Academic literature on the topic 'Neural interfaces'

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Journal articles on the topic "Neural interfaces"

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Grill, Warren. "Neural Interfaces." American Scientist 98, no. 1 (2010): 48. http://dx.doi.org/10.1511/2010.82.48.

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Warden, Melissa R., Jessica A. Cardin, and Karl Deisseroth. "Optical Neural Interfaces." Annual Review of Biomedical Engineering 16, no. 1 (July 11, 2014): 103–29. http://dx.doi.org/10.1146/annurev-bioeng-071813-104733.

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Zhang, Milin, Zijian Tang, Xilin Liu, and Jan Van der Spiegel. "Electronic neural interfaces." Nature Electronics 3, no. 4 (April 2020): 191–200. http://dx.doi.org/10.1038/s41928-020-0390-3.

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Zhang, Hongzhi, Mei Yu, Lei Xie, Linlin Jin, and Zhe Yu. "Carbon-Nanofibers-Based Micro-/Nanodevices for Neural-Electrical and Neural-Chemical Interfaces." Journal of Nanomaterials 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/280902.

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Carbon nanofibers (CNFs) have shown great potentials for development of micro-/nanodevices for neural interfaces due to their suitable properties, such as chemical stability, good electrical conductivity, ultramicro size with low electrical impedance, 3D structures with high surface-to-volume ratio, and long-term biocompatibility. In this paper, we review the applications of CNFs as neural-electrical interfaces and neural-chemical interfaces for neural recording and stimulation, electroconductive nanofibrous scaffolds for nerve tissue engineering, drug and gene delivery, and neurochemical sensing. The CNFs-based micro-/nanodevices provide new platforms to fine-tune electrical and chemical cues of neurons at subcellular nanoscale, which can be used for both fundamental studies of material-cell interactions and the development of chronically stable, implantable neural interface devices. Further development of this technology may potentially enable a highly multiplex closed-loop system with multifunctions for neuromodulation and neuroprostheses.
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Ahmed, Zabir, Jay W. Reddy, Mohammad H. Malekoshoaraie, Vahid Hassanzade, Ibrahim Kimukin, Vishal Jain, and Maysamreza Chamanzar. "Flexible optoelectric neural interfaces." Current Opinion in Biotechnology 72 (December 2021): 121–30. http://dx.doi.org/10.1016/j.copbio.2021.11.001.

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Kuncel, Alexis M., and Warren M. Grill. "NIH Neural Interfaces Workshop." Expert Review of Medical Devices 3, no. 6 (November 2006): 695–97. http://dx.doi.org/10.1586/17434440.3.6.695.

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Bellamkonda, Ravi V., S. Balakrishna Pai, and Philippe Renaud. "Materials for neural interfaces." MRS Bulletin 37, no. 6 (June 2012): 557–61. http://dx.doi.org/10.1557/mrs.2012.122.

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Sheng, Hao, Xiaomeng Wang, Ning Kong, Wang Xi, Hang Yang, Xiaotong Wu, Kangling Wu, et al. "Neural interfaces by hydrogels." Extreme Mechanics Letters 30 (July 2019): 100510. http://dx.doi.org/10.1016/j.eml.2019.100510.

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Wang, Yongchen, Hanlin Zhu, Huiran Yang, Aaron D. Argall, Lan Luan, Chong Xie, and Liang Guo. "Nano functional neural interfaces." Nano Research 11, no. 10 (July 10, 2018): 5065–106. http://dx.doi.org/10.1007/s12274-018-2127-4.

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Wang, Xiaomeng, Hao Sheng, and Hao Wang. "Neural interfaces by hydrogels." IBRO Reports 6 (September 2019): S394. http://dx.doi.org/10.1016/j.ibror.2019.07.1252.

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Dissertations / Theses on the topic "Neural interfaces"

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Minev, Ivan Rusev. "Soft neural interfaces." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610257.

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Park, Seongjun. "Multifunctional fiber-based neural interfaces." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118086.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 161-174).
Neurological disorders affect up to a billion people worldwide, and their socioeconomic burden is projected to increase as the population ages. However, our ability to understand and to treat neural disorders is currently limited by the lack of tools capable of interfacing with the brain over extended periods of time. This is hypothesized to stem from the mismatch in mechanical and chemical properties between the neural probes and the neural tissues, which leads to foreign body response and functional device failure due to tissue scarring in the probe vicinity. To address the challenge, I developed fiber-based bioelectronic devices integrating diverse modalities within a single platform using thermal drawing process (TDP). All-polymer or hydrogel integrated probes with optical, electrical, and fluidic capabilities were developed all within the 100-200 [mu]m diameter, which allowed one-step surgery to the mouse brain and spinal cord for optogenetic experiments. This probe also addressed the challenge of biocompatibility and enabled the recording isolated action potentials for 3 months. In addition, I applied TPD to produce biocompatible polymer-based neural scaffold with various geometries (round, rectangular, micro-grooved) and dimensions between 50-200 [mu]m. This allowed for investigation of the enhancement of neurite growth as a function of fiber parameters. We found that the topographical features and the narrow channels generally led to enhanced growth. This thesis illustrated a variety of applications of multifunctional fiber-based devices in neuroscience and neural engineering, which anticipated to enable basic studies of the nervous system and future treatment of neurological disorders.
by Seongjun Park.
Ph. D.
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3

Garcia, Cortadella Ramon. "High-Bandwidth Graphene Neural Interfaces." Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/673787.

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El funcionament del cervell es basa en processos complexos, que encara no s’han descrit i comprès detalladament. En les últimes dècades, la neurociència ha experimentat un desenvolupament accelerat, impulsat per noves neurotecnologías que permeten monitoritzar les dinàmiques de l’activitat elèctrica al cervell amb una major resolució espai-temporal i una àrea de cobertura més àmplia. No obstant això, a causa de l’alta complexitat de les xarxes neuronals al cervell, que són compostes per poblacions neuronals fortament interconnectades en àmplies regions cerebrals, estem lluny de detectar una fracció significativa de les neurones que donen lloc a funcions complexes. Per tal d’investigar les dinàmiques neuronals a gran escala amb alta resolució espacial, s’han utilitzat diverses tecnologies, que inclouen la ressonància magnética funcional (fMRI), imatges amb marcadors sensibles al voltatge o registres electrofisiològics d’alt recompte de sensors. No obstant això, la resolució temporal del fMRI i els mètodes òptics es limita típicament a uns pocs hertzs, gairebé tres ordres de magnitud per sota de la dels potencials d’acció, i es limiten a les condicions en què el subjecte es troba immòbil. D’altra banda, els registres electrofisiològics basats en matrius de microelèctrodes proporcionen una alta resolució espai-temporal, el que permet detectar amb precisió dinàmiques ràpides de centenars de neurones individuals simultàniament en animals que es mouen lliurement. No obstant això, les interfícies de detecció neuroelectrónica presenten una limitació en el producte entre la resolució espacial i l’àrea de cobertura. A més, presenten una baixa sensibilitat a la banda de freqüència infra-lenta (<0.5Hz), que està relacionada amb la connectivitat funcional de llarg abast. En aquesta tesi es presenta una nova tecnologia basada en sensors actius de grafè, que permet incrementar l’àrea de cobertura i la resolució espacial dels registres electrofisiològics conservant una alta sensibilitat en una banda de freqüència àmplia, des de l’activitat infra-lenta fins a la de una sola cèl·lula electrogénica. Aquest desenvolupament tecnològic es divideix en tres etapes principals; en primer lloc, s’obté una comprensió més profunda de les característiques intrínseques del soroll i la resposta en freqüència d’aquests sensors basant-se en l’estat de l’art en tecnologia de sensors de grafè. En la segona etapa, es mostra un sistema quasi-comercial basat en matrius de sensors de grafè epi-cortical i transmissió sense fil per a la implantació crònica en rates. Amb aquest sistema, es demostra la reproductibilitat de les matrius de sensors de grafè, la seva estabilitat a llarg termini i la seva biocompatibilitat crònica. A més, es proporciona evidència preliminar per a una àmplia gamma de nous patrons electrofisiològics gràcies a la seva sensibilitat en la banda de freqüència infra-lenta. Finalment, en l’última etapa d’aquesta tesi, l’enfocament se centra en el desenvolupament de noves estratègies de multiplexació per augmentar el nombre de sensors a les sondes neuronals. Aquestes tres etapes principals de desenvolupament han portat a la demostració del potencial de les matrius de sensors de grafè multiplexats per al mapejat de les dinàmiques neuronals a gran escala en una banda de freqüència àmplia, en animals que es mouen lliurement, durant llargs períodes. La combinació d’aquestes capacitats fa que les matrius de sensors actius de grafè siguin una tecnologia prometedora per a interfícies cervell-ordinador d’alt ample de banda i una eina única per investigar el paper de l’activitat infra-lenta en la coordinació de les dinàmiques neuronals d’alta freqüència.
El funcionamiento del cerebro se basa en procesos complejos, que aún no se han descrito y comprendido detalladamente. En las últimas décadas, la neurociencia ha experimentado un desarrollo acelerado, impulsado por nuevas neurotecnologías que permiten monitorear la dinámica de la actividad eléctrica en el cerebro con una mayor resolución espacio-temporal y un área de cobertura más amplia. Sin embargo, debido a la alta complejidad de las redes neuronales en el cerebro, que están compuestas por poblaciones neuronales fuertemente interconectadas en amplias regiones cerebrales, estamos lejos de monitorear una fracción significativa de neuronas que dan lugar a funciones complejas. Con el fin de investigar las dinámica neuronales a gran escala con alta resolución espacial, se han utilizado diversas tecnologías, que incluyen la resonancia magnética funcional (fMRI), imágenes con marcadores sensibles al voltaje o registros electrofisiológicos de alto conteo de sensores. Sin embargo, la resolución temporal del fMRI y los métodos ópticos se limita típicamente a unos pocos hercios, casi tres órdenes de magnitud por debajo de la de los potenciales de acción, y se limitan a condiciones en los que el sujeto se encuentra inmóvil. Por otro lado, los registros electrofisiológicos basados en matrices de microelectrodos proporcionan una alta resolución espacio-temporal, lo que permite detectar con precisión dinámicas rápidas de cientos de neuronas individuales simultáneamente en animales que se mueven libremente. Sin embargo, las interfaces de detección neuroelectrónica presentan una limitación en el producto entre la resolución espacial y el área de cobertura. Además, presentan una baja sensibilidad en la banda de frecuencia infra-lenta (<0.5Hz), que está relacionada con la conectividad funcional de largo alcance. En esta tesis se presenta una nueva tecnología basada en sensores activos de grafeno, que permite incrementar el área de cobertura y la resolución espacial de los registros electrofisiológicos conservando una alta sensibilidad en una amplia banda de frecuencia, desde la actividad infra-lenta hasta la de una sola célula electrogénica. Este desarrollo tecnológico se divide en tres etapas principales; en primer lugar, se obtiene una comprensión más profunda de las características intrínsecas del ruido y la respuesta en frecuencia de estos sensores basándose en el estado del arte en tecnología de sensores de grafeno. En la segunda etapa, se muestra un sistema cuasi-comercial basado en matrices de sensores de grafeno epi-cortical y transmisión inalámbrica para implantación crónica en ratas. Con este sistema, se demuestra la reproducibilidad de las matrices de sensores de grafeno, su estabilidad a largo plazo y su biocompatibilidad crónica. Además, se proporciona evidencia preliminar para una amplia gama de nuevos patrones electrofisiológicos debido a su sensibilidad en la banda de frecuencia infra-lenta. Finalmente, en la última etapa de esta tesis, el enfoque se centra en el desarrollo de nuevas estrategias de multiplexación para aumentar el número de sensores en las sondas neuronales. Estas tres etapas principales de desarrollo han llevado a la demostración del potencial de las matrices de sensores de grafeno multiplexados para el mapeado de las dinámicas neuronales a gran escala en una amplia banda de frecuencia en animales que se mueven libremente durante largos períodos. La combinación de estas capacidades hace que las matrices de sensores activos de grafeno sean una tecnología prometedora para interfaces cerebro-ordenador de alto ancho de banda y una herramienta única para investigar el papel de la actividad infra-lenta en la coordinación de las dinámicas neuronales de alta frecuencia.
Brain function is based on highly complex processes, which remain yet to be described and understood in detail. In the last decades, neuroscience has experienced an accelerated development, prompted by novel neurotechnologies that allow monitoring the dynamics of electrical activity in the brain with a higher spatio-temporal resolution and wider coverage area. However, due to the high complexity of neural networks in the brain, which are composed of strongly interconnected neural populations across large brain regions, we are far from monitoring a significant fraction of neurons mediating complex functions. In order to investigate large-scale brain dynamics with high spatial resolution several technologies have been extensively used, including functional magnetic resonance imaging (fMRI), voltage-sensitive dye imaging or high sensor-count electrophysiological recordings. However, the temporal resolution of fMRI and optical methods is typically limited to few hertz, almost three orders of magnitude below that of action potentials, and are limited to head-fixed conditions. On the other hand, electrophysiological recordings based on micro-electrode arrays provide a high spatio-temporal resolution, allowing to accurately detect fast dynamics from hundreds of individual neurons simultaneously in freely moving animals. However, neuroelectronic sensing interfaces present a trade-off between spatial resolution and coverage area. Moreover, they present a poor sensitivity in the infra-slow frequency band ($<0.5$\,$Hz$), which is related to long-range functional connectivity. In this thesis, a novel technology based on graphene active sensors is presented, which allows to increase the coverage area and spatial resolution of electrophysiological recordings while preserving a high sensitivity in a wide frequency band, from infra-slow to single electrogenic cell activity. This technological development is divided into three main stages; first, a deeper understanding of the intrinsic noise characteristics and frequency response of these sensors is obtained by building on prior graphene sensor technology. In the second stage, a quasi-commercial system based on epi-cortical graphene sensor arrays and a wireless headstage for chronic implantation in rats is shown. Using this system, the reproducibility of the graphene sensor arrays, their long-term stability and their chronic biocompatibility are demonstrated. Furthermore, preliminary evidence is provided for a wide range of novel electrophysiological patterns owing to their sensitivity in the infra-slow frequency band. Finally, in the last stage of this thesis, the focus is centred on the development of new multiplexing strategies to upscale the number of sensors on the neural probes. These three main development stages have led to the demonstration of the potential of multiplexed graphene sensor arrays for mapping of large-scale brain dynamics in a wide frequency band in freely moving animals over long periods. The combination of these capabilities makes graphene active sensor arrays a promising technology for high bandwidth brain computer interfaces and a unique tool to investigate the role of infra-slow activity on the coordination of higher frequency brain dynamics.
Universitat Autònoma de Barcelona. Programa de Doctorat en Enginyeria Electrònica i de Telecomunicació
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4

Barrett, Richard. "Novel processing routes for neural interfaces." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/5137/.

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The thesis describes novel processing routes that have been developed to fabricate neural interfaces. A process has been investigated that uses microfabrication techniques to fabricate a multi-channel regenerative implant that can record nerve impulses in the peripheral nervous system (PNS), called the Spiral Peripheral Nerve Interface (SPNI). It is shown both theoretically and experimentally that the implant improves the ability to record signals in the PNS via micro-channels that act as axonal amplifiers. New processing routes are introduced to create robust interconnections from the SPNI to external electronics via ‘Microflex’ technology. To incorporate the new interconnection technology the SPNI had to be modified. During this modification the strain in the device was given specific consideration, for which a new bending model is presented. Modelling is used to show that electrochemical impedance spectroscopy can be used to assess the quality of the fabrication process. Electrochemical and mechanical tests show that the interconnection technology is suitable for a neural interfaces but the fabrication of perfectly sealed micro-channels was not evident. Thus, the SPNI was further improved by the introduction of a silicone sealing layer in the construction of the micro-channel array that was implemented using a novel adhesive bonding technique.
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Watterson, William James. "Fractal Interfaces for Stimulating and Recording Neural Implants." Thesis, University of Oregon, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10636408.

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From investigating movement in an insect to deciphering cognition in a human brain to treating Parkinson's disease, hearing loss, or even blindness, electronic implants are an essential tool for understanding the brain and treating neural diseases. Currently, the stimulating and recording resolution of these implants remains low. For instance, they can record all the neuron activity associated with movement in an insect, but are quite far from recording, at an individual neuron resolution, the large volumes of brain tissue associated with cognition. Likewise, there is remarkable success in the cochlear implant restoring hearing due to the relatively simple anatomy of the auditory nerves, but are failing to restore vision to the blind due to poor signal fidelity and transmission in stimulating the more complex anatomy of the visual nerves. The critically important research needed to improve the resolution of these implants is to optimize the neuron-electrode interface. This thesis explores geometrical and material modifications to both stimulating and recording electrodes which can improve the neuron-electrode interface. First, we introduce a fractal electrode geometry which radically improves the restored visual acuity achieved by retinal implants and leads to safe, long-term operation of the implant. Next, we demonstrate excellent neuron survival and neurite outgrowth on carbon nanotube electrodes, thus providing a safe biomaterial which forms a strong connection between the electrode and neurons. Additional preliminary evidence suggests carbon nanotubes patterned into a fractal geometry will provide further benefits in improving the electrode-neuron interface. Finally, we propose a novel implant based off field effect transistor technology which utilizes an interconnecting fractal network of semiconducting carbon nanotubes to record from thousands of neurons simutaneously at an individual neuron resolution. Taken together, these improvements have the potential to radically improve our understanding of the brain and our ability to restore function to patients of neural diseases.

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Tringides, Christina M. (Christina Myra). "Materials selection and processing for reliable neural interfaces." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98667.

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Thesis: S.B., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 48-50).
The understanding of the brain would be revolutionized by a tool that can measure intra- and extra-cellular electrical potentials on a parallelized scale, without disrupting the neural physiology. Existing technologies do not sufficiently carry out these functions. Using a thermal drawing process (TDP), multimaterial fibers comprised of polymer-metal composites can be fabricated to create flexible, microelectrode arrays. These fibers can be further processed after the TDP, using selective etching to reduce the diameter of the probe. These devices have been implanted and have been used to record neural activity in vivo while evoking minimal tissue response. Additionally, electrodeposition of biocompatible metals onto the fiber-electrode tips can be implemented to increase the signal-to-noise ratio (SNR). Here, I describe the electroplating of gold onto the fiber-tips of tin and tin-indium electrodes, which were drawn using TDP. By adjusting the electrodeposition conditions, the electrode tip geometries can be tuned to optimize the interface between the device tips and neuronal membranes.
by Christina M. Tringides.
S.B.
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7

Watterson, William. "Fractal Interfaces for Stimulating and Recording Neural Implants." Thesis, University of Oregon, 2018. http://hdl.handle.net/1794/23169.

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From investigating movement in an insect to deciphering cognition in a human brain to treating Parkinson's disease, hearing loss, or even blindness, electronic implants are an essential tool for understanding the brain and treating neural diseases. Currently, the stimulating and recording resolution of these implants remains low. For instance, they can record all the neuron activity associated with movement in an insect, but are quite far from recording, at an individual neuron resolution, the large volumes of brain tissue associated with cognition. Likewise, there is remarkable success in the cochlear implant restoring hearing due to the relatively simple anatomy of the auditory nerves, but are failing to restore vision to the blind due to poor signal fidelity and transmission in stimulating the more complex anatomy of the visual nerves. The critically important research needed to improve the resolution of these implants is to optimize the neuron-electrode interface. This thesis explores geometrical and material modifications to both stimulating and recording electrodes which can improve the neuron-electrode interface. First, we introduce a fractal electrode geometry which radically improves the restored visual acuity achieved by retinal implants and leads to safe, long-term operation of the implant. Next, we demonstrate excellent neuron survival and neurite outgrowth on carbon nanotube electrodes, thus providing a safe biomaterial which forms a strong connection between the electrode and neurons. Additional preliminary evidence suggests carbon nanotubes patterned into a fractal geometry will provide further benefits in improving the electrode-neuron interface. Finally, we propose a novel implant based off field effect transistor technology which utilizes an interconnecting fractal network of semiconducting carbon nanotubes to record from thousands of neurons simutaneously at an individual neuron resolution. Taken together, these improvements have the potential to radically improve our understanding of the brain and our ability to restore function to patients of neural diseases.
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8

Bonaccini, Calia Andrea. "Graphene field-effect transistors as flexible neural interfaces for intracortical electrophysiology." Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/671635.

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En els últims anys s’han produït desenvolupaments tecnològics innovadors en el camp dels implants neuronals per a aplicacions mèdiques. La comprensió de el cervell humà es considera com un dels majors reptes científics del nostre temps; com a conseqüència, estem sent testimonis d’una intensificació de la investigació en el desenvolupament de les interfícies cervell-màquina (IMC) per llegir i estimular l’activitat cerebral. No obstant això, els implants neuronals actualment disponibles ofereixen una eficàcia clínica modesta, en part a causa de les limitacions que plantegen la invasivitat dels materials. Aquests materials comprometen la resolució de la interfície, el rendiment i l’estabilitat a llarg termini dels implants. El desenvolupament d’una electrònica flexible que utilitzi materials biocompatibles és clau per al desenvolupament d’implants neuronals mínimament invasius, que puguin implantar-se de forma crònica. Un camp d’investigació molt prometedor, és l’ús de materials bidimensionals, com el grafè, per a aplicacions bioelectròniques. El transistor d’efecte de camp en solució de grafè (gSGFET) és una de d’aquestes noves tecnologies neuronals emergents. Aquests dispositius poden superar les limitacions esmentades anteriorment gràcies a les extraordinàries propietats del grafè, com ara la seva alta flexibilitat mecànica, estabilitat electroquímica, biocompatibilitat i alta sensibilitat. En aquesta tesi doctoral, s’han fabricat matrius de gSGFET i s’han optimitzat iterativament en termes de sensibilitat i relació senyal / soroll, adoptant mètodes de microfabricació a escala d’oblia. S’ha caracteritzat el soroll 1 / f en els gSGFETs i s’ha optimitzat amb un tractament UVO de la interfície metall / grafè i desacoblant el grafè del substrat utilitzant diferents nanomaterials com ara l’encapsulació del grafè amb nitrur de bor hexagonal (hBN), monocapes autoacoblades i grafè bicapa. A més, s’han fabricat amb èxit sondes neuronals epicorticals i intracorticals flexibles, que contenien matrius de gSGFET, i s’han fet enregistraments de microelectrocorticografia in vivo en rosegadors. S’han inserit dispositius intracorticals flexibles en el cervell utilitzant un protocol de reforç de la capa posterior del dispositiu amb proteïna de fibroïna de seda biorresistent. Els resultats presentats en aquesta tesi demostren la superior resolució espai-temporal dels gSGFET en comparació amb la tecnologia estàndard de microelèctrodes; en particular, la capacitat de mapejar amb alta fidelitat, l’activitat de molt baixa freqüència (ISA, <0,1 Hz) juntament amb els senyals en el típic ample de banda dels LFP. Avui dia se sap que l’activitat cerebral de molt baixa freqüència, contribueix a la fisiopatologia de diversos trastorns neurològics com el vessament cerebral, la lesió cerebral traumàtica, la migranya i l’epilèpsia. No obstant això, aquesta activitat rares vegades es registra a causa de les limitacions tècniques intrínseques dels elèctrodes convencionals acoblats a la CA. S’han obtingut mesures neuronals amb sondes de profunditat flexibles i multicanal de grafè (gDNP) en models animals desperts amb convulsions i epilèpsia. S’ha detectat i cartografiat l’AIS a través de diferents capes corticals i regions subcorticals, registrant simultàniament l’activitat epilèptica en bandes de freqüència més convencionals (1-600Hz). A més, com a part d’aquesta tesi s’ha demostrat també l’estabilitat i funcionalitat de registres a llarg termini, així com la biocompatibilitat dels gDNPs. La tecnologia bioelectrònica basada en grafè aquí descrita té el potencial d’esdevenir una eina de referència per a l’electrofisiologia d’ample de banda complet. Es preveu que aquesta tecnologia tingui un gran impacte en una comunitat àmplia i multidisciplinària que inclogui investigadors en neurotecnologia, enginyers biomèdics, neurocientífics que estudien la dinàmica cortical de banda ampla associada amb el comportament espontani i /o els estats cerebrals, així com investigadors clínics interessats en el paper de l’activitat de molt baixa freqüència en epilèpsia, els accidents cerebrovasculars i la migranya.
En los últimos años se han producido nuevos desarrollos tecnológicos en el campo de los implantes neuronales para aplicaciones médicas. La comprensión del cerebro humano se considera uno de los mayores desafíos científicos de nuestro tiempo; como consecuencia, estamos siendo testigos de una intensificación de la investigación en el desarrollo de las interfaces cerebro-máquina (IMC) para leer y estimular la actividad cerebral. No obstante, los implantes neuronales actualmente disponibles ofrecen una eficacia clínica modesta, en parte debido a las limitaciones que plantea la invasividad de los materiales. Esos materiales comprometen la resolución de la interfaz, el rendimiento y la estabilidad a largo plazo de los implantes neurales. El desarrollo de una electrónica flexible que utilice materiales biocompatibles es clave para la realización de implantes neuronales mínimamente invasivos que puedan implantarse de forma crónica. Un campo de investigación muy prometedor es el uso de materiales bidimensionales, como el grafeno, para aplicaciones bioelectrónicas. El transistor de efecto de campo en solución de grafeno (gSGFET) es una de dichas nuevas tecnologías neurales emergentes. Estos dispositivos pueden superar las limitaciones mencionadas anteriormente gracias a las extraordinarias propiedades del grafeno, como su alta flexibilidad mecánica, estabilidad electroquímica, biocompatibilidad y sensibilidad. En esta tesis doctoral, se han fabricado matrices de gSGFET y se han optimizado iterativamente en términos de sensibilidad y relación señal/ruido, adoptando métodos de microfabricación a escala de oblea. Se ha caracterizado el ruido 1/f en los gSGFETs y optimizado haciendo un tratamiento UVO en la interfaz metal/grafeno y desacoplando el canal de grafeno del sustrato utilizando diferentes nanomateriales como la encapsulación con nitruro de boro hexagonal (hBN), monocapas autoensambladas y bicapas de grafeno. Además, se han fabricado con éxito sondas neurales epicorticales e intracorticales flexibles con matrices de gSGFET y se han utilizado durante las medidas de microelectrocorticografía in vivo en roedores. Se han insertado dispositivos intracorticales flexibles en el cerebro utilizando un protocolo de refuerzo de la capa posterior de los dispositivos con proteína de fibroína de seda biorresistente. Los resultados presentados en esta tesis demuestran la superior resolución espacio-temporal de los gSGFET en comparación con la tecnología estándar de microelectrodos; en particular, referente a la capacidad de mapear con alta fidelidad, la actividad de muy baja frecuencia (ISA, < 0,1 Hz) junto con las señales en el típico ancho de banda LFP. Hoy en día se sabe que la actividad cerebral de muy baja frecuencia, contribuye a la fisiopatología de varios trastornos neurológicos como el derrame cerebral, la lesión cerebral traumática, la migraña y la epilepsia. Sin embargo, esta actividad rara vez se registra debido a las limitaciones técnicas intrínsecas de los electrodos convencionales acoplados a la CA. Se han obtenido registros con sondas neuronales de profundidad de grafeno (gDNP) en modelos animales de epilepsia. Se detectó ISA a través de diferentes capas corticales y regiones subcorticales, registrando simultáneamente la actividad epiléptica en bandas de frecuencia más convencionales (1-600Hz). Además, se ha demostrado también la evaluación de la estabilidad y funcionalidad en registros crónicos, así como la biocompatibilidad del gDNP. La tecnología bioelectrónica basada en el grafeno aquí descrita tiene el potencial de convertirse en una herramienta de referencia para la electrofisiología de ancho de banda completo. Se prevé que esta tecnología tenga un gran impacto en una comunidad amplia y multidisciplinaria que incluya investigadores en neurotecnología, ingenieros biomédicos, neurocientíficos que estudien la dinámica cortical de banda ancha asociada con el comportamiento espontáneo y/o los estados cerebrales, así como investigadores clínicos interesados en la actividad de baja frecuencia en la epilepsia, los accidentes cerebrovasculares y la migraña.
Recent years have witnessed novel technology developments of neural implants for medical applications which are expected to pave the way to unveil functionalities of the central nervous system. Understanding the human brain is commonly considered one of the biggest scientific challenges of our time; as a consequence, we are witnessing an intensified research in the development of brain-machine-interfaces (BMIs), which would allow us to both read and stimulate brain activity. Nevertheless, currently available neural implants offer a modest clinical efficacy, partly due to the limitations posed by the invasiveness of the implants materials and technology and by the metals used at the electrical interface with the tissue. Such materials compromise the interfacing resolution, the performance and the long term stability of neural implants. Development of flexible electronics using biocompatible materials is key for the realisation of minimally invasive neural implants, which can be chronically implanted without causing rejection from the immune system. A relatively young yet very promising research field, that is increasingly drawing attention is the use of two dimensional materials, such as graphene, for bioelectronic applications. Graphene solution-gated field effect transistor (gSGFET) is one of several emerging new neural technologies. These devices can overcome the above-mentioned limitations thanks to the outstanding properties of graphene, such as mechanical flexibility, electrochemical inertness, biocompatibility and high sensitivity. In this PhD thesis, arrays of gSGFETs have been fabricated and iteratively optimized in terms of sensitivity and signal-to-noise ratio, adopting wafer-scale micro-fabrication methods. The 1/f noise in gSGFETs has been characterised and the optimisation of both, contact and channel noises was achieved by UVO-treatment at the metal/graphene interface, as well as by decoupling the graphene channel from the substrate, using different nanomaterials such as graphene encapsulation with hexagonal boron nitride (hBN), self assembled monolayers and double transferred graphene. Moreover, flexible and ultra-thin epicortical and intracortical neural probes, containing arrays of gSGFETs, have been successfully fabricated and used during in vivo microelectrocorticography recordings in anaesthesized and awake rodents. Flexible intracortical devices were inserted into the brain using a back-coating stiffening protocol with bioresobable silk fibroin protein, developed during this PhD thesis. The results presented in this PhD demonstrate the superior spatio-temporal resolution of gSGFETs compared to standard microelectordes technology; particularly the ability to map with high fidelity, infraslow activity (ISA, < 0.1 Hz) together with signals in the typical local field potential bandwidth. Today it is known that infraslow brain activity, including spreading depolarisations, contribute to the pathophysiology of several neurological disorders such as stroke, traumatic brain injury, migraine and epilepsy. However, this activity is seldom recorded due to intrinsic technical limitations of conventional AC-coupled electrodes. To demonstrate the usefulness of the developed flexible gSGFET arrays technology, recordings have been obtained with multichannel flexible graphene depth neural probes (gDNP) in relevant awake animal models of seizures and established epilepsy. ISA was detected and mapped through different cortical layers and subcortical regions, whilst simultaneously recording epileptiform activity in more conventional frequency bands (1-600Hz). Furthermore, the assessment of the long term recording stability and functionality, as well as biocompatibility of the gDNP has also been demonstrated as part of this thesis. The graphene based bioelectronic technology here described has the potential to become a gold standard tool for full bandwidth electrophysiology. This technology is envisioned to have a great impact on a broad and multidisciplinary community including neurotechnology researchers, biomedical engineers, neuroscientists studying wide-band cortical dynamics associated with spontaneous behaviour and/or brain states, as well as clinical researchers interested in the role of infraslow activity in epilepsy, stroke and migraine.
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Richards, Stephen M. "End-user interfaces to electronic books." Thesis, Teesside University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358404.

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Electronic book production is a developing field which is still in its infancy. As such, there is still relatively little material available in the form of design principles or guidelines for the production of such books. It is also extremely complex, in that electronic book designers can take advantage of a number of delivery techniques which are not available to authors of traditional paper-based books. Such techniques include: multimedia (the delivery of text, pictures, sound, and moving pictures); and hypermedia (the linking of reactive information items to form non-linear structures). This research investigates some of the key issues in the design of end-user interfaces to electronic books. Essentially, this centres on three basic problems: the use of metaphors in the design of interfaces to electronic books; models for the design of multimedia pages; and the provision of various knowledge corpus structures. Interface metaphors are investigated through the implementation and evaluation of the book metaphor. Applications were developed which either embedded or did not embed the book metaphor. Subjects used these applications while undertaking a number of information access tasks. Both qualitative and performance data werecollected and some significant results were obtained. Five page models were developed (referred to as: simple; tiled; overlay; oversize; and dynamic) which were used to design a number of page structures. These page structures were evaluated using qualitative measures of user reactions to the various page structures. Seven interface dimensions were measured and again significant results were obtained. To measure the effects of knowledge corpus structure on the design of electronic books three different book structures were created: linear; tree; and network. These were investigated in the light of some common information access tasks. The results indicated that some knowledge corpus structures were more appropriate for certain types of task.
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Valdar, William Seth Jermy. "Residue conservation in the prediction of protein-protein interfaces." Thesis, University College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246927.

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Books on the topic "Neural interfaces"

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I, Bey, ed. Neutral interfaces in design, simulation, and programming for robotics. Berlin: Springer-Verlag, 1994.

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Holleman, Jeremy, Fan Zhang, and Brian Otis. Ultra Low-Power Integrated Circuit Design for Wireless Neural Interfaces. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6727-5.

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Fan, Zhang, Otis Brian, and SpringerLink (Online service), eds. Ultra Low-Power Integrated Circuit Design for Wireless Neural Interfaces. New York, NY: Springer Science+Business Media, LLC, 2011.

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Fels, S. Sidney. Building adaptive interfaces with neural networks: The Glove-Talk pilot study. Toronto: University of Toronto, Dept. of Computer Science, 1990.

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Ran, Ginosar, and SpringerLink (Online service), eds. The NeuroProcessor: An Integrated Interface to Biological Neural Networks. Dordrecht: Springer Science+Business Media B.V., 2008.

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Coates, Thomas D. Neural interfacing: Forging the human-machine connection. San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2008.

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Taylor, Cynthia E. Documentation of TSMC software that interfaces with traffic analysis problems. [Olympia, Wash.]: Washington State Dept. of Transportation, 1997.

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Brain machine interfaces: Implications for science, clinical practice and society. Amsterdam: Elsevier, 2011.

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Vasquez, Daniel. Hierarchical Neural Network Structures for Phoneme Recognition. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Fels, S. Sidney. Glove-Talk II: Mapping hard gestures to speech using neural networks : an approach to building adaptive interfaces. Toronto: University of Toronto, Dept. of Computer Science, 1994.

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Book chapters on the topic "Neural interfaces"

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Yoda, Minami, Jean-Luc Garden, Olivier Bourgeois, Aeraj Haque, Aloke Kumar, Hans Deyhle, Simone Hieber, et al. "Neural Interfaces." In Encyclopedia of Nanotechnology, 1895. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-90-481-9751-4_100593.

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He, Bin, Han Yuan, Jianjun Meng, and Shangkai Gao. "Brain–Computer Interfaces." In Neural Engineering, 131–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43395-6_4.

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He, Bin, Shangkai Gao, Han Yuan, and Jonathan R. Wolpaw. "Brain–Computer Interfaces." In Neural Engineering, 87–151. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-5227-0_2.

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Kang, Woo Hyeun, Wenzhe Cao, Sigurd Wagner, and Barclay Morrison. "Stretchable Neural Interfaces." In Stretchable Electronics, 379–99. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527646982.ch16.

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Moore Jackson, Melody, and Rudolph Mappus. "Neural Control Interfaces." In Brain-Computer Interfaces, 21–33. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-272-8_2.

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Lebedev, Mikhail A., and Alexei Ossadtchi. "Bidirectional Neural Interfaces." In Brain–Computer Interfaces Handbook, 701–20. Boca Raton : Taylor & Francis, CRC Press, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351231954-37.

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Broccard, Frédéric D., Siddharth Joshi, Jun Wang, and Gert Cauwenberghs. "Neuromorphic Neural Interfaces." In Handbook of Neuroengineering, 1–33. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-15-2848-4_41-1.

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Oby, Emily R., Jay A. Hennig, Aaron P. Batista, Byron M. Yu, and Steven M. Chase. "Intracortical Brain–Machine Interfaces." In Neural Engineering, 185–221. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43395-6_5.

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Brockmeier, Austin J., and José C. Príncipe. "Decoding Algorithms for Brain–Machine Interfaces." In Neural Engineering, 223–57. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-5227-0_4.

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Laiwalla, Farah, and Arto Nurmikko. "Future of Neural Interfaces." In Advances in Experimental Medicine and Biology, 225–41. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2050-7_9.

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Conference papers on the topic "Neural interfaces"

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Балакин, Петр Владимирович, Светлана Анатольевна Микаева, and Юлия Алексеевна Журавлева. "NEURAL INTERFACES." In Высокие технологии и инновации в науке: сборник избранных статей Международной научной конференции (Санкт-Петербург, Май 2022). Crossref, 2022. http://dx.doi.org/10.37539/vt197.2022.39.20.012.

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Авторы описывают принципы работы нейроинтерфейсов и перспективные области, в которых проводятся исследования на данный момент. The authors describe the principles of operation of neurointerfaces and the promising areas in which research is currently being conducted.
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Walker, Ross M., Loren Rieth, Subramanian S. Iyer, Adeel A. Bajwa, Jason Silver, Taufiq Ahmed, Naila Tasneem, Mohit Sharma, and A. Tye Gardner. "Integrated neural interfaces." In 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2017. http://dx.doi.org/10.1109/mwscas.2017.8053106.

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Viventi, Jonathan. "Flexible electronics for neural interfaces." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.002.

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Rogers, John. "Soft, Biocompatible Optoelectronic Neural Interfaces." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.004.

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"Session IV: Neural interfaces, neural-inspired architectures and resistive sensor interfaces." In 2015 6th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI). IEEE, 2015. http://dx.doi.org/10.1109/iwasi.2015.7184999.

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"Session I: Neural interfaces." In 2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI). IEEE, 2017. http://dx.doi.org/10.1109/iwasi.2017.7974199.

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Harrison, Reid. "F8: Integrated neural interfaces." In 2009 IEEE International Solid-State Circuits Conference (ISSCC 2009). IEEE, 2009. http://dx.doi.org/10.1109/isscc.2009.4977536.

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Perez Fornos, Angelica, Nils Guinand, Raymond Van de Berg, Maurizio Ranieri, Samuel Cavuscens, Anissa Boutabla, Julie Corre, and Herman Kingma. "Vestibular Implants in Humans: Steps Towards a Clinical Application." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.001.

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Zhao, Zifang, Claudia Cea, Jennifer Gelinas, and Dion Khodagholy. "Ions-based high bandwidth communication for implantable bioelectronics." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.010.

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Seo, DJ. "Minimally invasive brain-machine interface at Neuralink." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.021.

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Reports on the topic "Neural interfaces"

1

Kipke, Daryl R., Jeffrey Carrier, and David J. Anderson. Implantable Neural Interfaces for Sharks. Fort Belvoir, VA: Defense Technical Information Center, May 2007. http://dx.doi.org/10.21236/ada470127.

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Shea, Thomas B. Optimization of Neuronal-Computer Interface. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada515409.

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Weber, Douglas J. A New Animal Model for Developing a Somatosensory Neural Interface for Prosthetic Limbs. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada482995.

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