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Relevant bibliographies by topics / Neuroengineering applications / Journal articles

Journal articles on the topic 'Neuroengineering applications'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Henniquau, D., C. Vanbesien-Mailliot, P. Falez, P. Devienne, A. Vlandas, A. Cappy, and V. Hoel. "Les systèmes neuroinspirés appliqués à la vision artificielle : pédagogie et interdisciplinarité." J3eA 21 (2022): 1023. http://dx.doi.org/10.1051/j3ea/20221023.

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Le traitement neuroinspiré de l’information et le domaine des neurobiosystèmes sont deux pans de la recherche à fort potentiel de développement. Appliquées au domaine de la vision artificielle, elles visent au développement de nouvelles applications comme la conception d’implants rétiniens et/ou de caméras « intelligentes ». Des actions sont menées dans le domaine de la médiation scientifique et de la formation, au travers d’un stand à l’Xpérium et le développement d’une nouvelle unité d’enseignement (UE) appelée « Neuroengineering », intégrée au parcours de formation du Master « Biotechnologies » proposé à l’université de Lille. Le stand présenté à l’Xpérium montre à des jeunes lycéens et étudiants que l’utilisation d’architectures neuroinspirées dans un système de vision artificielle doit conduire à une forte amélioration des performances associée à une réduction de la consommation énergétique. Il s’agit d’une expérience pédagogique innovante auprès des jeunes générations montrant les enjeux des activités de recherche en construction dans les laboratoires. Pour l’UE Neuroengineering, les sujets abordés en séance permettent d’amener les étudiants vers la compréhension des Trends and challenges in neuroengineering (1), notamment en posant la question du développement de neuroprothèses électroniques intelligentes permettant une communication bidirectionnelle entre des neurones vivants et artificiels.

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2

Tiwari, Ashish, Raj Kumar, Orit Shefi, and Jaspreet Kaur Randhawa. "Fluorescent Mantle Carbon Coated Core–Shell SPIONs for Neuroengineering Applications." ACS Applied Bio Materials 3, no. 7 (June 23, 2020): 4665–73. http://dx.doi.org/10.1021/acsabm.0c00582.

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3

Monaco, Antonina M., and Michele Giugliano. "Carbon-based smart nanomaterials in biomedicine and neuroengineering." Beilstein Journal of Nanotechnology 5 (October 23, 2014): 1849–63. http://dx.doi.org/10.3762/bjnano.5.196.

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The search for advanced biomimetic materials that are capable of offering a scaffold for biological tissues during regeneration or of electrically connecting artificial devices with cellular structures to restore damaged brain functions is at the forefront of interdisciplinary research in materials science. Bioactive nanoparticles for drug delivery, substrates for nerve regeneration and active guidance, as well as supramolecular architectures mimicking the extracellular environment to reduce inflammatory responses in brain implants, are within reach thanks to the advancements in nanotechnology. In particular, carbon-based nanostructured materials, such as graphene, carbon nanotubes (CNTs) and nanodiamonds (NDs), have demonstrated to be highly promising materials for designing and fabricating nanoelectrodes and substrates for cell growth, by virtue of their peerless optical, electrical, thermal, and mechanical properties. In this review we discuss the state-of-the-art in the applications of nanomaterials in biological and biomedical fields, with a particular emphasis on neuroengineering.

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4

Morillas, Christian, Samuel Romero, Antonio Martínez, Francisco Pelayo, Leonardo Reyneri, Markus Bongard, and Eduardo Fernández. "A neuroengineering suite of computational tools for visual prostheses." Neurocomputing 70, no. 16-18 (October 2007): 2817–27. http://dx.doi.org/10.1016/j.neucom.2006.04.017.

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5

Micera, Silvestro, Dominique M. Durand, and Janos Vrs. "Guest Editorial to the Special Letters Issue on Neuroengineering and Neuroprosthetics: Increasing Basic Understanding of the Nervous System to Develop More Effective Neuroengineering Applications." IEEE Transactions on Biomedical Engineering 56, no. 11 (November 2009): 2689–91. http://dx.doi.org/10.1109/tbme.2009.2034485.

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6

Panuccio, Gabriella, Marianna Semprini, Lorenzo Natale, Stefano Buccelli, Ilaria Colombi, and Michela Chiappalone. "Progress in Neuroengineering for brain repair: New challenges and open issues." Brain and Neuroscience Advances 2 (January 1, 2018): 239821281877647. http://dx.doi.org/10.1177/2398212818776475.

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Background: In recent years, biomedical devices have proven to be able to target also different neurological disorders. Given the rapid ageing of the population and the increase of invalidating diseases affecting the central nervous system, there is a growing demand for biomedical devices of immediate clinical use. However, to reach useful therapeutic results, these tools need a multidisciplinary approach and a continuous dialogue between neuroscience and engineering, a field that is named neuroengineering. This is because it is fundamental to understand how to read and perturb the neural code in order to produce a significant clinical outcome. Results: In this review, we first highlight the importance of developing novel neurotechnological devices for brain repair and the major challenges expected in the next years. We describe the different types of brain repair strategies being developed in basic and clinical research and provide a brief overview of recent advances in artificial intelligence that have the potential to improve the devices themselves. We conclude by providing our perspective on their implementation to humans and the ethical issues that can arise. Conclusions: Neuroengineering approaches promise to be at the core of future developments for clinical applications in brain repair, where the boundary between biology and artificial intelligence will become increasingly less pronounced.

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7

Song, Y. K., W. R. Patterson, C. W. Bull, J. Beals, N. Hwang, A. P. Deangelis, C. Lay, et al. "Development of a Chipscale Integrated Microelectrode/Microelectronic Device for Brain Implantable Neuroengineering Applications." IEEE Transactions on Neural Systems and Rehabilitation Engineering 13, no. 2 (June 2005): 220–26. http://dx.doi.org/10.1109/tnsre.2005.848337.

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8

Curtin, Adrian, and Hasan Ayaz. "Abstract #15: MazeSuite 3: Design, presentation and analysis platform for spatial navigation, cognitive neuroscience and neuroengineering applications." Brain Stimulation 12, no. 2 (March 2019): e6. http://dx.doi.org/10.1016/j.brs.2018.12.022.

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9

Kim, Sungshin, Thierri Callier, Gregg A. Tabot, Robert A. Gaunt, Francesco V. Tenore, and Sliman J. Bensmaia. "Behavioral assessment of sensitivity to intracortical microstimulation of primate somatosensory cortex." Proceedings of the National Academy of Sciences 112, no. 49 (October 26, 2015): 15202–7. http://dx.doi.org/10.1073/pnas.1509265112.

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Intracortical microstimulation (ICMS) is a powerful tool to investigate the functional role of neural circuits and may provide a means to restore sensation for patients for whom peripheral stimulation is not an option. In a series of psychophysical experiments with nonhuman primates, we investigate how stimulation parameters affect behavioral sensitivity to ICMS. Specifically, we deliver ICMS to primary somatosensory cortex through chronically implanted electrode arrays across a wide range of stimulation regimes. First, we investigate how the detectability of ICMS depends on stimulation parameters, including pulse width, frequency, amplitude, and pulse train duration. Then, we characterize the degree to which ICMS pulse trains that differ in amplitude lead to discriminable percepts across the range of perceptible and safe amplitudes. We also investigate how discriminability of pulse amplitude is modulated by other stimulation parameters—namely, frequency and duration. Perceptual judgments obtained across these various conditions will inform the design of stimulation regimes for neuroscience and neuroengineering applications.

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10

Kakran, Mitali, and Lin Li. "Carbon Nanomaterials for Drug Delivery." Key Engineering Materials 508 (March 2012): 76–80. http://dx.doi.org/10.4028/www.scientific.net/kem.508.76.

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Carbon Nanotubes (CNTs) and Graphene Have Attracted Tremendous Attention as the Most Promising Carbon Nanomaterials in the 21st Century for a Variety of Applications such as Electronics, Biomedical Engineering, Tissue Engineering, Neuroengineering, Gene Therapy and Biosensor Technology. For the Biomedical Applications, Cnts Have Been Utilized over Existing Drug Delivery Vectors due to their Ability to Cross Cell Membranes Easily and their High Aspect Ratio as Well as High Surface Area, which Provides Multiple Attachment Sites for Drug Targeting. Besides, it Has Also Been Proved that the Functionalization of CNTs May Remarkably Reduce their Cytotoxic Effects and at the Same Time Increase their Biocompatibility. So, the Functionalized CNTs Are Safer than Pristine or Purified CNTs, Thus Offering the Potential Exploitation of Nanotubes for Drug Administration. On the other Hand, More Recently Graphene and its Derivatives Have Been Enormously Investigated in the Biological Applications because of their Biocompatibility, Unique Conjugated Structure, Relatively Low Cost and Availability on both Sides of a Single Sheet for Drug Binding. In Our Study, we Have Covalently Functionalized Multiwalled Carbon Nanotubes (MWCNTs) and Graphene Oxide (GO) with Highly Hydrophilic and Biocompatible Excipients in Order to Increase their Aqueous Solubility and Biocompatibility. Various Excipients Used Were Polyvinyl Alcohol, Pluronic F38, Tween 80 and Maltodextrin. The Poorly Water-Soluble Anticancer Drugs such as, Camptothecin and Ellagic Acid, Were Loaded onto the Functionalized MWCNTs and GO via Non-Covalent Interactions. Furthermore, Drug Loading and Cytotoxic Activity of Drugs Incorporated with the Functionalized MWCNTs and GO as Nanocarriers Were Also Investigated. Drugs Loaded on both Carbon Nanocarriers Exhibited a Higher Cytotoxic Activity than Free Drug. On the other Hand, No Significant Toxicity Was Found even at Higher Concentrations when the Cells Were Incubated with the Functionalized Mwcnts and GO. Therefore, both these Functionalized Carbon Nanomaterials Are Ideal Carriers for Drug Delivery.

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11

Zhou, Xiaojun, S. Ruhaizin, Wei Zhu, Cheng Shen, and Xiaobo He. "Application of Neuroengineering Based on EEG Features in the Industrial Design of Comfort." Computational Intelligence and Neuroscience 2022 (June 10, 2022): 1–5. http://dx.doi.org/10.1155/2022/4667689.

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The smart wheelchair is a service robot that can be used as a means of transportation for the elderly and the disabled. The patients were given an intelligent wheelchair designed by electroencephalogram (EEG), which was used for more than 8 hours and tested continuously for 1 month. By ridit analysis, the difference between the two groups was statistically significant (U = 3.72, P < 0.01 ). The scores of visual analogue scale (VAS) and joint ground visuality (JGV) in the observation group were significantly better than those in the control group. The modules of physiological function (PF), physical pain (PP), overall health (OH), vitality (VT), social function (SF), emotional function (EF), and mental health (MH) in the SF-36 scores of the two groups were significantly improved ( P < 0.05 ), and the improvement of each module in the observation group was significantly better than that in the control group ( P < 0.05 ). The levels of serum IL-6, IL-10, and superoxide dismutase (SOD) in the two groups were significantly improved ( P < 0.05 ), and the improvement of serum IL-6, IL-10, and SOD in the observation group was significantly better than that in the control group ( P < 0.05 ). It is suggested that neural engineering based on EEG characteristics can be well applied in comfort industrial design.

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12

Семеріков, Сергій, Ілля Теплицький, Юлія Єчкало, and Арнольд Ків. "Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot." Педагогіка вищої та середньої школи 51 (December 13, 2018): 159–91. http://dx.doi.org/10.31812/pedag.v51i0.3667.

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Semerikov S.O., Teplytsʹkyy I.O., Yechkalo YU.V. and Kiv A.E. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890–1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). The role of Walter Pitts in combining the descriptive and quantitative theories of training is discussed. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. It is indicated that there are three groups of models, which are promising in terms of developing corresponding methods — the continuous two-factor model of Rashevsky, the discrete model of McCulloch and Pitts, and the discrete-continuous models of Householder and Landahl.

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13

Osler II, James Edward. "Neuroengineering Neuromathematics Notation: The Novel Trioinformatics System that Defines, Explains, and Expresses the Research Application of the Law of Trichotomy for Digital Instrumentation and Circuit Design." i-manager's Journal on Circuits and Systems 3, no. 3 (August 15, 2015): 1–16. http://dx.doi.org/10.26634/jcir.3.3.4779.

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14

Osler II, James Edward. "Trichotomous Charge States: The Novel Trioinformatics Application of Neuroengineering Neuromathematics Notation to Express and Expound Polyphase Electrical Systems and Tri-State Buffers for Digital Circuit Design." i-manager's Journal on Circuits and Systems 3, no. 4 (November 15, 2015): 1–19. http://dx.doi.org/10.26634/jcir.3.4.5926.

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15

JAMES, EDWARD OSLER II. "TRIOENGINEERING: THE PROCEDURES THAT USE TRIOINFORMATICS NEUROENGINEERING NEUROMATHEMATICS NOTATION TO EXPRESS, BUILD, DEFINE, AND INFORM THE APPLICATION OF THE TRICHOTOMOUS–BASED INQUIRY IN DIGITAL RESEARCH DESIGN." i-manager's Journal on Circuits and Systems 6, no. 4 (2018): 1. http://dx.doi.org/10.26634/jcir.6.4.15093.

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16

Gurke, Johannes, Tobias E. Naegele, Sam Hilton, Roberto Pezone, Vincenzo Curto, Damiano Barone, Emil J. W. List-Kratochvil, Alejandro Carnicer-Lombarte, and George Malliaras. "Hybrid fabrication of multimodal intracranial implants for electrophysiology and local drug delivery." Materials Horizons, 2022. http://dx.doi.org/10.1039/d1mh01855h.

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New fabrication approaches for mechanically flexible implants hold the key to advancing the applications of neuroengineering in fundamental neuroscience and clinic. By combining the high precision of thin film microfabrication...

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17

Won, Sang Min, Le Cai, Philipp Gutruf, and John A. Rogers. "Wireless and battery-free technologies for neuroengineering." Nature Biomedical Engineering, March 8, 2021. http://dx.doi.org/10.1038/s41551-021-00683-3.

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18

Curtin, Adrian, and Hasan Ayaz. "MazeSuite 3: A design, presentation and analysis platform for spatial navigation, cognitive neuroscience and neuroengineering applications." Frontiers in Human Neuroscience 12 (2018). http://dx.doi.org/10.3389/conf.fnhum.2018.227.00069.

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19

Rothschild, Ryan Mark. "Neuroengineering tools/applications for bidirectional interfaces, brain–computer interfaces, and neuroprosthetic implants – a review of recent progress." Frontiers in Neuroengineering 3 (2010). http://dx.doi.org/10.3389/fneng.2010.00112.

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