1
|
Yan T, Suzuki K, Kameda S, Maeda M, Mihara T, Hirata M. Chronic subdural electrocorticography in nonhuman primates by an implantable wireless device for brain-machine interfaces. Front Neurosci 2023; 17:1260675. [PMID: 37841689 PMCID: PMC10568031 DOI: 10.3389/fnins.2023.1260675] [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: 07/18/2023] [Accepted: 09/12/2023] [Indexed: 10/17/2023] Open
Abstract
Background Subdural electrocorticography (ECoG) signals have been proposed as a stable, good-quality source for brain-machine interfaces (BMIs), with a higher spatial and temporal resolution than electroencephalography (EEG). However, long-term implantation may lead to chronic inflammatory reactions and connective tissue encapsulation, resulting in a decline in signal recording quality. However, no study has reported the effects of the surrounding tissue on signal recording and device functionality thus far. Methods In this study, we implanted a wireless recording device with a customized 32-electrode-ECoG array subdurally in two nonhuman primates for 15 months. We evaluated the neural activities recorded from and wirelessly transmitted to the devices and the chronic tissue reactions around the electrodes. In addition, we measured the gain factor of the newly formed ventral fibrous tissue in vivo. Results Time-frequency analyses of the acute and chronic phases showed similar signal features. The average root mean square voltage and power spectral density showed relatively stable signal quality after chronic implantation. Histological examination revealed thickening of the reactive tissue around the electrode array; however, no evident inflammation in the cortex. From gain factor analysis, we found that tissue proliferation under electrodes reduced the amplitude power of signals. Conclusion This study suggests that subdural ECoG may provide chronic signal recordings for future clinical applications and neuroscience research. This study also highlights the need to reduce proliferation of reactive tissue ventral to the electrodes to enhance long-term stability.
Collapse
Affiliation(s)
- Tianfang Yan
- Department of Neurological Diagnosis and Restoration, Osaka University Graduate School of Medicine, Suita, Japan
| | | | - Seiji Kameda
- Department of Neurological Diagnosis and Restoration, Osaka University Graduate School of Medicine, Suita, Japan
| | - Masashi Maeda
- Candidate Discovery Science Labs, Astellas Pharma Inc., Tokyo, Japan
| | - Takuma Mihara
- Candidate Discovery Science Labs, Astellas Pharma Inc., Tokyo, Japan
| | - Masayuki Hirata
- Department of Neurological Diagnosis and Restoration, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
- Global Center for Medical Engineering and Informatics, Osaka University, Suita, Japan
| |
Collapse
|
2
|
Sun Y, Shen A, Du C, Sun J, Chen X, Gao X. A Real-Time Non-Implantation Bi-Directional Brain-Computer Interface Solution Without Stimulation Artifacts. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3566-3575. [PMID: 37665696 DOI: 10.1109/tnsre.2023.3311750] [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: 09/06/2023]
Abstract
The non-implantation bi-directional brain-computer interface (BCI) is a neural interface technology that enables direct two-way communication between the brain and the external world by both "reading" neural signals and "writing" stimulation patterns to the brain. This technology has vast potential applications, such as improving the quality of life for individuals with neurological and mental illnesses and even expanding the boundaries of human capabilities. Nonetheless, non-implantation bi-directional BCIs face challenges in generating real-time feedback and achieving compatibility between stimulation and recording. These issues arise due to the considerable overlap between electrical stimulation frequencies and electrophysiological recording frequencies, as well as the impediment caused by the skull to the interaction of external and internal currents. To address those challenges, this work proposes a novel solution that combines the temporal interference stimulation paradigm and minimally invasive skull modification. A longitudinal animal experiment has preliminarily validated the feasibility of the proposed method. In signal recording experiments, the average impedance of our scheme decreased by 4.59 kΩ , about 67%, compared to the conventional technique at 18 points. The peak-to-peak value of the Somatosensory Evoked Potential increased by 8%. Meanwhile, the signal-to-noise ratio of Steady-State Visual Evoked Potential increased by 5.13 dB, and its classification accuracy increased by 44%. The maximum bandwidth of the resting state rose by 63%. In electrical stimulation experiments, the signal-to-noise ratio of the low-frequency response evoked by our scheme rose by 8.04 dB, and no stimulation artifacts were generated. The experimental results show that signal quality in acquisition has significantly improved, and frequency-band isolation eliminates stimulation artifacts at the source. The acquisition and stimulation pathways are real-time compatible in this non-implantation bi-directional BCI solution, which can provide technical support and theoretical guidance for creating closed-loop adaptive systems coupled with particular application scenarios in the future.
Collapse
|
3
|
Nielsen JM, Kristinsdóttir ÁE, Zibrandtsen IC, Masulli P, Ballegaard M, Andersen TS, Kjær TW. Out-of-hospital multimodal seizure detection: a pilot study. BMJ Neurol Open 2023; 5:e000442. [PMID: 37547054 PMCID: PMC10401242 DOI: 10.1136/bmjno-2023-000442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/14/2023] [Indexed: 08/08/2023] Open
Abstract
Background Out-of-hospital seizure detection aims to provide clinicians and patients with objective seizure documentation in efforts to improve the clinical management of epilepsy. In-patient studies have found that combining different modalities helps improve the seizure detection accuracy. In this study, the objective was to evaluate the viability of out-of-hospital seizure detection using wearable ECG, accelerometry and behind-the-ear electroencephalography (EEG). Furthermore, we examined the signal quality of out-of-hospital EEG recordings. Methods Seventeen patients were monitored for up to 5 days. A support vector machine based seizure detection algorithm was applied using both in-patient seizures and out-of-hospital electrographic seizures in one patient. To assess the content of noise in the EEG signal, we compared the root-mean-square (RMS) of the recordings to a reference threshold derived from manually categorised segments of EEG recordings. Results In total 1427 hours of continuous EEG was recorded. In one patient, we identified 15 electrographic focal impaired awareness seizures with a motor component. After training our algorithm on in-patient data, we found a sensitivity of 91% and a false alarm rate (FAR) of 18/24 hours for the detection of out-of-hospital seizures using a combination of EEG and ECG recordings. We estimated that 30.1% of the recorded EEG signal was physiological EEG, with an RMS value within the reference threshold. Conclusion We found that detection of out-of-hospital focal impaired awareness seizures with a motor component is possible and that applying multiple modalities improves the diagnostic accuracy compared with unimodal EEG. However, significant challenges remain regarding a high FAR and that only 30.1% of the EEG data represented usable signal.
Collapse
Affiliation(s)
- Jonas Munch Nielsen
- Department of Neurology, Zealand University Hospital Roskilde, Roskilde, Denmark
- Department of Clinical Medicine, University of Copenhagen, Kobenhavn, Denmark
| | - Ástrós Eir Kristinsdóttir
- Department of Neurology, Zealand University Hospital Roskilde, Roskilde, Denmark
- Department of Applied Mathematics and Computer Science, Technical University, Lyngby, Denmark
| | | | - Paolo Masulli
- Department of Applied Mathematics and Computer Science, Technical University, Lyngby, Denmark
- iMotions A/S, Copenhagen K, Denmark
| | - Martin Ballegaard
- Department of Neurology, Zealand University Hospital Roskilde, Roskilde, Denmark
- Department of Clinical Medicine, University of Copenhagen, Kobenhavn, Denmark
| | - Tobias Søren Andersen
- Department of Applied Mathematics and Computer Science, Technical University, Lyngby, Denmark
| | - Troels Wesenberg Kjær
- Department of Neurology, Zealand University Hospital Roskilde, Roskilde, Denmark
- Department of Clinical Medicine, University of Copenhagen, Kobenhavn, Denmark
| |
Collapse
|
4
|
Branco MP, Geukes SH, Aarnoutse EJ, Ramsey NF, Vansteensel MJ. Nine decades of electrocorticography: A comparison between epidural and subdural recordings. Eur J Neurosci 2023; 57:1260-1288. [PMID: 36843389 DOI: 10.1111/ejn.15941] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 02/10/2023] [Accepted: 02/18/2023] [Indexed: 02/28/2023]
Abstract
In recent years, electrocorticography (ECoG) has arisen as a neural signal recording tool in the development of clinically viable neural interfaces. ECoG electrodes are generally placed below the dura mater (subdural) but can also be placed on top of the dura (epidural). In deciding which of these modalities best suits long-term implants, complications and signal quality are important considerations. Conceptually, epidural placement may present a lower risk of complications as the dura is left intact but also a lower signal quality due to the dura acting as a signal attenuator. The extent to which complications and signal quality are affected by the dura, however, has been a matter of debate. To improve our understanding of the effects of the dura on complications and signal quality, we conducted a literature review. We inventorized the effect of the dura on signal quality, decodability and longevity of acute and chronic ECoG recordings in humans and non-human primates. Also, we compared the incidence and nature of serious complications in studies that employed epidural and subdural ECoG. Overall, we found that, even though epidural recordings exhibit attenuated signal amplitude over subdural recordings, particularly for high-density grids, the decodability of epidural recorded signals does not seem to be markedly affected. Additionally, we found that the nature of serious complications was comparable between epidural and subdural recordings. These results indicate that both epidural and subdural ECoG may be suited for long-term neural signal recordings, at least for current generations of clinical and high-density ECoG grids.
Collapse
Affiliation(s)
- Mariana P Branco
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Simon H Geukes
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Erik J Aarnoutse
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Nick F Ramsey
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Mariska J Vansteensel
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| |
Collapse
|
5
|
Mitchell P, Lee SCM, Yoo PE, Morokoff A, Sharma RP, Williams DL, MacIsaac C, Howard ME, Irving L, Vrljic I, Williams C, Bush S, Balabanski AH, Drummond KJ, Desmond P, Weber D, Denison T, Mathers S, O’Brien TJ, Mocco J, Grayden DB, Liebeskind DS, Opie NL, Oxley TJ, Campbell BCV. Assessment of Safety of a Fully Implanted Endovascular Brain-Computer Interface for Severe Paralysis in 4 Patients: The Stentrode With Thought-Controlled Digital Switch (SWITCH) Study. JAMA Neurol 2023; 80:270-278. [PMID: 36622685 PMCID: PMC9857731 DOI: 10.1001/jamaneurol.2022.4847] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/18/2022] [Indexed: 01/10/2023]
Abstract
Importance Brain-computer interface (BCI) implants have previously required craniotomy to deliver penetrating or surface electrodes to the brain. Whether a minimally invasive endovascular technique to deliver recording electrodes through the jugular vein to superior sagittal sinus is safe and feasible is unknown. Objective To assess the safety of an endovascular BCI and feasibility of using the system to control a computer by thought. Design, Setting, and Participants The Stentrode With Thought-Controlled Digital Switch (SWITCH) study, a single-center, prospective, first in-human study, evaluated 5 patients with severe bilateral upper-limb paralysis, with a follow-up of 12 months. From a referred sample, 4 patients with amyotrophic lateral sclerosis and 1 with primary lateral sclerosis met inclusion criteria and were enrolled in the study. Surgical procedures and follow-up visits were performed at the Royal Melbourne Hospital, Parkville, Australia. Training sessions were performed at patients' homes and at a university clinic. The study start date was May 27, 2019, and final follow-up was completed January 9, 2022. Interventions Recording devices were delivered via catheter and connected to subcutaneous electronic units. Devices communicated wirelessly to an external device for personal computer control. Main Outcomes and Measures The primary safety end point was device-related serious adverse events resulting in death or permanent increased disability. Secondary end points were blood vessel occlusion and device migration. Exploratory end points were signal fidelity and stability over 12 months, number of distinct commands created by neuronal activity, and use of system for digital device control. Results Of 4 patients included in analyses, all were male, and the mean (SD) age was 61 (17) years. Patients with preserved motor cortex activity and suitable venous anatomy were implanted. Each completed 12-month follow-up with no serious adverse events and no vessel occlusion or device migration. Mean (SD) signal bandwidth was 233 (16) Hz and was stable throughout study in all 4 patients (SD range across all sessions, 7-32 Hz). At least 5 attempted movement types were decoded offline, and each patient successfully controlled a computer with the BCI. Conclusions and Relevance Endovascular access to the sensorimotor cortex is an alternative to placing BCI electrodes in or on the dura by open-brain surgery. These final safety and feasibility data from the first in-human SWITCH study indicate that it is possible to record neural signals from a blood vessel. The favorable safety profile could promote wider and more rapid translation of BCI to people with paralysis. Trial Registration ClinicalTrials.gov Identifier: NCT03834857.
Collapse
Affiliation(s)
- Peter Mitchell
- Department of Radiology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Sarah C. M. Lee
- Neurology, Calvary Healthcare Bethlehem, Parkdale, Australia
| | | | - Andrew Morokoff
- Parkville Neurosurgery, The University of Melbourne, Royal Melbourne Hospital, Parkville, Australia
| | - Rahul P. Sharma
- Stanford Healthcare Cardiovascular Medicine, Stanford University, Stanford, California
| | - Daryl L. Williams
- Department of Anaesthesia and Pain Management, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Christopher MacIsaac
- Intensive Care Department, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Mark E. Howard
- Victorian Respiratory Support Service, Austin Health, Heidelberg, Australia
| | - Lou Irving
- Peter MacCallum Cancer Centre, The University of Melbourne, The Royal Melbourne Hospital, Melbourne, Australia
| | - Ivan Vrljic
- Department of Radiology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Cameron Williams
- Department of Neurology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Steven Bush
- Department of Neurology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Anna H. Balabanski
- Department of Neurology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
- Melbourne Brain Centre, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
- Department of Neuroscience, Alfred Brain, Alfred Health, Melbourne, Australia
| | - Katharine J. Drummond
- Department of Neurosurgery, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Patricia Desmond
- Department of Radiology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| | - Douglas Weber
- Department of Biomedical Engineering, College of Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Timothy Denison
- Institute of Biomedical Engineering, The University of Oxford, Oxford, United Kingdom
| | - Susan Mathers
- Neurology, Calvary Healthcare Bethlehem, Parkdale, Australia
| | - Terence J. O’Brien
- Department of Neurology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
- Department of Neuroscience, The Central Clinical School, Monash University and Alfred Health, Melbourne, Australia
| | - J. Mocco
- Department of Neurosurgery, Klingenstein Clinical Center, The Mount Sinai Hospital, New York, New York
| | - David B. Grayden
- Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, Australia
| | - David S. Liebeskind
- UCLA Comprehensive Stroke Center, Department of Neurology, University of California, Los Angeles
| | - Nicholas L. Opie
- Vascular Bionics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, Australia
- Synchron, Carlton, Australia
| | - Thomas J. Oxley
- Synchron Inc, New York, New York
- Vascular Bionics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, Australia
| | - Bruce C. V. Campbell
- Department of Neurology, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
- Melbourne Brain Centre, The University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia
| |
Collapse
|
6
|
Sun Y, Shen A, Sun J, Du C, Chen X, Wang Y, Pei W, Gao X. Minimally Invasive Local-Skull Electrophysiological Modification With Piezoelectric Drill. IEEE Trans Neural Syst Rehabil Eng 2022; 30:2042-2051. [PMID: 35857723 DOI: 10.1109/tnsre.2022.3192543] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The research on non-invasive BCI is nowadays hitting the bottleneck due to the humble quality of scalp EEG signals. Whereas invasive solutions that offer higher signal quality in contrast are suffocated in their spreading because of the potential surgical complication and health risks caused by electrode implantation. Therefore, it puts forward a necessity to explore a scheme that could both collect high-quality EEG signals and guarantee high-level operation safety.This study proposed a Minimally Invasive Local-skull Electrophysiological Modification method to improve scalp EEG signals qualities at specific brain regions. Six eight-month-old SD rats were used for in vivo verification experiment. A hole with a diameter of about 500 micrometers was drilled in the skull above the visual cortex of rats. Significant changes in rsEEG and SSVEP signals before and after modification were observed. After modification, the skull impedance of rats decreases by about 84 %, the average maximum bandwidth of rsEEG increase by 57 %, and the broadband SNR of SSVEP is increased by 5.13 dB. The time of piezoelectric drilling operation is strictly controlled under 30 seconds for each rat to prevent possible brain damage from overheating. Compared with traditional invasive procedures such as ECoG, Minimally Invasive Local-skull Electrophysiological Modification operation time is shorter and no electrode implantation is needed while it remarkably boosts the scalp EEG signal quality. This technical solution has the potential to replace the use of ECoG in certain application scenarios and further invigorate studies in the field of scalp EEG in the future.
Collapse
|
7
|
Fang J, Huang S, Liu F, He G, Li X, Huang X, Chen HJ, Xie X. Semi-Implantable Bioelectronics. NANO-MICRO LETTERS 2022; 14:125. [PMID: 35633391 PMCID: PMC9148344 DOI: 10.1007/s40820-022-00818-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 02/09/2022] [Indexed: 06/15/2023]
Abstract
Developing techniques to effectively and real-time monitor and regulate the interior environment of biological objects is significantly important for many biomedical engineering and scientific applications, including drug delivery, electrophysiological recording and regulation of intracellular activities. Semi-implantable bioelectronics is currently a hot spot in biomedical engineering research area, because it not only meets the increasing technical demands for precise detection or regulation of biological activities, but also provides a desirable platform for externally incorporating complex functionalities and electronic integration. Although there is less definition and summary to distinguish it from the well-reviewed non-invasive bioelectronics and fully implantable bioelectronics, semi-implantable bioelectronics have emerged as highly unique technology to boost the development of biochips and smart wearable device. Here, we reviewed the recent progress in this field and raised the concept of "Semi-implantable bioelectronics", summarizing the principle and strategies of semi-implantable device for cell applications and in vivo applications, discussing the typical methodologies to access to intracellular environment or in vivo environment, biosafety aspects and typical applications. This review is meaningful for understanding in-depth the design principles, materials fabrication techniques, device integration processes, cell/tissue penetration methodologies, biosafety aspects, and applications strategies that are essential to the development of future minimally invasive bioelectronics.
Collapse
Affiliation(s)
- Jiaru Fang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Shuang Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Fanmao Liu
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Gen He
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Xiangling Li
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Xinshuo Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Hui-Jiuan Chen
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China
| | - Xi Xie
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China.
| |
Collapse
|
8
|
Pandarinath C, Bensmaia SJ. The science and engineering behind sensitized brain-controlled bionic hands. Physiol Rev 2022; 102:551-604. [PMID: 34541898 PMCID: PMC8742729 DOI: 10.1152/physrev.00034.2020] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 09/07/2021] [Accepted: 09/13/2021] [Indexed: 12/13/2022] Open
Abstract
Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.
Collapse
Affiliation(s)
- Chethan Pandarinath
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia
- Department of Neurosurgery, Emory University, Atlanta, Georgia
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois
- Grossman Institute for Neuroscience, Quantitative Biology, and Human Behavior, University of Chicago, Chicago, Illinois
| |
Collapse
|
9
|
Kiang L, Woodington B, Carnicer-Lombarte A, Malliaras G, Barone DG. Spinal cord bioelectronic interfaces: opportunities in neural recording and clinical challenges. J Neural Eng 2022; 19. [PMID: 35320780 DOI: 10.1088/1741-2552/ac605f] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 03/23/2022] [Indexed: 11/11/2022]
Abstract
Bioelectronic stimulation of the spinal cord has demonstrated significant progress in restoration of motor function in spinal cord injury (SCI). The proximal, uninjured spinal cord presents a viable target for the recording and generation of control signals to drive targeted stimulation. Signals have been directly recorded from the spinal cord in behaving animals and correlated with limb kinematics. Advances in flexible materials, electrode impedance and signal analysis will allow SCR to be used in next-generation neuroprosthetics. In this review, we summarize the technological advances enabling progress in SCR and describe systematically the clinical challenges facing spinal cord bioelectronic interfaces and potential solutions, from device manufacture, surgical implantation to chronic effects of foreign body reaction and stress-strain mismatches between electrodes and neural tissue. Finally, we establish our vision of bi-directional closed-loop spinal cord bioelectronic bypass interfaces that enable the communication of disrupted sensory signals and restoration of motor function in SCI.
Collapse
Affiliation(s)
- Lei Kiang
- Orthopaedic Surgery, Singapore General Hospital, Outram Road, Singapore, Singapore, 169608, SINGAPORE
| | - Ben Woodington
- Department of Engineering, University of Cambridge, Electrical Engineering Division, 9 JJ Thomson Ave, Cambridge, Cambridge, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Alejandro Carnicer-Lombarte
- Clinical Neurosciences, University of Cambridge, Bioelectronics Laboratory, Cambridge, CB2 0PY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - George Malliaras
- University of Cambridge, University of Cambridge, Cambridge, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Damiano G Barone
- Department of Engineering, University of Cambridge, Electrical Engineering Division, 9 JJ Thomson Ave, Cambridge, Cambridge, Cambridgeshire, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| |
Collapse
|
10
|
Sethia M, Sahin M. The size of via holes influence the amplitude and selectivity of neural signals in Micro-ECoG arrays. BMC Biomed Eng 2022; 4:3. [PMID: 35313997 PMCID: PMC8935835 DOI: 10.1186/s42490-022-00060-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/07/2022] [Indexed: 11/11/2022] Open
Abstract
Background Electrocorticography (ECoG) arrays are commonly used to record the brain activity both in animal and human subjects. There is a lack of guidelines in the literature as to how the array geometry, particularly the via holes in the substrate, affects the recorded signals. A finite element (FE) model was developed to simulate the electric field generated by neurons located at different depths in the rat brain cortex and a micro ECoG array (μECoG) was placed on the pia surface for recording the neural signal. The array design chosen was a typical array of 8 × 8 circular (100 μm in diam.) contacts with 500 μm pitch. The size of the via holes between the recording contacts was varied to see the effect. Results The results showed that recorded signal amplitudes were reduced if the substrate was smaller than about four times the depth of the neuron in the gray matter. The signal amplitude profiles had dips around the via holes and the amplitudes were also lower at the contact sites as compared to the design without the holes; an effect that increased with the hole size. Another noteworthy result is that the spatial selectivity of the multi-contact recordings could be improved or reduced by the selection of the via hole sizes, and the effect depended on the distance between the neuron pair targeted for selective recording and its depth. Conclusions The results suggest that the via-hole size clearly affects the recorded neural signal amplitudes and it can be leveraged as a parameter to reduce the inter-channel correlation and thus maximize the information content of neural signals with μECoG arrays.
Collapse
|
11
|
Larzabal C, Bonnet S, Costecalde T, Auboiroux V, Charvet G, Chabardes S, Aksenova T, Sauter-Starace F. Long-term stability of the chronic epidural wireless recorder WIMAGINE in tetraplegic patients. J Neural Eng 2021; 18. [PMID: 34425566 DOI: 10.1088/1741-2552/ac2003] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 08/23/2021] [Indexed: 11/12/2022]
Abstract
Objective.The evaluation of the long-term stability of ElectroCorticoGram (ECoG) signals is an important scientific question as new implantable recording devices can be used for medical purposes such as Brain-Computer Interface (BCI) or brain monitoring.Approach.The long-term clinical validation of wireless implantable multi-channel acquisition system for generic interface with neurons (WIMAGINE), a wireless 64-channel epidural ECoG recorder was investigated. The WIMAGINE device was implanted in two quadriplegic patients within the context of a BCI protocol. This study focused on the ECoG signal stability in two patients bilaterally implanted in June 2017 (P1) and in November 2019 (P2).Methods. The ECoG signal was recorded at rest prior to each BCI session resulting in a 32 month and in a 14 month follow-up for P1 and P2 respectively. State-of-the-art signal evaluation metrics such as root mean square (RMS), the band power (BP), the signal to noise ratio (SNR), the effective bandwidth (EBW) and the spectral edge frequency (SEF) were used to evaluate stability of signal over the implantation time course. The time-frequency maps obtained from task-related motor activations were also studied to investigate the long-term selectivity of the electrodes.Mainresults.Based on temporal linear regressions, we report a limited decrease of the signal average level (RMS), spectral distribution (BP) and SNR, and a remarkable steadiness of the EBW and SEF. Time-frequency maps obtained during motor imagery, showed a high level of discrimination 1 month after surgery and also after 2 years.Conclusions.The WIMAGINE epidural device showed high stability over time. The signal evaluation metrics of two quadriplegic patients during 32 months and 14 months respectively provide strong evidence that this wireless implant is well-suited for long-term ECoG recording.Significance.These findings are relevant for the future of implantable BCIs, and could benefit other patients with spinal cord injury, amyotrophic lateral sclerosis, neuromuscular diseases or drug-resistant epilepsy.
Collapse
Affiliation(s)
| | - Stéphane Bonnet
- University Grenoble Alpes, CEA, LETI, DTBS, Grenoble 38000, France
| | - Thomas Costecalde
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Vincent Auboiroux
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Guillaume Charvet
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Stéphan Chabardes
- University Grenoble Alpes, Grenoble University Hospital, Grenoble 38000, France
| | - Tetiana Aksenova
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | | |
Collapse
|
12
|
Jeong UJ, Lee J, Chou N, Kim K, Shin H, Chae U, Yu HY, Cho IJ. A minimally invasive flexible electrode array for simultaneous recording of ECoG signals from multiple brain regions. LAB ON A CHIP 2021; 21:2383-2397. [PMID: 33955442 DOI: 10.1039/d1lc00117e] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The minimal invasiveness of electrocorticography (ECoG) enabled its widespread use in clinical areas as well as in neuroscience research. However, most existing ECoG arrays require that the entire surface area of the brain that is to be recorded be exposed through a large craniotomy. We propose a device that overcomes this limitation, i.e., a minimally invasive, polyimide-based flexible array of electrodes that can enable the recording of ECoG signals in multiple regions of the brain with minimal exposure of the surface of the brain. Magnetic force-assisted positioning of a flexible electrode array enables recording from distant brain regions with a small cranial window. Also, a biodegradable organic compound used for attaching a magnet on the electrodes allows simple retrieval of the magnet. We demonstrate with an in vivo chronic recording that an implanted ECoG electrode array can record ECoG signals from the visual cortex and the motor cortex during a rat's free behavior. Our results indicate that the proposed device induced minimal damage to the animal. We expect the proposed device to be utilized for experiments for large-scale brain circuit analyses as well as clinical applications for intra-operative monitoring of epileptic activity.
Collapse
Affiliation(s)
- Ui-Jin Jeong
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea. and School of Electrical Engineering, Korea University, Seoul, Republic of Korea
| | - Jungpyo Lee
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea.
| | - Namsun Chou
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea.
| | - Kanghwan Kim
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea.
| | - Hyogeun Shin
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea. and Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology (UST), Seoul, Republic of Korea
| | - Uikyu Chae
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea. and School of Electrical Engineering, Korea University, Seoul, Republic of Korea
| | - Hyun-Yong Yu
- School of Electrical Engineering, Korea University, Seoul, Republic of Korea
| | - Il-Joo Cho
- Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea. and Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology (UST), Seoul, Republic of Korea and School of Electrical and Electronics Engineering, Yonsei University, Seoul, Republic of Korea and Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, Republic of Korea
| |
Collapse
|
13
|
Monkey V1 epidural field potentials provide detailed information about stimulus location, size, shape, and color. Commun Biol 2021; 4:690. [PMID: 34099840 PMCID: PMC8184760 DOI: 10.1038/s42003-021-02207-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/11/2021] [Indexed: 02/05/2023] Open
Abstract
Brain signal recordings with epidural microarrays constitute a low-invasive approach for recording distributed neuronal signals. Epidural field potentials (EFPs) may serve as a safe and highly beneficial signal source for a variety of research questions arising from both basic and applied neuroscience. A wider use of these signals, however, is constrained by a lack of data on their specific information content. Here, we make use of the high spatial resolution and the columnar organization of macaque primary visual cortex (V1) to investigate whether and to what extent EFP signals preserve information about various visual stimulus features. Two monkeys were presented with different feature combinations of location, size, shape, and color, yielding a total of 375 stimulus conditions. Visual features were chosen to access different spatial levels of functional organization. We found that, besides being highly specific for locational information, EFPs were significantly modulated by small differences in size, shape, and color, allowing for high stimulus classification rates even at the single-trial level. The results support the notion that EFPs constitute a low-invasive, highly beneficial signal source for longer-term recordings for medical and basic research by showing that they convey detailed and reliable information about constituent features of activating stimuli.
Collapse
|
14
|
Ranjandish R, Schmid A. A Review of Microelectronic Systems and Circuit Techniques for Electrical Neural Recording Aimed at Closed-Loop Epilepsy Control. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5716. [PMID: 33050032 PMCID: PMC7583980 DOI: 10.3390/s20195716] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/07/2020] [Accepted: 10/02/2020] [Indexed: 12/21/2022]
Abstract
Closed-loop implantable electronics offer a new trend in therapeutic systems aimed at controlling some neurological diseases such as epilepsy. Seizures are detected and electrical stimulation applied to the brain or groups of nerves. To this aim, the signal recording chain must be very carefully designed so as to operate in low-power and low-latency, while enhancing the probability of correct event detection. This paper reviews the electrical characteristics of the target brain signals pertaining to epilepsy detection. Commercial systems are presented and discussed. Finally, the major blocks of the signal acquisition chain are presented with a focus on the circuit architecture and a careful attention to solutions to issues related to data acquisition from multi-channel arrays of cortical sensors.
Collapse
Affiliation(s)
- Reza Ranjandish
- Department of Information Technology and Electrical Engineering, ETH Zürich, CH-8092 Zürich, Switzerland;
| | - Alexandre Schmid
- Institute of Electrical Engineering, EPF Lausanne, CH-1015 Lausanne, Switzerland
| |
Collapse
|
15
|
Nasseri M, Nurse E, Glasstetter M, Böttcher S, Gregg NM, Laks Nandakumar A, Joseph B, Pal Attia T, Viana PF, Bruno E, Biondi A, Cook M, Worrell GA, Schulze-Bonhage A, Dümpelmann M, Freestone DR, Richardson MP, Brinkmann BH. Signal quality and patient experience with wearable devices for epilepsy management. Epilepsia 2020; 61 Suppl 1:S25-S35. [PMID: 32497269 DOI: 10.1111/epi.16527] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 04/14/2020] [Accepted: 04/14/2020] [Indexed: 01/24/2023]
Abstract
Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor-quality or corrupt data segments. In this study, commercially available wearable sensors were placed on patients with epilepsy undergoing in-hospital or in-home electroencephalographic (EEG) monitoring, and healthy volunteers. Empatica E4 and Biovotion Everion were used to record accelerometry (ACC), photoplethysmography (PPG), and electrodermal activity (EDA). Byteflies Sensor Dots were used to record ACC and PPG, the Activinsights GENEActiv watch to record ACC, and Epitel Epilog to record EEG data. PPG and EDA signals were recorded for multiple days, then epochs of high-quality, marginal-quality, or poor-quality data were visually identified by reviewers, and reviewer annotations were compared to automated signal quality measures. For ACC, the ratio of spectral power from 0.8 to 5 Hz to broadband power was used to separate good-quality signals from noise. For EDA, the rate of amplitude change and prevalence of sharp peaks significantly differentiated between good-quality data and noise. Spectral entropy was used to assess PPG and showed significant differences between good-, marginal-, and poor-quality signals. EEG data were evaluated using methods to identify a spectral noise cutoff frequency. Patients were asked to rate the usability and comfort of each device in several categories. Patients showed a significant preference for the wrist-worn devices, and the Empatica E4 device was preferred most often. Current wearable devices can provide high-quality data and are acceptable for routine use, but continued development is needed to improve data quality, consistency, and management, as well as acceptability to patients.
Collapse
Affiliation(s)
- Mona Nasseri
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ewan Nurse
- Seer Medical, Melbourne, Victoria, Australia.,Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Martin Glasstetter
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Sebastian Böttcher
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Nicholas M Gregg
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Boney Joseph
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Tal Pal Attia
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Pedro F Viana
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.,Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Elisa Bruno
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Andrea Biondi
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Mark Cook
- Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Gregory A Worrell
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andreas Schulze-Bonhage
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Matthias Dümpelmann
- Department of Neurosurgery, Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | | | - Mark P Richardson
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Benjamin H Brinkmann
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
16
|
Iturrate I, Chavarriaga R, Millán JDR. General principles of machine learning for brain-computer interfacing. HANDBOOK OF CLINICAL NEUROLOGY 2020; 168:311-328. [PMID: 32164862 DOI: 10.1016/b978-0-444-63934-9.00023-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Brain-computer interfaces (BCIs) are systems that translate brain activity patterns into commands that can be executed by an artificial device. This enables the possibility of controlling devices such as a prosthetic arm or exoskeleton, a wheelchair, typewriting applications, or games directly by modulating our brain activity. For this purpose, BCI systems rely on signal processing and machine learning algorithms to decode the brain activity. This chapter provides an overview of the main steps required to do such a process, including signal preprocessing, feature extraction and selection, and decoding. Given the large amount of possible methods that can be used for these processes, a comprehensive review of them is beyond the scope of this chapter, and it is focused instead on the general principles that should be taken into account, as well as discussing good practices on how these methods should be applied and evaluated for proper design of reliable BCI systems.
Collapse
Affiliation(s)
- Iñaki Iturrate
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland; Institute of Applied Information Technology (InIT), Zurich University of Applied Sciences ZHAW, Winterthur, Switzerland.
| | - José Del R Millán
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States; Department of Neurology, The University of Texas at Austin, Austin, TX, United States
| |
Collapse
|
17
|
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.
Collapse
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
| |
Collapse
|
18
|
Torres-Martinez N, Ratel D, Crétallaz C, Gaude C, Maubert S, Divoux JL, Henry C, Guiraud D, Sauter-Starace F. Reliability of parylene-based multi-electrode arrays chronically implanted in adult rat brains, and evidence of electrical stimulation on contact impedance. J Neural Eng 2019; 16:066047. [PMID: 31374559 DOI: 10.1088/1741-2552/ab3836] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
OBJECTIVE The goal of this study was to evaluate the long-term behavior of the surface electrode through electrochemical characterization and follow-up of implanted parylene/platinum microelectrodes. APPROACH To this aim, we designed and manufactured specific planar electrodes for cortical implantation for a rat model. This work was included in the INTENSE® project, one of the goals of which was to prove the feasibility of selective neural recording or stimulation with cuff electrodes around the vagus nerve. MAIN RESULTS After a 12-week implantation in a rat model, we can report that these microelectrodes have withstood in vivo use. Regarding the biocompatibility of the electrodes (materials and manufacturing process), no adverse effect was reported. Indeed, after the three-month implantation, we characterized limited tissue reaction beneath the electrodes and showed an increase and a stabilization of their impedance. Interestingly, the follow-up of the electrochemical impedance combined with electrical stimulation highlighted a drop in the impedance up to 60% at 1 kHz after ten minutes of electrical stimulation at 110 Hz. SIGNIFICANCE This study gives evidence of the biocompatibility of the parylene platinum contact array designed for the project and confirms the effect of stimulation on the contact impedance.
Collapse
|
19
|
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
|
20
|
Fischer B, Schander A, Kreiter AK, Lang W, Wegener D. Visual epidural field potentials possess high functional specificity in single trials. J Neurophysiol 2019; 122:1634-1648. [PMID: 31412218 DOI: 10.1152/jn.00510.2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Recordings of epidural field potentials (EFPs) allow neuronal activity to be acquired over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations and possess a higher trial-by-trial variability and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short timescales relevant for many clinical and basic neuroscience purposes. We used the high spatial resolution of primary visual cortex to address these issues and investigated the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one of nine closely adjacent locations and recorded neuronal activity with a high-density epidural multielectrode array in three macaque monkeys. With the use of receiver operating characteristics (ROC) to identify the most informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.NEW & NOTEWORTHY Epidural field potential (EFP) recordings provide a minimally invasive approach to investigate large-scale neural networks, but little is known about whether they possess the required specificity for basic and clinical neuroscience. By making use of the spatial selectivity of primary visual cortex, we show that single-trial information can be decoded with close-to-perfect performance, even without using advanced classifiers and based on very few data. This labels EFPs as a highly attractive and widely usable signal.
Collapse
Affiliation(s)
- Benjamin Fischer
- Brain Research Institute, Center for Cognitive Sciences, University of Bremen, Bremen, Germany
| | - Andreas Schander
- Institute for Microsensors, -Actuators, and -Systems, University of Bremen, Bremen, Germany
| | - Andreas K Kreiter
- Brain Research Institute, Center for Cognitive Sciences, University of Bremen, Bremen, Germany
| | - Walter Lang
- Institute for Microsensors, -Actuators, and -Systems, University of Bremen, Bremen, Germany
| | - Detlef Wegener
- Brain Research Institute, Center for Cognitive Sciences, University of Bremen, Bremen, Germany
| |
Collapse
|
21
|
Flexible bioelectrodes with enhanced wrinkle microstructures for reliable electrochemical modification and neuromodulation in vivo. Biosens Bioelectron 2019; 135:181-191. [DOI: 10.1016/j.bios.2019.04.025] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 03/31/2019] [Accepted: 04/13/2019] [Indexed: 01/09/2023]
|
22
|
Romanelli P, Piangerelli M, Ratel D, Gaude C, Costecalde T, Puttilli C, Picciafuoco M, Benabid A, Torres N. A novel neural prosthesis providing long-term electrocorticography recording and cortical stimulation for epilepsy and brain-computer interface. J Neurosurg 2019:1-14. [DOI: 10.3171/2017.10.jns17400] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 10/16/2017] [Indexed: 11/06/2022]
Abstract
OBJECTIVEWireless technology is a novel tool for the transmission of cortical signals. Wireless electrocorticography (ECoG) aims to improve the safety and diagnostic gain of procedures requiring invasive localization of seizure foci and also to provide long-term recording of brain activity for brain-computer interfaces (BCIs). However, no wireless devices aimed at these clinical applications are currently available. The authors present the application of a fully implantable and externally rechargeable neural prosthesis providing wireless ECoG recording and direct cortical stimulation (DCS). Prolonged wireless ECoG monitoring was tested in nonhuman primates by using a custom-made device (the ECoG implantable wireless 16-electrode [ECOGIW-16E] device) containing a 16-contact subdural grid. This is a preliminary step toward large-scale, long-term wireless ECoG recording in humans.METHODSThe authors implanted the ECOGIW-16E device over the left sensorimotor cortex of a nonhuman primate (Macaca fascicularis), recording ECoG signals over a time span of 6 months. Daily electrode impedances were measured, aiming to maintain the impedance values below a threshold of 100 KΩ. Brain mapping was obtained through wireless cortical stimulation at fixed intervals (1, 3, and 6 months). After 6 months, the device was removed. The authors analyzed cortical tissues by using conventional histological and immunohistological investigation to assess whether there was evidence of damage after the long-term implantation of the grid.RESULTSThe implant was well tolerated; no neurological or behavioral consequences were reported in the monkey, which resumed his normal activities within a few hours of the procedure. The signal quality of wireless ECoG remained excellent over the 6-month observation period. Impedance values remained well below the threshold value; the average impedance per contact remains approximately 40 KΩ. Wireless cortical stimulation induced movements of the upper and lower limbs, and elicited fine movements of the digits as well. After the monkey was euthanized, the grid was found to be encapsulated by a newly formed dural sheet. The grid removal was performed easily, and no direct adhesions of the grid to the cortex were found. Conventional histological studies showed no cortical damage in the brain region covered by the grid, except for a single microscopic spot of cortical necrosis (not visible to the naked eye) in a region that had undergone repeated procedures of electrical stimulation. Immunohistological studies of the cortex underlying the grid showed a mild inflammatory process.CONCLUSIONSThis preliminary experience in a nonhuman primate shows that a wireless neuroprosthesis, with related long-term ECoG recording (up to 6 months) and multiple DCSs, was tolerated without sequelae. The authors predict that epilepsy surgery could realize great benefit from this novel prosthesis, providing an extended time span for ECoG recording.
Collapse
Affiliation(s)
| | - Marco Piangerelli
- 2Computer Science Division, School of Science and Technology, University of Camerino, Italy; and
| | - David Ratel
- 3Biomedical Research Center, Polygone Scientifique Grenoble (CLINATEC Campus), University of Grenoble Alpes, Grenoble, France
| | - Christophe Gaude
- 3Biomedical Research Center, Polygone Scientifique Grenoble (CLINATEC Campus), University of Grenoble Alpes, Grenoble, France
| | - Thomas Costecalde
- 3Biomedical Research Center, Polygone Scientifique Grenoble (CLINATEC Campus), University of Grenoble Alpes, Grenoble, France
| | | | | | - Alim Benabid
- 3Biomedical Research Center, Polygone Scientifique Grenoble (CLINATEC Campus), University of Grenoble Alpes, Grenoble, France
| | - Napoleon Torres
- 3Biomedical Research Center, Polygone Scientifique Grenoble (CLINATEC Campus), University of Grenoble Alpes, Grenoble, France
| |
Collapse
|
23
|
Slutzky MW. Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations. Neuroscientist 2019; 25:139-154. [PMID: 29772957 PMCID: PMC6611552 DOI: 10.1177/1073858418775355] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Brain-machine interfaces (BMIs) have exploded in popularity in the past decade. BMIs, also called brain-computer interfaces, provide a direct link between the brain and a computer, usually to control an external device. BMIs have a wide array of potential clinical applications, ranging from restoring communication to people unable to speak due to amyotrophic lateral sclerosis or a stroke, to restoring movement to people with paralysis from spinal cord injury or motor neuron disease, to restoring memory to people with cognitive impairment. Because BMIs are controlled directly by the activity of prespecified neurons or cortical areas, they also provide a powerful paradigm with which to investigate fundamental questions about brain physiology, including neuronal behavior, learning, and the role of oscillations. This article reviews the clinical and neuroscientific applications of BMIs, with a primary focus on motor BMIs.
Collapse
Affiliation(s)
- Marc W Slutzky
- 1 Departments of Neurology, Physiology, and Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
| |
Collapse
|
24
|
Progress in the Field of Micro-Electrocorticography. MICROMACHINES 2019; 10:mi10010062. [PMID: 30658503 PMCID: PMC6356841 DOI: 10.3390/mi10010062] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Revised: 01/10/2019] [Accepted: 01/15/2019] [Indexed: 12/30/2022]
Abstract
Since the 1940s electrocorticography (ECoG) devices and, more recently, in the last decade, micro-electrocorticography (µECoG) cortical electrode arrays were used for a wide set of experimental and clinical applications, such as epilepsy localization and brain⁻computer interface (BCI) technologies. Miniaturized implantable µECoG devices have the advantage of providing greater-density neural signal acquisition and stimulation capabilities in a minimally invasive fashion. An increased spatial resolution of the µECoG array will be useful for greater specificity diagnosis and treatment of neuronal diseases and the advancement of basic neuroscience and BCI research. In this review, recent achievements of ECoG and µECoG are discussed. The electrode configurations and varying material choices used to design µECoG arrays are discussed, including advantages and disadvantages of µECoG technology compared to electroencephalography (EEG), ECoG, and intracortical electrode arrays. Electrode materials that are the primary focus include platinum, iridium oxide, poly(3,4-ethylenedioxythiophene) (PEDOT), indium tin oxide (ITO), and graphene. We discuss the biological immune response to µECoG devices compared to other electrode array types, the role of µECoG in clinical pathology, and brain⁻computer interface technology. The information presented in this review will be helpful to understand the current status, organize available knowledge, and guide future clinical and research applications of µECoG technologies.
Collapse
|
25
|
Rabbani Q, Milsap G, Crone NE. The Potential for a Speech Brain-Computer Interface Using Chronic Electrocorticography. Neurotherapeutics 2019; 16:144-165. [PMID: 30617653 PMCID: PMC6361062 DOI: 10.1007/s13311-018-00692-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
A brain-computer interface (BCI) is a technology that uses neural features to restore or augment the capabilities of its user. A BCI for speech would enable communication in real time via neural correlates of attempted or imagined speech. Such a technology would potentially restore communication and improve quality of life for locked-in patients and other patients with severe communication disorders. There have been many recent developments in neural decoders, neural feature extraction, and brain recording modalities facilitating BCI for the control of prosthetics and in automatic speech recognition (ASR). Indeed, ASR and related fields have developed significantly over the past years, and many lend many insights into the requirements, goals, and strategies for speech BCI. Neural speech decoding is a comparatively new field but has shown much promise with recent studies demonstrating semantic, auditory, and articulatory decoding using electrocorticography (ECoG) and other neural recording modalities. Because the neural representations for speech and language are widely distributed over cortical regions spanning the frontal, parietal, and temporal lobes, the mesoscopic scale of population activity captured by ECoG surface electrode arrays may have distinct advantages for speech BCI, in contrast to the advantages of microelectrode arrays for upper-limb BCI. Nevertheless, there remain many challenges for the translation of speech BCIs to clinical populations. This review discusses and outlines the current state-of-the-art for speech BCI and explores what a speech BCI using chronic ECoG might entail.
Collapse
Affiliation(s)
- Qinwan Rabbani
- Department of Electrical Engineering, The Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.
| | - Griffin Milsap
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
26
|
Focal stimulation of the sheep motor cortex with a chronically implanted minimally invasive electrode array mounted on an endovascular stent. Nat Biomed Eng 2018; 2:907-914. [DOI: 10.1038/s41551-018-0321-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 10/22/2018] [Indexed: 12/29/2022]
|
27
|
John SE, Apollo NV, Opie NL, Rind GS, Ronayne SM, May CN, Oxley TJ, Grayden DB. In Vivo Impedance Characterization of Cortical Recording Electrodes Shows Dependence on Electrode Location and Size. IEEE Trans Biomed Eng 2018; 66:675-681. [PMID: 30004867 DOI: 10.1109/tbme.2018.2854623] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Neural prostheses are improving the quality of life for those suffering from neurological impairments. Electrocorticography electrodes located in subdural, epidural, and intravascular positions show promise as long-term neural prostheses. However, chronic implantation affects the electrochemical environments of these arrays. METHODS In the present work, the effect of electrode location on the electrochemical properties of the interface was compared. The impedances of the electrode arrays were measured using electrochemical impedance spectroscopy in vitro in saline and in vivo four-week postimplantation. RESULTS There was not a significant effect of electrode location (subdural, intravascular, or epidural) on the impedance magnitude, and the effect of the electrode size on the impedance magnitude was frequency dependent. There was a frequency-dependent statistically significant effect of electrode location and electrode size on the phase angles of the three arrays. The subdural and epidural arrays showed phase shifts closer to -90° indicating the capacitive nature of the interface in these locations. The impact of placing electrodes within a blood vessel and adjacent to the blood vessel wall was most obvious when looking at the phase responses at frequencies below 10 kHz. CONCLUSION Our results show that intravascular electrodes, like those in subdural and epidural positions, show electrical properties that are suitable for recording. These results provide support for the use of intravascular arrays in clinically relevant neural prostheses and diagnostic devices. SIGNIFICANCE Comparison of electrochemical impedance of the epidural, intravascular, and subdural electrode array showed that all three locations are possible placement options, since impedances are in comparable ranges.
Collapse
|
28
|
John SE, Opie NL, Wong YT, Rind GS, Ronayne SM, Gerboni G, Bauquier SH, O'Brien TJ, May CN, Grayden DB, Oxley TJ. Signal quality of simultaneously recorded endovascular, subdural and epidural signals are comparable. Sci Rep 2018; 8:8427. [PMID: 29849104 PMCID: PMC5976775 DOI: 10.1038/s41598-018-26457-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 05/10/2018] [Indexed: 02/07/2023] Open
Abstract
Recent work has demonstrated the feasibility of minimally-invasive implantation of electrodes into a cortical blood vessel. However, the effect of the dura and blood vessel on recording signal quality is not understood and may be a critical factor impacting implementation of a closed-loop endovascular neuromodulation system. The present work compares the performance and recording signal quality of a minimally-invasive endovascular neural interface with conventional subdural and epidural interfaces. We compared bandwidth, signal-to-noise ratio, and spatial resolution of recorded cortical signals using subdural, epidural and endovascular arrays four weeks after implantation in sheep. We show that the quality of the signals (bandwidth and signal-to-noise ratio) of the endovascular neural interface is not significantly different from conventional neural sensors. However, the spatial resolution depends on the array location and the frequency of recording. We also show that there is a direct correlation between the signal-noise-ratio and classification accuracy, and that decoding accuracy is comparable between electrode arrays. These results support the consideration for use of an endovascular neural interface in a clinical trial of a novel closed-loop neuromodulation technology.
Collapse
Affiliation(s)
- Sam E John
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia. .,Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia. .,Florey Institute of Neuroscience and Mental Health, Parkville, Australia. .,SmartStent Pty Ltd, Parkville, Australia.
| | - Nicholas L Opie
- Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,SmartStent Pty Ltd, Parkville, Australia
| | - Yan T Wong
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia.,Department of Physiology and Department of Electrical and Computer Systems Engineering, Monash University, Clayton, Australia
| | - Gil S Rind
- Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,SmartStent Pty Ltd, Parkville, Australia
| | - Stephen M Ronayne
- Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,SmartStent Pty Ltd, Parkville, Australia
| | - Giulia Gerboni
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia.,Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia
| | - Sebastien H Bauquier
- Department of Veterinary Science, The University of Melbourne, Werribee, Australia
| | - Terence J O'Brien
- Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia
| | - Clive N May
- Florey Institute of Neuroscience and Mental Health, Parkville, Australia
| | - David B Grayden
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia.,Centre for Neural Engineering, The University of Melbourne, Carlton, Australia
| | - Thomas J Oxley
- Vascular Bionics Laboratory, Department of Medicine, Royal Melbourne Hospital, (RMH), The University of Melbourne, Parkville, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, Australia.,SmartStent Pty Ltd, Parkville, Australia
| |
Collapse
|
29
|
Nurse ES, John SE, Freestone DR, Oxley TJ, Ung H, Berkovic SF, O'Brien TJ, Cook MJ, Grayden DB. Consistency of Long-Term Subdural Electrocorticography in Humans. IEEE Trans Biomed Eng 2018; 65:344-352. [DOI: 10.1109/tbme.2017.2768442] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
30
|
Wang X, Gkogkidis CA, Iljina O, Fiederer LDJ, Henle C, Mader I, Kaminsky J, Stieglitz T, Gierthmuehlen M, Ball T. Mapping the fine structure of cortical activity with different micro-ECoG electrode array geometries. J Neural Eng 2017; 14:056004. [DOI: 10.1088/1741-2552/aa785e] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
31
|
Slutzky MW, Flint RD. Physiological properties of brain-machine interface input signals. J Neurophysiol 2017; 118:1329-1343. [PMID: 28615329 DOI: 10.1152/jn.00070.2017] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 06/08/2017] [Accepted: 06/08/2017] [Indexed: 12/16/2022] Open
Abstract
Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability.
Collapse
Affiliation(s)
- Marc W Slutzky
- Department of Neurology, Northwestern University, Chicago, Illinois; .,Department of Physiology, Northwestern University, Chicago, Illinois; and.,Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois
| | - Robert D Flint
- Department of Neurology, Northwestern University, Chicago, Illinois
| |
Collapse
|
32
|
Yao PS, Zheng SF, Wang F, Kang DZ, Lin YX. Surgery guided with intraoperative electrocorticography in patients with low-grade glioma and refractory seizures. J Neurosurg 2017; 128:840-845. [PMID: 28387627 DOI: 10.3171/2016.11.jns161296] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Using intraoperative electrocorticography (ECoG) to identify epileptogenic areas and improve postoperative seizure control in patients with low-grade gliomas (LGGs) remains inconclusive. In this study the authors retrospectively report on a surgery strategy that is based on intraoperative ECoG monitoring. METHODS A total of 108 patients with LGGs presenting at the onset of refractory seizures were included. Patients were divided into 2 groups. In Group I, all patients underwent gross-total resection (GTR) combined with resection of epilepsy areas guided by intraoperative ECoG, while patients in Group II underwent only GTR. Tumor location, tumor side, tumor size, seizure-onset features, seizure frequency, seizure duration, preoperative antiepileptic drug therapy, intraoperative electrophysiological monitoring, postoperative Engel class, and histological tumor type were compared between the 2 groups. RESULTS Univariate analysis demonstrated that tumor location and intraoperative ECoG monitoring correlated with seizure control. There were 30 temporal lobe tumors, 22 frontal lobe tumors, and 2 parietal lobe tumors in Group I, with 18, 24, and 12 tumors in those same lobes, respectively, in Group II (p < 0.05). In Group I, 74.07% of patients were completely seizure free (Engel Class I), while 38.89% in Group II (p < 0.05). In Group I, 96.30% of the patients achieved satisfactory postoperative seizure control (Engel Class I or II), compared with 77.78% in Group II (p < 0.05). Intraoperative ECoG monitoring indicated that in patients with temporal lobe tumors, most of the epileptic discharges (86.7%) were detected at the anterior part of the temporal lobe. In these patients with epilepsy discharges located at the anterior part of the temporal lobe, satisfactory postoperative seizure control (93.3%) was achieved after resection of the tumor and the anterior part of the temporal lobe. CONCLUSIONS Intraoperative ECoG monitoring provided the exact location of epileptogenic areas and significantly improved postoperative seizure control of LGGs. In patients with temporal lobe LGGs, resection of the anterior temporal lobe with epileptic discharges was sufficient to control seizures.
Collapse
|
33
|
Flint RD, Rosenow JM, Tate MC, Slutzky MW. Continuous decoding of human grasp kinematics using epidural and subdural signals. J Neural Eng 2016; 14:016005. [PMID: 27900947 DOI: 10.1088/1741-2560/14/1/016005] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Restoring or replacing function in paralyzed individuals will one day be achieved through the use of brain-machine interfaces. Regaining hand function is a major goal for paralyzed patients. Two competing prerequisites for the widespread adoption of any hand neuroprosthesis are accurate control over the fine details of movement, and minimized invasiveness. Here, we explore the interplay between these two goals by comparing our ability to decode hand movements with subdural and epidural field potentials (EFPs). APPROACH We measured the accuracy of decoding continuous hand and finger kinematics during naturalistic grasping motions in five human subjects. We recorded subdural surface potentials (electrocorticography; ECoG) as well as with EFPs, with both standard- and high-resolution electrode arrays. MAIN RESULTS In all five subjects, decoding of continuous kinematics significantly exceeded chance, using either EGoG or EFPs. ECoG decoding accuracy compared favorably with prior investigations of grasp kinematics (mean ± SD grasp aperture variance accounted for was 0.54 ± 0.05 across all subjects, 0.75 ± 0.09 for the best subject). In general, EFP decoding performed comparably to ECoG decoding. The 7-20 Hz and 70-115 Hz spectral bands contained the most information about grasp kinematics, with the 70-115 Hz band containing greater information about more subtle movements. Higher-resolution recording arrays provided clearly superior performance compared to standard-resolution arrays. SIGNIFICANCE To approach the fine motor control achieved by an intact brain-body system, it will be necessary to execute motor intent on a continuous basis with high accuracy. The current results demonstrate that this level of accuracy might be achievable not just with ECoG, but with EFPs as well. Epidural placement of electrodes is less invasive, and therefore may incur less risk of encephalitis or stroke than subdural placement of electrodes. Accurately decoding motor commands at the epidural level may be an important step towards a clinically viable brain-machine interface.
Collapse
Affiliation(s)
- Robert D Flint
- Department of Neurology, Northwestern University, Chicago IL 60611, USA
| | | | | | | |
Collapse
|
34
|
Rouse AG, Williams JJ, Wheeler JJ, Moran DW. Spatial co-adaptation of cortical control columns in a micro-ECoG brain-computer interface. J Neural Eng 2016; 13:056018. [PMID: 27651034 DOI: 10.1088/1741-2560/13/5/056018] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Electrocorticography (ECoG) has been used for a range of applications including electrophysiological mapping, epilepsy monitoring, and more recently as a recording modality for brain-computer interfaces (BCIs). Studies that examine ECoG electrodes designed and implanted chronically solely for BCI applications remain limited. The present study explored how two key factors influence chronic, closed-loop ECoG BCI: (i) the effect of inter-electrode distance on BCI performance and (ii) the differences in neural adaptation and performance when fixed versus adaptive BCI decoding weights are used. APPROACH The amplitudes of epidural micro-ECoG signals between 75 and 105 Hz with 300 μm diameter electrodes were used for one-dimensional and two-dimensional BCI tasks. The effect of inter-electrode distance on BCI control was tested between 3 and 15 mm. Additionally, the performance and cortical modulation differences between constant, fixed decoding using a small subset of channels versus adaptive decoding weights using the entire array were explored. MAIN RESULTS Successful BCI control was possible with two electrodes separated by 9 and 15 mm. Performance decreased and the signals became more correlated when the electrodes were only 3 mm apart. BCI performance in a 2D BCI task improved significantly when using adaptive decoding weights (80%-90%) compared to using constant, fixed weights (50%-60%). Additionally, modulation increased for channels previously unavailable for BCI control under the fixed decoding scheme upon switching to the adaptive, all-channel scheme. SIGNIFICANCE Our results clearly show that neural activity under a BCI recording electrode (which we define as a 'cortical control column') readily adapts to generate an appropriate control signal. These results show that the practical minimal spatial resolution of these control columns with micro-ECoG BCI is likely on the order of 3 mm. Additionally, they show that the combination and interaction between neural adaptation and machine learning are critical to optimizing ECoG BCI performance.
Collapse
|
35
|
Opie NL, Rind GS, John SE, Ronayne SM, Grayden DB, Burkitt AN, May CN, O'Brien TJ, Oxley TJ. Feasibility of a chronic, minimally invasive endovascular neural interface. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2016:4455-4458. [PMID: 28269267 DOI: 10.1109/embc.2016.7591716] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Development of a neural interface that can be implanted without risky, open brain surgery will increase the safety and viability of chronic neural recording arrays. We have developed a minimally invasive surgical procedure and an endovascular electrode-array that can be delivered to overlie the cortex through blood vessels. Here, we describe feasibility of the endovascular interface through electrode viability, recording potential and safety. Electrochemical impedance spectroscopy demonstrated that electrode impedance was stable over 91 days and low frequency phase could be used to infer electrode incorporation into the vessel wall. Baseline neural recording were used to identify the maximum bandwidth of the neural interface, which remained stable around 193 Hz for six months. Cross-sectional areas of the implanted vessels were non-destructively measured using the Australian Synchrotron. There was no case of occlusion observed in any of the implanted animals. This work demonstrates the feasibility of an endovascular neural interface to safely and efficaciously record neural information over a chronic time course.
Collapse
|
36
|
O'Sullivan-Greene E, Kuhlmann L, Nurse ES, Freestone DR, Grayden DB, Cook M, Burkitt A, Mareels I. Probing to Observe Neural Dynamics Investigated with Networked Kuramoto Oscillators. Int J Neural Syst 2016; 27:1650038. [PMID: 27596927 DOI: 10.1142/s0129065716500386] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The expansion of frontiers in neural engineering is dependent on the ability to track, detect and predict dynamics in neural tissue. Recent innovations to elucidate information from electrical recordings of brain dynamics, such as epileptic seizure prediction, have involved switching to an active probing paradigm using electrically evoked recordings rather than traditional passive measurements. This paper positions the advantage of probing in terms of information extraction, by using a coupled oscillator Kuramoto model to represent brain dynamics. While active probing performs better at observing underlying system synchrony in Kuramoto networks, especially in non-Gaussian measurement environments, the benefits diminish with increasing relative size of electrode spatial resolution compared to synchrony area. This suggests probing will be useful for improved characterization of synchrony for suitably dense electrode recordings.
Collapse
Affiliation(s)
- Elma O'Sullivan-Greene
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Levin Kuhlmann
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.,† Brain & Psychological Sciences Research Centre, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
| | - Ewan S Nurse
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.,‡ Department of Medicine, The University of Melbourne, Parkville, VIC 3010, Australia.,§ St. Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia
| | - Dean R Freestone
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.,‡ Department of Medicine, The University of Melbourne, Parkville, VIC 3010, Australia.,§ St. Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia
| | - David B Grayden
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Mark Cook
- ‡ Department of Medicine, The University of Melbourne, Parkville, VIC 3010, Australia.,§ St. Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia
| | - Anthony Burkitt
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Iven Mareels
- * Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
| |
Collapse
|
37
|
Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity. Nat Biotechnol 2016; 34:320-7. [PMID: 26854476 DOI: 10.1038/nbt.3428] [Citation(s) in RCA: 152] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2015] [Accepted: 11/09/2015] [Indexed: 12/18/2022]
Abstract
High-fidelity intracranial electrode arrays for recording and stimulating brain activity have facilitated major advances in the treatment of neurological conditions over the past decade. Traditional arrays require direct implantation into the brain via open craniotomy, which can lead to inflammatory tissue responses, necessitating development of minimally invasive approaches that avoid brain trauma. Here we demonstrate the feasibility of chronically recording brain activity from within a vein using a passive stent-electrode recording array (stentrode). We achieved implantation into a superficial cortical vein overlying the motor cortex via catheter angiography and demonstrate neural recordings in freely moving sheep for up to 190 d. Spectral content and bandwidth of vascular electrocorticography were comparable to those of recordings from epidural surface arrays. Venous internal lumen patency was maintained for the duration of implantation. Stentrodes may have wide ranging applications as a neural interface for treatment of a range of neurological conditions.
Collapse
|
38
|
Dijkstra K, Brunner P, Gunduz A, Coon W, Ritaccio A, Farquhar J, Schalk G. Identifying the Attended Speaker Using Electrocorticographic (ECoG) Signals. BRAIN-COMPUTER INTERFACES 2015; 2:161-173. [PMID: 26949710 PMCID: PMC4776341 DOI: 10.1080/2326263x.2015.1063363] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
People affected by severe neuro-degenerative diseases (e.g., late-stage amyotrophic lateral sclerosis (ALS) or locked-in syndrome) eventually lose all muscular control. Thus, they cannot use traditional assistive communication devices that depend on muscle control, or brain-computer interfaces (BCIs) that depend on the ability to control gaze. While auditory and tactile BCIs can provide communication to such individuals, their use typically entails an artificial mapping between the stimulus and the communication intent. This makes these BCIs difficult to learn and use. In this study, we investigated the use of selective auditory attention to natural speech as an avenue for BCI communication. In this approach, the user communicates by directing his/her attention to one of two simultaneously presented speakers. We used electrocorticographic (ECoG) signals in the gamma band (70-170 Hz) to infer the identity of attended speaker, thereby removing the need to learn such an artificial mapping. Our results from twelve human subjects show that a single cortical location over superior temporal gyrus or pre-motor cortex is typically sufficient to identify the attended speaker within 10 s and with 77% accuracy (50% accuracy due to chance). These results lay the groundwork for future studies that may determine the real-time performance of BCIs based on selective auditory attention to speech.
Collapse
Affiliation(s)
- K. Dijkstra
- Ctr for Adapt Neurotech, Wadsworth Center, New York State Department of Health, Albany, NY
- Dept of Neurology, Albany Medical College, Albany, NY
- Donders Inst for Brain, Cognition and Behaviour, Radboud Univ Nijmegen, The Netherlands
| | - P. Brunner
- Ctr for Adapt Neurotech, Wadsworth Center, New York State Department of Health, Albany, NY
- Dept of Neurology, Albany Medical College, Albany, NY
| | - A. Gunduz
- Ctr for Adapt Neurotech, Wadsworth Center, New York State Department of Health, Albany, NY
- J. Crayton Pruitt Family Dept of Biomed Eng, Univ of Florida, Gainesville, FL
| | - W. Coon
- Ctr for Adapt Neurotech, Wadsworth Center, New York State Department of Health, Albany, NY
- Dept of Biomed Sci, State Univ of New York at Albany, Albany, NY
| | - A.L. Ritaccio
- Dept of Neurology, Albany Medical College, Albany, NY
| | - J. Farquhar
- Donders Inst for Brain, Cognition and Behaviour, Radboud Univ Nijmegen, The Netherlands
| | - G. Schalk
- Ctr for Adapt Neurotech, Wadsworth Center, New York State Department of Health, Albany, NY
- Dept of Neurology, Albany Medical College, Albany, NY
- Dept of Biomed Sci, State Univ of New York at Albany, Albany, NY
| |
Collapse
|
39
|
Schendel AA, Eliceiri KW, Williams JC. Advanced Materials for Neural Surface Electrodes. CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE 2014; 18:301-307. [PMID: 26392802 PMCID: PMC4574303 DOI: 10.1016/j.cossms.2014.09.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Designing electrodes for neural interfacing applications requires deep consideration of a multitude of materials factors. These factors include, but are not limited to, the stiffness, biocompatibility, biostability, dielectric, and conductivity properties of the materials involved. The combination of materials properties chosen not only determines the ability of the device to perform its intended function, but also the extent to which the body reacts to the presence of the device after implantation. Advances in the field of materials science continue to yield new and improved materials with properties well-suited for neural applications. Although many of these materials have been well-established for non-biological applications, their use in medical devices is still relatively novel. The intention of this review is to outline new material advances for neural electrode arrays, in particular those that interface with the surface of the nervous tissue, as well as to propose future directions for neural surface electrode development.
Collapse
Affiliation(s)
- Amelia A Schendel
- Materials Science Program, University of Wisconsin - Madison, 1550 Engineering Drive, Madison, WI 53703
| | - Kevin W Eliceiri
- Laboratory for Optical and Computational Instrumentation, University of Wisconsin-Madison, 1675 Observatory Drive, Madison, WI USA 53706
| | - Justin C Williams
- Department of Biomedical Engineering, University of Wisconsin - Madison, 1550 Engineering Drive, Madison, WI 53703
| |
Collapse
|
40
|
Schendel AA, Nonte MW, Vokoun C, Richner TJ, Brodnick SK, Atry F, Frye S, Bostrom P, Pashaie R, Thongpang S, Eliceiri KW, Williams JC. The effect of micro-ECoG substrate footprint on the meningeal tissue response. J Neural Eng 2014; 11:046011. [PMID: 24941335 DOI: 10.1088/1741-2560/11/4/046011] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE There is great interest in designing implantable neural electrode arrays that maximize function while minimizing tissue effects and damage. Although it has been shown that substrate geometry plays a key role in the tissue response to intracortically implanted, penetrating neural interfaces, there has been minimal investigation into the effect of substrate footprint on the tissue response to surface electrode arrays. This study investigates the effect of micro-electrocorticography (micro-ECoG) device geometry on the longitudinal tissue response. APPROACH The meningeal tissue response to two micro-ECoG devices with differing geometries was evaluated. The first device had each electrode site and trace individually insulated, with open regions in between, while the second device had a solid substrate, in which all 16 electrode sites were embedded in a continuous insulating sheet. These devices were implanted bilaterally in rats, beneath cranial windows, through which the meningeal tissue response was monitored for one month after implantation. Electrode site impedance spectra were also monitored during the implantation period. MAIN RESULTS It was observed that collagenous scar tissue formed around both types of devices. However, the distribution of the tissue growth was different between the two array designs. The mesh devices experienced thick tissue growth between the device and the cranial window, and minimal tissue growth between the device and the brain, while the solid device showed the opposite effect, with thick tissue forming between the brain and the electrode sites. SIGNIFICANCE These data suggest that an open architecture device would be more ideal for neural recording applications, in which a low impedance path from the brain to the electrode sites is critical for maximum recording quality.
Collapse
Affiliation(s)
- Amelia A Schendel
- Materials Science Program, University of Wisconsin-Madison, 1550 Engineering Drive, Madison, WI 53706, USA
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|