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Books on the topic 'Neural interfaces'

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Author: Grafiati
Published: 4 June 2021
Last updated: 29 January 2023

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1

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

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2

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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3

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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4

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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5

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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6

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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7

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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8

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

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9

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

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10

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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11

Naik, Ganesh R., and Yina Guo. Emerging theory and practice in neuroprosthetics. Hershey, PA: Medical Information Science Reference, an imprint of IGI Global, 2014.

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12

Guo, Liang, ed. Neural Interface Engineering. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41854-0.

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13

Jayanti, V. R. Neural network simulator interface. Manchester: UMIST, 1995.

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14

Zheng, Xiaoxiang, ed. Neural Interface: Frontiers and Applications. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2050-7.

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15

Beyond boundaries: The new neuroscience of connecting brains with machines--and how it will change our lives. New York: Times Books/Henry Holt and Co., 2011.

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16

1941-, Grillner Sten, and Graybiel A. M. 1942-, eds. Microcircuits: The interface between neurons and global brain function. Cambridge, Mass: MIT Press in cooperation with Dahlem University Press, 2006.

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17

Bey, Ingward, D. Ball, H. Bruhm, T. Clausen, W. Jakob, O. Knudsen, E. G. Schlechtendahl, and T. Sørensen, eds. Neutral Interfaces in Design, Simulation, and Programming for Robotics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85057-8.

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18

Friedhelm, Schwenker, Trentin Edmondo, and SpringerLink (Online service), eds. Artificial Neural Networks in Pattern Recognition: 5th INNS IAPR TC 3 GIRPR Workshop, ANNPR 2012, Trento, Italy, September 17-19, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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19

International Conference on Neural Interface and Control (1st 2005 Wuhan, China). 2005 First International Conference on Neural Interface and Control: Proceedings : 26-28 May 2005, Wuhan, China. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2005.

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20

Brain-computer interface research: A state-of-the-art summary 2. Berlin: Springer, 2014.

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21

Mayne, Andrew Humphrey. The development of a silicon based neuronal interface. Leicester: De Montfort University, 2002.

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22

Vassanelli, Stefano. Implantable neural interfaces. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0050.

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Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.
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23

De Vittorio, Massimo, Ferruccio Pisanello, and John A. Assad, eds. Optical Neural Interfaces. Frontiers Media SA, 2019. http://dx.doi.org/10.3389/978-2-88963-080-6.

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24

Kim, Chul, Patrick P. Mercier, Sohmyung Ha, and Gert Cauwenberghs. High-Density Integrated Electrocortical Neural Interfaces. Elsevier Science & Technology, 2019.

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25

High-Density Integrated Electrocortical Neural Interfaces. Elsevier, 2019. http://dx.doi.org/10.1016/c2017-0-01956-0.

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26

Electrophysiology Measurements for Studying Neural Interfaces. Elsevier, 2020. http://dx.doi.org/10.1016/c2018-0-01660-6.

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27

Aria, Mohammad M. Electrophysiology Measurements for Studying Neural Interfaces. Elsevier Science & Technology, 2020.

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28

Aria, Mohammad M. Electrophysiology Measurements for Studying Neural Interfaces. Elsevier Science & Technology Books, 2020.

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29

Advanced Rehabilitative Technology: Neural Interfaces and Devices. Elsevier Science & Technology Books, 2018.

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30

Aziz, Joseph N. Y. Multi-channel signal-processing integrated neural interfaces. 2007.

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31

Liu, Quan, Wei Meng, Sheng Quan Xie, and Qingsong Ai. Advanced Rehabilitative Technology: Neural Interfaces and Devices. Elsevier Science & Technology Books, 2018.

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32

(Foreword), Terrence J. Sejnowski, Guido Dornhege (Editor), José del R. Millán (Editor), Thilo Hinterberger (Editor), Dennis J. McFarland (Editor), and Klaus-Robert Müller (Editor), eds. Toward Brain-Computer Interfacing (Neural Information Processing). The MIT Press, 2007.

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33

Lehmann, Torsten, and André van Schaik. Implantable hearing interfaces. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0054.

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The chapter Implantable hearing interfaces describes the fundamental operation of a commonly available biohybrid system, the cochlear implant, or bionic ear. This neuro-stimulating biomedical implant is very successful in restoring hearing function to people with profound hearing loss. The fundamental operation of the biological cochlea is described and parallels are drawn between key aspects of the biological system and the biohybrid implementation: dynamic range compression, translation of sound to neural activity, and tonotopic mapping. Critical considerations are discussed for simultaneously meeting biological, surgical, and engineering restrictions in successful biohybrid systems design. Finally, challenges in present and future cochlear implants are outlined and directions of current research given.
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34

Glannon, Walter. Neural Prosthetics. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198813910.001.0001.

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Neural prosthetics (neuroprostheses, neural prostheses) are devices or systems that influence the input and output of information in the brain. They modulate, bypass, supplement, or replace regions of the brain and its connections to the body that are damaged, dysfunctional, or lost from brain injury, congenital conditions, limb loss, or neurodegenerative disease. Neural prosthetics can generate, improve, or restore sensory, motor, and cognitive functions. Some prosthetics are implanted in the brain. Others are connected to it in brain–computer interfacing. This book describes auditory and visual prosthetics, deep brain and responsive neurostimulation, brain–computer interfaces, brain-to-brain interfaces, optogenetics, and memory prosthetics and discusses some of their neuroscientific and philosophical implications. The neuroscientific discussion focuses on how neural prosthetics can restore brain and bodily functions. The philosophical discussion focuses on how people with these prosthetics can benefit from or be harmed by them. It also focuses on how these devices and systems can lead to a better understanding of or change our attitudes about the brain–mind relation, identity, mental causation, and agency. The book considers the therapeutic, rehabilitative, and restorative potential of neural prosthetics in improving functional independence and quality of life for millions of people with disabling conditions.
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35

Suri, Jasjit S., and Ayman S. El-Baz. Advances in Neural Engineering Volume 2: Brain-Computer Interfaces. Elsevier Science & Technology Books, 2023.

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36

Otis, Brian, Fan Zhang, and Jeremy Holleman. Ultra Low-Power Integrated Circuit Design for Wireless Neural Interfaces. Springer New York, 2014.

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37

(Editor), Enrique Alba, and Rafael Marti (Editor), eds. Metaheuristic Procedures for Training Neural Networks (Operations Research/Computer Science Interfaces Series). Springer, 2006.

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38

Hassanien, Aboul Ella, and Ahmad Taher Azar. Brain-Computer Interfaces: Current Trends and Applications. Springer, 2015.

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39

Hassanien, Aboul Ella, and Ahmad Taher Azar. Brain-Computer Interfaces: Current Trends and Applications. Springer, 2014.

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40

Hassanien, Aboul Ella, and Ahmad Taher Azar. Brain-Computer Interfaces: Current Trends and Applications. Springer, 2016.

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41

Building adaptive interfaces with neural networks: The glove-talk pilot study. Ottawa: National Library of Canada, 1990.

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42

Perelman, Yevgeny, and Ran Ginosar. NeuroProcessor: An Integrated Interface to Biological Neural Networks. Springer Netherlands, 2010.

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43

Mathematics of Neural Networks: Models, Algorithms and Applications (Operations Research/Computer Science Interfaces Series). Springer, 1997.

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44

Metaheuristic Procedures for Training Neural Networks (Operations Research/Computer Science Interfaces Series Book 35). Springer, 2006.

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45

Principe, José C., and Justin C. Sanchez. Brain-Machine Interface Engineering. Morgan & Claypool Publishers, 2007.

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46

Schouenborg, Jens, Martin Garwicz, and Nils Danielsen. Brain Machine Interfaces: Implications for Science, Clinical Practice and Society. Elsevier Science & Technology Books, 2011.

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47

Kim, Chul, Patrick P. Mercier, Sohmyung Ha, and Gert Cauwenberghs. High-Density Integrated Electrocortical Neural Interfaces: Low-Noise Low-Power System-On-Chip Design Methodology. Elsevier Science & Technology Books, 2019.

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48

Vasquez, Daniel, Rainer Gruhn, and Wolfgang Minker. Hierarchical Neural Network Structures for Phoneme Recognition. Springer, 2012.

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49

Fels, S. Sidney. Glove-talkII: Mapping hand gestures to speech using neural networks - an approach to building adaptive interfaces. 1994.

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50

Gandhi, Vaibhav. Brain-Computer Interfacing for Assistive Robotics: Electroencephalograms, Recurrent Quantum Neural Networks, and User-Centric Graphical Interfaces. Elsevier Science & Technology Books, 2014.

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