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Barth K, Schmitz C, Jochum T, Viventi J. Intan Technologies integrated circuits can produce analog-to-digital conversion artifacts that affect neural signal acquisition. J Neural Eng 2024; 21:044001. [PMID: 38865993 DOI: 10.1088/1741-2552/ad5762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 06/12/2024] [Indexed: 06/14/2024]
Abstract
Objective.Intan Technologies' integrated circuits (ICs) are valuable tools for neurophysiological data acquisition, providing signal amplification, filtering, and digitization from many channels (up to 64 channels/chip) at high sampling rates (up to 30 kSPS) within a compact package (⩽9× 7 mm). However, we found that the analog-to-digital converters (ADCs) in the Intan RHD2000 series ICs can produce artifacts in recorded signals. Here, we examine the effects of these ADC artifacts on neural signal quality and describe a method to detect them in recorded data.Approach.We identified two types of ADC artifacts produced by Intan ICs: 1) jumps, resulting from missing output codes, and 2) flatlines, resulting from overrepresented output codes. We identified ADC artifacts in neural recordings acquired with Intan RHD2000 ICs and tested the repeated performance of 17 ICsin vitro. With the on-chip digital-signal-processing disabled, we detected the ADC artifacts in each test recording by examining the distribution of unfiltered ADC output codes.Main Results.We found larger ADC artifacts in recordings using the Intan RHX data acquisition software versions 3.0-3.2, which did not run the necessary ADC calibration command when the inputs to the Intan recording controller were rescanned. This has been corrected in the Intan RHX software version 3.3. We found that the ADC calibration routine significantly reduced, but did not fully eliminate, the occurrence and size of ADC artifacts as compared with recordings acquired when the calibration routine was not run (p< 0.0001). When the ADC calibration routine was run, we found that the artifacts produced by each ADC were consistent over time, enabling us to sort ICs by performance.Significance.Our findings call attention to the importance of evaluating signal quality when acquiring electrophysiological data using Intan Technologies ICs and offer a method for detecting ADC artifacts in recorded data.
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Affiliation(s)
- Katrina Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Cecilia Schmitz
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Thomas Jochum
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, United States of America
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, United States of America
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States of America
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, United States of America
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2
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Tchoe Y, Wu T, U HS, Roth DM, Kim D, Lee J, Cleary DR, Pizarro P, Tonsfeldt KJ, Lee K, Chen PC, Bourhis AM, Galton I, Coughlin B, Yang JC, Paulk AC, Halgren E, Cash SS, Dayeh SA. An electroencephalogram microdisplay to visualize neuronal activity on the brain surface. Sci Transl Med 2024; 16:eadj7257. [PMID: 38657026 PMCID: PMC11093107 DOI: 10.1126/scitranslmed.adj7257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 04/03/2024] [Indexed: 04/26/2024]
Abstract
Functional mapping during brain surgery is applied to define brain areas that control critical functions and cannot be removed. Currently, these procedures rely on verbal interactions between the neurosurgeon and electrophysiologist, which can be time-consuming. In addition, the electrode grids that are used to measure brain activity and to identify the boundaries of pathological versus functional brain regions have low resolution and limited conformity to the brain surface. Here, we present the development of an intracranial electroencephalogram (iEEG)-microdisplay that consists of freestanding arrays of 2048 GaN light-emitting diodes laminated on the back of micro-electrocorticography electrode grids. With a series of proof-of-concept experiments in rats and pigs, we demonstrate that these iEEG-microdisplays allowed us to perform real-time iEEG recordings and display cortical activities by spatially corresponding light patterns on the surface of the brain in the surgical field. Furthermore, iEEG-microdisplays allowed us to identify and display cortical landmarks and pathological activities from rat and pig models. Using a dual-color iEEG-microdisplay, we demonstrated coregistration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The iEEG-microdisplay holds promise to facilitate monitoring of pathological brain activity in clinical settings.
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Affiliation(s)
- Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Tianhai Wu
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Hoi Sang U
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - David M Roth
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Dongwoo Kim
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Daniel R Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Center for the Future of Surgery, Department of Surgery, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Neurological Surgery, University of California, San Diego, La Jolla, CA 92093, USA
| | - Patricia Pizarro
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Neurological Surgery, Oregon Health & Science University, Mail code CH8N, 3303 SW Bond Avenue, Portland, OR 97239, USA
| | - Karen J Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Po Chun Chen
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Andrew M Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ian Galton
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Brian Coughlin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Jimmy C Yang
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurological Surgery, Ohio State University, Columbus, OH 43210, USA
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Eric Halgren
- Department of Neurological Surgery, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Shadi A Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093, USA
- Departments of Radiology and Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
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3
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Lee K, Paulk AC, Ro YG, Cleary DR, Tonsfeldt KJ, Kfir Y, Pezaris JS, Tchoe Y, Lee J, Bourhis AM, Vatsyayan R, Martin JR, Russman SM, Yang JC, Baohan A, Richardson RM, Williams ZM, Fried SI, Hoi Sang U, Raslan AM, Ben-Haim S, Halgren E, Cash SS, Dayeh SA. Flexible, scalable, high channel count stereo-electrode for recording in the human brain. Nat Commun 2024; 15:218. [PMID: 38233418 PMCID: PMC10794240 DOI: 10.1038/s41467-023-43727-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 11/14/2023] [Indexed: 01/19/2024] Open
Abstract
Over the past decade, stereotactically placed electrodes have become the gold standard for deep brain recording and stimulation for a wide variety of neurological and psychiatric diseases. Current electrodes, however, are limited in their spatial resolution and ability to record from small populations of neurons, let alone individual neurons. Here, we report on an innovative, customizable, monolithically integrated human-grade flexible depth electrode capable of recording from up to 128 channels and able to record at a depth of 10 cm in brain tissue. This thin, stylet-guided depth electrode is capable of recording local field potentials and single unit neuronal activity (action potentials), validated across species. This device represents an advance in manufacturing and design approaches which extends the capabilities of a mainstay technology in clinical neurology.
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Affiliation(s)
- Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Angelique C Paulk
- Department of Neurology, Harvard Medical School, Boston, MA, 02114, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Yun Goo Ro
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Daniel R Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Neurological Surgery, University of California San Diego, La Jolla, CA, 92093, USA
| | - Karen J Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - John S Pezaris
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Andrew M Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Ritwik Vatsyayan
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Joel R Martin
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Samantha M Russman
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jimmy C Yang
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Amy Baohan
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Shelley I Fried
- Department of Neurosurgery, Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - U Hoi Sang
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Ahmed M Raslan
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Sharona Ben-Haim
- Department of Neurological Surgery, University of California San Diego, La Jolla, CA, 92093, USA
| | - Eric Halgren
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Sydney S Cash
- Department of Neurology, Harvard Medical School, Boston, MA, 02114, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Shadi A Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
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4
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Paulk AC, Salami P, Zelmann R, Cash SS. Electrode Development for Epilepsy Diagnosis and Treatment. Neurosurg Clin N Am 2024; 35:135-149. [PMID: 38000837 DOI: 10.1016/j.nec.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2023]
Abstract
Recording neural activity has been a critical aspect in the diagnosis and treatment of patients with epilepsy. For those with intractable epilepsy, intracranial neural monitoring has been of substantial importance. Clinically, however, methods for recording neural information have remained essentially unchanged for decades. Over the last decade or so, rapid advances in electrode technology have begun to change this landscape. New systems allow for the observation of neural activity with high spatial resolution and, in some cases, at the level of the activity of individual neurons. These new tools have contributed greatly to our understanding of brain function and dysfunction. Here, the authors review the primary technologies currently in use in humans. The authors discuss other possible systems, some of the challenges which come along with these devices, and how they will become incorporated into the clinical workflow. Ultimately, the expectation is that these new, high-density, high-spatial-resolution recording systems will become a valuable part of the clinical arsenal used in the diagnosis and surgical management of epilepsy.
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Affiliation(s)
- Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA.
| | - Pariya Salami
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Rina Zelmann
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
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5
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Duraivel S, Rahimpour S, Chiang CH, Trumpis M, Wang C, Barth K, Harward SC, Lad SP, Friedman AH, Southwell DG, Sinha SR, Viventi J, Cogan GB. High-resolution neural recordings improve the accuracy of speech decoding. Nat Commun 2023; 14:6938. [PMID: 37932250 PMCID: PMC10628285 DOI: 10.1038/s41467-023-42555-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 10/13/2023] [Indexed: 11/08/2023] Open
Abstract
Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed high-resolution, micro-electrocorticographic (µECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57× higher spatial resolution and 48% higher signal-to-noise ratio compared to macro-ECoG and SEEG. This increased signal quality improved decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show that high-density µECoG can enable high-quality speech decoding for future neural speech prostheses.
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Affiliation(s)
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA
- Department of Neurosurgery, Clinical Neuroscience Center, University of Utah, Salt Lake City, UT, USA
| | - Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Katrina Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Stephen C Harward
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, USA
| | - Shivanand P Lad
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA
| | - Allan H Friedman
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA
| | - Derek G Southwell
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, USA
- Department of Neurobiology, Duke School of Medicine, Durham, NC, USA
| | - Saurabh R Sinha
- Penn Epilepsy Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA.
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, USA.
- Department of Neurobiology, Duke School of Medicine, Durham, NC, USA.
| | - Gregory B Cogan
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, USA.
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, USA.
- Department of Neurology, Duke School of Medicine, Durham, NC, USA.
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA.
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6
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Fallegger F, Trouillet A, Coen FV, Schiavone G, Lacour SP. A low-profile electromechanical packaging system for soft-to-flexible bioelectronic interfaces. APL Bioeng 2023; 7:036109. [PMID: 37600068 PMCID: PMC10439817 DOI: 10.1063/5.0152509] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 08/02/2023] [Indexed: 08/22/2023] Open
Abstract
Interfacing the human body with the next generation of electronics requires technological advancement in designing and producing bioelectronic circuits. These circuits must integrate electrical functionality while simultaneously addressing limitations in mechanical compliance and dynamics, biocompatibility, and consistent, scalable manufacturing. The combination of mechanically disparate materials ranging from elastomers to inorganic crystalline semiconductors calls for modular designs with reliable and scalable electromechanical connectors. Here, we report on a novel interconnection solution for soft-to-flexible bioelectronic interfaces using a patterned and machined flexible printed circuit board, which we term FlexComb, interfaced with soft transducing systems. Using a simple assembly process, arrays of protruding "fingers" bearing individual electrical terminals are laser-machined on a standard flexible printed circuit board to create a comb-like structure, namely, the FlexComb. A matching pattern is also machined in the soft system to host and interlock electromechanically the FlexComb connections via a soft electrically conducting composite. We examine the electrical and electromechanical properties of the interconnection and demonstrate the versatility and scalability of the method through various customized submillimetric designs. In a pilot in vivo study, we validate the stability and compatibility of the FlexComb technology in a subdural electrocorticography system implanted for 6 months on the auditory cortex of a minipig. The FlexComb provides a reliable and simple technique to bond and connect soft transducing systems with flexible or rigid electronic boards, which should find many implementations in soft robotics and wearable and implantable bioelectronics.
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Affiliation(s)
- Florian Fallegger
- Laboratory for Soft Bioelectronic Interfaces, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Alix Trouillet
- Laboratory for Soft Bioelectronic Interfaces, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Florent-Valéry Coen
- Laboratory for Soft Bioelectronic Interfaces, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | | | - Stéphanie P. Lacour
- Laboratory for Soft Bioelectronic Interfaces, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
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7
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Tchoe Y, Wu T, U HS, Roth DM, Kim D, Lee J, Cleary DR, Pizarro P, Tonsfeldt KJ, Lee K, Chen PC, Bourhis AM, Galton I, Coughlin B, Yang JC, Paulk AC, Halgren E, Cash SS, Dayeh SA. The Brain Electroencephalogram Microdisplay for Precision Neurosurgery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549735. [PMID: 37503216 PMCID: PMC10370209 DOI: 10.1101/2023.07.19.549735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Brain surgeries are among the most delicate clinical procedures and must be performed with the most technologically robust and advanced tools. When such surgical procedures are performed in functionally critical regions of the brain, functional mapping is applied as a standard practice that involves direct coordinated interactions between the neurosurgeon and the clinical neurology electrophysiology team. However, information flow during these interactions is commonly verbal as well as time consuming which in turn increases the duration and cost of the surgery, possibly compromising the patient outcomes. Additionally, the grids that measure brain activity and identify the boundaries of pathological versus functional brain regions suffer from low resolution (3-10 mm contact to contact spacing) with limited conformity to the brain surface. Here, we introduce a brain intracranial electroencephalogram microdisplay (Brain-iEEG-microdisplay) which conforms to the brain to measure the brain activity and display changes in near real-time (40 Hz refresh rate) on the surface of the brain in the surgical field. We used scalable engineered gallium nitride (GaN) substrates with 6" diameter to fabricate, encapsulate, and release free-standing arrays of up to 2048 GaN light emitting diodes (μLEDs) in polyimide substrates. We then laminated the μLED arrays on the back of micro-electrocorticography (μECoG) platinum nanorod grids (PtNRGrids) and developed hardware and software to perform near real-time intracranial EEG analysis and activation of light patterns that correspond to specific cortical activities. Using the Brain-iEEG-microdisplay, we precisely ideFSntified and displayed important cortical landmarks and pharmacologically induced pathological activities. In the rat model, we identified and displayed individual cortical columns corresponding to individual whiskers and the near real-time evolution of epileptic discharges. In the pig animal model, we demonstrated near real-time mapping and display of cortical functional boundaries using somatosensory evoked potentials (SSEP) and display of responses to direct electrical stimulation (DES) from the surface or within the brain tissue. Using a dual-color Brain-iEEG-microdisplay, we demonstrated co-registration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The Brain-iEEG-microdisplay holds the promise of increasing the efficiency of diagnosis and possibly surgical treatment, thereby reducing the cost and improving patient outcomes which would mark a major advancement in neurosurgery. These advances can also be translated to broader applications in neuro-oncology and neurophysiology.
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Affiliation(s)
- Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Tianhai Wu
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Hoi Sang U
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - David M Roth
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Center for the Future of Surgery, Department of Surgery, University of California San Diego, La Jolla, California 92093, United States
- Department of Anesthesiology, University of California San Diego, La Jolla, California 92093, United States
| | - Dongwoo Kim
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Daniel R Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Department of Neurological Surgery, Oregon Health & Science University, Mail code CH8N, 3303 SW Bond Avenue, Portland, Oregon 97239- 3098, United States
| | - Patricia Pizarro
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Center for the Future of Surgery, Department of Surgery, University of California San Diego, La Jolla, California 92093, United States
| | - Karen J Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California San Diego, La Jolla, California 92093, United States
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Po Chun Chen
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Andrew M Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Ian Galton
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
| | - Brian Coughlin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Jimmy C Yang
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts 02114, United States
- Department of Neurological Surgery, Ohio State University, Columbus, Ohio 43210, United States
| | - Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Eric Halgren
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
- Department of Radiology, University of California San Diego, La Jolla, California 92093, United States
| | - Sydney S Cash
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California San Diego, La Jolla, California 92093, United States
| | - Shadi A Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093, United States
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8
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Barth KJ, Sun J, Chiang CH, Qiao S, Wang C, Rahimpour S, Trumpis M, Duraivel S, Dubey A, Wingel KE, Voinas AE, Ferrentino B, Doyle W, Southwell DG, Haglund MM, Vestal M, Harward SC, Solzbacher F, Devore S, Devinsky O, Friedman D, Pesaran B, Sinha SR, Cogan GB, Blanco J, Viventi J. Flexible, high-resolution cortical arrays with large coverage capture microscale high-frequency oscillations in patients with epilepsy. Epilepsia 2023; 64:1910-1924. [PMID: 37150937 PMCID: PMC10524535 DOI: 10.1111/epi.17642] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 05/09/2023]
Abstract
OBJECTIVE Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity. In this study, we sought to characterize microscale HFO activity captured on thin, flexible microelectrocorticographic (μECoG) arrays, which provide high spatial resolution over large cortical surface areas. METHODS We used novel liquid crystal polymer thin-film μECoG arrays (.76-1.72-mm intercontact spacing) to capture HFOs in eight intraoperative recordings from seven patients with epilepsy. We identified ripple (80-250 Hz) and fast ripple (250-600 Hz) HFOs using a common energy thresholding detection algorithm along with two stages of artifact rejection. We visualized microscale subregions of HFO activity using spatial maps of HFO rate, signal-to-noise ratio, and mean peak frequency. We quantified the spatial extent of HFO events by measuring covariance between detected HFOs and surrounding activity. We also compared HFO detection rates on microcontacts to simulated macrocontacts by spatially averaging data. RESULTS We found visually delineable subregions of elevated HFO activity within each μECoG recording. Forty-seven percent of HFOs occurred on single 200-μm-diameter recording contacts, with minimal high-frequency activity on surrounding contacts. Other HFO events occurred across multiple contacts simultaneously, with covarying activity most often limited to a .95-mm radius. Through spatial averaging, we estimated that macrocontacts with 2-3-mm diameter would only capture 44% of the HFOs detected in our μECoG recordings. SIGNIFICANCE These results demonstrate that thin-film microcontact surface arrays with both highresolution and large coverage accurately capture microscale HFO activity and may improve the utility of HFOs to localize the EZ for treatment of drug-resistant epilepsy.
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Affiliation(s)
- Katrina J. Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - James Sun
- Center for Neural Science, New York University, New York, NY, USA
| | - Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Shaoyu Qiao
- Center for Neural Science, New York University, New York, NY, USA
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Shervin Rahimpour
- Department of Neurosurgery, Clinical Neuroscience Center, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Agrita Dubey
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katie E. Wingel
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alex E. Voinas
- Center for Neural Science, New York University, New York, NY, USA
| | | | - Werner Doyle
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, USA
| | - Derek G. Southwell
- Department of Neurobiology, Duke School of Medicine, Durham, NC, USA
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Michael M. Haglund
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Matthew Vestal
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Stephen C. Harward
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Florian Solzbacher
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Materials Science and Engineering, University of Utah, Salt Lake City, UT, USA
| | - Sasha Devore
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Orrin Devinsky
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, USA
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
- Comprehensive Epilepsy Center, NYU Langone Health, New York, NY, USA
| | - Daniel Friedman
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Bijan Pesaran
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Saurabh R. Sinha
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gregory B. Cogan
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Justin Blanco
- Department of Electrical and Computer Engineering, United States Naval Academy, Annapolis, MD, USA
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Neurobiology, Duke School of Medicine, Durham, NC, USA
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
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Vatsyayan R, Lee J, Bourhis AM, Tchoe Y, Cleary DR, Tonsfeldt KJ, Lee K, Montgomery-Walsh R, Paulk AC, U HS, Cash SS, Dayeh SA. Electrochemical and electrophysiological considerations for clinical high channel count neural interfaces. MRS BULLETIN 2023; 48:531-546. [PMID: 37476355 PMCID: PMC10357958 DOI: 10.1557/s43577-023-00537-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 04/10/2023] [Indexed: 07/22/2023]
Abstract
Electrophysiological recording and stimulation are the gold standard for functional mapping during surgical and therapeutic interventions as well as capturing cellular activity in the intact human brain. A critical component probing human brain activity is the interface material at the electrode contact that electrochemically transduces brain signals to and from free charge carriers in the measurement system. Here, we summarize state-of-the-art electrode array systems in the context of translation for use in recording and stimulating human brain activity. We leverage parametric studies with multiple electrode materials to shed light on the varied levels of suitability to enable high signal-to-noise electrophysiological recordings as well as safe electrophysiological stimulation delivery. We discuss the effects of electrode scaling for recording and stimulation in pursuit of high spatial resolution, channel count electrode interfaces, delineating the electrode-tissue circuit components that dictate the electrode performance. Finally, we summarize recent efforts in the connectorization and packaging for high channel count electrode arrays and provide a brief account of efforts toward wireless neuronal monitoring systems.
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Affiliation(s)
- Ritwik Vatsyayan
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Andrew M. Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Daniel R. Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Neurological Surgery, School of Medicine, Oregon Health & Science University, Portland, USA
| | - Karen J. Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California, San Diego, San Diego, USA
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Rhea Montgomery-Walsh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Bioengineering, University of California, San Diego, San Diego, USA
| | - Angelique C. Paulk
- Department of Neurology, Harvard Medical School, Boston, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, USA
| | - Hoi Sang U
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Sydney S. Cash
- Department of Neurology, Harvard Medical School, Boston, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, USA
| | - Shadi A. Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Bioengineering, University of California, San Diego, San Diego, USA
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10
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Coles L, Oluwasanya PW, Karam N, Proctor CM. Fluidic enabled bioelectronic implants: opportunities and challenges. J Mater Chem B 2022; 10:7122-7131. [PMID: 35959561 PMCID: PMC9518646 DOI: 10.1039/d2tb00942k] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/26/2022] [Indexed: 11/21/2022]
Abstract
Bioelectronic implants are increasingly facilitating novel strategies for clinical diagnosis and treatment. The integration of fluidic technologies into such implants enables new complementary routes for sensing and therapy alongside electrical interaction. Indeed, these two technologies, electrical and fluidic, can work synergistically in a bioelectronics implant towards the fabrication of a complete therapeutic platform. In this perspective article, the leading applications of fluidic enabled bioelectronic implants are highlighted and methods of operation and material choices are discussed. Furthermore, a forward-looking perspective is offered on emerging opportunities as well as critical materials and technological challenges.
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Affiliation(s)
- Lawrence Coles
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, UK.
| | - Pelumi W Oluwasanya
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, UK.
| | - Nuzli Karam
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, UK.
| | - Christopher M Proctor
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, UK.
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11
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Dasgupta D, Miserocchi A, McEvoy AW, Duncan JS. Previous, current, and future stereotactic EEG techniques for localising epileptic foci. Expert Rev Med Devices 2022; 19:571-580. [PMID: 36003028 DOI: 10.1080/17434440.2022.2114830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required. AREAS COVERED This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally. EXPERT OPINION We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future.
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Affiliation(s)
- Debayan Dasgupta
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.,Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Anna Miserocchi
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew W McEvoy
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
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12
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Witham NS, Reiche CF, Odell T, Barth K, Chiang CH, Wang C, Dubey A, Wingel K, Devore S, Friedman D, Pesaran B, Viventi J, Solzbacher F. Flexural bending to approximate cortical forces exerted by electrocorticography (ECoG) arrays. J Neural Eng 2022; 19:10.1088/1741-2552/ac8452. [PMID: 35882223 PMCID: PMC10002477 DOI: 10.1088/1741-2552/ac8452] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 07/26/2022] [Indexed: 11/11/2022]
Abstract
Objective.The force that an electrocorticography (ECoG) array exerts on the brain manifests when it bends to match the curvature of the skull and cerebral cortex. This force can negatively impact both short-term and long-term patient outcomes. Here we provide a mechanical characterization of a novel liquid crystal polymer (LCP) ECoG array prototype to demonstrate that its thinner geometry reduces the force potentially applied to the cortex of the brain.Approach.We built a low-force flexural testing machine to measure ECoG array bending forces, calculate their effective flexural moduli, and approximate the maximum force they could exerted on the human brain.Main results.The LCP ECoG prototype was found to have a maximal force less than 20% that of any commercially available ECoG arrays that were tested. However, as a material, LCP was measured to be as much as 24× more rigid than silicone, which is traditionally used in ECoG arrays. This suggests that the lower maximal force resulted from the prototype's thinner profile (2.9×-3.25×).Significance.While decreasing material stiffness can lower the force an ECoG array exhibits, our LCP ECoG array prototype demonstrated that flexible circuit manufacturing techniques can also lower these forces by decreasing ECoG array thickness. Flexural tests of ECoG arrays are necessary to accurately assess these forces, as material properties for polymers and laminates are often scale dependent. As the polymers used are anisotropic, elastic modulus cannot be used to predict ECoG flexural behavior. Accounting for these factors, we used our four-point flexure testing procedure to quantify the forces exerted on the brain by ECoG array bending. With this experimental method, ECoG arrays can be designed to minimize force exerted on the brain, potentially improving both acute and chronic clinical utility.
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Affiliation(s)
- Nicholas S Witham
- The University of Utah, Salt Lake City, UT, United States of America
| | | | - Thomas Odell
- The University of Utah, Salt Lake City, UT, United States of America
| | - Katrina Barth
- Duke University, Durham, NC, United States of America
| | | | - Charles Wang
- Duke University, Durham, NC, United States of America
| | - Agrita Dubey
- New York University Grossman School of Medicine, New York City, NY, United States of America
| | - Katie Wingel
- New York University Grossman School of Medicine, New York City, NY, United States of America
| | - Sasha Devore
- New York University Grossman School of Medicine, New York City, NY, United States of America
| | - Daniel Friedman
- New York University Grossman School of Medicine, New York City, NY, United States of America
| | - Bijan Pesaran
- New York University, New York City, NY, United States of America
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13
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Sun J, Barth K, Qiao S, Chiang CH, Wang C, Rahimpour S, Trumpis M, Duraivel S, Dubey A, Wingel KE, Rachinskiy I, Voinas AE, Ferrentino B, Southwell DG, Haglund MM, Friedman AH, Lad SP, Doyle WK, Solzbacher F, Cogan G, Sinha SR, Devore S, Devinsky O, Friedman D, Pesaran B, Viventi J. Intraoperative microseizure detection using a high-density micro-electrocorticography electrode array. Brain Commun 2022; 4:fcac122. [PMID: 35663384 PMCID: PMC9155612 DOI: 10.1093/braincomms/fcac122] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 02/10/2022] [Accepted: 05/24/2022] [Indexed: 11/14/2022] Open
Abstract
One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30-70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, subdural electrode arrays with hundreds of microelectrodes over a 100-1000 mm2 area to enable high-resolution mapping of neural activity. Here, we used these high-density arrays to study microscale properties of human epileptiform activity. We performed intraoperative micro-electrocorticographic recordings in nine patients with epilepsy. In addition, we recorded from four patients with movement disorders undergoing deep brain stimulator implantation as non-epileptic controls. A board-certified epileptologist identified microseizures, which resembled electrographic seizures normally observed with clinical macroelectrodes. Recordings in epileptic patients had a significantly higher microseizure rate (2.01 events/min) than recordings in non-epileptic subjects (0.01 events/min; permutation test, P = 0.0068). Using spatial averaging to simulate recordings from larger electrode contacts, we found that the number of detected microseizures decreased rapidly with increasing contact diameter and decreasing contact density. In cases in which microseizures were spatially distributed across multiple channels, the approximate onset region was identified. Our results suggest that micro-electrocorticographic electrode arrays with a high density of contacts and large coverage are essential for capturing microseizures in epilepsy patients and may be beneficial for localizing epileptogenic tissue to plan surgery or target brain stimulation.
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Affiliation(s)
- James Sun
- Center for Neural Science, New York University, New York, NY, USA
| | - Katrina Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Shaoyu Qiao
- Center for Neural Science, New York University, New York, NY, USA
| | - Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Department of Neurosurgery, Clinical Neuroscience Center, University of Utah, Salt Lake City, UT, USA
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Agrita Dubey
- Center for Neural Science, New York University, New York, NY, USA
| | - Katie E. Wingel
- Center for Neural Science, New York University, New York, NY, USA
| | - Iakov Rachinskiy
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Alex E. Voinas
- Center for Neural Science, New York University, New York, NY, USA
| | | | - Derek G. Southwell
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Michael M. Haglund
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Allan H. Friedman
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Shivanand P. Lad
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Werner K. Doyle
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Florian Solzbacher
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Materials Science & Engineering, University of Utah, Salt Lake City, UT, USA
| | - Gregory Cogan
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - Saurabh R. Sinha
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - Sasha Devore
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Orrin Devinsky
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Daniel Friedman
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Bijan Pesaran
- Center for Neural Science, New York University, New York, NY, USA
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
- Duke Comprehensive Epilepsy Center, Duke University School of Medicine, Durham, NC, USA
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Neuromotor prosthetic to treat stroke-related paresis: N-of-1 trial. COMMUNICATIONS MEDICINE 2022; 2:37. [PMID: 35603289 PMCID: PMC9053238 DOI: 10.1038/s43856-022-00105-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 03/18/2022] [Indexed: 11/25/2022] Open
Abstract
Background Functional recovery of arm movement typically plateaus following a stroke, leaving chronic motor deficits. Brain-computer interfaces (BCI) may be a potential treatment for post-stroke deficits Methods In this n-of-1 trial (NCT03913286), a person with chronic subcortical stroke with upper-limb motor impairment used a powered elbow-wrist-hand orthosis that opened and closed the affected hand using cortical activity, recorded from a percutaneous BCI comprised of four microelectrode arrays implanted in the ipsilesional precentral gyrus, based on decoding of spiking patterns and high frequency field potentials generated by imagined hand movements. The system was evaluated in a home setting for 12 weeks Results Robust single unit activity, modulating with attempted or imagined movement, was present throughout the precentral gyrus. The participant acquired voluntary control over a hand-orthosis, achieving 10 points on the Action Research Arm Test using the BCI, compared to 0 without any device, and 5 using myoelectric control. Strength, spasticity, the Fugl-Meyer scores improved. Conclusions We demonstrate in a human being that ensembles of individual neurons in the cortex overlying a chronic supratentorial, subcortical stroke remain active and engaged in motor representation and planning and can be used to electrically bypass the stroke and promote limb function. The participant’s ability to rapidly acquire control over otherwise paralyzed hand opening, more than 18 months after a stroke, may justify development of a fully implanted movement restoration system to expand the utility of fully implantable BCI to a clinical population that numbers in the tens of millions worldwide. Stroke is a restriction of blood flow to part of the brain and can lead to chronic issues with a person’s ability to control the limbs. The aim of this study was to see if a new type of device could restore movement in a person with arm weakness due to a stroke that occurred a year earlier. In our trial, a sensor was implanted into the surface of the brain, near the site of the stroke, and was connected to a computer that generated a command to open and close the hand with a motorized brace worn on the hand. This person was able to use their own brain activity to trigger the brace and pick up and move objects. This research could support the development of similar medical devices to restore movement in people who have had strokes. Serruya et al. test in an N-of-1 trial whether a wearable, powered exoskeletal orthosis, driven by a percutaneous, implanted brain–computer interface can restore voluntary upper extremity function following chronic hemiparesis subsequent to a cerebral subcortical stroke. Using this approach, voluntary opening of the paralyzed hand is restored.
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Thin Film Encapsulation for LCP-Based Flexible Bioelectronic Implants: Comparison of Different Coating Materials Using Test Methodologies for Life-Time Estimation. MICROMACHINES 2022; 13:mi13040544. [PMID: 35457851 PMCID: PMC9028940 DOI: 10.3390/mi13040544] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/22/2022] [Accepted: 03/28/2022] [Indexed: 02/01/2023]
Abstract
Liquid crystal polymer (LCP) has gained wide interest in the electronics industry largely due to its flexibility, stable insulation and dielectric properties and chip integration capabilities. Recently, LCP has also been investigated as a biocompatible substrate for the fabrication of multielectrode arrays. Realizing a fully implantable LCP-based bioelectronic device, however, still necessitates a low form factor packaging solution to protect the electronics in the body. In this work, we investigate two promising encapsulation coatings based on thin-film technology as the main packaging for LCP-based electronics. Specifically, a HfO2–based nanolaminate ceramic (TFE1) deposited via atomic layer deposition (ALD), and a hybrid Parylene C-ALD multilayer stack (TFE2), both with a silicone finish, were investigated and compared to a reference LCP coating. T-peel, water-vapour transmission rate (WVTR) and long-term electrochemical impedance spectrometry (EIS) tests were performed to evaluate adhesion, barrier properties and overall encapsulation performance of the coatings. Both TFE materials showed stable impedance characteristics while submerged in 60 °C saline, with TFE1-silicone lasting more than 16 months under a continuous 14V DC bias (experiment is ongoing). The results presented in this work show that WVTR is not the main factor in determining lifetime, but the adhesion of the coating to the substrate materials plays a key role in maintaining a stable interface and thus longer lifetimes.
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Rachinskiy I, Wong L, Chiang CH, Wang C, Trumpis M, Ogren JI, Hu Z, McLaughlin B, Viventi J. High-Density, Actively Multiplexed µECoG Array on Reinforced Silicone Substrate. FRONTIERS IN NANOTECHNOLOGY 2022; 4. [PMID: 35898702 PMCID: PMC9310058 DOI: 10.3389/fnano.2022.837328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Simultaneous interrogation of electrical signals from wide areas of the brain is vital for neuroscience research and can aid in understanding the mechanisms of brain function and treatments for neurological disorders. There emerges a demand for development of devices with highly conformal interfaces that can span large cortical regions, have sufficient spatial resolution, and chronic recording capability while keeping a small implantation footprint. In this work, we have designed 61 channel and 48 channel high-density, cortical, micro-electrocorticographic electrode arrays with 400 μm pitch on an ultra-soft but durable substrate. We have also developed a custom multiplexing integrated circuit (IC), methods for packaging the IC in a water-tight liquid crystal polymer casing, and a micro-bonding method for attaching the electronics package to the electrode array. With the integrated multiplexer, the number of external wire connections can be reduced to 16 wires, thereby diminishing the invasive footprint of the device. Both the electrode array and IC were tested in vivo in a rat model to demonstrate the ability to sense finely-localized electrophysiological signals.
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Affiliation(s)
- Iakov Rachinskiy
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Correspondence: Iakov Rachinskiy
| | - Liane Wong
- Micro-Leads Inc., Somerville, MA, United States
| | - Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | | | - Zhe Hu
- Micro-Leads Inc., Somerville, MA, United States
| | | | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, United States
- Duke Institute of Brain Sciences, Duke University School of Medicine, Durham, NC, United States
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, United States
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17
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Tchoe Y, Bourhis AM, Cleary DR, Stedelin B, Lee J, Tonsfeldt KJ, Brown EC, Siler DA, Paulk AC, Yang JC, Oh H, Ro YG, Lee K, Russman SM, Ganji M, Galton I, Ben-Haim S, Raslan AM, Dayeh SA. Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics. Sci Transl Med 2022; 14:eabj1441. [PMID: 35044788 DOI: 10.1126/scitranslmed.abj1441] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Electrophysiological devices are critical for mapping eloquent and diseased brain regions and for therapeutic neuromodulation in clinical settings and are extensively used for research in brain-machine interfaces. However, the existing clinical and experimental devices are often limited in either spatial resolution or cortical coverage. Here, we developed scalable manufacturing processes with a dense electrical connection scheme to achieve reconfigurable thin-film, multithousand-channel neurophysiological recording grids using platinum nanorods (PtNRGrids). With PtNRGrids, we have achieved a multithousand-channel array of small (30 μm) contacts with low impedance, providing high spatial and temporal resolution over a large cortical area. We demonstrated that PtNRGrids can resolve submillimeter functional organization of the barrel cortex in anesthetized rats that captured the tissue structure. In the clinical setting, PtNRGrids resolved fine, complex temporal dynamics from the cortical surface in an awake human patient performing grasping tasks. In addition, the PtNRGrids identified the spatial spread and dynamics of epileptic discharges in a patient undergoing epilepsy surgery at 1-mm spatial resolution, including activity induced by direct electrical stimulation. Collectively, these findings demonstrated the power of the PtNRGrids to transform clinical mapping and research with brain-machine interfaces.
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Affiliation(s)
- Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Andrew M Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Daniel R Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA.,Department of Neurological Surgery, University of California San Diego, La Jolla, CA 92093, USA
| | - Brittany Stedelin
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Karen J Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Erik C Brown
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Dominic A Siler
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jimmy C Yang
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA.,Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Hongseok Oh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Yun Goo Ro
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Samantha M Russman
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Mehran Ganji
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Ian Galton
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Sharona Ben-Haim
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA.,Department of Neurological Surgery, University of California San Diego, La Jolla, CA 92093, USA
| | - Ahmed M Raslan
- Department of Neurological Surgery, Oregon Health and Science University, Portland, OR 97239, USA
| | - Shadi A Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA.,Department of Neurological Surgery, University of California San Diego, La Jolla, CA 92093, USA.,Graduate Program of Materials Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
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18
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Subdural neural interfaces for long-term electrical recording, optical microscopy and magnetic resonance imaging. Biomaterials 2021; 281:121352. [PMID: 34995902 DOI: 10.1016/j.biomaterials.2021.121352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 12/23/2021] [Accepted: 12/27/2021] [Indexed: 01/23/2023]
Abstract
Though commonly used, metal electrodes are incompatible with brain tissues, often leading to injury and failure to achieve long-term implantation. Here we report a subdural neural interface of hydrogel functioning as an ionic conductor, and elastomer as a dielectric. We demonstrate that it incurs a far less glial reaction and less cerebrovascular destruction than a metal electrode. Using a cat model, the hydrogel electrode was able to record electrical signals comparably in quality to a metal electrode. The hydrogel-elastomer neural interface also readily facilitated multimodal functions. Both the hydrogel and elastomer are transparent, enabling in vivo optical microscopy. For imaging, cerebral vessels and calcium signals were imaged using two-photon microscopy. The new electrode is compatible with magnetic resonance imaging and does not cause artifact images. Such a new multimodal neural interface could represent immediate opportunity for use in broad areas of application in neuroscience research and clinical neurology.
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19
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Schweigmann M, Caudal LC, Stopper G, Scheller A, Koch KP, Kirchhoff F. Versatile Surface Electrodes for Combined Electrophysiology and Two-Photon Imaging of the Mouse Central Nervous System. Front Cell Neurosci 2021; 15:720675. [PMID: 34447299 PMCID: PMC8383317 DOI: 10.3389/fncel.2021.720675] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 07/19/2021] [Indexed: 11/23/2022] Open
Abstract
Understanding and modulating CNS function in physiological as well as pathophysiological contexts remains a significant ambition in research and clinical applications. The investigation of the multifaceted CNS cell types including their interactions and contributions to neural function requires a combination of the state-of-the-art in vivo electrophysiology and imaging techniques. We developed a novel type of liquid crystal polymer (LCP) surface micro-electrode manufactured in three customized designs with up to 16 channels for recording and stimulation of brain activity. All designs include spare central spaces for simultaneous 2P-imaging. Nanoporous platinum-plated contact sites ensure a low impedance and high current transfer. The epidural implantation of the LCP micro-electrodes could be combined with standard cranial window surgery. The epidurally positioned electrodes did not only display long-term biocompatibility, but we also observed an additional stabilization of the underlying CNS tissue. We demonstrate the electrode’s versatility in combination with in vivo 2P-imaging by monitoring anesthesia-awake cycles of transgenic mice with GCaMP3 expression in neurons or astrocytes. Cortical stimulation and simultaneous 2P Ca2+ imaging in neurons or astrocytes highlighted the astrocytes’ integrative character in neuronal activity processing. Furthermore, we confirmed that spontaneous astroglial Ca2+ signals are dampened under anesthesia, while evoked signals in neurons and astrocytes showed stronger dependency on stimulation intensity rather than on various levels of anesthesia. Finally, we show that the electrodes provide recordings of the electrocorticogram (ECoG) with a high signal-to noise ratio and spatial signal differences which help to decipher brain activity states during experimental procedures. Summarizing, the novel LCP surface micro-electrode is a versatile, convenient, and reliable tool to investigate brain function in vivo.
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Affiliation(s)
- Michael Schweigmann
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany.,Department of Electrical Engineering, Trier University of Applied Sciences, Trier, Germany
| | - Laura C Caudal
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| | - Gebhard Stopper
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| | - Anja Scheller
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| | - Klaus P Koch
- Department of Electrical Engineering, Trier University of Applied Sciences, Trier, Germany
| | - Frank Kirchhoff
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
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20
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Sellers KK, Chung JE, Zhou J, Triplett MG, Dawes HE, Haque R, Chang EF. Thin-film microfabrication and intraoperative testing of µECoG and iEEG depth arrays for sense and stimulation. J Neural Eng 2021; 18:10.1088/1741-2552/ac1984. [PMID: 34330113 PMCID: PMC10495194 DOI: 10.1088/1741-2552/ac1984] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 07/30/2021] [Indexed: 11/11/2022]
Abstract
Objective.Intracranial neural recordings and electrical stimulation are tools used in an increasing range of applications, including intraoperative clinical mapping and monitoring, therapeutic neuromodulation, and brain computer interface control and feedback. However, many of these applications suffer from a lack of spatial specificity and localization, both in terms of sensed neural signal and applied stimulation. This stems from limited manufacturing processes of commercial-off-the-shelf (COTS) arrays unable to accommodate increased channel density, higher channel count, and smaller contact size.Approach.Here, we describe a manufacturing and assembly approach using thin-film microfabrication for 32-channel high density subdural micro-electrocorticography (µECoG) surface arrays (contacts 1.2 mm diameter, 2 mm pitch) and intracranial electroencephalography (iEEG) depth arrays (contacts 0.5 mm × 1.5 mm, pitch 0.8 mm × 2.5 mm). Crucially, we tackle the translational hurdle and test these arrays during intraoperative studies conducted in four humans under regulatory approval.Main results.We demonstrate that the higher-density contacts provide additional unique information across the recording span compared to the density of COTS arrays which typically have electrode pitch of 8 mm or greater; 4 mm in case of specially ordered arrays. Our intracranial stimulation study results reveal that refined spatial targeting of stimulation elicits evoked potentials with differing spatial spread.Significance.Thin-film,μECoG and iEEG depth arrays offer a promising substrate for advancing a number of clinical and research applications reliant on high-resolution neural sensing and intracranial stimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
- These authors contributed equally
| | - Jason E Chung
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
- These authors contributed equally
| | - Jenny Zhou
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Michael G Triplett
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Heather E Dawes
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
| | - Razi Haque
- Lawrence Livermore National Laboratories, Livermore, CA, United States of America
| | - Edward F Chang
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States of America
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21
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Chiang CH, Wang C, Barth K, Rahimpour S, Trumpis M, Duraivel S, Rachinskiy I, Dubey A, Wingel KE, Wong M, Witham NS, Odell T, Woods V, Bent B, Doyle W, Friedman D, Bihler E, Reiche CF, Southwell DG, Haglund MM, Friedman AH, Lad SP, Devore S, Devinsky O, Solzbacher F, Pesaran B, Cogan G, Viventi J. Flexible, high-resolution thin-film electrodes for human and animal neural research. J Neural Eng 2021; 18: 10.1088/1741-2552/ac02dc. [PMID: 34010815 PMCID: PMC8496685 DOI: 10.1088/1741-2552/ac02dc] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/19/2021] [Indexed: 11/11/2022]
Abstract
Objective.Brain functions such as perception, motor control, learning, and memory arise from the coordinated activity of neuronal assemblies distributed across multiple brain regions. While major progress has been made in understanding the function of individual neurons, circuit interactions remain poorly understood. A fundamental obstacle to deciphering circuit interactions is the limited availability of research tools to observe and manipulate the activity of large, distributed neuronal populations in humans. Here we describe the development, validation, and dissemination of flexible, high-resolution, thin-film (TF) electrodes for recording neural activity in animals and humans.Approach.We leveraged standard flexible printed-circuit manufacturing processes to build high-resolution TF electrode arrays. We used biocompatible materials to form the substrate (liquid crystal polymer; LCP), metals (Au, PtIr, and Pd), molding (medical-grade silicone), and 3D-printed housing (nylon). We designed a custom, miniaturized, digitizing headstage to reduce the number of cables required to connect to the acquisition system and reduce the distance between the electrodes and the amplifiers. A custom mechanical system enabled the electrodes and headstages to be pre-assembled prior to sterilization, minimizing the setup time required in the operating room. PtIr electrode coatings lowered impedance and enabled stimulation. High-volume, commercial manufacturing enables cost-effective production of LCP-TF electrodes in large quantities.Main Results. Our LCP-TF arrays achieve 25× higher electrode density, 20× higher channel count, and 11× reduced stiffness than conventional clinical electrodes. We validated our LCP-TF electrodes in multiple human intraoperative recording sessions and have disseminated this technology to >10 research groups. Using these arrays, we have observed high-frequency neural activity with sub-millimeter resolution.Significance.Our LCP-TF electrodes will advance human neuroscience research and improve clinical care by enabling broad access to transformative, high-resolution electrode arrays.
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Affiliation(s)
- Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- These authors contributed equally to this work
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- These authors contributed equally to this work
| | - Katrina Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | | | - Iakov Rachinskiy
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Agrita Dubey
- Center for Neural Science, New York University, NY, NY, United States of America
| | - Katie E Wingel
- Center for Neural Science, New York University, NY, NY, United States of America
| | - Megan Wong
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Nicholas S Witham
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Thomas Odell
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Virginia Woods
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Brinnae Bent
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Werner Doyle
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, United States of America
| | - Daniel Friedman
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | | | - Christopher F Reiche
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Derek G Southwell
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Michael M Haglund
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Allan H Friedman
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Shivanand P Lad
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Sasha Devore
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | - Orrin Devinsky
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, United States of America
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
- Comprehensive Epilepsy Center, NYU Langone Health, NY, NY, United States of America
| | - Florian Solzbacher
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Materials Science & Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Bijan Pesaran
- Center for Neural Science, New York University, NY, NY, United States of America
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | - Gregory Cogan
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States of America
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States of America
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, United States of America
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
- Department of Neurobiology, Duke School of Medicine, Durham, NC, United States of America
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, United States of America
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