1
|
Jung T, Zeng N, Fabbri JD, Eichler G, Li Z, Willeke K, Wingel KE, Dubey A, Huq R, Sharma M, Hu Y, Ramakrishnan G, Tien K, Mantovani P, Parihar A, Yin H, Oswalt D, Misdorp A, Uguz I, Shinn T, Rodriguez GJ, Nealley C, Gonzales I, Roukes M, Knecht J, Yoshor D, Canoll P, Spinazzi E, Carloni LP, Pesaran B, Patel S, Youngerman B, Cotton RJ, Tolias A, Shepard KL. Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594333. [PMID: 38798494 PMCID: PMC11118429 DOI: 10.1101/2024.05.17.594333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-μm-thick, mechanically flexible micro-electrocorticography (μECoG) BCI, integrating 256×256 electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording and 16,384 stimulation channels, from which we can simultaneously record up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.
Collapse
|
2
|
Viana D, Walston ST, Masvidal-Codina E, Illa X, Rodríguez-Meana B, Del Valle J, Hayward A, Dodd A, Loret T, Prats-Alfonso E, de la Oliva N, Palma M, Del Corro E, Del Pilar Bernicola M, Rodríguez-Lucas E, Gener T, de la Cruz JM, Torres-Miranda M, Duvan FT, Ria N, Sperling J, Martí-Sánchez S, Spadaro MC, Hébert C, Savage S, Arbiol J, Guimerà-Brunet A, Puig MV, Yvert B, Navarro X, Kostarelos K, Garrido JA. Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation. NATURE NANOTECHNOLOGY 2024; 19:514-523. [PMID: 38212522 PMCID: PMC11026161 DOI: 10.1038/s41565-023-01570-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/07/2023] [Indexed: 01/13/2024]
Abstract
One of the critical factors determining the performance of neural interfaces is the electrode material used to establish electrical communication with the neural tissue, which needs to meet strict electrical, electrochemical, mechanical, biological and microfabrication compatibility requirements. This work presents a nanoporous graphene-based thin-film technology and its engineering to form flexible neural interfaces. The developed technology allows the fabrication of small microelectrodes (25 µm diameter) while achieving low impedance (∼25 kΩ) and high charge injection (3-5 mC cm-2). In vivo brain recording performance assessed in rodents reveals high-fidelity recordings (signal-to-noise ratio >10 dB for local field potentials), while stimulation performance assessed with an intrafascicular implant demonstrates low current thresholds (<100 µA) and high selectivity (>0.8) for activating subsets of axons within the rat sciatic nerve innervating tibialis anterior and plantar interosseous muscles. Furthermore, the tissue biocompatibility of the devices was validated by chronic epicortical (12 week) and intraneural (8 week) implantation. This work describes a graphene-based thin-film microelectrode technology and demonstrates its potential for high-precision and high-resolution neural interfacing.
Collapse
Affiliation(s)
- Damià Viana
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Steven T Walston
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Eduard Masvidal-Codina
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Xavi Illa
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
| | - Bruno Rodríguez-Meana
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jaume Del Valle
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
- Secció de Fisiologia, Department de Bioquímica i Fisiologia, Facultat de Farmàcia i Ciències de l'Alimentació, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Andrew Hayward
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Abbie Dodd
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Thomas Loret
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Elisabet Prats-Alfonso
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
| | - Natàlia de la Oliva
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marie Palma
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Elena Del Corro
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - María Del Pilar Bernicola
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Elisa Rodríguez-Lucas
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Thomas Gener
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Jose Manuel de la Cruz
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Miguel Torres-Miranda
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Fikret Taygun Duvan
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Nicola Ria
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Justin Sperling
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Sara Martí-Sánchez
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Maria Chiara Spadaro
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Clément Hébert
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Sinead Savage
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Jordi Arbiol
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Anton Guimerà-Brunet
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
| | - M Victoria Puig
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Blaise Yvert
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Xavier Navarro
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Kostas Kostarelos
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain.
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain.
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK.
| | - Jose A Garrido
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain.
- ICREA, Barcelona, Spain.
| |
Collapse
|
3
|
Silemek B, Seifert F, Petzold J, Brühl R, Ittermann B, Winter L. Wirelessly interfacing sensor-equipped implants and MR scanners for improved safety and imaging. Magn Reson Med 2023; 90:2608-2626. [PMID: 37533167 DOI: 10.1002/mrm.29818] [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: 02/07/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 08/04/2023]
Abstract
PURPOSE To investigate a novel reduced RF heating method for imaging in the presence of active implanted medical devices (AIMDs) which employs a sensor-equipped implant that provides wireless feedback. METHODS The implant, consisting of a generator case and a lead, measures RF-inducedE $$ E $$ -fields at the implant tip using a simple sensor in the generator case and transmits these values wirelessly to the MR scanner. Based on the sensor signal alone, parallel transmission (pTx) excitation vectors were calculated to suppress tip heating and maintain image quality. A sensor-based imaging metric was introduced to assess the image quality. The methodology was studied at 7T in testbed experiments, and at a 3T scanner in an ASTM phantom containing AIMDs instrumented with six realistic deep brain stimulation (DBS) lead configurations adapted from patients. RESULTS The implant successfully measured RF-inducedE $$ E $$ -fields (Pearson correlation coefficient squared [R2 ] = 0.93) and temperature rises (R2 = 0.95) at the implant tip. The implant acquired the relevant data needed to calculate the pTx excitation vectors and transmitted them wirelessly to the MR scanner within a single shot RF sequence (<60 ms). Temperature rises for six realistic DBS lead configurations were reduced to 0.03-0.14 K for heating suppression modes compared to 0.52-3.33 K for the worst-case heating, while imaging quality remained comparable (five of six lead imaging scores were ≥0.80/1.00) to conventional circular polarization (CP) images. CONCLUSION Implants with sensors that can communicate with an MR scanner can substantially improve safety for patients in a fast and automated manner, easing the current burden for MR personnel.
Collapse
Affiliation(s)
- Berk Silemek
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Frank Seifert
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Johannes Petzold
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Lukas Winter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| |
Collapse
|
4
|
Identifying Thematics in a Brain-Computer Interface Research. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2023; 2023:2793211. [PMID: 36643889 PMCID: PMC9833923 DOI: 10.1155/2023/2793211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/21/2022] [Accepted: 12/24/2022] [Indexed: 01/05/2023]
Abstract
This umbrella review is motivated to understand the shift in research themes on brain-computer interfacing (BCI) and it determined that a shift away from themes that focus on medical advancement and system development to applications that included education, marketing, gaming, safety, and security has occurred. The background of this review examined aspects of BCI categorisation, neuroimaging methods, brain control signal classification, applications, and ethics. The specific area of BCI software and hardware development was not examined. A search using One Search was undertaken and 92 BCI reviews were selected for inclusion. Publication demographics indicate the average number of authors on review papers considered was 4.2 ± 1.8. The results also indicate a rapid increase in the number of BCI reviews from 2003, with only three reviews before that period, two in 1972, and one in 1996. While BCI authors were predominantly Euro-American in early reviews, this shifted to a more global authorship, which China dominated by 2020-2022. The review revealed six disciplines associated with BCI systems: life sciences and biomedicine (n = 42), neurosciences and neurology (n = 35), and rehabilitation (n = 20); (2) the second domain centred on the theme of functionality: computer science (n = 20), engineering (n = 28) and technology (n = 38). There was a thematic shift from understanding brain function and modes of interfacing BCI systems to more applied research novel areas of research-identified surround artificial intelligence, including machine learning, pre-processing, and deep learning. As BCI systems become more invasive in the lives of "normal" individuals, it is expected that there will be a refocus and thematic shift towards increased research into ethical issues and the need for legal oversight in BCI application.
Collapse
|
5
|
Luo J, Xue N, Chen J. A Review: Research Progress of Neural Probes for Brain Research and Brain-Computer Interface. BIOSENSORS 2022; 12:bios12121167. [PMID: 36551135 PMCID: PMC9775442 DOI: 10.3390/bios12121167] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/07/2022] [Accepted: 12/13/2022] [Indexed: 06/01/2023]
Abstract
Neural probes, as an invasive physiological tool at the mesoscopic scale, can decipher the code of brain connections and communications from the cellular or even molecular level, and realize information fusion between the human body and external machines. In addition to traditional electrodes, two new types of neural probes have been developed in recent years: optoprobes based on optogenetics and magnetrodes that record neural magnetic signals. In this review, we give a comprehensive overview of these three kinds of neural probes. We firstly discuss the development of microelectrodes and strategies for their flexibility, which is mainly represented by the selection of flexible substrates and new electrode materials. Subsequently, the concept of optogenetics is introduced, followed by the review of several novel structures of optoprobes, which are divided into multifunctional optoprobes integrated with microfluidic channels, artifact-free optoprobes, three-dimensional drivable optoprobes, and flexible optoprobes. At last, we introduce the fundamental perspectives of magnetoresistive (MR) sensors and then review the research progress of magnetrodes based on it.
Collapse
Affiliation(s)
- Jiahui Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ning Xue
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiamin Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
6
|
Chiappalone M, Cota VR, Carè M, Di Florio M, Beaubois R, Buccelli S, Barban F, Brofiga M, Averna A, Bonacini F, Guggenmos DJ, Bornat Y, Massobrio P, Bonifazi P, Levi T. Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering. Brain Sci 2022; 12:1578. [PMID: 36421904 PMCID: PMC9688667 DOI: 10.3390/brainsci12111578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/09/2022] [Accepted: 11/17/2022] [Indexed: 08/27/2023] Open
Abstract
Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.
Collapse
Affiliation(s)
- Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Vinicius R. Cota
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marta Carè
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Mattia Di Florio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Romain Beaubois
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Federico Barban
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, 3012 Bern, Switzerland
| | - Francesco Bonacini
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - David J. Guggenmos
- Department of Rehabilitation Medicine, University of Kansas Medical Center, Kansas City, KS 66103, USA
- Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Yannick Bornat
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- National Institute for Nuclear Physics (INFN), 16146 Genova, Italy
| | - Paolo Bonifazi
- IKERBASQUE, The Basque Fundation, 48009 Bilbao, Spain
- Biocruces Health Research Institute, 48903 Barakaldo, Spain
| | - Timothée Levi
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| |
Collapse
|
7
|
Sensor Technology and Intelligent Systems in Anorexia Nervosa: Providing Smarter Healthcare Delivery Systems. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1955056. [PMID: 36193321 PMCID: PMC9526573 DOI: 10.1155/2022/1955056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/06/2022] [Indexed: 11/22/2022]
Abstract
Ubiquitous technology, big data, more efficient electronic health records, and predictive analytics are now at the core of smart healthcare systems supported by artificial intelligence. In the present narrative review, we focus on sensing technologies for the healthcare of Anorexia Nervosa (AN). We employed a framework inspired by the Interpersonal Neurobiology Theory (IPNB), which posits that human experience is characterized by a flow of energy and information both within us (within our whole body), and between us (in the connections we have with others and with nature). In line with this framework, we focused on sensors designed to evaluate bodily processes (body sensors such as implantable sensors, epidermal sensors, and wearable and portable sensors), human social interaction (sociometric sensors), and the physical environment (indoor and outdoor ambient sensors). There is a myriad of man-made sensors as well as nature-based sensors such as plants that can be used to design and deploy intelligent systems for human monitoring and healthcare. In conclusion, sensing technologies and intelligent systems can be employed for smarter healthcare of AN and help to relieve the burden of health professionals. However, there are technical, ethical, and environmental sustainability issues that must be considered prior to implementing these systems. A joint collaboration of professionals and other members of the society involved in the healthcare of individuals with AN can help in the development of these systems. The evolution of cyberphysical systems should also be considered in these collaborations.
Collapse
|
8
|
The Sheep as a Large Animal Model for the Investigation and Treatment of Human Disorders. BIOLOGY 2022; 11:biology11091251. [PMID: 36138730 PMCID: PMC9495394 DOI: 10.3390/biology11091251] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/08/2022] [Accepted: 08/16/2022] [Indexed: 12/19/2022]
Abstract
Simple Summary We review the value of large animal models for improving the translation of biomedical research for human application, focusing primarily on sheep. Abstract An essential aim of biomedical research is to translate basic science information obtained from preclinical research using small and large animal models into clinical practice for the benefit of humans. Research on rodent models has enhanced our understanding of complex pathophysiology, thus providing potential translational pathways. However, the success of translating drugs from pre-clinical to clinical therapy has been poor, partly due to the choice of experimental model. The sheep model, in particular, is being increasingly applied to the field of biomedical research and is arguably one of the most influential models of human organ systems. It has provided essential tools and insights into cardiovascular disorder, orthopaedic examination, reproduction, gene therapy, and new insights into neurodegenerative research. Unlike the widely adopted rodent model, the use of the sheep model has an advantage over improving neuroscientific translation, in particular due to its large body size, gyrencephalic brain, long lifespan, more extended gestation period, and similarities in neuroanatomical structures to humans. This review aims to summarise the current status of sheep to model various human diseases and enable researchers to make informed decisions when considering sheep as a human biomedical model.
Collapse
|
9
|
Davis KC, Meschede-Krasa B, Cajigas I, Prins NW, Alver C, Gallo S, Bhatia S, Abel JH, Naeem JA, Fisher L, Raza F, Rifai WR, Morrison M, Ivan ME, Brown EN, Jagid JR, Prasad A. Design-development of an at-home modular brain-computer interface (BCI) platform in a case study of cervical spinal cord injury. J Neuroeng Rehabil 2022; 19:53. [PMID: 35659259 PMCID: PMC9166490 DOI: 10.1186/s12984-022-01026-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 05/13/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE The objective of this study was to develop a portable and modular brain-computer interface (BCI) software platform independent of input and output devices. We implemented this platform in a case study of a subject with cervical spinal cord injury (C5 ASIA A). BACKGROUND BCIs can restore independence for individuals with paralysis by using brain signals to control prosthetics or trigger functional electrical stimulation. Though several studies have successfully implemented this technology in the laboratory and the home, portability, device configuration, and caregiver setup remain challenges that limit deployment to the home environment. Portability is essential for transitioning BCI from the laboratory to the home. METHODS The BCI platform implementation consisted of an Activa PC + S generator with two subdural four-contact electrodes implanted over the dominant left hand-arm region of the sensorimotor cortex, a minicomputer fixed to the back of the subject's wheelchair, a custom mobile phone application, and a mechanical glove as the end effector. To quantify the performance for this at-home implementation of the BCI, we quantified system setup time at home, chronic (14-month) decoding accuracy, hardware and software profiling, and Bluetooth communication latency between the App and the minicomputer. We created a dataset of motor-imagery labeled signals to train a binary motor imagery classifier on a remote computer for online, at-home use. RESULTS Average bluetooth data transmission delay between the minicomputer and mobile App was 23 ± 0.014 ms. The average setup time for the subject's caregiver was 5.6 ± 0.83 min. The average times to acquire and decode neural signals and to send those decoded signals to the end-effector were respectively 404.1 ms and 1.02 ms. The 14-month median accuracy of the trained motor imagery classifier was 87.5 ± 4.71% without retraining. CONCLUSIONS The study presents the feasibility of an at-home BCI system that subjects can seamlessly operate using a friendly mobile user interface, which does not require daily calibration nor the presence of a technical person for at-home setup. The study also describes the portability of the BCI system and the ability to plug-and-play multiple end effectors, providing the end-user the flexibility to choose the end effector to accomplish specific motor tasks for daily needs. Trial registration ClinicalTrials.gov: NCT02564419. First posted on 9/30/2015.
Collapse
Affiliation(s)
- Kevin C Davis
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Benyamin Meschede-Krasa
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Iahn Cajigas
- Department of Neurological Surgery, University of Miami, 1095 NW 14th Terrace, Miami, FL, 33136, USA
| | - Noeline W Prins
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
- Department of Electrical and Information Engineering, University of Ruhuna, Matara, Sri Lanka
| | - Charles Alver
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Sebastian Gallo
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Shovan Bhatia
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - John H Abel
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Jasim A Naeem
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Letitia Fisher
- Miami Project to Cure Paralysis, University of Miami, Miami, FL, 33136, USA
| | - Fouzia Raza
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Wesley R Rifai
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Matthew Morrison
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA
| | - Michael E Ivan
- Department of Neurological Surgery, University of Miami, 1095 NW 14th Terrace, Miami, FL, 33136, USA
| | - Emery N Brown
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jonathan R Jagid
- Department of Neurological Surgery, University of Miami, 1095 NW 14th Terrace, Miami, FL, 33136, USA.
- Miami Project to Cure Paralysis, University of Miami, Miami, FL, 33136, USA.
| | - Abhishek Prasad
- Department of Biomedical Engineering, University of Miami, 1251 Memorial Dr, MEA 204, Coral Gables, Miami, FL, 33146, USA.
- Miami Project to Cure Paralysis, University of Miami, Miami, FL, 33136, USA.
| |
Collapse
|
10
|
Schönthaler EMD, Hofer G, Grinschgl S, Neubauer AC. Super-Men and Wonder-Women: the Relationship Between the Acceptance of Self-enhancement, Personality, and Values. JOURNAL OF COGNITIVE ENHANCEMENT 2022. [DOI: 10.1007/s41465-022-00244-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
AbstractDue to ongoing technological innovations, self-enhancement methods are publicly discussed, researched from different perspectives, and part of ethical debates. However, only few studies investigated the acceptance of these methods and its relationship with personality traits and values. The present study investigated to what extent people accept different enhancement methods and whether acceptance can be predicted by Big Five and Dark Triad traits, vulnerable narcissism, and values. In an online survey (N = 450), we measured personality traits and values. Additionally, participants read scenarios about enhancement methods and answered questions about their acceptance of these scenarios. Factor analysis indicated a general factor of acceptance across scenarios. Correlation analyses showed that high agreeableness, agreeableness-compassion, conscientiousness, conscientiousness-industriousness, and conservation- and self-transcendence values are related to less acceptance of self-enhancement. Moreover, individuals high on Dark Triad traits, vulnerable narcissism, and self-enhancement values exhibit more acceptance. Hierarchical regression analysis revealed that said values and Big Five traits explained unique variance in the acceptance of self-enhancement. These findings highlight the importance of considering personality and values when investigating self-enhancement—a topic that is receiving increasing attention by the public, politicians, and scientists.
Collapse
|
11
|
Neuromotor prosthetic to treat stroke-related paresis: N-of-1 trial. COMMUNICATIONS MEDICINE 2022; 2:37. [PMID: 35603289 PMCID: PMC9053238 DOI: 10.1038/s43856-022-00105-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 03/18/2022] [Indexed: 11/25/2022] Open
Abstract
Background Functional recovery of arm movement typically plateaus following a stroke, leaving chronic motor deficits. Brain-computer interfaces (BCI) may be a potential treatment for post-stroke deficits Methods In this n-of-1 trial (NCT03913286), a person with chronic subcortical stroke with upper-limb motor impairment used a powered elbow-wrist-hand orthosis that opened and closed the affected hand using cortical activity, recorded from a percutaneous BCI comprised of four microelectrode arrays implanted in the ipsilesional precentral gyrus, based on decoding of spiking patterns and high frequency field potentials generated by imagined hand movements. The system was evaluated in a home setting for 12 weeks Results Robust single unit activity, modulating with attempted or imagined movement, was present throughout the precentral gyrus. The participant acquired voluntary control over a hand-orthosis, achieving 10 points on the Action Research Arm Test using the BCI, compared to 0 without any device, and 5 using myoelectric control. Strength, spasticity, the Fugl-Meyer scores improved. Conclusions We demonstrate in a human being that ensembles of individual neurons in the cortex overlying a chronic supratentorial, subcortical stroke remain active and engaged in motor representation and planning and can be used to electrically bypass the stroke and promote limb function. The participant’s ability to rapidly acquire control over otherwise paralyzed hand opening, more than 18 months after a stroke, may justify development of a fully implanted movement restoration system to expand the utility of fully implantable BCI to a clinical population that numbers in the tens of millions worldwide. Stroke is a restriction of blood flow to part of the brain and can lead to chronic issues with a person’s ability to control the limbs. The aim of this study was to see if a new type of device could restore movement in a person with arm weakness due to a stroke that occurred a year earlier. In our trial, a sensor was implanted into the surface of the brain, near the site of the stroke, and was connected to a computer that generated a command to open and close the hand with a motorized brace worn on the hand. This person was able to use their own brain activity to trigger the brace and pick up and move objects. This research could support the development of similar medical devices to restore movement in people who have had strokes. Serruya et al. test in an N-of-1 trial whether a wearable, powered exoskeletal orthosis, driven by a percutaneous, implanted brain–computer interface can restore voluntary upper extremity function following chronic hemiparesis subsequent to a cerebral subcortical stroke. Using this approach, voluntary opening of the paralyzed hand is restored.
Collapse
|
12
|
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.
Collapse
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
| |
Collapse
|
13
|
Schalk G, Worrell S, Mivalt F, Belsten A, Kim I, Morris JM, Hermes D, Klassen BT, Staff NP, Messina S, Kaufmann T, Rickert J, Brunner P, Worrell GA, Miller KJ. Toward a fully implantable ecosystem for adaptive neuromodulation in humans: Preliminary experience with the CorTec BrainInterchange device in a canine model. Front Neurosci 2022; 16:932782. [PMID: 36601593 PMCID: PMC9806357 DOI: 10.3389/fnins.2022.932782] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 10/24/2022] [Indexed: 12/23/2022] Open
Abstract
This article describes initial work toward an ecosystem for adaptive neuromodulation in humans by documenting the experience of implanting CorTec's BrainInterchange (BIC) device in a beagle canine and using the BCI2000 environment to interact with the BIC device. It begins with laying out the substantial opportunity presented by a useful, easy-to-use, and widely available hardware/software ecosystem in the current landscape of the field of adaptive neuromodulation, and then describes experience with implantation, software integration, and post-surgical validation of recording of brain signals and implant parameters. Initial experience suggests that the hardware capabilities of the BIC device are fully supported by BCI2000, and that the BIC/BCI2000 device can record and process brain signals during free behavior. With further development and validation, the BIC/BCI2000 ecosystem could become an important tool for research into new adaptive neuromodulation protocols in humans.
Collapse
Affiliation(s)
- Gerwin Schalk
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
- Chen Frontier Lab for Applied Neurotechnology, Tianqiao and Chrissy Chen Institute, Shanghai, China
- *Correspondence: Gerwin Schalk
| | - Samuel Worrell
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
| | - Filip Mivalt
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czechia
| | - Alexander Belsten
- Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
- National Center for Adaptive Neurotechnologies, Albany, NY, United States
| | - Inyong Kim
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | | | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
| | - Bryan T. Klassen
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Nathan P. Staff
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Steven Messina
- Department of Neuroradiology, Mayo Clinic, Rochester, MN, United States
| | - Timothy Kaufmann
- Department of Neuroradiology, Mayo Clinic, Rochester, MN, United States
| | | | - Peter Brunner
- Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
- National Center for Adaptive Neurotechnologies, Albany, NY, United States
| | - Gregory A. Worrell
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
| | - Kai J. Miller
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
| |
Collapse
|
14
|
Cho YH, Park YG, Kim S, Park JU. 3D Electrodes for Bioelectronics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2005805. [PMID: 34013548 DOI: 10.1002/adma.202005805] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/04/2020] [Indexed: 05/08/2023]
Abstract
In recent studies related to bioelectronics, significant efforts have been made to form 3D electrodes to increase the effective surface area or to optimize the transfer of signals at tissue-electrode interfaces. Although bioelectronic devices with 2D and flat electrode structures have been used extensively for monitoring biological signals, these 2D planar electrodes have made it difficult to form biocompatible and uniform interfaces with nonplanar and soft biological systems (at the cellular or tissue levels). Especially, recent biomedical applications have been expanding rapidly toward 3D organoids and the deep tissues of living animals, and 3D bioelectrodes are getting significant attention because they can reach the deep regions of various 3D tissues. An overview of recent studies on 3D bioelectronic devices, such as the use of electrical stimulations and the recording of neural signals from biological subjects, is presented. Subsequently, the recent developments in materials and fabrication processing to 3D micro- and nanostructures are introduced, followed by broad applications of these 3D bioelectronic devices at various in vitro and in vivo conditions.
Collapse
Affiliation(s)
- Yo Han Cho
- Nano Science Technology Institute, Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, 03722, Republic of Korea
- Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul, 03722, Republic of Korea
| | - Young-Geun Park
- Nano Science Technology Institute, Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, 03722, Republic of Korea
- Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul, 03722, Republic of Korea
| | - Sumin Kim
- Nano Science Technology Institute, Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, 03722, Republic of Korea
- Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul, 03722, Republic of Korea
| | - Jang-Ung Park
- Nano Science Technology Institute, Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, 03722, Republic of Korea
- Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul, 03722, Republic of Korea
| |
Collapse
|
15
|
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]
|
16
|
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.
Collapse
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
| |
Collapse
|
17
|
Tanskanen JM, Ahtiainen A, Hyttinen JA. Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review. Bioelectricity 2020; 2:328-347. [PMID: 34471853 PMCID: PMC8370352 DOI: 10.1089/bioe.2020.0028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Biological neuronal cells communicate using neurochemistry and electrical signals. The same phenomena also allow us to probe and manipulate neuronal systems and communicate with them. Neuronal system malfunctions cause a multitude of symptoms and functional deficiencies that can be assessed and sometimes alleviated by electrical stimulation. Our working hypothesis is that real-time closed-loop full-duplex measurement and stimulation paradigms can provide more in-depth insight into neuronal networks and enhance our capability to control diseases of the nervous system. In this study, we review extracellular electrical stimulation methods used in in vivo, in vitro, and in silico neuroscience research and in the clinic (excluding methods mainly aimed at neuronal growth and other similar effects) and highlight the potential of closed-loop measurement and stimulation systems. A multitude of electrical stimulation and measurement-based methods are widely used in research and the clinic. Closed-loop methods have been proposed, and some are used in the clinic. However, closed-loop systems utilizing more complex measurement analysis and adaptive stimulation systems, such as artificial intelligence systems connected to biological neuronal systems, do not yet exist. Our review promotes the research and development of intelligent paradigms aimed at meaningful communications between neuronal and information and communications technology systems, "dialogical paradigms," which have the potential to take neuroscience and clinical methods to a new level.
Collapse
Affiliation(s)
- Jarno M.A. Tanskanen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Annika Ahtiainen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jari A.K. Hyttinen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| |
Collapse
|
18
|
Beuter A, Balossier A, Vassal F, Hemm S, Volpert V. Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation. BIOLOGICAL CYBERNETICS 2020; 114:5-21. [PMID: 32020368 DOI: 10.1007/s00422-020-00818-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Accepted: 01/28/2020] [Indexed: 06/10/2023]
Abstract
The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.
Collapse
Affiliation(s)
- Anne Beuter
- Bordeaux INP, University of Bordeaux, Bordeaux, France.
| | - Anne Balossier
- Service de neurochirurgie fonctionnelle et stéréotaxique, AP-HM La Timone, Aix-Marseille University, Marseille, France
| | - François Vassal
- INSERM U1028 Neuropain, UMR 5292, Centre de Recherche en Neurosciences, Universités Lyon 1 et Saint-Etienne, Saint-Étienne, France
- Service de Neurochirurgie, Hôpital Nord, Centre Hospitalier Universitaire de Saint-Etienne, Saint-Étienne, France
| | - Simone Hemm
- School of Life Sciences, Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, 4132, Muttenz, Switzerland
| | - Vitaly Volpert
- Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622, Villeurbanne, France
- INRIA Team Dracula, INRIA Lyon La Doua, 69603, Villeurbanne, France
- People's Friendship University of Russia (RUDN University), Miklukho-Maklaya St, Moscow, Russian Federation, 117198
| |
Collapse
|
19
|
|
20
|
Wang PT, Camacho E, Wang M, Li Y, Shaw SJ, Armacost M, Gong H, Kramer D, Lee B, Andersen RA, Liu CY, Heydari P, Nenadic Z, Do AH. A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface. J Neural Eng 2019; 16:066043. [PMID: 31585451 DOI: 10.1088/1741-2552/ab4b0c] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices. Here, a prototype BMI system whose size and power consumption are comparable to those of fully implantable medical devices was designed and implemented, and its performance was tested at the benchtop and bedside. APPROACH A prototype of a fully implantable BMI system was designed and implemented as a miniaturized embedded system. This benchtop analogue was tested in its ability to acquire signals, train a decoder, perform online decoding, wirelessly control external devices, and operate independently on battery. Furthermore, performance metrics such as power consumption were benchmarked. MAIN RESULTS An analogue of a fully implantable BMI was fabricated with a miniaturized form factor. A patient undergoing epilepsy surgery evaluation with an electrocorticogram (ECoG) grid implanted over the primary motor cortex was recruited to operate the system. Seven online runs were performed with an average binary state decoding accuracy of 87.0% (lag optimized, or 85.0% at fixed latency). The system was powered by a wirelessly rechargeable battery, consumed ∼150 mW, and operated for >60 h on a single battery cycle. SIGNIFICANCE The BMI analogue achieved immediate and accurate decoding of ECoG signals underlying hand movements. A wirelessly rechargeable battery and other supporting functions allowed the system to function independently. In addition to the small footprint and acceptable power and heat dissipation, these results suggest that fully implantable BMI systems are feasible.
Collapse
Affiliation(s)
- Po T Wang
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
21
|
Buccelli S, Bornat Y, Colombi I, Ambroise M, Martines L, Pasquale V, Bisio M, Tessadori J, Nowak P, Grassia F, Averna A, Tedesco M, Bonifazi P, Difato F, Massobrio P, Levi T, Chiappalone M. A Neuromorphic Prosthesis to Restore Communication in Neuronal Networks. iScience 2019; 19:402-414. [PMID: 31421595 PMCID: PMC6706626 DOI: 10.1016/j.isci.2019.07.046] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/18/2019] [Accepted: 07/29/2019] [Indexed: 12/20/2022] Open
Abstract
Recent advances in bioelectronics and neural engineering allowed the development of brain machine interfaces and neuroprostheses, capable of facilitating or recovering functionality in people with neurological disability. To realize energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation systems for brain repair. We demonstrate here a real-time hardware neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or missing. We used in vitro modular cell cultures to mimic the mutual interaction between neuronal assemblies and created a focal lesion to functionally disconnect the two populations. Then, we employed our neuromorphic prosthesis for bidirectional bridging to artificially reconnect two disconnected neuronal modules and for hybrid bidirectional bridging to replace the activity of one module with a real-time hardware neuromorphic Spiking Neural Network. Our neuroprosthetic system opens avenues for the exploitation of neuromorphic-based devices in bioelectrical therapeutics for health care.
Collapse
Affiliation(s)
- Stefano Buccelli
- Rehab Technologies IIT-INAIL Lab, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child science (DINOGMI), University of Genova, L.go P. Daneo 3, 16132 Genova, Italy; Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Yannick Bornat
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, 351 Cours de la Libération, 33405 Talence Cedex, France
| | - Ilaria Colombi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child science (DINOGMI), University of Genova, L.go P. Daneo 3, 16132 Genova, Italy; Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Matthieu Ambroise
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, 351 Cours de la Libération, 33405 Talence Cedex, France
| | - Laura Martines
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Via all'Opera Pia 13, 16145 Genova, Italy
| | - Valentina Pasquale
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Marta Bisio
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Department of Neurosciences, University of Padova, Via Nicolò Giustiniani 5, 35128 Padova, Italy
| | - Jacopo Tessadori
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Przemysław Nowak
- Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Via all'Opera Pia 13, 16145 Genova, Italy; Institute of Information Technology, Lodz University of Technology, ul. Wolczanska 215, 90-924 Lodz, Poland
| | - Filippo Grassia
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, 351 Cours de la Libération, 33405 Talence Cedex, France; University of Picardie Jules Verne, Laboratory of Innovative Technologies (LTI, EA 3899), Avenue des Facultés, Le Bailly, 80025 Amiens, France
| | - Alberto Averna
- Rehab Technologies IIT-INAIL Lab, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child science (DINOGMI), University of Genova, L.go P. Daneo 3, 16132 Genova, Italy; Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Mariateresa Tedesco
- Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Via all'Opera Pia 13, 16145 Genova, Italy
| | - Paolo Bonifazi
- School of Physics and Astronomy, Tel Aviv University, 69978 Tel Aviv, Israel; Computational Neuroimaging Laboratory, Biocruces Health Research Institute, Hospital Universitario Cruces, Baracaldo, Vizcaya 48903, Spain; Ikerbasque: The Basque Foundation for Science, Bilbao, Bizkaia 48013, Spain
| | - Francesco Difato
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics, System Engineering (DIBRIS), University of Genova, Via all'Opera Pia 13, 16145 Genova, Italy
| | - Timothée Levi
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, 351 Cours de la Libération, 33405 Talence Cedex, France; LIMMS CNRS-IIS, The University of Tokyo, 153-8505 Tokyo, Japan.
| | - Michela Chiappalone
- Rehab Technologies IIT-INAIL Lab, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy.
| |
Collapse
|
22
|
Sauter-Starace F, Ratel D, Cretallaz C, Foerster M, Lambert A, Gaude C, Costecalde T, Bonnet S, Charvet G, Aksenova T, Mestais C, Benabid AL, Torres-Martinez N. Long-Term Sheep Implantation of WIMAGINE ®, a Wireless 64-Channel Electrocorticogram Recorder. Front Neurosci 2019; 13:847. [PMID: 31496929 PMCID: PMC6712079 DOI: 10.3389/fnins.2019.00847] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 07/30/2019] [Indexed: 11/23/2022] Open
Abstract
This article deals with the long-term preclinical validation of WIMAGINE® (Wireless Implantable Multi-channel Acquisition system for Generic Interface with Neurons), a 64-channel wireless implantable recorder that measures the electrical activity at the cortical surface (electrocorticography, ECoG). The WIMAGINE® implant was designed for chronic wireless neuronal signal acquisition, to be used e.g., as an intracranial Brain–Computer Interface (BCI) for severely motor-impaired patients. Due to the size and shape of WIMAGINE®, sheep appeared to be the best animal model on which to carry out long-term in vivo validation. The devices were implanted in two sheep for a follow-up period of 10 months, including idle state cortical recordings and Somato-Sensory Evoked Potential (SSEP) sessions. ECoG and SSEP demonstrated relatively stable behavior during the 10-month observation period. Information recorded from the SensoriMotor Cortex (SMC) showed an SSEP phase reversal, indicating the cortical site of the sensorimotor activity was retained after 10 months of contact. Based on weekly recordings of raw ECoG signals, the effective bandwidth was in the range of 230 Hz for both animals and remarkably stable over time, meaning preservation of the high frequency bands valuable for decoding of the brain activity using BCIs. The power spectral density (in dB/Hz), on a log scale, was of the order of 2.2, –4.5 and –18 for the frequency bands (10–40), (40–100), and (100–200) Hz, respectively. The outcome of this preclinical work is the first long-term in vivo validation of the WIMAGINE® implant, highlighting its ability to record the brain electrical activity through the dura mater and to send wireless digitized data to the external base station. Apart from local adhesion of the dura to the skull, the neurosurgeon did not face any difficulty in the implantation of the WIMAGINE® device and post-mortem analysis of the brain revealed no side effect related to the implantation. We also report on the reliability of the system; including the implantable device, the antennas module and the external base station.
Collapse
Affiliation(s)
| | - D Ratel
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - C Cretallaz
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - M Foerster
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - A Lambert
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - C Gaude
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - T Costecalde
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - S Bonnet
- Univ. Grenoble Alpes, CEA, Leti, DTBS, Grenoble, France
| | - G Charvet
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - T Aksenova
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | - C Mestais
- Univ. Grenoble Alpes, CEA, Leti, CLINATEC, Grenoble, France
| | | | | |
Collapse
|
23
|
Stieglitz T. Why Neurotechnologies? About the Purposes, Opportunities and Limitations of Neurotechnologies in Clinical Applications. NEUROETHICS-NETH 2019. [DOI: 10.1007/s12152-019-09406-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
AbstractNeurotechnologies describe a field of science and engineering in which the nervous system is interfaced with technical devices. Fundamental research is conducted to explore functions of the brain, decipher the neural code and get a better understanding of diseases and disorders. Risk benefit assessment has been well established in all medical disciplines to treat patients best possible while minimizing jeopardizing their lives by the interventions. Is this set of assessment rules sufficient when the brain will be interfaced with a technical system and is this assessment enough? How will these new technologies change personality and society? This article will shortly review different stakeholders’ opinions and their expectation in the field, assembles information the state-of-the art in medical applications of neurotechnological implants and describes and assesses the fundamental technologies that are used to build up these implants starting with essential requirements of technical materials in contact with living tissue. The different paragraphs guide the reader through the main aspects of neurotechnologies and lay a foundation of knowledge to be able to contribute to the discussion in which cases implants will be beneficial and in which cases we should express serious concerns.
Collapse
|
24
|
Lancashire HT, Jiang D, Demosthenous A, Donaldson N. An ASIC for Recording and Stimulation in Stacked Microchannel Neural Interfaces. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:259-270. [PMID: 30624225 DOI: 10.1109/tbcas.2019.2891284] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
This paper presents an active microchannel neural interface (MNI) using seven stacked application specific integrated circuits (ASICs). The approach provides a solution to the present problem of interconnect density in three-dimensional (3-D) MNIs. The 4 mm2 ASIC is implemented in 0.35 μm high-voltage CMOS technology. Each ASIC is the base for seven microchannels each with three electrodes in a pseudo-tripolar arrangement. Multiplexing allows stimulating or recording from any one of 49 channels, across seven ASICs. Connections to the ASICs are made with a five-line parallel bus. Current controlled biphasic stimulation from 5 to 500 μA has been demonstrated with switching between channels and ASICs. The high-voltage technology gives a compliance of 40 V for stimulation, appropriate for the high impedances within microchannels. High frequency biphasic stimulation, up to 40 kHz is achieved, suitable for reversible high frequency nerve blockades. Recording has been demonstrated with mV level signals; common-mode inputs are differentially distorted and limit the CMRR to 40 dB. The ASIC has been used in vitro in conjunction with an oversize (2 mm diameter) microchannel in phosphate buffered saline, demonstrating attenuation of interference from outside the microchannel and tripolar recording of signals from within the microchannel. By using five-lines for 49 active microchannels the device overcomes limitations when connecting many electrodes in a 3-D miniaturized nerve interface.
Collapse
|
25
|
Robinson JT, Pohlmeyer E, Gather MC, Kemere C, Kitching JE, Malliaras GG, Marblestone A, Shepard KL, Stieglitz T, Xie C. Developing Next-generation Brain Sensing Technologies - A Review. IEEE SENSORS JOURNAL 2019; 19:10.1109/jsen.2019.2931159. [PMID: 32116472 PMCID: PMC7047830 DOI: 10.1109/jsen.2019.2931159] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Advances in sensing technology raise the possibility of creating neural interfaces that can more effectively restore or repair neural function and reveal fundamental properties of neural information processing. To realize the potential of these bioelectronic devices, it is necessary to understand the capabilities of emerging technologies and identify the best strategies to translate these technologies into products and therapies that will improve the lives of patients with neurological and other disorders. Here we discuss emerging technologies for sensing brain activity, anticipated challenges for translation, and perspectives for how to best transition these technologies from academic research labs to useful products for neuroscience researchers and human patients.
Collapse
Affiliation(s)
- Jacob T. Robinson
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Pohlmeyer
- John Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA
| | - Malte C. Gather
- SUPA, School of Physics & Astronomy, University of St Andrews, St Andrews KY16 9SS Scotland, UK
| | - Caleb Kemere
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - John E. Kitching
- Time and Frequency Division, NIST, 325 Broadway, Boulder, Colorado 80305, USA
| | - George G. Malliaras
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK
| | - Adam Marblestone
- MIT Media Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Kenneth L. Shepard
- Department of Electrical Engineering, Columbia University, New York, NY 10027, USA
| | - Thomas Stieglitz
- Institute of Microsystem Technology, Laboratory for Biomedical Microtechnology, D-79110 Freiburg, Germany
- Cluster of Excellence BrainLinks-BrainTools, University of Freiburg, 79110 Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
| | - Chong Xie
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| |
Collapse
|
26
|
Gkogkidis CA, Bentler C, Wang X, Gierthmuehlen M, Scheiwe C, Schmitz HC, Haberstroh J, Stieglitz T, Ball T. Neurophysiological Evaluation of a Customizable μECoG-based Wireless Brain Implant. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:2953-2956. [PMID: 30441019 DOI: 10.1109/embc.2018.8513044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The number of implantable bidirectional neural interfaces available for neuroscientific research applications is still limited, despite the rapidly increasing number of customized components. We previously reported on how to translate available components into "ready-to-use" wireless implantable systems utilizing components off-the-shelf (COTS). The aim of the present study was to verify the viability of a micro-electrocorticographic ($\mu $ECoG) device built by this approach. Functionality for both neural recording and stimulation was evaluated in an ovine animal model using acoustic stimuli and cortical electrical stimulation, respectively. We show that auditory evoked responses were reliably recorded in both time and frequency domain and present data that demonstrates the cortical electrical stimulation functionality. The successful recording of neuronal activity suggests that the device can compete with existing implantable systems as a neurotechnological research tool.
Collapse
|
27
|
Hoch K, Pothof F, Becker F, Paul O, Ruther P. Development, Modeling, Fabrication, and Characterization of a Magnetic, Micro-Spring-Suspended System for the Safe Electrical Interconnection of Neural Implants. MICROMACHINES 2018; 9:mi9090424. [PMID: 30424357 PMCID: PMC6187687 DOI: 10.3390/mi9090424] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 08/20/2018] [Accepted: 08/21/2018] [Indexed: 11/29/2022]
Abstract
The development of innovative tools for neuroscientific research is based on in vivo tests typically applied to small animals. Most often, the interfacing of neural probes relies on commercially available connector systems which are difficult to handle during connection, particularly when freely behaving animals are involved. Furthermore, the connectors often exert high mechanical forces during plugging and unplugging, potentially damaging the fragile bone structure. In order to facilitate connector usage and increase the safety of laboratory animals, we developed a new magnetic connector system circumventing the drawbacks of existing tools. The connector system uses multiple magnet pairs and spring-suspended electrical contact pads realized using micro-electromechanical systems (MEMS) technologies. While the contact pad suspension increases the system tolerance in view of geometrical variations, we achieved a reliable self-alignment of the connector parts at ±50 µm provided by the specifically oriented magnet pairs and without the need of alignment pins. While connection forces are negligible, we can adjust the forces during connector release by modifying the magnet distance. With the connector test structures developed here, we achieved an electrical connection yield of 100%. Based on these findings, we expect that in vivo experiments with freely behaving animals will be facilitated with improved animal safety.
Collapse
Affiliation(s)
- Katharina Hoch
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany.
| | - Frederick Pothof
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany.
| | - Felix Becker
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany.
| | - Oliver Paul
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany.
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, 79110 Freiburg, Germany.
| | - Patrick Ruther
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110 Freiburg, Germany.
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, 79110 Freiburg, Germany.
| |
Collapse
|
28
|
Schaeffer MC, Aksenova T. Data-Driven Transducer Design and Identification for Internally-Paced Motor Brain Computer Interfaces: A Review. Front Neurosci 2018; 12:540. [PMID: 30158847 PMCID: PMC6104172 DOI: 10.3389/fnins.2018.00540] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 07/17/2018] [Indexed: 11/13/2022] Open
Abstract
Brain-Computer Interfaces (BCIs) are systems that establish a direct communication pathway between the users' brain activity and external effectors. They offer the potential to improve the quality of life of motor-impaired patients. Motor BCIs aim to permit severely motor-impaired users to regain limb mobility by controlling orthoses or prostheses. In particular, motor BCI systems benefit patients if the decoded actions reflect the users' intentions with an accuracy that enables them to efficiently interact with their environment. One of the main challenges of BCI systems is to adapt the BCI's signal translation blocks to the user to reach a high decoding accuracy. This paper will review the literature of data-driven and user-specific transducer design and identification approaches and it focuses on internally-paced motor BCIs. In particular, continuous kinematic biomimetic and mental-task decoders are reviewed. Furthermore, static and dynamic decoding approaches, linear and non-linear decoding, offline and real-time identification algorithms are considered. The current progress and challenges related to the design of clinical-compatible motor BCI transducers are additionally discussed.
Collapse
Affiliation(s)
| | - Tetiana Aksenova
- CEA, LETI, CLINATEC, MINATEC Campus, Université Grenoble Alpes, Grenoble, France
| |
Collapse
|
29
|
Rudmann L, Alt MT, Ashouri Vajari D, Stieglitz T. Integrated optoelectronic microprobes. Curr Opin Neurobiol 2018; 50:72-82. [PMID: 29414738 DOI: 10.1016/j.conb.2018.01.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Revised: 01/08/2018] [Accepted: 01/17/2018] [Indexed: 12/31/2022]
Abstract
Optogenetics opened not only new exciting opportunities to interrogate the nervous system but also requires adequate probes to facilitate these wishes. Therefore, a multidisciplinary effort is essential to match these technical opportunities with biological needs in order to establish a stable and functional material-tissue interface. This in turn can address an optical intervention of the genetically modified, light sensitive cells in the nervous system and recording of electrical signals from single cells and neuronal networks that result in behavioral changes. In this review, we present the state of the art of optoelectronic probes and assess advantages and challenges of the different design approaches. At first, we discuss mechanisms and processes at the material-tissue interface that influence the performance of optoelectronic probes in acute and chronic implantations. We classify optoelectronic probes by their property of delivering light to the tissue: by waveguides or by integrated light sources at the sites of intervention. Both approaches are discussed with respect to size, spatial resolution, opportunity to integrate electrodes for electrical recording and potential interactions with the target tissue. At last, we assess translational aspects of the state of the art. Long-term stability of probes and the opportunity to integrate them into fully implantable, wireless systems are a prerequisite for chronic applications and a transfer from fundamental neuroscientific studies into treatment options for diseases and clinical trials.
Collapse
Affiliation(s)
- L Rudmann
- Laboratory for Biomedical Microsystems, Department of Microsystems Engineering - IMTEK & BrainLinks-BrainTools Center, University of Freiburg, Georges-Koehler-Allee 102, 79110 Freiburg, Germany
| | - M T Alt
- Laboratory for Biomedical Microsystems, Department of Microsystems Engineering - IMTEK & BrainLinks-BrainTools Center, University of Freiburg, Georges-Koehler-Allee 102, 79110 Freiburg, Germany
| | - D Ashouri Vajari
- Laboratory for Biomedical Microsystems, Department of Microsystems Engineering - IMTEK & BrainLinks-BrainTools Center, University of Freiburg, Georges-Koehler-Allee 102, 79110 Freiburg, Germany
| | - T Stieglitz
- Laboratory for Biomedical Microsystems, Department of Microsystems Engineering - IMTEK & BrainLinks-BrainTools Center, University of Freiburg, Georges-Koehler-Allee 102, 79110 Freiburg, Germany.
| |
Collapse
|
30
|
Casimo K, Levinson LH, Zanos S, Gkogkidis CA, Ball T, Fetz E, Weaver KE, Ojemann JG. An interspecies comparative study of invasive electrophysiological functional connectivity. Brain Behav 2017; 7:e00863. [PMID: 29299382 PMCID: PMC5745242 DOI: 10.1002/brb3.863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 09/27/2017] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Resting-state connectivity patterns have been observed in humans and other mammal species, and can be recorded using a variety of different technologies. Functional connectivity has been previously compared between species using resting-state fMRI, but not in electrophysiological studies. METHODS We compared connectivity with implanted electrodes in humans (electrocorticography) to macaques and sheep (microelectrocorticography), which are capable of recording neural data at high frequencies with spatial precision. We specifically examined synchrony, implicated in functional integration between regions. RESULTS We found that connectivity strength was overwhelmingly similar in humans and monkeys for pairs of two different brain regions (prefrontal, motor, premotor, parietal), but differed more often within single brain regions. The two connectivity measures, correlation and phase locking value, were similar in most comparisons. Connectivity strength agreed more often between the species at higher frequencies. Where the species differed, monkey synchrony was stronger than human in all but one case. In contrast, human and sheep connectivity within somatosensory cortex diverged in almost all frequencies, with human connectivity stronger than sheep. DISCUSSION Our findings imply greater heterogeneity within regions in humans than in monkeys, but comparable functional interactions between regions in the two species. This suggests that monkeys may be effectively used to probe resting-state connectivity in humans, and that such findings can then be validated in humans. Although the discrepancy between humans and sheep is larger, we suggest that findings from sheep in highly invasive studies may be used to provide guidance for studies in other species.
Collapse
Affiliation(s)
- Kaitlyn Casimo
- Graduate Program in Neuroscience University of Washington Seattle WA USA.,Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA
| | | | - Stavros Zanos
- Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA.,Department of Physiology and Biophysics University of Washington Seattle WA USA.,Washington National Primate Research Center University of Washington Seattle WA USA.,Feinstein Institute for Medical Research New York City NY USA
| | - C Alexis Gkogkidis
- Translational Neurotechnology Laboratory Department of Neurosurgery Faculty of Medicine Medical Center - University of Freiburg Freiburg Germany.,Laboratory for Biomedical Microtechnology Department of Microsystems Engineering Faculty of Engineering University of Freiburg Freiburg Germany
| | - Tonio Ball
- Translational Neurotechnology Laboratory Department of Neurosurgery Faculty of Medicine Medical Center - University of Freiburg Freiburg Germany.,Laboratory for Biomedical Microtechnology Department of Microsystems Engineering Faculty of Engineering University of Freiburg Freiburg Germany
| | - Eberhard Fetz
- Graduate Program in Neuroscience University of Washington Seattle WA USA.,Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA.,Department of Physiology and Biophysics University of Washington Seattle WA USA.,Washington National Primate Research Center University of Washington Seattle WA USA
| | - Kurt E Weaver
- Graduate Program in Neuroscience University of Washington Seattle WA USA.,Department of Radiology University of Washington Seattle WA USA.,Integrated Brain Imaging Center University of Washington Seattle WA USA
| | - Jeffrey G Ojemann
- Graduate Program in Neuroscience University of Washington Seattle WA USA.,Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA.,Department of Neurological Surgery University of Washington Seattle WA USA.,Department of Neurological Surgery Seattle Children's Hospital Seattle WA USA
| |
Collapse
|