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Vallejo-Mancero B, Faci-Lázaro S, Zapata M, Soriano J, Madrenas J. Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models. Neural Netw 2024; 179:106593. [PMID: 39142177 DOI: 10.1016/j.neunet.2024.106593] [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: 03/18/2024] [Revised: 06/20/2024] [Accepted: 07/31/2024] [Indexed: 08/16/2024]
Abstract
Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological systems. An inspiring alternative is to implement hardware architectures that replicate the behavior of biological neurons but with the flexibility in programming capabilities of an electronic device, all combined with a relatively low operational cost. To advance in this quest, here we analyze the capacity of the HEENS hardware architecture to operate in a similar manner as an in vitro neuronal network grown in the laboratory. For that, we considered data of spontaneous activity in living neuronal cultures of about 400 neurons and compared their collective dynamics and functional behavior with those obtained from direct numerical simulations (in silico) and hardware implementations (in duris silico). The results show that HEENS is capable to mimic both the in vitro and in silico systems with high efficient-cost ratio, and on different network topological designs. Our work shows that compact low-cost hardware implementations are feasible, opening new avenues for future, highly efficient neuromorphic devices and advanced human-machine interfacing.
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Affiliation(s)
- Bernardo Vallejo-Mancero
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain.
| | - Sergio Faci-Lázaro
- Department of Condensed Matter Physics, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain; GOTHAM Lab, Institute of Biocomputation and Physics of Complex Systems, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain
| | - Mireya Zapata
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain; Centro de Investigación en Mecatrónica y Sistemas Interactivos - MIST, Universidad Indoamérica, Machala y Sabanilla, Quito, 170103, Ecuador
| | - Jordi Soriano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martíi Franquès 1, Barcelona, 08028, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Gran Via Corts Catalanes 585, Barcelona, 08007, Spain
| | - Jordi Madrenas
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain
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2
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Wang X, Bai G, Liang J, Xie Q, Chen Z, Zhou E, Li M, Wei X, Sun L, Zhang Z, Yang C, Tao TH, Zhou Z. Gustatory interface for operative assessment and taste decoding in patients with tongue cancer. Nat Commun 2024; 15:8967. [PMID: 39420050 PMCID: PMC11487085 DOI: 10.1038/s41467-024-53379-y] [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: 03/07/2024] [Accepted: 10/10/2024] [Indexed: 10/19/2024] Open
Abstract
Taste, a pivotal sense modality, plays a fundamental role in discerning flavors and evaluating the potential harm of food, thereby contributing to human survival, physical and mental health. Patients with tongue cancer may experience a loss of taste following extensive surgical resection with flap reconstruction. Here, we designed a gustatory interface that enables the non-invasive detection of tongue electrical activities for a comprehensive operative assessment. Moreover, it decodes gustatory information from the reconstructed tongue without taste buds. Our gustatory interface facilitates the recording and analysis of electrical activities on the tongue, yielding an electrical mapping across the entire tongue surface, which delineates the safe margin for surgical management and assesses flap viability for postoperative structure monitoring and prompt intervention. Furthermore, the gustatory interface helps patients discern tastes with an accuracy of 97.8%. Our invention offers a promising approach to clinical assessment and management and holds potential for improving the quality of life for individuals with tongue cancer.
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Affiliation(s)
- Xiner Wang
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guo Bai
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, 200011, China
| | - Jizhi Liang
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qianyang Xie
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, 200011, China
| | | | - Erda Zhou
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Meng Li
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
| | - Xiaoling Wei
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
| | - Liuyang Sun
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiyuan Zhang
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, 200011, China
| | - Chi Yang
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, 200011, China.
| | - Tiger H Tao
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China.
- Neuroxess Co. Ltd, Shanghai, 200023, China.
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, 519031, China.
- Tianqiao and Chrissy Chen Institute for Translational Research, Shanghai, China.
| | - Zhitao Zhou
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
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3
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Ding K, Rakhshan M, Paredes-Acuña N, Cheng G, Thakor NV. Sensory integration for neuroprostheses: from functional benefits to neural correlates. Med Biol Eng Comput 2024; 62:2939-2960. [PMID: 38760597 DOI: 10.1007/s11517-024-03118-8] [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: 04/21/2023] [Accepted: 04/19/2024] [Indexed: 05/19/2024]
Abstract
In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.
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Affiliation(s)
- Keqin Ding
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.
| | - Mohsen Rakhshan
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816, USA
- Disability, Aging, and Technology Cluster, University of Central Florida, Orlando, FL, 32816, USA
| | - Natalia Paredes-Acuña
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Gordon Cheng
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
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Jiang Z, Zhu M, Chen X. Interfacing Neuron-Motor Pathways with Stretchable and Biocompatible Electrode Arrays. Acc Chem Res 2024; 57:2255-2266. [PMID: 39023124 DOI: 10.1021/acs.accounts.4c00215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
ConspectusIn the field of neuroscience, understanding the complex interactions within the intricate neuron-motor system depends crucially on the use of high-density, physiological multiple electrode arrays (MEAs). In the neuron-motor system, the transmission of biological signals primarily occurs through electrical and chemical signaling. Taking neurons for instance, when a neuron receives external stimuli, it generates an electrical signal known as the action potential. This action potential propagates along the neuron's axon and is transmitted to other neurons via synapses. At the synapse, chemical signals (neurotransmitters) are released, allowing the electrical signal to traverse the synaptic gap and influence the next neuron. MEAs can provide unparalleled insights into neural signal patterns when interfacing with the nerve systems through their excellent spatiotemporal resolution. However, the inherent differences in mechanical and chemical properties between these artificial devices and biological tissues can lead to serious complications after chronic implantation, such as body rejection, infection, tissue damage, or device malfunction. A promising strategy to enhance MEAs' biocompatibility involves minimizing their thickness, which aligns their bending stiffness with that of surrounding tissues, thereby minimizing damage over time. However, this solution has its limits; the resulting ultrathin devices, typically based on plastic films, lack the necessary stretchability, restricting their use to organs that neither stretch nor grow.For practical deployments, devices must exhibit certain levels of stretchability (ranging from 20 to 70%), tailored to the specific requirements of the target organs. In this Account, we outline recent advancements in developing stretchable MEAs that balance stretchability with sufficient electrical conductivity for effective use in physiological research, acting as sensors and stimulators. By concentrating on the neuron-motor pathways, we summarize how the stretchable MEAs meet various application needs and examine their effectiveness. We distinguish between on-skin and implantable uses, given their vastly different requirements. Within each application scope, we highlight cutting-edge technologies, evaluating their strengths and shortcomings. Recognizing that most current devices rely on elastic films with a Young's modulus value between ∼0.5 and 5 MPa, we delve into the potential for softer MEAs, particularly those using multifunctional hydrogels for an optimizing tissue-device interface and address the challenges in adapting such hydrogel-based MEAs for chronic implants. Additionally, transitioning soft MEAs from lab to fab involves connecting them to a rigid adapter and external machinery, highlighting a critical challenge at the soft-rigid interface due to strain concentration, especially in chronic studies subject to unforeseen mechanical strains. We discuss innovative solutions to this integration challenge, being optimistic that the development of durable, biocompatible, stretchable MEAs will significantly advance neuroscience and related fields.
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Affiliation(s)
- Zhi Jiang
- Innovative Centre for Flexible Devices (iFLEX), School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
- School of Integrated Circuits, Harbin Institute of Technology (Shen Zhen), Shenzhen 518055, China
| | - Ming Zhu
- Innovative Centre for Flexible Devices (iFLEX), School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Xiaodong Chen
- Innovative Centre for Flexible Devices (iFLEX), School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
- Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
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Tankus A, Stern E, Klein G, Kaptzon N, Nash L, Marziano T, Shamia O, Gurevitch G, Bergman L, Goldstein L, Fahoum F, Strauss I. A Speech Neuroprosthesis in the Frontal Lobe and Hippocampus: Decoding High-Frequency Activity into Phonemes. Neurosurgery 2024:00006123-990000000-01250. [PMID: 38934637 DOI: 10.1227/neu.0000000000003068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 05/05/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Loss of speech due to injury or disease is devastating. Here, we report a novel speech neuroprosthesis that artificially articulates building blocks of speech based on high-frequency activity in brain areas never harnessed for a neuroprosthesis before: anterior cingulate and orbitofrontal cortices, and hippocampus. METHODS A 37-year-old male neurosurgical epilepsy patient with intact speech, implanted with depth electrodes for clinical reasons only, silently controlled the neuroprosthesis almost immediately and in a natural way to voluntarily produce 2 vowel sounds. RESULTS During the first set of trials, the participant made the neuroprosthesis produce the different vowel sounds artificially with 85% accuracy. In the following trials, performance improved consistently, which may be attributed to neuroplasticity. We show that a neuroprosthesis trained on overt speech data may be controlled silently. CONCLUSION This may open the way for a novel strategy of neuroprosthesis implantation at earlier disease stages (eg, amyotrophic lateral sclerosis), while speech is intact, for improved training that still allows silent control at later stages. The results demonstrate clinical feasibility of direct decoding of high-frequency activity that includes spiking activity in the aforementioned areas for silent production of phonemes that may serve as a part of a neuroprosthesis for replacing lost speech control pathways.
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Affiliation(s)
- Ariel Tankus
- Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Einat Stern
- Department of Neurology and Neurosurgery, School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Guy Klein
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Nufar Kaptzon
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Lilac Nash
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Tal Marziano
- School of Electrical Engineering, Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Omer Shamia
- School of Electrical Engineering, Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Guy Gurevitch
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lottem Bergman
- Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Lilach Goldstein
- Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Firas Fahoum
- Department of Neurology and Neurosurgery, School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Ido Strauss
- Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Levett JJ, Elkaim LM, Niazi F, Weber MH, Iorio-Morin C, Bonizzato M, Weil AG. Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review. Neuromodulation 2024; 27:597-603. [PMID: 37943244 DOI: 10.1016/j.neurom.2023.10.006] [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: 06/12/2023] [Revised: 09/10/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023]
Abstract
STUDY DESIGN Systematic review of the literature. OBJECTIVES In recent years, brain-computer interface (BCI) has emerged as a potential treatment for patients with spinal cord injury (SCI). This is the first systematic review of the literature on invasive closed-loop BCI technologies for the treatment of SCI in humans. MATERIALS AND METHODS A comprehensive search of PubMed MEDLINE, Web of Science, and Ovid EMBASE was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS Of 8316 articles collected, 19 studies met all the inclusion criteria. Data from 21 patients were extracted from these studies. All patients sustained a cervical SCI and were treated using either a BCI with intracortical microelectrode arrays (n = 18, 85.7%) or electrocorticography (n = 3, 14.3%). To decode these neural signals, machine learning and statistical models were used: support vector machine in eight patients (38.1%), linear estimator in seven patients (33.3%), Hidden Markov Model in three patients (14.3%), and other in three patients (14.3%). As the outputs, ten patients (47.6%) underwent noninvasive functional electrical stimulation (FES) with a cuff; one (4.8%) had an invasive FES with percutaneous stimulation, and ten (47.6%) used an external device (neuroprosthesis or virtual avatar). Motor function was restored in all patients for each assigned task. Clinical outcome measures were heterogeneous across all studies. CONCLUSIONS Invasive techniques of BCI show promise for the treatment of SCI, but there is currently no technology that can restore complete functional autonomy in patients with SCI. The current techniques and outcomes of BCI vary greatly. Because invasive BCIs are still in the early stages of development, further clinical studies should be conducted to optimize the prognosis for patients with SCI.
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Affiliation(s)
- Jordan J Levett
- Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Lior M Elkaim
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Farbod Niazi
- Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Michael H Weber
- Department of Orthopaedic Surgery, McGill University, Montreal, Quebec, Canada
| | | | - Marco Bonizzato
- Department of Electrical Engineering and Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, Quebec, Canada; Department of Neuroscience and Centre interdisciplinaire sur le cerveau et l'apprentissage, University of Montreal, Montreal, Quebec, Canada
| | - Alexander G Weil
- Division of Neurosurgery, St-Justine University Hospital, Montreal, Quebec, Canada.
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Villar Ortega E, Buetler KA, Aksöz EA, Marchal-Crespo L. Enhancing touch sensibility with sensory electrical stimulation and sensory retraining. J Neuroeng Rehabil 2024; 21:79. [PMID: 38750521 PMCID: PMC11096118 DOI: 10.1186/s12984-024-01371-4] [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: 09/18/2023] [Accepted: 05/08/2024] [Indexed: 05/18/2024] Open
Abstract
A large proportion of stroke survivors suffer from sensory loss, negatively impacting their independence, quality of life, and neurorehabilitation prognosis. Despite the high prevalence of somatosensory impairments, our understanding of somatosensory interventions such as sensory electrical stimulation (SES) in neurorehabilitation is limited. We aimed to study the effectiveness of SES combined with a sensory discrimination task in a well-controlled virtual environment in healthy participants, setting a foundation for its potential application in stroke rehabilitation. We employed electroencephalography (EEG) to gain a better understanding of the underlying neural mechanisms and dynamics associated with sensory training and SES. We conducted a single-session experiment with 26 healthy participants who explored a set of three visually identical virtual textures-haptically rendered by a robotic device and that differed in their spatial period-while physically guided by the robot to identify the odd texture. The experiment consisted of three phases: pre-intervention, intervention, and post-intervention. Half the participants received subthreshold whole-hand SES during the intervention, while the other half received sham stimulation. We evaluated changes in task performance-assessed by the probability of correct responses-before and after intervention and between groups. We also evaluated differences in the exploration behavior, e.g., scanning speed. EEG was employed to examine the effects of the intervention on brain activity, particularly in the alpha frequency band (8-13 Hz) associated with sensory processing. We found that participants in the SES group improved their task performance after intervention and their scanning speed during and after intervention, while the sham group did not improve their task performance. However, the differences in task performance improvements between groups only approached significance. Furthermore, we found that alpha power was sensitive to the effects of SES; participants in the stimulation group exhibited enhanced brain signals associated with improved touch sensitivity likely due to the effects of SES on the central nervous system, while the increase in alpha power for the sham group was less pronounced. Our findings suggest that SES enhances texture discrimination after training and has a positive effect on sensory-related brain areas. Further research involving brain-injured patients is needed to confirm the potential benefit of our solution in neurorehabilitation.
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Affiliation(s)
- Eduardo Villar Ortega
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Karin A Buetler
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Efe Anil Aksöz
- rehaLab-The Laboratory for Rehabilitation Engineering, Institute for Human Centred Engineering HuCE, Division of Mechatronics and Systems Engineering, Department of Engineering and Information Technology, Bern University of Applied Sciences, Biel, Switzerland
| | - Laura Marchal-Crespo
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
- Department of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands.
- Department of Rehabilitation Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
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Voigtlaender S, Pawelczyk J, Geiger M, Vaios EJ, Karschnia P, Cudkowicz M, Dietrich J, Haraldsen IRJH, Feigin V, Owolabi M, White TL, Świeboda P, Farahany N, Natarajan V, Winter SF. Artificial intelligence in neurology: opportunities, challenges, and policy implications. J Neurol 2024; 271:2258-2273. [PMID: 38367046 DOI: 10.1007/s00415-024-12220-8] [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: 12/20/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/19/2024]
Abstract
Neurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain health has become a global priority with adoption of the World Health Organization's Intersectoral Global Action Plan in 2022. Simultaneously, rapid advancements in artificial intelligence (AI) are revolutionizing neurological research and practice. This scoping review of 66 original articles explores the value of AI in neurology and brain health, systematizing the landscape for emergent clinical opportunities and future trends across the care trajectory: prevention, risk stratification, early detection, diagnosis, management, and rehabilitation. AI's potential to advance personalized precision neurology and global brain health directives hinges on resolving core challenges across four pillars-models, data, feasibility/equity, and regulation/innovation-through concerted pursuit of targeted recommendations. Paramount actions include swift, ethical, equity-focused integration of novel technologies into clinical workflows, mitigating data-related issues, counteracting digital inequity gaps, and establishing robust governance frameworks balancing safety and innovation.
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Affiliation(s)
- Sebastian Voigtlaender
- Systems Neuroscience Division, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Virtual Diagnostics Team, QuantCo Inc., Cambridge, MA, USA
| | - Johannes Pawelczyk
- Faculty of Medicine, Ruprecht-Karls-University, Heidelberg, Germany
- Graduate Center of Medicine and Health, Technical University Munich, Munich, Germany
| | - Mario Geiger
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- NVIDIA, Zurich, Switzerland
| | - Eugene J Vaios
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Philipp Karschnia
- Department of Neurosurgery, Ludwig-Maximilians-University and University Hospital Munich, Munich, Germany
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Merit Cudkowicz
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jorg Dietrich
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ira R J Hebold Haraldsen
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Valery Feigin
- National Institute for Stroke and Applied Neurosciences, Auckland University of Technology, Auckland, New Zealand
| | - Mayowa Owolabi
- Center for Genomics and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Neurology Unit, Department of Medicine, University of Ibadan, Ibadan, Nigeria
- Blossom Specialist Medical Center, Ibadan, Nigeria
- Lebanese American University of Beirut, Beirut, Lebanon
| | - Tara L White
- Department of Behavioral and Social Sciences, Brown University, Providence, RI, USA
| | | | | | | | - Sebastian F Winter
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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9
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Varaganti P, Seo S. Recent Advances in Biomimetics for the Development of Bio-Inspired Prosthetic Limbs. Biomimetics (Basel) 2024; 9:273. [PMID: 38786483 PMCID: PMC11118077 DOI: 10.3390/biomimetics9050273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 04/29/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Recent advancements in biomimetics have spurred significant innovations in prosthetic limb development by leveraging the intricate designs and mechanisms found in nature. Biomimetics, also known as "nature-inspired engineering", involves studying and emulating biological systems to address complex human challenges. This comprehensive review provides insights into the latest trends in biomimetic prosthetics, focusing on leveraging knowledge from natural biomechanics, sensory feedback mechanisms, and control systems to closely mimic biological appendages. Highlighted breakthroughs include the integration of cutting-edge materials and manufacturing techniques such as 3D printing, facilitating seamless anatomical integration of prosthetic limbs. Additionally, the incorporation of neural interfaces and sensory feedback systems enhances control and movement, while technologies like 3D scanning enable personalized customization, optimizing comfort and functionality for individual users. Ongoing research efforts in biomimetics hold promise for further advancements, offering enhanced mobility and integration for individuals with limb loss or impairment. This review illuminates the dynamic landscape of biomimetic prosthetic technology, emphasizing its transformative potential in rehabilitation and assistive technologies. It envisions a future where prosthetic solutions seamlessly integrate with the human body, augmenting both mobility and quality of life.
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Affiliation(s)
| | - Soonmin Seo
- Department of Bionano Technology, Gachon University, Seongnam 13120, Republic of Korea;
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10
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Carè M, Chiappalone M, Cota VR. Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function. Front Neurosci 2024; 18:1363128. [PMID: 38516316 PMCID: PMC10954825 DOI: 10.3389/fnins.2024.1363128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 02/22/2024] [Indexed: 03/23/2024] Open
Abstract
Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.
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Affiliation(s)
- Marta Carè
- IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, Genova, Italy
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genova, Italy
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11
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Vardalakis N, Aussel A, Rougier NP, Wagner FB. A dynamical computational model of theta generation in hippocampal circuits to study theta-gamma oscillations during neurostimulation. eLife 2024; 12:RP87356. [PMID: 38354040 PMCID: PMC10942594 DOI: 10.7554/elife.87356] [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] [Indexed: 02/16/2024] Open
Abstract
Neurostimulation of the hippocampal formation has shown promising results for modulating memory but the underlying mechanisms remain unclear. In particular, the effects on hippocampal theta-nested gamma oscillations and theta phase reset, which are both crucial for memory processes, are unknown. Moreover, these effects cannot be investigated using current computational models, which consider theta oscillations with a fixed amplitude and phase velocity. Here, we developed a novel computational model that includes the medial septum, represented as a set of abstract Kuramoto oscillators producing a dynamical theta rhythm with phase reset, and the hippocampal formation, composed of biophysically realistic neurons and able to generate theta-nested gamma oscillations under theta drive. We showed that, for theta inputs just below the threshold to induce self-sustained theta-nested gamma oscillations, a single stimulation pulse could switch the network behavior from non-oscillatory to a state producing sustained oscillations. Next, we demonstrated that, for a weaker theta input, pulse train stimulation at the theta frequency could transiently restore seemingly physiological oscillations. Importantly, the presence of phase reset influenced whether these two effects depended on the phase at which stimulation onset was delivered, which has practical implications for designing neurostimulation protocols that are triggered by the phase of ongoing theta oscillations. This novel model opens new avenues for studying the effects of neurostimulation on the hippocampal formation. Furthermore, our hybrid approach that combines different levels of abstraction could be extended in future work to other neural circuits that produce dynamical brain rhythms.
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Affiliation(s)
- Nikolaos Vardalakis
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
| | - Amélie Aussel
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
- University of Bordeaux, CNRS, Bordeaux INPTalenceFrance
| | - Nicolas P Rougier
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
- University of Bordeaux, CNRS, Bordeaux INPTalenceFrance
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12
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Qian Y, Alhaskawi A, Dong Y, Ni J, Abdalbary S, Lu H. Transforming medicine: artificial intelligence integration in the peripheral nervous system. Front Neurol 2024; 15:1332048. [PMID: 38419700 PMCID: PMC10899496 DOI: 10.3389/fneur.2024.1332048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/01/2024] [Indexed: 03/02/2024] Open
Abstract
In recent years, artificial intelligence (AI) has undergone remarkable advancements, exerting a significant influence across a multitude of fields. One area that has particularly garnered attention and witnessed substantial progress is its integration into the realm of the nervous system. This article provides a comprehensive examination of AI's applications within the peripheral nervous system, with a specific focus on AI-enhanced diagnostics for peripheral nervous system disorders, AI-driven pain management, advancements in neuroprosthetics, and the development of neural network models. By illuminating these facets, we unveil the burgeoning opportunities for revolutionary medical interventions and the enhancement of human capabilities, thus paving the way for a future in which AI becomes an integral component of our nervous system's interface.
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Affiliation(s)
- Yue Qian
- Rehabilitation Center, Hangzhou Wuyunshan Hospital (Hangzhou Institute of Health Promotion), Hangzhou, China
| | - Ahmad Alhaskawi
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yanzhao Dong
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Juemin Ni
- Rehabilitation Center, Hangzhou Wuyunshan Hospital (Hangzhou Institute of Health Promotion), Hangzhou, China
| | - Sahar Abdalbary
- Department of Orthopedic Physical Therapy, Faculty of Physical Therapy, Nahda University in Beni Suef, Beni Suef, Egypt
| | - Hui Lu
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
- Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Zhejiang University, Hangzhou, China
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13
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Wang S, Aljirafi FO, Payne GF, Bentley WE. Excite the unexcitable: engineering cells and redox signaling for targeted bioelectronic control. Curr Opin Biotechnol 2024; 85:103052. [PMID: 38150921 DOI: 10.1016/j.copbio.2023.103052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/17/2023] [Accepted: 11/28/2023] [Indexed: 12/29/2023]
Abstract
The ever-growing influence of technology in our lives has led to an increasing interest in the development of smart electronic devices to interrogate and control biological systems. Recently, redox-mediated electrogenetics introduced a novel avenue that enables direct bioelectronic control at the genetic level. In this review, we discuss recent advances in methodologies for bioelectronic control, ranging from electrical stimulation to engineering efforts that allow traditionally unexcitable cells to be electrically 'programmable.' Alongside ion-transport signaling, we suggest redox as a route for rational engineering because it is a native form of electronic communication in biology. Using redox as a common language allows the interfacing of electronics and biology. This newfound connection opens a gateway of possibilities for next-generation bioelectronic tools.
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Affiliation(s)
- Sally Wang
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA; Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA; Fischell Institute of Biomedical Devices, University of Maryland, College Park, MD, USA
| | - Futoon O Aljirafi
- Fischell Institute of Biomedical Devices, University of Maryland, College Park, MD, USA; Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, USA
| | - Gregory F Payne
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA; Fischell Institute of Biomedical Devices, University of Maryland, College Park, MD, USA
| | - William E Bentley
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA; Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD, USA; Fischell Institute of Biomedical Devices, University of Maryland, College Park, MD, USA
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Mishra S, Shah H, Patel A, Tripathi SM, Malviya R, Prajapati BG. Applications of Bioengineered Polymer in the Field of Nano-Based Drug Delivery. ACS OMEGA 2024; 9:81-96. [PMID: 38222544 PMCID: PMC10785663 DOI: 10.1021/acsomega.3c07356] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 01/16/2024]
Abstract
The most favored route of drug administration is oral administration; however, several factors, including poor solubility, low bioavailability, and degradation, in the severe gastrointestinal environment frequently compromise the effectiveness of drugs taken orally. Bioengineered polymers have been developed to overcome these difficulties and enhance the delivery of therapeutic agents. Polymeric nanoparticles, including carbon dots, fullerenes, and quantum dots, have emerged as crucial components in this context. They provide a novel way to deliver various therapeutic materials, including proteins, vaccine antigens, and medications, precisely to the locations where they are supposed to have an effect. The promise of this integrated strategy, which combines nanoparticles with bioengineered polymers, is to address the drawbacks of conventional oral medication delivery such as poor solubility, low bioavailability, and early degradation. In recent years, we have seen substantially increased interest in bioengineered polymers because of their distinctive qualities, such as biocompatibility, biodegradability, and flexible physicochemical characteristics. The different bioengineered polymers, such as chitosan, alginate, and poly(lactic-co-glycolic acid), can shield medications or antigens from degradation in unfavorable conditions and aid in the administration of drugs orally through mucosal delivery with lower cytotoxicity, thus used in targeted drug delivery. Future research in this area should focus on optimizing the physicochemical properties of these polymers to improve their performance as drug delivery carriers.
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Affiliation(s)
- Sudhanshu Mishra
- Department
of Pharmaceutical Science & Technology, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh 273016, India
| | - Harshil Shah
- Cosette
Pharmaceuticals Inc., South
Plainfield, New Jersey 07080, United States
| | - Artiben Patel
- Cosette
Pharmaceuticals Inc., South
Plainfield, New Jersey 07080, United States
| | - Shivendra Mani Tripathi
- Department
of Pharmaceutical Science & Technology, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh 273016, India
| | - Rishabha Malviya
- Department
of Pharmacy, School of Medical and Allied Sciences, Galgotias University, Noida, Uttar Pradesh 203201, India
| | - Bhupendra G. Prajapati
- Shree
S. K. Patel College of Pharmaceutical Education and Research, Ganpat University, Kherva 384012, India
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15
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Sparling T, Iyer L, Pasquina P, Petrus E. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery. J Neurosci 2024; 44:e1051232024. [PMID: 38171645 PMCID: PMC10851691 DOI: 10.1523/jneurosci.1051-23.2023] [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: 06/08/2023] [Revised: 08/28/2023] [Accepted: 09/29/2023] [Indexed: 01/05/2024] Open
Abstract
Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.
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Affiliation(s)
- Tawnee Sparling
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Laxmi Iyer
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817
| | - Paul Pasquina
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Emily Petrus
- Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, Maryland 20814
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Muzaimi M, Prakash KNB, Cheah PS, Feng L. Editorial: New challenges and future perspectives in pathological conditions. Front Behav Neurosci 2023; 17:1201044. [PMID: 37304763 PMCID: PMC10250722 DOI: 10.3389/fnbeh.2023.1201044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 05/11/2023] [Indexed: 06/13/2023] Open
Affiliation(s)
- Mustapha Muzaimi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - K. N. Bhanu Prakash
- Cellular Image Informatics Division, Bioinformatics Institute (ASTAR), Singapore, Singapore
| | - Pike See Cheah
- Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia
| | - Linqing Feng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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Abstract
Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although prosthetic hand devices with myoelectric control can be dated back to more than 70 years ago, their applications with anthropomorphic robotic mechanisms and sensory feedback functions are still at a relatively preliminary and laboratory stage. Nevertheless, a recent series of proof-of-concept studies suggest that soft robotics technology may be promising and useful in alleviating the design complexity of the dexterous mechanism and integration difficulty of multifunctional artificial skins, in particular, in the context of personalized applications. Here, we review the evolution of neuroprosthetic hands with the emerging and cutting-edge soft robotics, covering the soft and anthropomorphic prosthetic hand design and relating bidirectional neural interactions with myoelectric control and sensory feedback. We further discuss future opportunities on revolutionized mechanisms, high-performance soft sensors, and compliant neural-interaction interfaces for the next generation of neuroprosthetic hands.
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Affiliation(s)
- Guoying Gu
- Robotics Institute, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- Meta Robotics Institute, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ningbin Zhang
- Robotics Institute, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chen Chen
- Robotics Institute, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Haipeng Xu
- Robotics Institute, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xiangyang Zhu
- Robotics Institute, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- Meta Robotics Institute, Shanghai Jiao Tong University, Shanghai 200240, China
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