1
|
Silva AB, Littlejohn KT, Liu JR, Moses DA, Chang EF. The speech neuroprosthesis. Nat Rev Neurosci 2024; 25:473-492. [PMID: 38745103 DOI: 10.1038/s41583-024-00819-9] [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] [Accepted: 04/12/2024] [Indexed: 05/16/2024]
Abstract
Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.
Collapse
Affiliation(s)
- Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Kaylo T Littlejohn
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - David A Moses
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
2
|
Chen ZS, Kulkarni P(P, Galatzer-Levy IR, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. PATTERNS (NEW YORK, N.Y.) 2022; 3:100602. [PMID: 36419447 PMCID: PMC9676543 DOI: 10.1016/j.patter.2022.100602] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of precision psychiatry. Combining ML/AI with neuromodulation technologies can potentially provide explainable solutions in clinical practice and effective therapeutic treatment. Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health. In this review, we provide a comprehensive review of ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice. We further review the role of ML in molecular phenotyping and cross-species biomarker identification in precision psychiatry. We also discuss explainable AI (XAI) and neuromodulation in a closed human-in-the-loop manner and highlight the ML potential in multi-media information extraction and multi-modal data fusion. Finally, we discuss conceptual and practical challenges in precision psychiatry and highlight ML opportunities in future research.
Collapse
Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA
| | | | - Isaac R. Galatzer-Levy
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Meta Reality Lab, New York, NY, USA
| | - Benedetta Bigio
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Carla Nasca
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Yu Zhang
- Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA
- Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA 18015, USA
| |
Collapse
|
3
|
Mamun AA, Zhao F. In-Plane Si Microneedles: Fabrication, Characterization, Modeling and Applications. MICROMACHINES 2022; 13:657. [PMID: 35630124 PMCID: PMC9146885 DOI: 10.3390/mi13050657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/16/2022] [Accepted: 04/17/2022] [Indexed: 01/26/2023]
Abstract
Microneedles are getting more and more attention in research and commercialization since their advancement in the 1990s due to the advantages over traditional hypodermic needles such as minimum invasiveness, low material and fabrication cost, and precise needle geometry control, etc. The design and fabrication of microneedles depend on various factors such as the type of materials used, fabrication planes and techniques, needle structures, etc. In the past years, in-plane and out-of-plane microneedle technologies made by silicon (Si), polymer, metal, and other materials have been developed for numerous biomedical applications including drug delivery, sample collections, medical diagnostics, and bio-sensing. Among these microneedle technologies, in-plane Si microneedles excel by the inherent properties of Si such as mechanical strength, wear resistance, biocompatibility, and structural advantages of in-plane configuration such as a wide range of length, readiness of integration with other supporting components, and complementary metal-oxide-semiconductor (CMOS) compatible fabrication. This article aims to provide a review of in-plane Si microneedles with a focus on fabrication techniques, theoretical and numerical analysis, experimental characterization of structural and fluidic behaviors, major applications, potential challenges, and future prospects.
Collapse
Affiliation(s)
| | - Feng Zhao
- Micro/Nanoelectronics and Energy Laboratory, School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA;
| |
Collapse
|
4
|
Balakrishnan G, Song J, Mou C, Bettinger CJ. Recent Progress in Materials Chemistry to Advance Flexible Bioelectronics in Medicine. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2106787. [PMID: 34751987 PMCID: PMC8917047 DOI: 10.1002/adma.202106787] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/15/2021] [Indexed: 05/09/2023]
Abstract
Designing bioelectronic devices that seamlessly integrate with the human body is a technological pursuit of great importance. Bioelectronic medical devices that reliably and chronically interface with the body can advance neuroscience, health monitoring, diagnostics, and therapeutics. Recent major efforts focus on investigating strategies to fabricate flexible, stretchable, and soft electronic devices, and advances in materials chemistry have emerged as fundamental to the creation of the next generation of bioelectronics. This review summarizes contemporary advances and forthcoming technical challenges related to three principal components of bioelectronic devices: i) substrates and structural materials, ii) barrier and encapsulation materials, and iii) conductive materials. Through notable illustrations from the literature, integration and device fabrication strategies and associated challenges for each material class are highlighted.
Collapse
Affiliation(s)
| | - Jiwoo Song
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA
| | - Chenchen Mou
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA
| | | |
Collapse
|
5
|
Lanzio V, Telian G, Koshelev A, Micheletti P, Presti G, D’Arpa E, De Martino P, Lorenzon M, Denes P, West M, Sassolini S, Dhuey S, Adesnik H, Cabrini S. Small footprint optoelectrodes using ring resonators for passive light localization. MICROSYSTEMS & NANOENGINEERING 2021; 7:40. [PMID: 34567754 PMCID: PMC8433201 DOI: 10.1038/s41378-021-00263-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 02/16/2021] [Accepted: 03/30/2021] [Indexed: 05/31/2023]
Abstract
The combination of electrophysiology and optogenetics enables the exploration of how the brain operates down to a single neuron and its network activity. Neural probes are in vivo invasive devices that integrate sensors and stimulation sites to record and manipulate neuronal activity with high spatiotemporal resolution. State-of-the-art probes are limited by tradeoffs involving their lateral dimension, number of sensors, and ability to access independent stimulation sites. Here, we realize a highly scalable probe that features three-dimensional integration of small-footprint arrays of sensors and nanophotonic circuits to scale the density of sensors per cross-section by one order of magnitude with respect to state-of-the-art devices. For the first time, we overcome the spatial limit of the nanophotonic circuit by coupling only one waveguide to numerous optical ring resonators as passive nanophotonic switches. With this strategy, we achieve accurate on-demand light localization while avoiding spatially demanding bundles of waveguides and demonstrate the feasibility with a proof-of-concept device and its scalability towards high-resolution and low-damage neural optoelectrodes.
Collapse
Affiliation(s)
- Vittorino Lanzio
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
- Department of Applied Science and Technology, Politecnico di Torino, Torino, 10129 Italy
| | - Gregory Telian
- Adesnik Lab, University of California Berkeley, Berkeley, CA 94720 USA
| | | | - Paolo Micheletti
- Department of Applied Science and Technology, Politecnico di Torino, Torino, 10129 Italy
| | - Gianni Presti
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Elisa D’Arpa
- Department of Applied Science and Technology, Politecnico di Torino, Torino, 10129 Italy
| | - Paolo De Martino
- Department of Applied Science and Technology, Politecnico di Torino, Torino, 10129 Italy
| | - Monica Lorenzon
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Peter Denes
- Lawrence Berkeley National Laboratory, (LBNL), Berkeley, CA 94720 USA
| | - Melanie West
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Simone Sassolini
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Scott Dhuey
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Hillel Adesnik
- Adesnik Lab, University of California Berkeley, Berkeley, CA 94720 USA
| | - Stefano Cabrini
- The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| |
Collapse
|
6
|
Yang W, Gong Y, Li W. A Review: Electrode and Packaging Materials for Neurophysiology Recording Implants. Front Bioeng Biotechnol 2021; 8:622923. [PMID: 33585422 PMCID: PMC7873964 DOI: 10.3389/fbioe.2020.622923] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 12/10/2020] [Indexed: 01/28/2023] Open
Abstract
To date, a wide variety of neural tissue implants have been developed for neurophysiology recording from living tissues. An ideal neural implant should minimize the damage to the tissue and perform reliably and accurately for long periods of time. Therefore, the materials utilized to fabricate the neural recording implants become a critical factor. The materials of these devices could be classified into two broad categories: electrode materials as well as packaging and substrate materials. In this review, inorganic (metals and semiconductors), organic (conducting polymers), and carbon-based (graphene and carbon nanostructures) electrode materials are reviewed individually in terms of various neural recording devices that are reported in recent years. Properties of these materials, including electrical properties, mechanical properties, stability, biodegradability/bioresorbability, biocompatibility, and optical properties, and their critical importance to neural recording quality and device capabilities, are discussed. For the packaging and substrate materials, different material properties are desired for the chronic implantation of devices in the complex environment of the body, such as biocompatibility and moisture and gas hermeticity. This review summarizes common solid and soft packaging materials used in a variety of neural interface electrode designs, as well as their packaging performances. Besides, several biopolymers typically applied over the electrode package to reinforce the mechanical rigidity of devices during insertion, or to reduce the immune response and inflammation at the device-tissue interfaces are highlighted. Finally, a benchmark analysis of the discussed materials and an outlook of the future research trends are concluded.
Collapse
Affiliation(s)
| | | | - Wen Li
- Microtechnology Lab, Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, United States
| |
Collapse
|
7
|
Mokni M, Pedroli F, D’Ambrogio G, Le MQ, Cottinet PJ, Capsal JF. High-Capacity, Fast-Response, and Photocapacitor-Based Terpolymer Phosphor Composite. Polymers (Basel) 2020; 12:polym12020349. [PMID: 32041111 PMCID: PMC7077481 DOI: 10.3390/polym12020349] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 01/17/2020] [Accepted: 01/20/2020] [Indexed: 12/28/2022] Open
Abstract
This paper describes a new class of light transducer-based poly (vinylidene fluoride-trifluoroethylene-chlorotrifluoroethylene) (P(VDF-TrFE-CTFE)) terpolymer doped with 50% wt. phosphor particles that enables to efficiently transform light energy into an electrical signal. Broadband dielectric characterization together with experimental results on photo-electric conversion demonstrated high capacitance variation of the proposed composite under light exposure, confirming promising potential of our sensor device for application in retinal prostheses where the converted electrical signal can affect the biological activity of the neuron system. In addition to the benefit of being light-weight, having ultra-flexibility, and used in a simple process, the proposed photodetector composite leads to fast response and high sensibility in terms of photoelectrical coupling where significant increases in capacitance change of 78% and 25% have been recorded under blue and green light sources, respectively. These results demonstrated high-performance material design where phosphor filler contributes to promote charge-discharge efficiency as well as reduced dielectric loss in P(VDF-TrFE-CTFE), which facilitate the composite for flexible light transducer applications, especially in the medical environment.
Collapse
|
8
|
Beygi M, Bentley JT, Frewin CL, Kuliasha CA, Takshi A, Bernardin EK, La Via F, Saddow SE. Fabrication of a Monolithic Implantable Neural Interface from Cubic Silicon Carbide. MICROMACHINES 2019; 10:E430. [PMID: 31261887 PMCID: PMC6680876 DOI: 10.3390/mi10070430] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 06/18/2019] [Accepted: 06/26/2019] [Indexed: 02/07/2023]
Abstract
One of the main issues with micron-sized intracortical neural interfaces (INIs) is their long-term reliability, with one major factor stemming from the material failure caused by the heterogeneous integration of multiple materials used to realize the implant. Single crystalline cubic silicon carbide (3C-SiC) is a semiconductor material that has been long recognized for its mechanical robustness and chemical inertness. It has the benefit of demonstrated biocompatibility, which makes it a promising candidate for chronically-stable, implantable INIs. Here, we report on the fabrication and initial electrochemical characterization of a nearly monolithic, Michigan-style 3C-SiC microelectrode array (MEA) probe. The probe consists of a single 5 mm-long shank with 16 electrode sites. An ~8 µm-thick p-type 3C-SiC epilayer was grown on a silicon-on-insulator (SOI) wafer, which was followed by a ~2 µm-thick epilayer of heavily n-type (n+) 3C-SiC in order to form conductive traces and the electrode sites. Diodes formed between the p and n+ layers provided substrate isolation between the channels. A thin layer of amorphous silicon carbide (a-SiC) was deposited via plasma-enhanced chemical vapor deposition (PECVD) to insulate the surface of the probe from the external environment. Forming the probes on a SOI wafer supported the ease of probe removal from the handle wafer by simple immersion in HF, thus aiding in the manufacturability of the probes. Free-standing probes and planar single-ended test microelectrodes were fabricated from the same 3C-SiC epiwafers. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were performed on test microelectrodes with an area of 491 µm2 in phosphate buffered saline (PBS) solution. The measurements showed an impedance magnitude of 165 kΩ ± 14.7 kΩ (mean ± standard deviation) at 1 kHz, anodic charge storage capacity (CSC) of 15.4 ± 1.46 mC/cm2, and a cathodic CSC of 15.2 ± 1.03 mC/cm2. Current-voltage tests were conducted to characterize the p-n diode, n-p-n junction isolation, and leakage currents. The turn-on voltage was determined to be on the order of ~1.4 V and the leakage current was less than 8 μArms. This all-SiC neural probe realizes nearly monolithic integration of device components to provide a likely neurocompatible INI that should mitigate long-term reliability issues associated with chronic implantation.
Collapse
Affiliation(s)
- Mohammad Beygi
- Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA
| | - John T Bentley
- Department of Medical Engineering, University of South Florida, Tampa, FL 33620, USA
| | | | - Cary A Kuliasha
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Arash Takshi
- Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA
| | - Evans K Bernardin
- Department of Medical Engineering, University of South Florida, Tampa, FL 33620, USA
| | - Francesco La Via
- CNR Institute for Microelectronics and Microsystems, Catania, Sicily 95121, Italy
| | - Stephen E Saddow
- Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA.
- Department of Medical Engineering, University of South Florida, Tampa, FL 33620, USA.
| |
Collapse
|
9
|
Ershad F, Sim K, Thukral A, Zhang YS, Yu C. Invited Article: Emerging soft bioelectronics for cardiac health diagnosis and treatment. APL MATERIALS 2019; 7:031301. [PMID: 32551188 PMCID: PMC7187908 DOI: 10.1063/1.5060270] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 10/19/2018] [Indexed: 05/05/2023]
Abstract
Cardiovascular diseases are among the leading causes of death worldwide. Conventional technologies for diagnosing and treating lack the compliance and comfort necessary for those living with life-threatening conditions. Soft electronics presents a promising outlet for conformal, flexible, and stretchable devices that can overcome the mechanical mismatch that is often associated with conventional technologies. Here, we review the various methods in which electronics have been made flexible and stretchable, to better interface with the human body, both externally with the skin and internally with the outer surface of the heart. Then, we review soft, wearable, noninvasive heart monitors designed to be attached to the chest or other parts of the body for mechano-acoustic and electrophysiological sensing. A common method of treatment for various abnormal heart rhythms involves catheter ablation procedures and we review the current soft bioelectronics that can be placed on the balloon or head of the catheter. Cardiac mapping is integral to determine the state of the heart; we discuss the various parameters for sensing aside from electrophysiological sensing, such as temperature, pH, strain, and tactile sensing. Finally, we review the soft devices that harvest energy from the natural and spontaneous beating of the heart by converting its mechanical motion into electrical energy to power implants.
Collapse
Affiliation(s)
- Faheem Ershad
- Department of Biomedical Engineering, University
of Houston, Houston, Texas 77204, USA
| | - Kyoseung Sim
- Department of Mechanical Engineering, University
of Houston, Houston, Texas 77204, USA
| | - Anish Thukral
- Materials Science and Engineering Program,
University of Houston, Houston, Texas 77204, USA
| | - Yu Shrike Zhang
- Division of Engineering in Medicine, Department of
Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge,
Massachusetts 02139, USA
- Authors to whom correspondence should be addressed:
and
| | - Cunjiang Yu
- Authors to whom correspondence should be addressed:
and
| |
Collapse
|
10
|
Polino G, Lubrano C, Ciccone G, Santoro F. Photogenerated Electrical Fields for Biomedical Applications. Front Bioeng Biotechnol 2018; 6:167. [PMID: 30474026 PMCID: PMC6237932 DOI: 10.3389/fbioe.2018.00167] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Accepted: 10/23/2018] [Indexed: 12/11/2022] Open
Abstract
The application of electrical engineering principles to biology represents the main issue of bioelectronics, focusing on interfacing of electronics with biological systems. In particular, it includes many applications that take advantage of the peculiar optoelectronic and mechanical properties of organic or inorganic semiconductors, from sensing of biomolecules to functional substrates for cellular growth. Among these, technologies for interacting with bioelectrical signals in living systems exploiting the electrical field of biomedical devices have attracted considerable attention. In this review, we present an overview of principal applications of phototransduction for the stimulation of electrogenic and non-electrogenic cells focusing on photovoltaic-based platforms.
Collapse
Affiliation(s)
| | | | | | - Francesca Santoro
- Center for Advanced Biomaterials for Healthcare, Istituto Italiano di Tecnologia, Naples, Italy
| |
Collapse
|