementing motion identification optimization based on artificial intelligence machine learning results from EEG signals, this study contributes to the emerging field of exercise rehabilitation, presenting an innovative paradigm that reveals the interconnectedness between the brain and the science of exercise.
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Affiliation(s)
- Kyoung-Seok Yoo
- Department of Sport Sciences, Hannam University, Daejeon,
Korea
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Ryun S, Kim M, Kim JS, Chung CK. Cortical maps of somatosensory perception in human. Neuroimage 2023; 276:120197. [PMID: 37245558 DOI: 10.1016/j.neuroimage.2023.120197] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 05/05/2023] [Accepted: 05/25/2023] [Indexed: 05/30/2023] Open
Abstract
Tactile and movement-related somatosensory perceptions are crucial for our daily lives and survival. Although the primary somatosensory cortex is thought to be the key structure of somatosensory perception, various cortical downstream areas are also involved in somatosensory perceptual processing. However, little is known about whether cortical networks of these downstream areas can be dissociated depending on each perception, especially in human. We address this issue by combining data from direct cortical stimulation (DCS) for eliciting somatosensation and data from high-gamma band (HG) elicited during tactile stimulation and movement tasks. We found that artificial somatosensory perception is elicited not only from conventional somatosensory-related areas such as the primary and secondary somatosensory cortices but also from a widespread network including superior/inferior parietal lobules and premotor cortex. Interestingly, DCS on the dorsal part of the fronto-parietal area including superior parietal lobule and dorsal premotor cortex often induces movement-related somatosensations, whereas that on the ventral one including inferior parietal lobule and ventral premotor cortex generally elicits tactile sensations. Furthermore, the HG mapping results of the movement and passive tactile stimulation tasks revealed considerable similarity in the spatial distribution between the HG and DCS functional maps. Our findings showed that macroscopic neural processing for tactile and movement-related perceptions could be segregated.
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Affiliation(s)
- Seokyun Ryun
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea
| | - Minkyu Kim
- Department of Cognitive Sciences, University of California Irvine, Irvine, USA
| | - June Sic Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Chun Kee Chung
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea; Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea; Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea.
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Sohn WJ, Lim J, Wang PT, Pu H, Malekzadeh-Arasteh O, Shaw SJ, Armacost M, Gong H, Kellis S, Andersen RA, Liu CY, Heydari P, Nenadic Z, Do AH. Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research. Front Neurosci 2023; 16:1075971. [PMID: 36711153 PMCID: PMC9878125 DOI: 10.3389/fnins.2022.1075971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/16/2022] [Indexed: 01/15/2023] Open
Abstract
Introduction Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Methods A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system. Results The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R 2 > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R 2 > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses. Significance This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems.
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Affiliation(s)
- Won Joon Sohn
- Department of Neurology, University of California, Irvine, Irvine, CA, United States,*Correspondence: Won Joon Sohn ✉
| | - Jeffrey Lim
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Po T. Wang
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Haoran Pu
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Omid Malekzadeh-Arasteh
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Susan J. Shaw
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States,Department of Neurology, University of Southern California, Los Angeles, CA, United States
| | - Michelle Armacost
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States,Department of Neurology, University of Southern California, Los Angeles, CA, United States
| | - Hui Gong
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States,Department of Neurology, University of Southern California, Los Angeles, CA, United States
| | - Spencer Kellis
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
| | - Richard A. Andersen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
| | - Charles Y. Liu
- Department of Neurosurgery, Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States,Department of Neurological Surgery, University of Southern California, Los Angeles, CA, United States
| | - Payam Heydari
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States,Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - An H. Do
- Department of Neurology, University of California, Irvine, Irvine, CA, United States,An H. Do ✉
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Gupta A, Vardalakis N, Wagner FB. Neuroprosthetics: from sensorimotor to cognitive disorders. Commun Biol 2023; 6:14. [PMID: 36609559 PMCID: PMC9823108 DOI: 10.1038/s42003-022-04390-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/19/2022] [Indexed: 01/07/2023] Open
Abstract
Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.
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Affiliation(s)
- Ankur Gupta
- grid.462010.1Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
| | | | - Fabien B. Wagner
- grid.462010.1Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
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Serrano-Amenos C, Heydari P, Liu CY, Do AH, Nenadic Z. Power Budget of a Skull Unit in a Fully-Implantable Brain-Computer Interface: Bio-Heat Model. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4029-4039. [PMID: 37856256 DOI: 10.1109/tnsre.2023.3323916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
The aim of this study is to estimate the maximum power consumption that guarantees the thermal safety of a skull unit (SU). The SU is part of a fully-implantable bi-directional brain computer-interface (BD-BCI) system that aims to restore walking and leg sensation to those with spinal cord injury (SCI). To estimate the SU power budget, we created a bio-heat model using the finite element method (FEM) implemented in COMSOL. To ensure that our predictions were robust against the natural variation of the model's parameters, we also performed a sensitivity analysis. Based on our simulations, we estimated that the SU can nominally consume up to 70 mW of power without raising the surrounding tissues' temperature above the thermal safety threshold of 1°C. When considering the natural variation of the model's parameters, we estimated that the power budget could range between 47 and 81 mW. This power budget should be sufficient to power the basic operations of the SU, including amplification, serialization and A/D conversion of the neural signals, as well as control of cortical stimulation. Determining the power budget is an important specification for the design of the SU and, in turn, the design of a fully-implantable BD-BCI system.
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Obara K, Kaneshige M, Suzuki M, Yokoyama O, Tazoe T, Nishimura Y. Corticospinal interface to restore voluntary control of joint torque in a paralyzed forearm following spinal cord injury in non-human primates. Front Neurosci 2023; 17:1127095. [PMID: 36960166 PMCID: PMC10028188 DOI: 10.3389/fnins.2023.1127095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 01/23/2023] [Indexed: 03/09/2023] Open
Abstract
The corticospinal tract plays a major role in the control of voluntary limb movements, and its damage impedes voluntary limb control. We investigated the feasibility of closed-loop brain-controlled subdural spinal stimulation through a corticospinal interface for the modulation of wrist torque in the paralyzed forearm of monkeys with spinal cord injury at C4/C5. Subdural spinal stimulation of the preserved cervical enlargement activated multiple muscles on the paralyzed forearm and wrist torque in the range from flexion to ulnar-flexion. The magnitude of the evoked torque could be modulated by changing current intensity. We then employed the corticospinal interface designed to detect the firing rate of an arbitrarily selected "linked neuron" in the forearm territory of the primary motor cortex (M1) and convert it in real time to activity-contingent electrical stimulation of a spinal site caudal to the lesion. Linked neurons showed task-related activity that modulated the magnitude of the evoked torque and the activation of multiple muscles depending on the required torque. Unlinked neurons, which were independent of spinal stimulation and located in the vicinity of the linked neurons, exhibited task-related or -unrelated activity. Thus, monkeys were able to modulate the wrist torque of the paralyzed forearm by modulating the firing rate of M1 neurons including unlinked and linked neurons via the corticospinal interface. These results suggest that the corticospinal interface can replace the function of the corticospinal tract after spinal cord injury.
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Affiliation(s)
- Kei Obara
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Division of Neural Engineering, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Miki Kaneshige
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Michiaki Suzuki
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Osamu Yokoyama
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Toshiki Tazoe
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Yukio Nishimura
- Neural Prosthetics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Division of Neural Engineering, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
- *Correspondence: Yukio Nishimura,
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Lim J, Wang PT, Shaw SJ, Gong H, Armacost M, Liu CY, Do AH, Heydari P, Nenadic Z. Artifact propagation in subdural cortical electrostimulation: Characterization and modeling. Front Neurosci 2022; 16:1021097. [PMID: 36312030 PMCID: PMC9596776 DOI: 10.3389/fnins.2022.1021097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/21/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 μV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.
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Affiliation(s)
- Jeffrey Lim
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Jeffrey Lim
| | - Po T. Wang
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Susan J. Shaw
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Hui Gong
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Michelle Armacost
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Charles Y. Liu
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - An H. Do
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Payam Heydari
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
- Zoran Nenadic
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Andersen RA, Aflalo T. Preserved cortical somatotopic and motor representations in tetraplegic humans. Curr Opin Neurobiol 2022; 74:102547. [DOI: 10.1016/j.conb.2022.102547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 03/16/2022] [Accepted: 03/27/2022] [Indexed: 11/16/2022]
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Heng W, Solomon S, Gao W. Flexible Electronics and Devices as Human-Machine Interfaces for Medical Robotics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2107902. [PMID: 34897836 PMCID: PMC9035141 DOI: 10.1002/adma.202107902] [Citation(s) in RCA: 107] [Impact Index Per Article: 53.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/08/2021] [Indexed: 05/02/2023]
Abstract
Medical robots are invaluable players in non-pharmaceutical treatment of disabilities. Particularly, using prosthetic and rehabilitation devices with human-machine interfaces can greatly improve the quality of life for impaired patients. In recent years, flexible electronic interfaces and soft robotics have attracted tremendous attention in this field due to their high biocompatibility, functionality, conformability, and low-cost. Flexible human-machine interfaces on soft robotics will make a promising alternative to conventional rigid devices, which can potentially revolutionize the paradigm and future direction of medical robotics in terms of rehabilitation feedback and user experience. In this review, the fundamental components of the materials, structures, and mechanisms in flexible human-machine interfaces are summarized by recent and renowned applications in five primary areas: physical and chemical sensing, physiological recording, information processing and communication, soft robotic actuation, and feedback stimulation. This review further concludes by discussing the outlook and current challenges of these technologies as a human-machine interface in medical robotics.
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Affiliation(s)
- Wenzheng Heng
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Samuel Solomon
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
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13
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Xiang W, Xie Y, Han Y, Long Z, Zhang W, Zhong T, Liang S, Xing L, Xue X, Zhan Y. A self-powered wearable brain-machine-interface system for ceasing action. NANOSCALE 2022; 14:4671-4678. [PMID: 35262127 DOI: 10.1039/d1nr08168c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A self-powered wearable brain-machine-interface system with pulse detection and brain stimulation for ceasing action has been realized. The system is composed of (1) a power supply unit that employs a piezoelectric generator and converts the mechanical energy of human daily activities into electricity; (2) a neck pulse biosensor that allows continuous measurements of carotid pulse by using a piezoelectric polyvinylidene fluoride film; (3) a data analysis module that enables a coordinated brain-machine-interface system to output brain stimulation signals; and (4) brain stimulating electrodes linked to the brain that implement behavioral intervention. Demonstration of the system with stimulating electrodes implanted in the periaqueductal gray (PAG) in running mice reveals the great effect of forced ceasing action. The mice stop their running within several seconds when the stimulation signals are sent into the PAG brain region (inducing fear). This self-powered scheme for neural stimulation realizes specific behavioral intervention without any external power supply, thus providing a new concept for future behavior intervention.
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Affiliation(s)
- Wang Xiang
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Yan Xie
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yechao Han
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Key Laboratory of Translational Research for Brain Diseases, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Zhihe Long
- Department of Mechanical Engineering, City University of Hong Kong, Hong Kong 999077, China
| | - Wanglinhan Zhang
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Tianyan Zhong
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Shan Liang
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Lili Xing
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Xinyu Xue
- School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Yang Zhan
- CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Key Laboratory of Translational Research for Brain Diseases, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
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14
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Zhang J, Hao M, Yang F, Liang W, Sun A, Chou CH, Lan N. Evaluation of multiple perceptual qualities of transcutaneous electrical nerve stimulation for evoked tactile sensation in forearm amputees. J Neural Eng 2022; 19. [PMID: 35320789 DOI: 10.1088/1741-2552/ac6062] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 03/23/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Evoked tactile sensation (ETS) elicited by transcutaneous electrical nerve stimulation (TENS) is promising to convey digit-specific sensory information to amputees naturally and non-invasively. Fitting ETS-based sensory feedback to amputees entails customizing coding of multiple sensory information for each stimulation site. This study was to elucidate the consistency of percepts and qualities by TENS at multiple stimulation sites in amputees retaining ETS. APPROACH Five transradial amputees with ETS and fourteen able-bodied subjects participated in this study. Surface electrodes with small size (10 mm in diameter) were adopted to fit the restricted projected finger map on the forearm stump of amputees. Effects of stimulus frequency on sensory types were assessed, and the map of perceptual threshold for each sensation was characterized. Sensitivity for vibration and buzz sensations was measured using distinguishable difference in stimulus pulse width. Rapid assessments for modulation ranges of pulse width at fixed amplitude and frequency were developed for coding sensory information. Buzz sensation was demonstrated for location discrimination relating to prosthetic fingers. MAIN RESULTS Vibration and buzz sensations were consistently evoked at 20 Hz and 50 Hz as dominant sensation types in all amputees and able-bodied subjects. Perceptual thresholds of different sensations followed a similar strength-duration curve relating stimulus amplitude to pulse width. The averaged distinguishable difference in pulse width was 12.84 ± 7.23 μs for vibration and 15.21 ± 6.47 μs for buzz in able-bodied subjects, and 14.91 ± 10.54 μs for vibration and 11.30 ± 3.42 μs for buzz in amputees. Buzz coding strategy enabled five amputees to discriminate contact of individual fingers with an overall accuracy of 77.85%. SIGNIFICANCE The consistency in perceptual qualities of dominant sensations can be exploited for coding multi-modality sensory feedback. A fast protocol of sensory coding is possible for fitting ETS-based, non-invasive sensory feedback to amputees.
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Affiliation(s)
- Jie Zhang
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 404 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Manzhao Hao
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 401 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Fei Yang
- Shanghai Jiao Tong University, Room 404 South Building Med-X, No. 1954 Rd. Huashan, Xuhui, Shanghai, Shanghai, 200030, CHINA
| | - Wenyuan Liang
- National Research Center for Rehabilitation Technical Aids, No.1 Rong Hua Zhong Road, Beijing Economic and Technological Development Area, Beijing, Beijing, 100176, CHINA
| | - Aiping Sun
- National Research Center for Rehabilitation Technical Aids, No.1 Rong Hua Zhong Road, Beijing Economic and Technological Development Area, Beijing, Beijing, 100176, CHINA
| | - Chi-Hong Chou
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 401 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Ning Lan
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 405 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
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15
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Fifer MS, McMullen DP, Osborn LE, Thomas TM, Christie B, Nickl RW, Candrea DN, Pohlmeyer EA, Thompson MC, Anaya MA, Schellekens W, Ramsey NF, Bensmaia SJ, Anderson WS, Wester BA, Crone NE, Celnik PA, Cantarero GL, Tenore FV. Intracortical Somatosensory Stimulation to Elicit Fingertip Sensations in an Individual With Spinal Cord Injury. Neurology 2022; 98:e679-e687. [PMID: 34880087 PMCID: PMC8865889 DOI: 10.1212/wnl.0000000000013173] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/19/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The restoration of touch to fingers and fingertips is critical to achieving dexterous neuroprosthetic control for individuals with sensorimotor dysfunction. However, localized fingertip sensations have not been evoked via intracortical microstimulation (ICMS). METHODS Using a novel intraoperative mapping approach, we implanted electrode arrays in the finger areas of left and right somatosensory cortex and delivered ICMS over a 2-year period in a human participant with spinal cord injury. RESULTS Stimulation evoked tactile sensations in 8 fingers, including fingertips, spanning both hands. Evoked percepts followed expected somatotopic arrangements. The subject was able to reliably identify up to 7 finger-specific sites spanning both hands in a finger discrimination task. The size of the evoked percepts was on average 33% larger than a finger pad, as assessed via manual markings of a hand image. The size of the evoked percepts increased modestly with increased stimulation intensity, growing 21% as pulse amplitude increased from 20 to 80 µA. Detection thresholds were estimated on a subset of electrodes, with estimates of 9.2 to 35 µA observed, roughly consistent with prior studies. DISCUSSION These results suggest that ICMS can enable the delivery of consistent and localized fingertip sensations during object manipulation by neuroprostheses for individuals with somatosensory deficits. CLINICALTRIALSGOV IDENTIFIER NCT03161067.
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Affiliation(s)
- Matthew S Fifer
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL.
| | - David P McMullen
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Luke E Osborn
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Tessy M Thomas
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Breanne Christie
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Robert W Nickl
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Daniel N Candrea
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Eric A Pohlmeyer
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Margaret C Thompson
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Manuel A Anaya
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Wouter Schellekens
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Nick F Ramsey
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Sliman J Bensmaia
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - William S Anderson
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Brock A Wester
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Nathan E Crone
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Pablo A Celnik
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Gabriela L Cantarero
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Francesco V Tenore
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
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16
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Huggins JE, Krusienski D, Vansteensel MJ, Valeriani D, Thelen A, Stavisky S, Norton JJS, Nijholt A, Müller-Putz G, Kosmyna N, Korczowski L, Kapeller C, Herff C, Halder S, Guger C, Grosse-Wentrup M, Gaunt R, Dusang AN, Clisson P, Chavarriaga R, Anderson CW, Allison BZ, Aksenova T, Aarnoutse E. Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier. BRAIN-COMPUTER INTERFACES 2022; 9:69-101. [PMID: 36908334 PMCID: PMC9997957 DOI: 10.1080/2326263x.2021.2009654] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/15/2021] [Indexed: 12/11/2022]
Abstract
The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.
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Affiliation(s)
- Jane E Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744, 734-936-7177
| | - Dean Krusienski
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23219
| | - Mariska J Vansteensel
- UMC Utrecht Brain Center, Dept of Neurosurgery, University Medical Center Utrecht, The Netherlands
| | | | - Antonia Thelen
- eemagine Medical Imaging Solutions GmbH, Berlin, Germany
| | | | - James J S Norton
- National Center for Adaptive Neurotechnologies, US Department of Veterans Affairs, 113 Holland Ave, Albany, NY 12208
| | - Anton Nijholt
- Faculty EEMCS, University of Twente, Enschede, The Netherlands
| | - Gernot Müller-Putz
- Institute of Neural Engineering, GrazBCI Lab, Graz University of Technology, Stremayrgasse 16/4, 8010 Graz, Austria
| | - Nataliya Kosmyna
- Massachusetts Institute of Technology (MIT), Media Lab, E14-548, Cambridge, MA 02139, Unites States
| | | | | | - Christian Herff
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Christoph Guger
- g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria, +43725122240-0
| | - Moritz Grosse-Wentrup
- Research Group Neuroinformatics, Faculty of Computer Science, Vienna Cognitive Science Hub, Data Science @ Uni Vienna University of Vienna
| | - Robert Gaunt
- Rehab Neural Engineering Labs, Department of Physical Medicine and Rehabilitation, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA, 3520 5th Ave, Suite 300, Pittsburgh, PA 15213, 412-383-1426
| | - Aliceson Nicole Dusang
- Department of Electrical and Computer Engineering, School of Engineering, Brown University, Carney Institute for Brain Science, Brown University, Providence, RI
- Department of Veterans Affairs Medical Center, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence, RI
- Center for Neurotechnology and Neurorecovery, Neurology, Massachusetts General Hospital, Boston, MA
| | | | - Ricardo Chavarriaga
- IEEE Standards Association Industry Connections group on neurotechnologies for brain-machine interface, Center for Artificial Intelligence, School of Engineering, ZHAW-Zurich University of Applied Sciences, Switzerland, Switzerland
| | - Charles W Anderson
- Department of Computer Science, Molecular, Cellular and Integrative Neurosience Program, Colorado State University, Fort Collins, CO 80523
| | - Brendan Z Allison
- Dept. of Cognitive Science, Mail Code 0515, University of California at San Diego, La Jolla, United States, 619-534-9754
| | - Tetiana Aksenova
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Erik Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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17
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Valle G, Iberite F, Strauss I, D'Anna E, Granata G, Di Iorio R, Stieglitz T, Raspopovic S, Petrini FM, Rossini PM, Micera S. A Psychometric Platform to Collect Somatosensory Sensations for Neuroprosthetic Use. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 3:619280. [PMID: 35047903 PMCID: PMC8757828 DOI: 10.3389/fmedt.2021.619280] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 02/08/2021] [Indexed: 11/13/2022] Open
Abstract
Somatosensory neuroprostheses exploit invasive and non-invasive feedback technologies to restore sensorimotor functions lost to disease or trauma. These devices use electrical stimulation to communicate sensory information to the brain. A sensation characterization procedure is thus necessary to determine the appropriate stimulation parameters and to establish a clear personalized map of the sensations that can be restored. Several questionnaires have been described in the literature to collect the quality, type, location, and intensity of the evoked sensations, but there is still no standard psychometric platform. Here, we propose a new psychometric system containing previously validated questionnaires on evoked sensations, which can be applied to any kind of somatosensory neuroprosthesis. The platform collects stimulation parameters used to elicit sensations and records subjects' percepts in terms of sensation location, type, quality, perceptual threshold, and intensity. It further collects data using standardized assessment questionnaires and scales, performs measurements over time, and collects phantom limb pain syndrome data. The psychometric platform is user-friendly and provides clinicians with all the information needed to assess the sensory feedback. The psychometric platform was validated with three trans-radial amputees. The platform was used to assess intraneural sensory feedback provided through implanted peripheral nerve interfaces. The proposed platform could act as a new standardized assessment toolbox to homogenize the reporting of results obtained with different technologies in the field of somatosensory neuroprosthetics.
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Affiliation(s)
- Giacomo Valle
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | | | - Ivo Strauss
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Edoardo D'Anna
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Institute of Bioengineering, Lausanne, Switzerland
| | - Giuseppe Granata
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Riccardo Di Iorio
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Freiburg, Germany
| | - Stanisa Raspopovic
- Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | - Francesco M Petrini
- Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | - Paolo M Rossini
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Institute of Bioengineering, Lausanne, Switzerland
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18
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Abstract
Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.
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Affiliation(s)
- Richard A Andersen
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, California 90033, USA
| | - Tyson Aflalo
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;
| | - Luke Bashford
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;
| | - David Bjånes
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;
| | - Spencer Kellis
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA;
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, California 90033, USA
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, California 90033, USA
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19
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Foldes ST, Chandrasekaran S, Camerone J, Lowe J, Ramdeo R, Ebersole J, Bouton CE. Case Study: Mapping Evoked Fields in Primary Motor and Sensory Areas via Magnetoencephalography in Tetraplegia. Front Neurol 2021; 12:739693. [PMID: 34630308 PMCID: PMC8497881 DOI: 10.3389/fneur.2021.739693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 08/13/2021] [Indexed: 12/02/2022] Open
Abstract
Devices interfacing with the brain through implantation in cortical or subcortical structures have great potential for restoration and rehabilitation in patients with sensory or motor dysfunction. Typical implantation surgeries are planned based on maps of brain activity generated from intact function. However, mapping brain activity for planning implantation surgeries is challenging in the target population due to abnormal residual function and, increasingly often, existing MRI-incompatible implanted hardware. Here, we present methods and results for mapping impaired somatosensory and motor function in an individual with paralysis and an existing brain–computer interface (BCI) device. Magnetoencephalography (MEG) was used to directly map the neural activity evoked during transcutaneous electrical stimulation and attempted movement of the impaired hand. Evoked fields were found to align with the expected anatomy and somatotopic organization. This approach may be valuable for guiding implants in other applications, such as cortical stimulation for pain and to improve implant targeting to help reduce the craniotomy size.
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Affiliation(s)
- Stephen T Foldes
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Santosh Chandrasekaran
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States
| | - Joseph Camerone
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - James Lowe
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - Richard Ramdeo
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States
| | - John Ebersole
- MEG Center, Overlook Medical Center, Atlantic Health, Summit, NJ, United States
| | - Chad E Bouton
- Neural Bypass and Brain-Computer Interface Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research at Northwell Health, New York, NY, United States.,Department of Molecular Medicine, Hofstra-Northwell Medical School, New York, NY, United States
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20
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Chandrasekaran S, Fifer M, Bickel S, Osborn L, Herrero J, Christie B, Xu J, Murphy RKJ, Singh S, Glasser MF, Collinger JL, Gaunt R, Mehta AD, Schwartz A, Bouton CE. Historical perspectives, challenges, and future directions of implantable brain-computer interfaces for sensorimotor applications. Bioelectron Med 2021; 7:14. [PMID: 34548098 PMCID: PMC8456563 DOI: 10.1186/s42234-021-00076-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 08/29/2021] [Indexed: 11/10/2022] Open
Abstract
Almost 100 years ago experiments involving electrically stimulating and recording from the brain and the body launched new discoveries and debates on how electricity, movement, and thoughts are related. Decades later the development of brain-computer interface technology began, which now targets a wide range of applications. Potential uses include augmentative communication for locked-in patients and restoring sensorimotor function in those who are battling disease or have suffered traumatic injury. Technical and surgical challenges still surround the development of brain-computer technology, however, before it can be widely deployed. In this review we explore these challenges, historical perspectives, and the remarkable achievements of clinical study participants who have bravely forged new paths for future beneficiaries.
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Affiliation(s)
- Santosh Chandrasekaran
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Matthew Fifer
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA
| | - Stephan Bickel
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Neurosurgery, Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA
- Department of Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA
| | - Luke Osborn
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA
| | - Jose Herrero
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Breanne Christie
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA
| | - Junqian Xu
- Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Rory K J Murphy
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, USA
| | - Sandeep Singh
- Good Shepherd Rehabilitation Hospital, Allentown, PA, USA
| | - Matthew F Glasser
- Departments of Radiology and Neuroscience, Washington University in St Louis, Saint Louis, MO, USA
| | - Jennifer L Collinger
- Rehabilitation Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert Gaunt
- Rehabilitation Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashesh D Mehta
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Neurosurgery, Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA
| | - Andrew Schwartz
- McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chad E Bouton
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Department of Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA.
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21
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Chandrasekaran S, Bickel S, Herrero JL, Kim JW, Markowitz N, Espinal E, Bhagat NA, Ramdeo R, Xu J, Glasser MF, Bouton CE, Mehta AD. Evoking highly focal percepts in the fingertips through targeted stimulation of sulcal regions of the brain for sensory restoration. Brain Stimul 2021; 14:1184-1196. [PMID: 34358704 PMCID: PMC8884403 DOI: 10.1016/j.brs.2021.07.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 06/29/2021] [Accepted: 07/19/2021] [Indexed: 01/06/2023] Open
Abstract
Background: Paralysis and neuropathy, affecting millions of people worldwide, can be accompanied by significant loss of somatosensation. With tactile sensation being central to achieving dexterous movement, brain-computer interface (BCI) researchers have used intracortical and cortical surface electrical stimulation to restore somatotopically-relevant sensation to the hand. However, these approaches are restricted to stimulating the gyral areas of the brain. Since representation of distal regions of the hand extends into the sulcal regions of human primary somatosensory cortex (S1), it has been challenging to evoke sensory percepts localized to the fingertips. Objective/hypothesis: Targeted stimulation of sulcal regions of S1, using stereoelectroencephalography (SEEG) depth electrodes, can evoke focal sensory percepts in the fingertips. Methods: Two participants with intractable epilepsy received cortical stimulation both at the gyri via high-density electrocorticography (HD-ECoG) grids and in the sulci via SEEG depth electrode leads. We characterized the evoked sensory percepts localized to the hand. Results: We show that highly focal percepts can be evoked in the fingertips of the hand through sulcal stimulation. fMRI, myelin content, and cortical thickness maps from the Human Connectome Project elucidated specific cortical areas and sub-regions within S1 that evoked these focal percepts. Within-participant comparisons showed that percepts evoked by sulcal stimulation via SEEG electrodes were significantly more focal (80% less area; p = 0.02) and localized to the fingertips more often, than by gyral stimulation via HD-ECoG electrodes. Finally, sulcal locations with consistent modulation of high-frequency neural activity during mechanical tactile stimulation of the fingertips showed the same somatotopic correspondence as cortical stimulation. Conclusions: Our findings indicate minimally invasive sulcal stimulation via SEEG electrodes could be a clinically viable approach to restoring sensation.
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Affiliation(s)
- Santosh Chandrasekaran
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
| | - Stephan Bickel
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Department of Neurosurgery, Northwell, Manhasset, NY, USA; Department of Neurology, Donald and Barbara Zucker School of Medicine at Hofstra, Northwell, Manhasset, NY, USA
| | - Jose L Herrero
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Department of Neurosurgery, Northwell, Manhasset, NY, USA
| | - Joo-Won Kim
- Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Noah Markowitz
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Elizabeth Espinal
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Nikunj A Bhagat
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Richard Ramdeo
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Junqian Xu
- Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Matthew F Glasser
- Departments of Radiology and Neuroscience, Washington University in St Louis, Saint Louis, MO, USA
| | - Chad E Bouton
- Neural Bypass and Brain Computer Interface Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Department of Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA.
| | - Ashesh D Mehta
- The Human Brain Mapping Laboratory, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Department of Neurosurgery, Northwell, Manhasset, NY, USA
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22
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Shokur S, Mazzoni A, Schiavone G, Weber DJ, Micera S. A modular strategy for next-generation upper-limb sensory-motor neuroprostheses. MED 2021; 2:912-937. [DOI: 10.1016/j.medj.2021.05.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 04/28/2021] [Accepted: 05/10/2021] [Indexed: 02/06/2023]
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23
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Szymanski LJ, Kellis S, Liu CY, Jones KT, Andersen RA, Commins D, Lee B, McCreery DB, Miller CA. Neuropathological effects of chronically implanted, intracortical microelectrodes in a tetraplegic patient. J Neural Eng 2021; 18. [PMID: 34314384 DOI: 10.1088/1741-2552/ac127e] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 07/08/2021] [Indexed: 11/12/2022]
Abstract
Objective.Intracortical microelectrode arrays (MEA) can be used as part of a brain-machine interface system to provide sensory feedback control of an artificial limb to assist persons with tetraplegia. Variability in functionality of electrodes has been reported but few studies in humans have examined the impact of chronic brain tissue responses revealed postmortem on electrode performancein vivo. Approach.In a tetraplegic man, recording MEAs were implanted into the anterior intraparietal area and Brodmann's area 5 (BA5) of the posterior parietal cortex and a recording and stimulation array was implanted in BA1 of the primary somatosensory cortex (S1). The participant expired from unrelated causes seven months after MEA implantation. The underlying tissue of two of the three devices was processed for histology and electrophysiological recordings were assessed.Main results.Recordings of neuronal activity were obtained from all three MEAs despite meningeal encapsulation. However, the S1 array had a greater encapsulation, yielded lower signal quality than the other arrays and failed to elicit somatosensory percepts with electrical stimulation. Histological examination of tissues underlying S1 and BA5 implant sites revealed localized leptomeningeal proliferation and fibrosis, lymphocytic infiltrates, astrogliosis, and foreign body reaction around the electrodes. The BA5 recording site showed focal cerebral microhemorrhages and leptomeningeal vascular ectasia. The S1 site showed focal tissue damage including vascular recanalization, neuronal loss, and extensive subcortical white matter necrosis. The tissue response at the S1 site included hemorrhagic-induced injury suggesting a likely mechanism for reduced function of the S1 implant.Significance.Our findings are similar to those from animal studies with chronic intracortical implants and suggest that vascular disruption and microhemorrhage during device implantation are important contributors to overall array and individual electrode performance and should be a topic for future device development to mitigate tissue responses. Neurosurgical considerations are also discussed.
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Affiliation(s)
- Linda J Szymanski
- Department of Pathology, Keck USC School of Medicine, Los Angeles, CA, United States of America.,Department of Pathology and Laboratory Medicine, Children's Hospital of Los Angeles, Los Angeles, CA, United States of America
| | - Spencer Kellis
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States of America.,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, United States of America.,Department of Neurosurgery, Keck USC School of Medicine, Los Angeles, CA, United States of America.,USC Neurorestoration Center, Keck USC School of Medicine, Los Angeles, CA, United States of America
| | - Charles Y Liu
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States of America.,Department of Neurosurgery, Keck USC School of Medicine, Los Angeles, CA, United States of America.,USC Neurorestoration Center, Keck USC School of Medicine, Los Angeles, CA, United States of America
| | - Kymry T Jones
- Department of Pathology, Keck USC School of Medicine, Los Angeles, CA, United States of America
| | - Richard A Andersen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States of America.,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, United States of America
| | - Deborah Commins
- Department of Pathology, Keck USC School of Medicine, Los Angeles, CA, United States of America
| | - Brian Lee
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States of America.,Department of Neurosurgery, Keck USC School of Medicine, Los Angeles, CA, United States of America.,USC Neurorestoration Center, Keck USC School of Medicine, Los Angeles, CA, United States of America
| | - Douglas B McCreery
- Huntington Medical Research Institute, Pasadena, CA, United States of America
| | - Carol A Miller
- Department of Pathology, Keck USC School of Medicine, Los Angeles, CA, United States of America
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24
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Zheng XS, Yang Q, Vazquez AL, Tracy Cui X. Imaging the Efficiency of Poly(3,4-ethylenedioxythiophene) Doped with Acid-Functionalized Carbon Nanotube and Iridium Oxide Electrode Coatings for Microstimulation. ADVANCED NANOBIOMED RESEARCH 2021; 1:2000092. [PMID: 34746928 PMCID: PMC8552016 DOI: 10.1002/anbr.202000092] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 03/18/2021] [Indexed: 12/02/2022] Open
Abstract
Electrical microstimulation has shown promise in restoring neural deficits in humans. Electrodes coated with materials like the conducting polymer poly(3,4-ethylenedioxythiophene) doped with acid-functionalized carbon nanotubes (PEDOT/CNTs, or PC) exhibit superior charge injection than traditional metals like platinum. However, the stimulation performance of PC remains to be fully characterized. Advanced imaging techniques and transgenic tools allow for real-time observations of neural activity in vivo. Herein, microelectrodes coated with PC and iridium oxide (IrOx) (a commonly used high-charge-injection material) are implanted in GCaMP6s mice and electrical stimulation is applied while imaging neuronal calcium responses. Results show that PC-coated electrodes stimulate more intense and broader GCaMP responses than IrOx. Two-photon microscopy reveals that PC-coated electrodes activate significantly more neuronal soma and neuropil than IrOx-coated electrodes in constant-voltage stimulation and significantly more neuronal soma in constant-current stimulation. Furthermore, with the same injected charge, both materials activate more spatially confined neural elements with shorter pulses than longer pulses, providing a means to tune stimulation selectivity. Finite element analyses reveal that the PC coating creates a denser and nonuniform electric field, increasing the likelihood of activating nearby neural elements. PC coating can significantly improve energy efficiency for electrical stimulation applications.
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Affiliation(s)
- Xin S. Zheng
- Department of BioengineeringUniversity of Pittsburgh3501 Fifth Ave.PittsburghPA15213USA
| | - Qianru Yang
- Department of BioengineeringUniversity of Pittsburgh3501 Fifth Ave.PittsburghPA15213USA
| | - Alberto L. Vazquez
- Departments of Radiology and BioengineeringUniversity of Pittsburgh3025 E. Carson St.PittsburghPA15203USA
| | - Xinyan Tracy Cui
- Department of BioengineeringUniversity of Pittsburgh3501 Fifth Ave.PittsburghPA15213USA
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25
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Serruya MD, Rosenwasser RH. An artificial nervous system to treat chronic stroke. Artif Organs 2021; 45:804-812. [PMID: 34156104 DOI: 10.1111/aor.13998] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/20/2021] [Accepted: 05/18/2021] [Indexed: 01/01/2023]
Abstract
Despite remarkable advances in the treatment of numerous medical conditions, neurological disease and injury remains an outstanding challenge and cause of disability worldwide. The decreased regenerative capacity and extreme complexity and heterogeneity of nervous tissue, in particular the brain, and the fact that the brain remains the least understood organ, have hampered our ability to provide definitive treatments for prevalent conditions such as stroke. Stroke is the second-leading cause of death worldwide, and the nervous system is intimately involved in other prevalent conditions including ischemic heart disease, diabetes mellitus, and hypertension. Advances in neuromodulation, electroceuticals, microsurgical techniques, optogenetics, brain-computer interfaces, and autologous constructs offer potential solutions to address the otherwise permanent neurological deficits of stroke and other conditions. Here we review these various approaches to build an "artificial nervous system" that could restore function and independence in people living with these conditions. We focus on stroke both because it is the leading cause of neurological disability worldwide and because we anticipate that advances in the reversal of stroke-related deficits will have ripple effects benefiting people with other neurological conditions including spinal cord injury, traumatic brain injury, ALS, and muscular dystrophy.
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Affiliation(s)
- Mijail D Serruya
- Department of Neurology, Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA
| | - Robert H Rosenwasser
- Department of Neurosurgery, Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA
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26
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McMullen DP, Thomas TM, Fifer MS, Candrea DN, Tenore FV, Nickl RW, Pohlmeyer EA, Coogan C, Osborn LE, Schiavi A, Wojtasiewicz T, Gordon CR, Cohen AB, Ramsey NF, Schellekens W, Bensmaia SJ, Cantarero GL, Celnik PA, Wester BA, Anderson WS, Crone NE. Novel intraoperative online functional mapping of somatosensory finger representations for targeted stimulating electrode placement: technical note. J Neurosurg 2021; 135:1493-1500. [PMID: 33770760 DOI: 10.3171/2020.9.jns202675] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/29/2020] [Indexed: 11/06/2022]
Abstract
Defining eloquent cortex intraoperatively, traditionally performed by neurosurgeons to preserve patient function, can now help target electrode implantation for restoring function. Brain-machine interfaces (BMIs) have the potential to restore upper-limb motor control to paralyzed patients but require accurate placement of recording and stimulating electrodes to enable functional control of a prosthetic limb. Beyond motor decoding from recording arrays, precise placement of stimulating electrodes in cortical areas associated with finger and fingertip sensations allows for the delivery of sensory feedback that could improve dexterous control of prosthetic hands. In this study, the authors demonstrated the use of a novel intraoperative online functional mapping (OFM) technique with high-density electrocorticography to localize finger representations in human primary somatosensory cortex. In conjunction with traditional pre- and intraoperative targeting approaches, this technique enabled accurate implantation of stimulating microelectrodes, which was confirmed by postimplantation intracortical stimulation of finger and fingertip sensations. This work demonstrates the utility of intraoperative OFM and will inform future studies of closed-loop BMIs in humans.
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Affiliation(s)
- David P McMullen
- 1National Institute of Mental Health, National Institutes of Health, Bethesda
| | | | - Matthew S Fifer
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Francesco V Tenore
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Eric A Pohlmeyer
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Luke E Osborn
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | | | - Chad R Gordon
- 8Plastic and Reconstructive Surgery, Johns Hopkins University, Baltimore
| | - Adam B Cohen
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
- 5Neurology
| | - Nick F Ramsey
- 9UMC Utrecht Brain Center, Utrecht, The Netherlands; and
| | | | - Sliman J Bensmaia
- 10Department of Organismal Biology and Anatomy, University of Chicago, Illinois
| | | | | | - Brock A Wester
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
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Extensive Cortical Convergence to Primate Reticulospinal Pathways. J Neurosci 2021; 41:1005-1018. [PMID: 33268548 PMCID: PMC7880280 DOI: 10.1523/jneurosci.1379-20.2020] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/19/2020] [Accepted: 10/21/2020] [Indexed: 11/30/2022] Open
Abstract
Early evolution of the motor cortex included development of connections to brainstem reticulospinal neurons; these projections persist in primates. In this study, we examined the organization of corticoreticular connections in five macaque monkeys (one male) using both intracellular and extracellular recordings from reticular formation neurons, including identified reticulospinal cells. Synaptic responses to stimulation of different parts of primary motor cortex (M1) and supplementary motor area (SMA) bilaterally were assessed. Widespread short latency excitation, compatible with monosynaptic transmission over fast-conducting pathways, was observed, as well as longer latency responses likely reflecting a mixture of slower monosynaptic and oligosynaptic pathways. There was a high degree of convergence: 56% of reticulospinal cells with input from M1 received projections from M1 in both hemispheres; for SMA, the equivalent figure was even higher (70%). Of reticulospinal neurons with input from the cortex, 78% received projections from both M1 and SMA (regardless of hemisphere); 83% of reticulospinal cells with input from M1 received projections from more than one of the tested M1 sites. This convergence at the single cell level allows reticulospinal neurons to integrate information from across the motor areas of the cortex, taking account of the bilateral motor context. Reticulospinal connections are known to strengthen following damage to the corticospinal tract, such as after stroke, partially contributing to functional recovery. Extensive corticoreticular convergence provides redundancy of control, which may allow the cortex to continue to exploit this descending pathway even after damage to one area.SIGNIFICANCE STATEMENT The reticulospinal tract (RST) provides a parallel pathway for motor control in primates, alongside the more sophisticated corticospinal system. We found extensive convergent inputs to primate reticulospinal cells from primary and supplementary motor cortex bilaterally. These redundant connections could maintain transmission of voluntary commands to the spinal cord after damage (e.g., after stroke or spinal cord injury), possibly assisting recovery of function.
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Kramer DR, Lamorie-Foote K, Barbaro M, Lee MB, Peng T, Gogia A, Nune G, Liu CY, Kellis SS, Lee B. Utility and lower limits of frequency detection in surface electrode stimulation for somatosensory brain-computer interface in humans. Neurosurg Focus 2021; 48:E2. [PMID: 32006952 DOI: 10.3171/2019.11.focus19696] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Accepted: 11/04/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Stimulation of the primary somatosensory cortex (S1) has been successful in evoking artificial somatosensation in both humans and animals, but much is unknown about the optimal stimulation parameters needed to generate robust percepts of somatosensation. In this study, the authors investigated frequency as an adjustable stimulation parameter for artificial somatosensation in a closed-loop brain-computer interface (BCI) system. METHODS Three epilepsy patients with subdural mini-electrocorticography grids over the hand area of S1 were asked to compare the percepts elicited with different stimulation frequencies. Amplitude, pulse width, and duration were held constant across all trials. In each trial, subjects experienced 2 stimuli and reported which they thought was given at a higher stimulation frequency. Two paradigms were used: first, 50 versus 100 Hz to establish the utility of comparing frequencies, and then 2, 5, 10, 20, 50, or 100 Hz were pseudorandomly compared. RESULTS As the magnitude of the stimulation frequency was increased, subjects described percepts that were "more intense" or "faster." Cumulatively, the participants achieved 98.0% accuracy when comparing stimulation at 50 and 100 Hz. In the second paradigm, the corresponding overall accuracy was 73.3%. If both tested frequencies were less than or equal to 10 Hz, accuracy was 41.7% and increased to 79.4% when one frequency was greater than 10 Hz (p = 0.01). When both stimulation frequencies were 20 Hz or less, accuracy was 40.7% compared with 91.7% when one frequency was greater than 20 Hz (p < 0.001). Accuracy was 85% in trials in which 50 Hz was the higher stimulation frequency. Therefore, the lower limit of detection occurred at 20 Hz, and accuracy decreased significantly when lower frequencies were tested. In trials testing 10 Hz versus 20 Hz, accuracy was 16.7% compared with 85.7% in trials testing 20 Hz versus 50 Hz (p < 0.05). Accuracy was greater than chance at frequency differences greater than or equal to 30 Hz. CONCLUSIONS Frequencies greater than 20 Hz may be used as an adjustable parameter to elicit distinguishable percepts. These findings may be useful in informing the settings and the degrees of freedom achievable in future BCI systems.
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Affiliation(s)
- Daniel R Kramer
- Departments of1Neurosurgery and.,2Neurorestoration Center, and
| | | | - Michael Barbaro
- 3Keck School of Medicine, University of Southern California, Los Angeles; and
| | - Morgan B Lee
- 3Keck School of Medicine, University of Southern California, Los Angeles; and
| | - Terrance Peng
- 3Keck School of Medicine, University of Southern California, Los Angeles; and
| | - Angad Gogia
- 3Keck School of Medicine, University of Southern California, Los Angeles; and
| | | | - Charles Y Liu
- Departments of1Neurosurgery and.,2Neurorestoration Center, and
| | - Spencer S Kellis
- 2Neurorestoration Center, and.,5Department of Biology and Biological Engineering and.,6Tianqiao and Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California
| | - Brian Lee
- Departments of1Neurosurgery and.,2Neurorestoration Center, and
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29
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Georgiev DD. Quantum information theoretic approach to the mind–brain problem. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2020; 158:16-32. [DOI: 10.1016/j.pbiomolbio.2020.08.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/02/2020] [Accepted: 08/05/2020] [Indexed: 12/25/2022]
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Mazurek KA, Schieber MH. Injecting Information into the Mammalian Cortex: Progress, Challenges, and Promise. Neuroscientist 2020; 27:129-142. [PMID: 32648527 DOI: 10.1177/1073858420936253] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
For 150 years artificial stimulation has been used to study the function of the nervous system. Such stimulation-whether electrical or optogenetic-eventually may be used in neuroprosthetic devices to replace lost sensory inputs and to otherwise introduce information into the nervous system. Efforts toward this goal can be classified broadly as either biomimetic or arbitrary. Biomimetic stimulation aims to mimic patterns of natural neural activity, so that the subject immediately experiences the artificial stimulation as if it were natural sensation. Arbitrary stimulation, in contrast, makes no attempt to mimic natural patterns of neural activity. Instead, different stimuli-at different locations and/or in different patterns-are assigned different meanings randomly. The subject's time and effort then are required to learn to interpret different stimuli, a process that engages the brain's inherent plasticity. Here we will examine progress in using artificial stimulation to inject information into the cerebral cortex and discuss the challenges for and the promise of future development.
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Affiliation(s)
- Kevin A Mazurek
- Department of Neuroscience, University of Rochester, Rochester, NY, USA.,Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA
| | - Marc H Schieber
- Department of Neuroscience, University of Rochester, Rochester, NY, USA.,Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA.,Department of Neurology, University of Rochester, Rochester, NY, USA.,Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
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31
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Sohn WJ, Wang PT, Kellis S, Andersen RA, Liu CY, Heydari P, Nenadic Z, Do AH. A Prototype of a Fully-Implantable Charge-Balanced Artificial Sensory Stimulator for Bi-directional Brain-Computer-Interface (BD-BCI). ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3083-3085. [PMID: 33018656 DOI: 10.1109/embc44109.2020.9176718] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Previously we developed and validated a benchtop prototype of a fully implantable BCI system for motor decoding. Here, a prototype artificial sensory stimulator was integrated into the benchtop system to develop a prototype of a fully-implantable BD-BCI. The artificial sensory stimulator incorporates an active charge balancing mechanism based on pulse-width modulation to ensure safe stimulation for chronically interfaced electrodes to prevent damage to brain tissue and electrodes. The feasibility of the BD-BCI system's active charge balancing was tested in phantom brain tissue. With the charge-balancing, the removal of the residual charges on an electrode was evident. This is a critical milestone toward fully-implantable BD-BCI systems.
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32
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Lim J, Wang PT, Shaw SJ, Armacost M, Gong H, Liu CY, Do AH, Heydari P, Nenadic Z. Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3493-3496. [PMID: 33018756 DOI: 10.1109/embc44109.2020.9175760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end. Herein we demonstrate the effectiveness of a pre-whitening and null projection artifact suppression method using ECoG data recorded during a clinical neurostimulation procedure. Our method achieved a maximum artifact suppression of 21.49 dB and significantly increased the number of artifact-free frequencies in the frequency domain. This performance surpasses that of a more traditional independent component analysis methodology, while retaining a reduced complexity and increased computational efficiency.
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33
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Idowu OP, Huang J, Zhao Y, Samuel OW, Yu M, Fang P, Li G. A stacked sparse auto-encoder and back propagation network model for sensory event detection via a flexible ECoG. Cogn Neurodyn 2020; 14:591-607. [PMID: 33014175 DOI: 10.1007/s11571-020-09603-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/22/2020] [Accepted: 05/22/2020] [Indexed: 01/22/2023] Open
Abstract
Current prostheses are limited in their ability to provide direct sensory feedback to users with missing limb. Several efforts have been made to restore tactile sensation to amputees but the somatotopic tactile feedback often results in unnatural sensations, and it is yet unclear how and what information the somatosensory system receives during voluntary movement. The present study proposes an efficient model of stacked sparse autoencoder and back propagation neural network for detecting sensory events from a highly flexible electrocorticography (ECoG) electrode. During the mechanical stimulation with Von Frey (VF) filament on the plantar surface of rats' foot, simultaneous recordings of tactile afferent signals were obtained from primary somatosensory cortex (S1) in the brain. In order to achieve a model with optimal performance, Particle Swarm Optimization and Adaptive Moment Estimation (Adam) were adopted to select the appropriate number of neurons, hidden layers and learning rate of each sparse auto-encoder. We evaluated the stimulus-evoked sensation by using an automated up-down (UD) method otherwise called UDReader. The assessment of tactile thresholds with VF shows that the right side of the hind-paw was significantly more sensitive at the tibia-(p = 6.50 × 10-4), followed by the saphenous-(p = 7.84 × 10-4), and sural-(p = 8.24 × 10-4). We then validated our proposed model by comparing with the state-of-the-art methods, and recorded accuracy of 98.8%, sensitivity of 96.8%, and specificity of 99.1%. Hence, we demonstrated the effectiveness of our algorithms in detecting sensory events through flexible ECoG recordings which could be a viable option in restoring somatosensory feedback.
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Affiliation(s)
- Oluwagbenga Paul Idowu
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Jianping Huang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Yang Zhao
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Oluwarotimi William Samuel
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Mei Yu
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Peng Fang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
| | - Guanglin Li
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, 518055 China.,Shenzhen Engineering Laboratory of Neural Rehabilitation Technology, Shenzhen, 518055 China
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Song E, Li J, Won SM, Bai W, Rogers JA. Materials for flexible bioelectronic systems as chronic neural interfaces. NATURE MATERIALS 2020; 19:590-603. [PMID: 32461684 DOI: 10.1038/s41563-020-0679-7] [Citation(s) in RCA: 170] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 04/09/2020] [Indexed: 05/03/2023]
Abstract
Engineered systems that can serve as chronically stable, high-performance electronic recording and stimulation interfaces to the brain and other parts of the nervous system, with cellular-level resolution across macroscopic areas, are of broad interest to the neuroscience and biomedical communities. Challenges remain in the development of biocompatible materials and the design of flexible implants for these purposes, where ulimate goals are for performance attributes approaching those of conventional wafer-based technologies and for operational timescales reaching the human lifespan. This Review summarizes recent advances in this field, with emphasis on active and passive constituent materials, design architectures and integration methods that support necessary levels of biocompatibility, electronic functionality, long-term stable operation in biofluids and reliability for use in vivo. Bioelectronic systems that enable multiplexed electrophysiological mapping across large areas at high spatiotemporal resolution are surveyed, with a particular focus on those with proven chronic stability in live animal models and scalability to thousands of channels over human-brain-scale dimensions. Research in materials science will continue to underpin progress in this field of study.
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Affiliation(s)
- Enming Song
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Jinghua Li
- Department of Materials Science and Engineering, The Ohio State University, Columbus, OH, USA
- Center for Chronic Brain Injury, The Ohio State University, Columbus, OH, USA
| | - Sang Min Won
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Wubin Bai
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA
| | - John A Rogers
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
- Department of Neurological Surgery, Northwestern University, Evanston, IL, USA.
- Department of Chemistry, Northwestern University, Evanston, IL, USA.
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
- Department of Electrical Engineering, Northwestern University, Evanston, IL, USA.
- Department of Computer Science, Northwestern University, Evanston, IL, USA.
- Feinberg School of Medicine, Northwestern University, Evanston, IL, USA.
- Querrey-Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA.
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35
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Pu H, Lim J, Kellis S, Liu CY, Andersen RA, Do AH, Heydari P, Nenadic Z. Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications. J Neural Eng 2020; 17:026038. [PMID: 32208379 DOI: 10.1088/1741-2552/ab82ac] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI's analog front-end operates in an ultra-low power regime, which is a basic requirement for fully implantable medical devices. In this study, we developed a novel method for the suppression of stimulation artifacts before they reach the analog front-end. APPROACH Using elementary biophysical considerations, we devised an artifact suppression method that employs a weak auxiliary stimulation delivered between the primary stimulator and the recording grid. The exact location and amplitude of this auxiliary stimulating dipole were then found through a constrained optimization procedure. The performance of our method was tested in both simulations and phantom brain tissue experiments. MAIN RESULTS The solution found through the optimization procedure matched the optimal canceling dipole in both simulations and experiments. Artifact suppression as large as 28.7 dB and 22.9 dB were achieved in simulations and brain phantom experiments, respectively. SIGNIFICANCE We developed a simple constrained optimization-based method for finding the parameters of an auxiliary stimulating dipole that yields optimal artifact suppression. Our method suppresses stimulation artifacts before they reach the analog front-end and may prevent the front-end amplifiers from saturation. Additionally, it can be used along with other artifact mitigation techniques to further reduce stimulation artifacts.
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Affiliation(s)
- Haoran Pu
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, 92697, United States of America
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36
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Caldwell DJ, Cronin JA, Rao RPN, Collins KL, Weaver KE, Ko AL, Ojemann JG, Kutz JN, Brunton BW. Signal recovery from stimulation artifacts in intracranial recordings with dictionary learning. J Neural Eng 2020; 17:026023. [PMID: 32103828 PMCID: PMC7333778 DOI: 10.1088/1741-2552/ab7a4f] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Electrical stimulation of the human brain is commonly used for eliciting and inhibiting neural activity for clinical diagnostics, modifying abnormal neural circuit function for therapeutics, and interrogating cortical connectivity. However, recording electrical signals with concurrent stimulation results in dominant electrical artifacts that mask the neural signals of interest. Here we develop a method to reproducibly and robustly recover neural activity during concurrent stimulation. We concentrate on signal recovery across an array of electrodes without channel-wise fine-tuning of the algorithm. Our goal includes signal recovery with trains of stimulation pulses, since repeated, high-frequency pulses are often required to induce desired effects in both therapeutic and research domains. We have made all of our code and data publicly available. APPROACH We developed an algorithm that automatically detects templates of artifacts across many channels of recording, creating a dictionary of learned templates using unsupervised clustering. The artifact template that best matches each individual artifact pulse is subtracted to recover the underlying activity. To assess the success of our method, we focus on whether it extracts physiologically interpretable signals from real recordings. MAIN RESULTS We demonstrate our signal recovery approach on invasive electrophysiologic recordings from human subjects during stimulation. We show the recovery of meaningful neural signatures in both electrocorticographic (ECoG) arrays and deep brain stimulation (DBS) recordings. In addition, we compared cortical responses induced by the stimulation of primary somatosensory (S1) by natural peripheral touch, as well as motor cortex activity with and without concurrent S1 stimulation. SIGNIFICANCE Our work will enable future advances in neural engineering with simultaneous stimulation and recording.
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Affiliation(s)
- D J Caldwell
- Department of Bioengineering, University of Washington, Seattle, WA, United States of America. Medical Scientist Training Program, University of Washington, Seattle, WA, United States of America. Center for Neurotechnology, Seattle, WA, United States of America. University of Washington Institute for Neuroengineering, Seattle, WA, United States of America. Author to whom any correspondence should be addressed
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37
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Kramer DR, Lee MB, Barbaro M, Gogia AS, Peng T, Liu C, Kellis S, Lee B. Mapping of primary somatosensory cortex of the hand area using a high-density electrocorticography grid for closed-loop brain computer interface. J Neural Eng 2020; 18. [PMID: 32131064 PMCID: PMC7483626 DOI: 10.1088/1741-2552/ab7c8e] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 03/04/2020] [Indexed: 11/11/2022]
Abstract
The ideal modality for generating sensation in sensorimotor brain computer interfaces (BCI) has not been determined. Here we report the feasibility of using a high-density "mini"-electrocorticography (mECoG) grid in a somatosensory BCI system. Thirteen subjects with intractable epilepsy underwent standard clinical implantation of subdural electrodes for the purpose of seizure localization. An additional high-density mECoG grid was placed (Adtech, 8 by 8, 1.2-mm exposed, 3-mm center-to-center spacing) over the hand area of primary somatosensory cortex. Following implantation, cortical mapping was performed with stimulation parameters of frequency: 50 Hz, pulse-width: 250 µs, pulse duration: 4 s, polarity: alternating, and current that ranged from 0.5 mA to 12 mA at the discretion of the epileptologist. Location of the evoked sensory percepts was recorded along with a description of the sensation. The hand was partitioned into 48 distinct boxes. A box was included if sensation was felt anywhere within the box. The percentage of the hand covered was 63.9% (± 34.4%) (mean ± s.d.). Mean redundancy, measured as electrode pairs stimulating the same box, was 1.9 (± 2.2) electrodes per box; and mean resolution, measured as boxes included per electrode pair stimulation, was 11.4 (± 13.7) boxes with 8.1 (± 10.7) boxes in the digits and 3.4 (± 6.0) boxes in the palm. Functional utility of the system was assessed by quantifying usable percepts. Under the strictest classification, "dermatomally exclusive" percepts, the mean was 2.8 usable percepts per grid. Allowing "perceptually unique" percepts at the same anatomical location, the mean was 5.5 usable percepts per grid. Compared to the small area of coverage and redundancy of a microelectrode system, or the poor resolution of a standard ECoG grid, a mECoG is likely the best modality for a somatosensory BCI system with good coverage of the hand and minimal redundancy.
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Affiliation(s)
- Daniel Richard Kramer
- Neurosurgery, Stanford University, 300 Pasteur Drive, Palo Alto, Stanford, California, 94305-6104, UNITED STATES
| | - Morgan Brianna Lee
- Neurosurgery, University of Southern California, Los Angeles, California, 90089-0001, UNITED STATES
| | - Michael Barbaro
- Neurosurgery, USC Keck School of Medicine, Los Angeles, California, UNITED STATES
| | - Angad S Gogia
- University of Southern California Keck School of Medicine, Los Angeles, California, 90089-9034, UNITED STATES
| | - Terrance Peng
- Neurosurgery, USC Keck School of Medicine, Los Angeles, California, UNITED STATES
| | - Charles Liu
- Neuroresotoration Center and Department of Neurosurgery and Neurology, University of Southern California, Los Angeles, California, UNITED STATES
| | - Spencer Kellis
- Neurosurgery, USC Keck School of Medicine, Los Angeles, California, UNITED STATES
| | - Brian Lee
- University of Southern California, Los Angeles, California, UNITED STATES
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38
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Schofield JS, Shell CE, Beckler DT, Thumser ZC, Marasco PD. Long-Term Home-Use of Sensory-Motor-Integrated Bidirectional Bionic Prosthetic Arms Promotes Functional, Perceptual, and Cognitive Changes. Front Neurosci 2020; 14:120. [PMID: 32140096 PMCID: PMC7042391 DOI: 10.3389/fnins.2020.00120] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 01/30/2020] [Indexed: 12/24/2022] Open
Abstract
Cutaneous sensation is vital to controlling our hands and upper limbs. It helps close the motor control loop by informing adjustments of grasping forces during object manipulations and provides much of the information the brain requires to perceive our limbs as a part of our bodies. This sensory information is absent to upper-limb prosthesis users. Although robotic prostheses are becoming increasingly sophisticated, the absence of feedback imposes a reliance on open-loop control and limits the functional potential as an integrated part of the body. Experimental systems to restore physiologically relevant sensory information to prosthesis users are beginning to emerge. However, the impact of their long-term use on functional abilities, body image, and neural adaptation processes remains unclear. Understanding these effects is essential to transition sensate prostheses from sophisticated assistive tools to integrated replacement limbs. We recruited three participants with high-level upper-limb amputation who previously received targeted reinnervation surgery. Each participant was fit with a neural-machine-interface prosthesis that allowed participants to operate their device by thinking about moving their missing limb. Additionally, we fit a sensory feedback system that allowed participants to experience touch to the prosthesis as touch on their missing limb. All three participants performed a long-term take-home trial. Two participants used their neural-machine-interface systems with touch feedback and one control participant used his prescribed, insensate prosthesis. A series of functional outcome metrics and psychophysical evaluations were performed using sensate neural-machine-interface prostheses before and after the take-home period to capture changes in functional abilities, limb embodiment, and neural adaptation. Our results demonstrated that the relationship between users and sensate neural-machine-interface prostheses is dynamic and changes with long-term use. The presence of touch sensation had a near-immediate impact on how the users operated their prostheses. In the multiple independent measures of users’ functional abilities employed, we observed a spectrum of performance changes following long-term use. Furthermore, after the take-home period, participants more appropriately integrated their prostheses into their body images and psychophysical tests provided strong evidence that neural and cortical adaptation occurred.
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Affiliation(s)
- Jonathon S Schofield
- Department of Mechanical and Aerospace Engineering, University of California, Davis, Davis, CA, United States
| | - Courtney E Shell
- Department of Biomedical Engineering, Lerner Research Institute-Cleveland Clinic, Cleveland, OH, United States.,Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States
| | - Dylan T Beckler
- Department of Biomedical Engineering, Lerner Research Institute-Cleveland Clinic, Cleveland, OH, United States
| | - Zachary C Thumser
- Department of Biomedical Engineering, Lerner Research Institute-Cleveland Clinic, Cleveland, OH, United States.,Research Service, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States
| | - Paul D Marasco
- Department of Biomedical Engineering, Lerner Research Institute-Cleveland Clinic, Cleveland, OH, United States.,Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States
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Eles JR, Kozai TDY. In vivo imaging of calcium and glutamate responses to intracortical microstimulation reveals distinct temporal responses of the neuropil and somatic compartments in layer II/III neurons. Biomaterials 2020; 234:119767. [PMID: 31954232 DOI: 10.1016/j.biomaterials.2020.119767] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 12/22/2019] [Accepted: 01/05/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Intracortical microelectrode implants can generate a tissue response hallmarked by glial scarring and neuron cell death within 100-150 μm of the biomaterial device. Many have proposed that any performance decline in intracortical microstimulation (ICMS) due to this foreign body tissue response could be offset by increasing the stimulation amplitude. The mechanisms of this approach are unclear, however, as there has not been consensus on how increasing amplitude affects the spatial and temporal recruitment patterns of ICMS. APPROACH We clarify these unknowns using in vivo two-photon imaging of mice transgenically expressing the calcium sensor GCaMP6s in Thy1 neurons or virally expressing the glutamate sensor iGluSnFr in neurons. Calcium and neurotransmitter activity are tracked in the neuronal somas and neuropil during long-train stimulation in Layer II/III of somatosensory cortex. MAIN RESULTS Neural calcium activity and glutamate release are dense and strongest within 20-40 μm around the electrode, falling off with distance from the electrode. Neuronal calcium increases with higher amplitude stimulations. During prolonged stimulation trains, a sub-population of somas fail to maintain calcium activity. Interestingly, neuropil calcium activity is 3-fold less correlated to somatic calcium activity for cells that drop-out during the long stimulation train compared to cells that sustain activity throughout the train. Glutamate release is apparent only within 20 μm of the electrode and is sustained for at least 10s after cessation of the 15 and 20 μA stimulation train, but not lower amplitudes. SIGNIFICANCE These results demonstrate that increasing amplitude can increase the radius and intensity of neural recruitment, but it also alters the temporal response of some neurons. Further, dense glutamate release is highest within the first 20 μm of the electrode site even at high amplitudes, suggesting that there may be spatial limitations to the amplitude parameter space. The glutamate elevation outlasts stimulation, suggesting that high-amplitude stimulation may affect neurotransmitter re-uptake. This ultimately suggests that increasing the amplitude of ICMS device stimulation may fundamentally alter the temporal neural response, which could have implications for using amplitude to improve the ICMS effect or "offset" the effects of glial scarring.
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Affiliation(s)
- James R Eles
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Takashi D Y Kozai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, University of Pittsburgh, Carnegie Mellon University, Pittsburgh, PA, USA; Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA; NeuroTech Center, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA.
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40
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Hughes C, Herrera A, Gaunt R, Collinger J. Bidirectional brain-computer interfaces. BRAIN-COMPUTER INTERFACES 2020; 168:163-181. [DOI: 10.1016/b978-0-444-63934-9.00013-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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41
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Volkova K, Lebedev MA, Kaplan A, Ossadtchi A. Decoding Movement From Electrocorticographic Activity: A Review. Front Neuroinform 2019; 13:74. [PMID: 31849632 PMCID: PMC6901702 DOI: 10.3389/fninf.2019.00074] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 11/14/2019] [Indexed: 01/08/2023] Open
Abstract
Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.
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Affiliation(s)
- Ksenia Volkova
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
| | - Mikhail A. Lebedev
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
| | - Alexander Kaplan
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
- Center for Biotechnology Development, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Alexei Ossadtchi
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
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42
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Bockbrader MA, Francisco G, Lee R, Olson J, Solinsky R, Boninger ML. Brain Computer Interfaces in Rehabilitation Medicine. PM R 2019; 10:S233-S243. [PMID: 30269808 DOI: 10.1016/j.pmrj.2018.05.028] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 05/22/2018] [Accepted: 05/31/2018] [Indexed: 12/24/2022]
Abstract
One innovation currently influencing physical medicine and rehabilitation is brain-computer interface (BCI) technology. BCI systems used for motor control record neural activity associated with thoughts, perceptions, and motor intent; decode brain signals into commands for output devices; and perform the user's intended action through an output device. BCI systems used for sensory augmentation transduce environmental stimuli into neural signals interpretable by the central nervous system. Both types of systems have potential for reducing disability by facilitating a user's interaction with the environment. Investigational BCI systems are being used in the rehabilitation setting both as neuroprostheses to replace lost function and as potential plasticity-enhancing therapy tools aimed at accelerating neurorecovery. Populations benefitting from motor and somatosensory BCI systems include those with spinal cord injury, motor neuron disease, limb amputation, and stroke. This article discusses the basic components of BCI for rehabilitation, including recording systems and locations, signal processing and translation algorithms, and external devices controlled through BCI commands. An overview of applications in motor and sensory restoration is provided, along with ethical questions and user perspectives regarding BCI technology.
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Affiliation(s)
- Marcia A Bockbrader
- Department of Physical Medicine & Rehabilitation, The Ohio State University, 480 Medical Center Dr, Columbus, OH 43210; and Neurological Institute, Ohio State University Wexner Medical Center, Columbus, OH(∗).
| | - Gerard Francisco
- Department of Physical Medicine & Rehabilitation, The University of Texas, Houston, TX(†)
| | - Ray Lee
- Department of Orthopaedic and Rehabilitation, Schwab Rehabilitation Hospital, University of Chicago, Chicago, IL(‡)
| | - Jared Olson
- Department of Physical Medicine and Rehabilitation, University of Colorado, Aurora, CO(§)
| | - Ryan Solinsky
- Spaulding Rehabilitation Hospital, Boston; and Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA(¶)
| | - Michael L Boninger
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh; and VA Pittsburgh Health Care System, Pittsburgh, PA(#)
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43
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Kirin SC, Yanagisawa T, Oshino S, Edakawa K, Tanaka M, Kishima H, Nishimura Y. Somatosensation Evoked by Cortical Surface Stimulation of the Human Primary Somatosensory Cortex. Front Neurosci 2019; 13:1019. [PMID: 31607854 PMCID: PMC6769168 DOI: 10.3389/fnins.2019.01019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 09/09/2019] [Indexed: 11/13/2022] Open
Abstract
Electrical stimulation of the primary somatosensory cortex using intracranial electrodes is crucial for the evocation of artificial somatosensations, typically tactile sensations associated with specific regions of the body, in brain-machine interface (BMI) applications. The qualitative characteristics of these artificially evoked somatosensations has been well documented. As of yet, however, the quantitative aspects of these evoked somatosensations, that is to say the quantitative relationship between intensity of electrical stimulation and perceived intensity of the resultant somatosensation remains obscure. This study aimed to explore this quantitative relationship by surface electrical stimulation of the primary somatosensory cortex in two human participants undergoing electrocorticographic monitoring prior to surgical treatment of intractable epilepsy. Electrocorticogram electrodes on the primary somatosensory cortical surface were stimulated with varying current intensities, and a visual analogue scale was employed to provide a quantitative measure of intensity of the evoked sensations. Evoked sensations included those of the thumb, tongue, and hand. A clear linear relationship between current intensity and perceived intensity of sensation was observed. These findings provide novel insight into the quantitative nature of primary somatosensory cortex electrical stimulation-evoked sensation for development of somatosensory neuroprosthetics for clinical use.
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Affiliation(s)
- St. Clair Kirin
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama, Japan
| | - Takufumi Yanagisawa
- Department of Neurosurgery, Graduate School of Medicine Osaka University, Suita, Japan
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan
- Institute for Advanced Co-Creation Studies, Osaka University, Suita, Japan
- *Correspondence: Takufumi Yanagisawa, ;
| | - Satoru Oshino
- Department of Neurosurgery, Graduate School of Medicine Osaka University, Suita, Japan
| | - Kohtaroh Edakawa
- Department of Neurosurgery, Graduate School of Medicine Osaka University, Suita, Japan
| | - Masataka Tanaka
- Department of Neurosurgery, Graduate School of Medicine Osaka University, Suita, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Graduate School of Medicine Osaka University, Suita, Japan
| | - Yukio Nishimura
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama, Japan
- Neural Prosthesis Project, Department of Dementia and Higher Brain Function, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Yukio Nishimura,
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44
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Kramer DR, Lamorie-Foote K, Barbaro M, Lee M, Peng T, Gogia A, Liu CY, Kellis SS, Lee B. Functional Frequency Discrimination From Cortical Somatosensory Stimulation in Humans. Front Neurosci 2019; 13:832. [PMID: 31440133 PMCID: PMC6692717 DOI: 10.3389/fnins.2019.00832] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 07/25/2019] [Indexed: 01/14/2023] Open
Abstract
Recently, efforts to produce artificial sensation through cortical stimulation of primary somatosensory cortex (PSC) in humans have proven safe and reliable. Changes in stimulation parameters like frequency and amplitude have been shown to elicit different percepts, but without clearly defined psychometric profiles. This study investigates the functionally useful limits of frequency changes on the percepts felt by three epilepsy patients with subdural electrocorticography (ECoG) grids. Subjects performing a hidden target task were stimulated with parameters of constant amplitude, pulse-width, and pulse-duration, and a randomly selected set of two frequencies (20, 30, 40, 50, 60, and 100 Hz). They were asked to decide which target had the “higher” frequency. Objectively, an increase in frequency differences was associated with an increase in perceived intensity. Reliable detection of stimulation occurred at and above 40 Hz with a lower limit of detection around 20 Hz and a just-noticeable difference estimated at less than 10 Hz. These findings suggest that frequency can be used as a reliable, adjustable parameter and may be useful in establishing settings and thresholds of functionality in future BCI systems.
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Affiliation(s)
- Daniel R Kramer
- Department of Neurosurgery, University of Southern California, Los Angeles, CA, United States.,Neurorestoration Center, University of Southern California, Los Angeles, CA, United States
| | - Krista Lamorie-Foote
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Michael Barbaro
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Morgan Lee
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Terrance Peng
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Angad Gogia
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Charles Y Liu
- Department of Neurosurgery, University of Southern California, Los Angeles, CA, United States.,Neurorestoration Center, University of Southern California, Los Angeles, CA, United States
| | - Spencer S Kellis
- Neurorestoration Center, University of Southern California, Los Angeles, CA, United States.,Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States.,Tianqiao and Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, CA, United States
| | - Brian Lee
- Department of Neurosurgery, University of Southern California, Los Angeles, CA, United States.,Neurorestoration Center, University of Southern California, Los Angeles, CA, United States
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45
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Caldwell DJ, Ojemann JG, Rao RPN. Direct Electrical Stimulation in Electrocorticographic Brain-Computer Interfaces: Enabling Technologies for Input to Cortex. Front Neurosci 2019; 13:804. [PMID: 31440127 PMCID: PMC6692891 DOI: 10.3389/fnins.2019.00804] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 07/18/2019] [Indexed: 12/22/2022] Open
Abstract
Electrocorticographic brain computer interfaces (ECoG-BCIs) offer tremendous opportunities for restoring function in individuals suffering from neurological damage and for advancing basic neuroscience knowledge. ECoG electrodes are already commonly used clinically for monitoring epilepsy and have greater spatial specificity in recording neuronal activity than techniques such as electroencephalography (EEG). Much work to date in the field has focused on using ECoG signals recorded from cortex as control outputs for driving end effectors. An equally important but less explored application of an ECoG-BCI is directing input into cortex using ECoG electrodes for direct electrical stimulation (DES). Combining DES with ECoG recording enables a truly bidirectional BCI, where information is both read from and written to the brain. We discuss the advantages and opportunities, as well as the barriers and challenges presented by using DES in an ECoG-BCI. In this article, we review ECoG electrodes, the physics and physiology of DES, and the use of electrical stimulation of the brain for the clinical treatment of disorders such as epilepsy and Parkinson’s disease. We briefly discuss some of the translational, regulatory, financial, and ethical concerns regarding ECoG-BCIs. Next, we describe the use of ECoG-based DES for providing sensory feedback and for probing and modifying cortical connectivity. We explore future directions, which may draw on invasive animal studies with penetrating and surface electrodes as well as non-invasive stimulation methods such as transcranial magnetic stimulation (TMS). We conclude by describing enabling technologies, such as smaller ECoG electrodes for more precise targeting of cortical areas, signal processing strategies for simultaneous stimulation and recording, and computational modeling and algorithms for tailoring stimulation to each individual brain.
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Affiliation(s)
- David J Caldwell
- Department of Bioengineering, University of Washington, Seattle, WA, United States.,Medical Scientist Training Program, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - Jeffrey G Ojemann
- Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Neurological Surgery, University of Washington, Seattle, WA, United States
| | - Rajesh P N Rao
- Department of Bioengineering, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States
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46
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Remote-Controlled Fully Implantable Neural Stimulator for Freely Moving Small Animal. ELECTRONICS 2019. [DOI: 10.3390/electronics8060706] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The application of a neural stimulator to small animals is highly desired for the investigation of electrophysiological studies and development of neuroprosthetic devices. For this purpose, it is essential for the device to be implemented with the capabilities of full implantation and wireless control. Here, we present a fully implantable stimulator with remote controllability, compact size, and minimal power consumption. Our stimulator consists of modular units of (1) a surface-type cortical array for inducing directional change of a rat, (2) a depth-type array for providing rewards, and (3) a package for accommodating the stimulating electronics, a battery and ZigBee telemetry, all of which are assembled after independent fabrication and implantation using customized flat cables and connectors. All three modules were packaged using liquid crystal polymer (LCP) to avoid any chemical reaction after implantation. After bench-top evaluation of device functionality, the stimulator was implanted into rats to train the animals to turn to the left (or right) following a directional cue applied to the barrel cortex. Functionality of the device was also demonstrated in a three-dimensional (3D) maze structure, by guiding the rats to better navigate in the maze. The movement of the rat could be wirelessly controlled by a combination of artificial sensation evoked by the surface electrode array and reward stimulation. We could induce rats to turn left or right in free space and help their navigation through the maze. The polymeric packaging and modular design could encapsulate the devices with strict size limitations, which made it possible to fully implant the device into rats. Power consumption was minimized by a dual-mode power-saving scheme with duty cycling. The present study demonstrated feasibility of the proposed neural stimulator to be applied to neuroprosthesis research.
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47
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Caldwell DJ, Cronin JA, Wu J, Weaver KE, Ko AL, Rao RPN, Ojemann JG. Direct stimulation of somatosensory cortex results in slower reaction times compared to peripheral touch in humans. Sci Rep 2019; 9:3292. [PMID: 30824821 PMCID: PMC6397274 DOI: 10.1038/s41598-019-38619-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 01/04/2019] [Indexed: 01/13/2023] Open
Abstract
Direct cortical stimulation (DCS) of primary somatosensory cortex (S1) could help restore sensation and provide task-relevant feedback in a neuroprosthesis. However, the psychophysics of S1 DCS is poorly studied, including any comparison to cutaneous haptic stimulation. We compare the response times to DCS of human hand somatosensory cortex through electrocorticographic grids with response times to haptic stimuli delivered to the hand in four subjects. We found that subjects respond significantly slower to S1 DCS than to natural, haptic stimuli for a range of DCS train durations. Median response times for haptic stimulation varied from 198 ms to 313 ms, while median responses to reliably perceived DCS ranged from 254 ms for one subject, all the way to 528 ms for another. We discern no significant impact of learning or habituation through the analysis of blocked trials, and find no significant impact of cortical stimulation train duration on response times. Our results provide a realistic set of expectations for latencies with somatosensory DCS feedback for future neuroprosthetic applications and motivate the study of neural mechanisms underlying human perception of somatosensation via DCS.
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Affiliation(s)
- David J Caldwell
- Department of Bioengineering, University of Washington, Seattle, USA. .,Medical Scientist Training Program, University of Washington, Seattle, USA. .,National Science Foundation Center for Neurotechnology, Seattle, USA.
| | - Jeneva A Cronin
- Department of Bioengineering, University of Washington, Seattle, USA. .,National Science Foundation Center for Neurotechnology, Seattle, USA.
| | - Jing Wu
- Department of Bioengineering, University of Washington, Seattle, USA.,National Science Foundation Center for Neurotechnology, Seattle, USA
| | - Kurt E Weaver
- Department of Radiology, University of Washington, Seattle, USA.,National Science Foundation Center for Neurotechnology, Seattle, USA
| | - Andrew L Ko
- Department of Neurological Surgery, University of Washington, Seattle, USA.,National Science Foundation Center for Neurotechnology, Seattle, USA
| | - Rajesh P N Rao
- Department of Computer Science and Engineering, University of Washington, Seattle, USA.,National Science Foundation Center for Neurotechnology, Seattle, USA
| | - Jeffrey G Ojemann
- Department of Neurological Surgery, University of Washington, Seattle, USA.,National Science Foundation Center for Neurotechnology, Seattle, USA
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48
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Holmes NP, Tamè L. Locating primary somatosensory cortex in human brain stimulation studies: systematic review and meta-analytic evidence. J Neurophysiol 2019; 121:152-162. [DOI: 10.1152/jn.00614.2018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) over human primary somatosensory cortex (S1), unlike over primary motor cortex (M1), does not produce an immediate, objective output. Researchers must therefore rely on one or more indirect methods to position the TMS coil over S1. The “gold standard” method of TMS coil positioning is to use individual functional and structural magnetic resonance imaging (f/sMRI) alongside a stereotactic navigation system. In the absence of these facilities, however, one common method used to locate S1 is to find the scalp location that produces twitches in a hand muscle (e.g., the first dorsal interosseus, M1-FDI) and then move the coil posteriorly to target S1. There has been no systematic assessment of whether this commonly reported method of finding the hand area of S1 is optimal. To do this, we systematically reviewed 124 TMS studies targeting the S1 hand area and 95 fMRI studies involving passive finger and hand stimulation. Ninety-six TMS studies reported the scalp location assumed to correspond to S1-hand, which was on average 1.5–2 cm posterior to the functionally defined M1-hand area. Using our own scalp measurements combined with similar data from MRI and TMS studies of M1-hand, we provide the estimated scalp locations targeted in these TMS studies of the S1-hand. We also provide a summary of reported S1 coordinates for passive finger and hand stimulation in fMRI studies. We conclude that S1-hand is more lateral to M1-hand than assumed by the majority of TMS studies.
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Affiliation(s)
- Nicholas Paul Holmes
- School of Psychology, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Luigi Tamè
- Department of Psychological Sciences, Birkbeck University of London, London, United Kingdom
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49
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Peng X, Hickman JL, Bowles SG, Donegan DC, Welle CG. Innovations in electrical stimulation harness neural plasticity to restore motor function. BIOELECTRONICS IN MEDICINE 2018; 1:251-263. [PMID: 33859830 DOI: 10.2217/bem-2019-0002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Novel technology and innovative stimulation paradigms allow for unprecedented spatiotemporal precision and closed-loop implementation of neurostimulation systems. In turn, precise, closed-loop neurostimulation appears to preferentially drive neural plasticity in motor networks, promoting neural repair. Recent clinical studies demonstrate that electrical stimulation can drive neural plasticity in damaged motor circuits, leading to meaningful improvement in users. Future advances in these areas hold promise for the treatment of a wide range of motor systems disorders.
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Affiliation(s)
- Xiaoyu Peng
- Dept. of Neurosurgery, University of Colorado, Anschutz Medical Campus, 12700 East 19th Avenue, Aurora, CO 80045
| | - Jordan L Hickman
- Dept. of Neurosurgery, University of Colorado, Anschutz Medical Campus, 12700 East 19th Avenue, Aurora, CO 80045
| | - Spencer G Bowles
- Dept. of Neurosurgery, University of Colorado, Anschutz Medical Campus, 12700 East 19th Avenue, Aurora, CO 80045
| | - Dane C Donegan
- Dept. of Neurosurgery, University of Colorado, Anschutz Medical Campus, 12700 East 19th Avenue, Aurora, CO 80045.,ETH Zurich, Department Health Science and Technology, Institute for Neuroscience. Schorenstrasse 16, 8603 Schwerzenbach, Switzerland
| | - Cristin G Welle
- Dept. of Neurosurgery, University of Colorado, Anschutz Medical Campus, 12700 East 19th Avenue, Aurora, CO 80045
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50
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Lim J, Wang PT, Bidhendi AK, Arasteh OM, Shaw SJ, Armacost M, Gong H, Liu CY, Heydari P, Do AH, Nenadic Z. Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and Recording. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:4748-4751. [PMID: 30441410 DOI: 10.1109/embc.2018.8513216] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. It is therefore important that the interface be able to distinguish between neural signals of interest and stimulation artifacts. Current bi-directional BCIs address this problem by temporally multiplexing stimulation and recording. This approach, however, is suboptimal in many BCI applications. Alternative artifact mitigation methods can be devised by investigating the mechanics of artifact propagation. To characterize stimulation artifact behaviors, we collected and analyzed electrocorticography (ECoG) data from eloquent cortex mapping. Ratcheting and phase-locking of stimulation artifacts were observed, as well as dipole-like properties. Artifacts as large as ±1,100 μV appeared as far as 15-37 mm away from the stimulating channel when stimulating at 10 mA. Analysis also showed that the majority of the artifact power was concentrated at the stimulation pulse train frequency (50 Hz) and its super-harmonics (100, 150, 200 Hz). Lower frequencies (0-32 Hz) experienced minimal artifact contamination. These findings could inform the design of future bi-directional ECoG-based BCIs.
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