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Journal articles on the topic 'NeuroElectronics'

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Author: Grafiati

Published: 6 September 2023

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1

Jastrzebska‐Perfect, Patricia, Shilpika Chowdhury, George D. Spyropoulos, Zifang Zhao, Claudia Cea, Jennifer N. Gelinas, and Dion Khodagholy. "Translational Neuroelectronics." Advanced Functional Materials 30, no. 29 (June 8, 2020): 1909165. http://dx.doi.org/10.1002/adfm.201909165.

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2

Waldrop, M. Mitchell. "Neuroelectronics: Smart connections." Nature 503, no. 7474 (November 2013): 22–24. http://dx.doi.org/10.1038/503022a.

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3

Krook-Magnuson, Esther, Jennifer N. Gelinas, Ivan Soltesz, and György Buzsáki. "Neuroelectronics and Biooptics." JAMA Neurology 72, no. 7 (July 1, 2015): 823. http://dx.doi.org/10.1001/jamaneurol.2015.0608.

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4

Go, Gyeong‐Tak, Yeongjun Lee, Dae‐Gyo Seo, and Tae‐Woo Lee. "Organic Neuroelectronics: From Neural Interfaces to Neuroprosthetics." Advanced Materials 35, no. 12 (March 2023): 2300758. http://dx.doi.org/10.1002/adma.202300758.

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5

Vitale, Flavia, and Raghav Garg. "Novel materials and fabrication strategies for multimodal neuroelectronics." Brain Stimulation 16, no. 1 (January 2023): 117. http://dx.doi.org/10.1016/j.brs.2023.01.014.

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6

Di Palma, Valerio, Andrea Pianalto, Michele Perego, Graziella Tallarida, Davide Codegoni, and Marco Fanciulli. "Plasma-Assisted Atomic Layer Deposition of IrO2 for Neuroelectronics." Nanomaterials 13, no. 6 (March 8, 2023): 976. http://dx.doi.org/10.3390/nano13060976.

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In vitro and in vivo stimulation and recording of neuron action potential is currently achieved with microelectrode arrays, either in planar or 3D geometries, adopting different materials and strategies. IrO2 is a conductive oxide known for its excellent biocompatibility, good adhesion on different substrates, and charge injection capabilities higher than noble metals. Atomic layer deposition (ALD) allows excellent conformal growth, which can be exploited on 3D nanoelectrode arrays. In this work, we disclose the growth of nanocrystalline rutile IrO2 at T = 150 °C adopting a new plasma-assisted ALD (PA-ALD) process. The morphological, structural, physical, chemical, and electrochemical properties of the IrO2 thin films are reported. To the best of our knowledge, the electrochemical characterization of the electrode/electrolyte interface in terms of charge injection capacity, charge storage capacity, and double-layer capacitance for IrO2 grown by PA-ALD was not reported yet. IrO2 grown on PtSi reveals a double-layer capacitance (Cdl) above 300 µF∙cm−2, and a charge injection capacity of 0.22 ± 0.01 mC∙cm−2 for an electrode of 1.0 cm2, confirming IrO2 grown by PA-ALD as an excellent material for neuroelectronic applications.

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7

Bourrier, Antoine, Anna Szarpak-Jankowska, Farida Veliev, Renato Olarte-Hernandez, Polina Shkorbatova, Marco Bonizzato, Elodie Rey, et al. "Introducing a biomimetic coating for graphene neuroelectronics: toward in-vivo applications." Biomedical Physics & Engineering Express 7, no. 1 (December 4, 2020): 015006. http://dx.doi.org/10.1088/2057-1976/ab42d6.

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8

Go, Gyeong‐Tak, Yeongjun Lee, Dae‐Gyo Seo, and Tae‐Woo Lee. "Organic Neuroelectronics: From Neural Interfaces to Neuroprosthetics (Adv. Mater. 45/2022)." Advanced Materials 34, no. 45 (November 2022): 2270311. http://dx.doi.org/10.1002/adma.202270311.

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9

Golabchi, Asiyeh, Kevin M. Woeppel, Xia Li, Carl F. Lagenaur, and X. Tracy Cui. "Neuroadhesive protein coating improves the chronic performance of neuroelectronics in mouse brain." Biosensors and Bioelectronics 155 (May 2020): 112096. http://dx.doi.org/10.1016/j.bios.2020.112096.

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10

Zhao, Zifang, Claudia Cea, Jennifer N. Gelinas, and Dion Khodagholy. "Responsive manipulation of neural circuit pathology by fully implantable, front-end multiplexed embedded neuroelectronics." Proceedings of the National Academy of Sciences 118, no. 20 (May 10, 2021): e2022659118. http://dx.doi.org/10.1073/pnas.2022659118.

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Responsive neurostimulation is increasingly required to probe neural circuit function and treat neuropsychiatric disorders. We introduce a multiplex-then-amplify (MTA) scheme that, in contrast to current approaches (which necessitate an equal number of amplifiers as number of channels), only requires one amplifier per multiplexer, significantly reducing the number of components and the size of electronics in multichannel acquisition systems. It also enables simultaneous stimulation of arbitrary waveforms on multiple independent channels. We validated the function of MTA by developing a fully implantable, responsive embedded system that merges the ability to acquire individual neural action potentials using conformable conducting polymer-based electrodes with real-time onboard processing, low-latency arbitrary waveform stimulation, and local data storage within a miniaturized physical footprint. We verified established responsive neurostimulation protocols and developed a network intervention to suppress pathological coupling between the hippocampus and cortex during interictal epileptiform discharges. The MTA design enables effective, self-contained, chronic neural network manipulation with translational relevance to the treatment of neuropsychiatric disease.

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11

Ouellette, Mathieu, Jessy Mathault, Shimwe Dominique Niyonambaza, Amine Miled, and Elodie Boisselier. "Electrochemical Detection of Dopamine Based on Functionalized Electrodes." Coatings 9, no. 8 (August 6, 2019): 496. http://dx.doi.org/10.3390/coatings9080496.

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The rapid electrochemical identification and quantification of neurotransmitters being a challenge in the ever-growing field of neuroelectronics, we aimed to facilitate the electrochemical selective detection of dopamine by functionalizing commercially available electrodes through the deposition of a thin film containing pre-formed gold nanoparticles. The influence of different parameters and experimental conditions, such as buffer solution, fiber material, concentration, and cyclic voltammetry (CV) cycle number, were tested during neurotransmitter detection. In each case, without drastically changing the outcome of the functionalization process, the selectivity towards dopamine was improved. The detected oxidation current for dopamine was increased by 92%, while ascorbic acid and serotonin oxidation currents were lowered by 66% under the best conditions. Moreover, dopamine sensing was successfully achieved in tandem with home-made triple electrodes and an in-house built potentiostat at a high scan rate mode.

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12

Boriskov, Petr, and Andrei Velichko. "Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators." Electronics 8, no. 9 (August 22, 2019): 922. http://dx.doi.org/10.3390/electronics8090922.

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In this paper, we present circuit solutions based on a switch element with the S-type I–V characteristic implemented using the classic FitzHugh–Nagumo and FitzHugh–Rinzel models. Using the proposed simplified electrical circuits allows the modeling of the integrate-and-fire neuron and burst oscillation modes with the emulation of the mammalian cold receptor patterns. The circuits were studied using the experimental I–V characteristic of an NbO2 switch with a stable section of negative differential resistance (NDR) and a VO2 switch with an unstable NDR, considering the temperature dependences of the threshold characteristics. The results are relevant for modern neuroelectronics and have practical significance for the introduction of the neurodynamic models in circuit design and the brain–machine interface. The proposed systems of differential equations with the piecewise linear approximation of the S-type I–V characteristic may be of scientific interest for further analytical and numerical research and development of neural networks with artificial intelligence.

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13

Rodrigues, Fabiano de Abreu. "NEUROELETRÓNICO: COMUNICAÇÃO ENTRE NEURÔNIOS ARTIFICIAIS, CEREBRAIS E A INTERNET / NEUROELECTRONICS: COMMUNICATION BETWEEN ARTIFICIAL NEURONS, BRAINS, AND THE INTERNET." Brazilian Journal of Development 7, no. 2 (2021): 15766–71. http://dx.doi.org/10.34117/bjdv7n2-276.

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14

Durand, D. "Neural Engineering." Methods of Information in Medicine 46, no. 02 (2007): 142–46. http://dx.doi.org/10.1055/s-0038-1625395.

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Summary Objectives : The field of neural engineering focuses on an area of research at the interface between neuroscience and engineering. The area of neural engineering was first associated with the brain machine interface but is much broader and encompasses experimental, computational, and theoretical aspects of neural interfacing, neuroelectronics, neuromechanical systems, neuroinformatics, neuroimaging, neural prostheses, artificial and biological neural circuits, neural control, neural tissue regeneration, neural signal processing, neural modelling and neuro-computation. One of the goals of neural engineering is to develop a selective interface for the peripheral nervous system. Methods : Nerve cuffs electrodes have been developed to either reshape or maintain the nerve into an elongated shape in order to increase the circumference to cross sectional ratio. It is then possible to place many electrodes around the nerve to achieve selectivity. This new cuff (flat interface nerve electrode: FINE) was applied to the hypoglossal nerve and the sciatic nerve in dogs and cats to estimate the selectivity of the interface. Results : By placing many contacts close to the axons, three different types of selectivity were achieved: 1) The FINE could generate a high degree of stimulation selectivity as estimated by the individual fascicle recording. 2) Similarly, recording selectivity was also demonstrated and blind source algorithms were applied to recover the signals. 3) Finally, by placing arrays of electrodes along the nerve, small fiber diameters could be excited before large fibers thereby reversing the recruitment order. Conclusion : Taking advantage of the fact that nerves are not round but oblong or flat allows a novel design for selective nerve interface with the peripheral nervous system. This new design has found applications in many disorders of the nervous system such as bladder incontinence, obstructive sleep apnea and stroke.

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15

Rinklin, Philipp, and Bernhard Wolfrum. "Recent developments and future perspectives on neuroelectronic devices." Neuroforum 27, no. 4 (October 8, 2021): 213–24. http://dx.doi.org/10.1515/nf-2021-0019.

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Abstract Neuroscientific discoveries and the development of recording and stimulation tools are deeply connected. Over the past decades, the progress in seamlessly integrating such tools in the form of neuroelectronic devices has been tremendous. Here, we review recent advances and key aspects of this goal. Firstly, we illustrate improvements with respect to the coupling between cells/tissue and recording/stimulation electrodes. Thereafter, we cover attempts to mitigate the foreign body response by reducing the devices’ invasiveness. We follow up with a description of specialized electronic hardware aimed at the needs of bioelectronic applications. Lastly, we outline how additional modalities such as optical techniques or ultrasound could in the future be integrated into neuroelectronic implants.

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16

Kim, Raeyoung, Nari Hong, and Yoonkey Nam. "Gold nanograin microelectrodes for neuroelectronic interfaces." Biotechnology Journal 8, no. 2 (November 9, 2012): 206–14. http://dx.doi.org/10.1002/biot.201200219.

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17

Frommherz, P. "Neuroelectronic Interfacing, its Nature and Implementation." Chemie Ingenieur Technik 78, no. 9 (September 2006): 1435. http://dx.doi.org/10.1002/cite.200690098.

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18

Birmingham, John T., Dustin M. Graham, and David L. Tauck. "Lymnaea stagnalis and the development of neuroelectronic technologies." Journal of Neuroscience Research 76, no. 3 (2004): 277–81. http://dx.doi.org/10.1002/jnr.20022.

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19

Guimerà-Brunet, Anton, Eduard Masvidal-Codina, Jose Cisneros-Fernández, Francesc Serra-Graells, and Jose A. Garrido. "Novel transducers for high-channel-count neuroelectronic recording interfaces." Current Opinion in Biotechnology 72 (December 2021): 39–47. http://dx.doi.org/10.1016/j.copbio.2021.10.002.

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20

Rutten, W., J. M. Mouveroux, J. Buitenweg, C. Heida, T. Ruardij, E. Marani, and E. Lakke. "Neuroelectronic interfacing with cultured multielectrode arrays toward a cultured probe." Proceedings of the IEEE 89, no. 7 (July 2001): 1013–29. http://dx.doi.org/10.1109/5.939810.

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21

Wolf, Nikolaus R., Pratika Rai, Manuel Glass, Frano Milos, Vanessa Maybeck, Andreas Offenhäusser, and Roger Wördenweber. "Mechanical and Electronic Cell–Chip Interaction of APTES-Functionalized Neuroelectronic Interfaces." ACS Applied Bio Materials 4, no. 8 (August 4, 2021): 6326–37. http://dx.doi.org/10.1021/acsabm.1c00576.

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22

Zhang, Anqi, Emiri T. Mandeville, Lijun Xu, Creed M. Stary, Eng H. Lo, and Charles M. Lieber. "Ultraflexible endovascular probes for brain recording through micrometer-scale vasculature." Science 381, no. 6655 (July 21, 2023): 306–12. http://dx.doi.org/10.1126/science.adh3916.

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Implantable neuroelectronic interfaces have enabled advances in both fundamental research and treatment of neurological diseases but traditional intracranial depth electrodes require invasive surgery to place and can disrupt neural networks during implantation. We developed an ultrasmall and flexible endovascular neural probe that can be implanted into sub-100-micrometer–scale blood vessels in the brains of rodents without damaging the brain or vasculature. In vivo electrophysiology recording of local field potentials and single-unit spikes have been selectively achieved in the cortex and olfactory bulb. Histology analysis of the tissue interface showed minimal immune response and long-term stability. This platform technology can be readily extended as both research tools and medical devices for the detection and intervention of neurological diseases.

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23

Kuliasha, Cary A., and Jack W. Judy. "The Materials Science Foundation Supporting the Microfabrication of Reliable Polyimide–Metal Neuroelectronic Interfaces." Advanced Materials Technologies 6, no. 6 (May 3, 2021): 2100149. http://dx.doi.org/10.1002/admt.202100149.

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24

Zeck, G., and P. Fromherz. "Noninvasive neuroelectronic interfacing with synaptically connected snail neurons immobilized on a semiconductor chip." Proceedings of the National Academy of Sciences 98, no. 18 (August 28, 2001): 10457–62. http://dx.doi.org/10.1073/pnas.181348698.

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25

Chang, C. H., S. R. Chang, J. S. Lin, Y. T. Lee, S. R. Yeh, and H. Chen. "A CMOS neuroelectronic interface based on two-dimensional transistor arrays with monolithically-integrated circuitry." Biosensors and Bioelectronics 24, no. 6 (February 2009): 1757–64. http://dx.doi.org/10.1016/j.bios.2008.09.007.

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26

Hai, Aviad, Joseph Shappir, and Micha E. Spira. "Long-Term, Multisite, Parallel, In-Cell Recording and Stimulation by an Array of Extracellular Microelectrodes." Journal of Neurophysiology 104, no. 1 (July 2010): 559–68. http://dx.doi.org/10.1152/jn.00265.2010.

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Here we report on the development of a novel neuroelectronic interface consisting of an array of noninvasive gold-mushroom-shaped microelectrodes (gMμEs) that practically provide intracellular recordings and stimulation of many individual neurons, while the electrodes maintain an extracellular position. The development of this interface allows simultaneous, multisite, long-term recordings of action potentials and subthreshold potentials with matching quality and signal-to-noise ratio of conventional intracellular sharp glass microelectrodes or patch electrodes. We refer to the novel approach as “in-cell recording and stimulation by extracellular electrodes” to differentiate it from the classical intracellular recording and stimulation methods. This novel technique is expected to revolutionize the analysis of neuronal networks in relations to learning, information storage and can be used to develop novel drugs as well as high fidelity neural prosthetics and brain-machine systems.

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27

FROMHERZ, P. "Three Levels of Neuroelectronic Interfacing: Silicon Chips with Ion Channels, Nerve Cells, and Brain Tissue." Annals of the New York Academy of Sciences 1093, no. 1 (December 1, 2006): 143–60. http://dx.doi.org/10.1196/annals.1382.011.

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28

Hegel, Lena, Andrea Kauth, Karsten Seidl, and Sven Ingebrandt. "Self-Assembling Flexible 3D-MEAs for Cortical Implants." Current Directions in Biomedical Engineering 7, no. 2 (October 1, 2021): 359–62. http://dx.doi.org/10.1515/cdbme-2021-2091.

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Abstract Flexible Multi Electrode Arrays (MEAs) for neural interfacing reduce the mechanical mismatch between the soft brain tissue and the electrode arrays allowing accurate signal recordings and neural stimulation while reducing inflammatory responses. Many standard manufacturing processes of MEAs are designed for planar structures and the production of three-dimensional structures is challenging. In the present study, shaft structures with one to two circular gold microelectrodes (10 - 20 μm), each on a base polyimide (PI) substrate, were investigated. We describe a fabrication method, with which shafts made from bi-layer PI flip into the third dimension, which is a first step towards spontaneous assembly of electrodes in flexible 3D MEAs for neuroelectronic applications. A lift-up of the shafts was achieved by the contraction of a second PI layer and a steady nitrogen flow during polycondensation. This shrinking PI was structured in pits with a width of 5 - 600 μm. We achieved liftup angles of up to 42 degrees. The shaft structures can be hardened and later be used for neural implantation experiments.

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29

VanDersarl, Jules J., André Mercanzini, and Philippe Renaud. "Integration of 2D and 3D Thin Film Glassy Carbon Electrode Arrays for Electrochemical Dopamine Sensing in Flexible Neuroelectronic Implants." Advanced Functional Materials 25, no. 1 (November 6, 2014): 78–84. http://dx.doi.org/10.1002/adfm.201402934.

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30

Wan, Jiandi, Sitong Zhou, Hing Jii Mea, Yaojun Guo, Hansol Ku, and Brianna M. Urbina. "Emerging Roles of Microfluidics in Brain Research: From Cerebral Fluids Manipulation to Brain-on-a-Chip and Neuroelectronic Devices Engineering." Chemical Reviews 122, no. 7 (January 26, 2022): 7142–81. http://dx.doi.org/10.1021/acs.chemrev.1c00480.

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31

Pashkevich, S. G., and N. S. Serdyuchenko. "Glycosaminoglycans role in hippocampal neural networks interneuronal communications." Doklady of the National Academy of Sciences of Belarus 64, no. 5 (November 5, 2020): 590–98. http://dx.doi.org/10.29235/1561-8323-2020-64-5-590-598.

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In the development of neurotechnologies, the search for applications for invasive neuroelectronic devices is relevant. One of the promising areas can be the development of ways of influencing intercellular communication, that is, not by acting on pre-, post- and extrasynaptic receptors, but on the extracellular matrix surrounding neurons and glia. For the development of bioelectronic pharmaceuticals, it is important to search for stimulation parameters at which a controlled change in the structural and functional parameters of the nervous tissue is possible. We considered one of the actual mechanisms of the molecular pathogenesis of SARS-CoV-2 infection - the induction of glycosaminoglycan metabolism. It is assumed that, getting into the olfactory epithelium and the olfactory bulbs of the brain, the virus is able to reach the structures of the central nervous system. When modeling changes in the enzymatic activity of hyaluronidase (0.1; 1.0; 10.0 U/ml) for 5 minutes in one of the key structures of the limbic system - the hippocampus (3-4-week-old ratpups, n = 64), the conditions for the transformation of intercellular contacts were revealed and evoked electrical activity of populations of CA1 region. The recorded development of synaptic plasticity processes has an adaptive potential at hyaluronidase concentrations not exceeding 1.0 U/ml.The in vitro method proposed in this work and a reasonable target for exposure - elements of the extracellular matrix, make it possible to simulate one of the mechanisms of the development of viral infection, optimize the process of preliminary screening of new medicinal substances that can minimize the risk of developing neuroinflammatory processes, and also substantiate the conditions for safe and/or therapeutic effects and electrical impulses on the elements of the nervous tissue.

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32

Trzpil-Jurgielewicz, Beata, Władysław Dąbrowski, and Paweł Hottowy. "Analysis and Reduction of Nonlinear Distortion in AC-Coupled CMOS Neural Amplifiers with Tunable Cutoff Frequencies." Sensors 21, no. 9 (April 30, 2021): 3116. http://dx.doi.org/10.3390/s21093116.

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Integrated CMOS neural amplifiers are key elements of modern large-scale neuroelectronic interfaces. The neural amplifiers are routinely AC-coupled to electrodes to remove the DC voltage. The large resistances required for the AC coupling circuit are usually realized using MOSFETs that are nonlinear. Specifically, designs with tunable cutoff frequency of the input high‑pass filter may suffer from excessive nonlinearity, since the gate-source voltages of the transistors forming the pseudoresistors vary following the signal being amplified. Consequently, the nonlinear distortion in such circuits may be high for signal frequencies close to the cutoff frequency of the input filter. Here we propose a simple modification of the architecture of a tunable AC-coupled amplifier, in which the bias voltages Vgs of the transistors forming the pseudoresistor are kept constant independently of the signal levels, what results in significantly improved linearity. Based on numerical simulations of the proposed circuit designed in 180 nm technology we analyze the Total Harmonic Distortion levels as a function of signal frequency and amplitude. We also investigate the impact of basic amplifier parameters—gain, cutoff frequency of the AC coupling circuit, and silicon area—on the distortion and noise performance. The post-layout simulations of the complete test ASIC show that the distortion is very significantly reduced at frequencies near the cutoff frequency, when compared to the commonly used circuits. The THD values are below 1.17% for signal frequencies 1 Hz–10 kHz and signal amplitudes up to 10 mV peak-to-peak. The preamplifier area is only 0.0046 mm2 and the noise is 8.3 µVrms in the 1 Hz–10 kHz range. To our knowledge this is the first report on a CMOS neural amplifier with systematic characterization of THD across complete range of frequencies and amplitudes of neuronal signals recorded by extracellular electrodes.

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33

Qi, Yongli, Seung-Kyun Kang, and Hui Fang. "Advanced materials for implantable neuroelectronics." MRS Bulletin, May 24, 2023. http://dx.doi.org/10.1557/s43577-023-00540-5.

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34

Kim, Giheon, Minki Hong, Yerim Lee, and Jahyun Koo. "Biodegradable materials and devices for neuroelectronics." MRS Bulletin, May 12, 2023. http://dx.doi.org/10.1557/s43577-023-00529-0.

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35

Andreeva, Natalia V., Eugeny A. Ryndin, Dmitriy S. Mazing, Oleg Y. Vilkov, and Victor V. Luchinin. "Organismic Memristive Structures With Variable Functionality for Neuroelectronics." Frontiers in Neuroscience 16 (June 14, 2022). http://dx.doi.org/10.3389/fnins.2022.913618.

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In this paper, we report an approach to design nanolayered memristive compositions based on TiO2/Al2O3 bilayer structures with analog non-volatile and volatile tuning of the resistance. The structure of the TiO2 layer drives the physical mechanism underlying the non-volatile resistance switching, which can be changed from electronic to ionic, enabling the synaptic behavior emulation. The presence of the anatase phase in the amorphous TiO2 layer induces the resistive switching mechanism due to electronic processes. In this case, the switching of the resistance within the range of seven orders of magnitude is experimentally observed. In the bilayer with amorphous titanium dioxide, the participation of ionic processes in the switching mechanism results in narrowing the tuning range down to 2–3 orders of magnitude and increasing the operating voltages. In this way, a combination of TiO2/Al2O3 bilayers with inert electrodes enables synaptic behavior emulation, while active electrodes induce the neuronal behavior caused by cation density variation in the active Al2O3 layer of the structure. We consider that the proposed approach could help to explore the memristive capabilities of nanolayered compositions in a more functional way, enabling implementation of artificial neural network algorithms at the material level and simplifying neuromorphic layouts, while maintaining all benefits of neuromorphic architectures.

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36

"Solution-Processed High-k Dielectric Films for Wearable Neuroelectronics." ECS Meeting Abstracts, 2018. http://dx.doi.org/10.1149/ma2018-01/26/1562.

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37

Mikhaylov, Alexey N., Sergey A. Shchanikov, Vyacheslav A. Demin, Valeri A. Makarov, and Victor B. Kazantsev. "Editorial: Neuroelectronics: towards symbiosis of neuronal systems and emerging electronics." Frontiers in Neuroscience 17 (June 7, 2023). http://dx.doi.org/10.3389/fnins.2023.1227798.

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38

Dainow, Brandt. "Threats to Autonomy from Emerging ICTs." Australasian Journal of Information Systems 21 (November 26, 2017). http://dx.doi.org/10.3127/ajis.v21i0.1438.

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This paper examines threats to autonomy created by significant emerging ICTs. Emerging ICTs cover a wide range of technologies, from intelligent environments to neuroelectronics, and human autonomy is potentially threatened by all of them in some way. However, there is no single agreed definition of autonomy. This paper therefore considers the ways in which different accounts of autonomy are impacted by the different IC technologies. From this range of threats we will derive some properties which any ICT must exhibit in order to threaten human autonomy. Finally, we will show how the range of definitions of autonomy creates problems for customary approaches to vale-sensitive design, and how this indicates a need for greater flexibility when attempting to improve the ethical status of emerging ICTs.

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39

Bruno, Ugo, Anna Mariano, Daniela Rana, Tobias Gemmeke, Simon Musall, and Francesca Santoro. "From neuromorphic to neurohybrid: transition from the emulation to the integration of neuronal networks." Neuromorphic Computing and Engineering, March 22, 2023. http://dx.doi.org/10.1088/2634-4386/acc683.

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Abstract The highly efficient computation of the brain relies on its plastic and reconfigurable nature, enabling complex computations and maintenance of vital functions with a remarkably low power consumption of only ~20 W. First efforts to leverage brain-inspired computational principles have led to the introduction of artificial neural networks (ANNs) that revolutionized information processing and daily life. The relentless pursuit of the definitive computing platform is now pushing researchers towards the investigation of novel solutions to emulate specific brain features (such as synaptic plasticity) to allow local and energy efficient computations. The development of such devices may also be pivotal in addressing major challenges of a continuously aging world, including the treatment of neurodegenerative diseases. To date, the neuroelectronics field has been instrumental in deepening our understanding of how neurons exchange information, owing to the rapid development of silicon-based platforms for neural recordings and stimulation. However, this approach still does not allow for in loco processing of the observed biological signals due to two aspects. Firstly, silicon chips applying conventional processing are simply too power hungry to be embedded into the brain. Secondly, despite the success of silicon-based devices in electronic applications, they are ill-suited for directly interfacing with biological tissue. A cornucopia of solutions has therefore been proposed in the last years to obtain neuromorphic materials to create effective biointerfaces and enable reliable bidirectional communication with neurons. Organic conductive materials are not only highly biocompatible and able to electrochemically transduce biological signals, but also promise to include neuromorphic features, such as neuro-transmitter mediated plasticity and learning capabilities. Furthermore, organic electronics, relying on mixed electronic/ionic conduction mechanism, can be efficiently coupled with biological neural networks, while still communicating with silicon-based electronics. We envision neurohybrid systems that integrate silicon-based and organic electronics-based neuromorphic technologies to create active artificial interfaces with biological tissues.

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40

Adewole, Dayo O., Mijail D. Serruya, John A. Wolf, and D. Kacy Cullen. "Bioactive Neuroelectronic Interfaces." Frontiers in Neuroscience 13 (March 29, 2019). http://dx.doi.org/10.3389/fnins.2019.00269.

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41

Seo, Kyung Jin, Mackenna Hill, Jaehyeon Ryu, Chia-Han Chiang, Iakov Rachinskiy, Yi Qiang, Dongyeol Jang, et al. "A soft, high-density neuroelectronic array." npj Flexible Electronics 7, no. 1 (August 22, 2023). http://dx.doi.org/10.1038/s41528-023-00271-2.

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AbstractTechniques to study brain activities have evolved dramatically, yet tremendous challenges remain in acquiring high-throughput electrophysiological recordings minimally invasively. Here, we develop an integrated neuroelectronic array that is filamentary, high-density and flexible. Specifically, with a design of single-transistor multiplexing and current sensing, the total 256 neuroelectrodes achieve only a 2.3 × 0.3 mm2 area, unprecedentedly on a flexible substrate. A single-transistor multiplexing acquisition circuit further reduces noise from the electrodes, decreases the footprint of each pixel, and potentially increases the device’s lifetime. The filamentary neuroelectronic array also integrates with a rollable contact pad design, allowing the device to be injected through a syringe, enabling potential minimally invasive array delivery. Successful acute auditory experiments in rats validate the ability of the array to record neural signals with high tone decoding accuracy. Together, these results establish soft, high-density neuroelectronic arrays as promising devices for neuroscience research and clinical applications.

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Hofmann, Ulrich G., and Jeffrey R. Capadona. "Editorial: Bridging the Gap in Neuroelectronic Interfaces." Frontiers in Neuroscience 14 (June 3, 2020). http://dx.doi.org/10.3389/fnins.2020.00457.

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Jiaxiang, Xue, and Liu Zhixin. "Advances and Development of Electronic Neural Interfaces." Journal of Computing and Natural Science, July 5, 2023, 147–57. http://dx.doi.org/10.53759/181x/jcns202303014.

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The discipline of neural engineering is working to enhance the functional and stability lifespan of present implanted neuroelectronic interfaces by developing next-generation interfaces employing biologically-derived and biologically-inspired materials. Humans and robots may exchange information using input devices like keyboards and touchscreens. Future information sharing may be facilitated through neural interfaces that provide a more direct electric connection between digital (man-made) systems and analog nerve systems. This paper presents the history and development of electronic brain interface; and classifies and analyzes the interfaces into four generations based on the technical landmarks within the electronic sensor interface and its evolution, including the patch clamp method, integrated neural interfaces, wearable or implantable neural interfaces, and multi-based neural interfaces. In this paper, we also discuss the potential presented by cutting-edge technology and critical system and circuit problems in the neural interface model.

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Yang, Qianru, and X. Tracy Cui. "Advanced in vivo fluorescence microscopy of neural electronic interface." MRS Bulletin, May 5, 2023. http://dx.doi.org/10.1557/s43577-023-00530-7.

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AbstractNeuroelectronic devices are essential tools in neuroscience research, diagnosis, and/or treatment of neurological diseases, as well as in neuro-prosthetics and brain–computer interfaces. Despite a long history of application, neuroelectronic devices are still facing challenges of unsatisfactory chronic stability and a lack of understanding of cellular mechanisms for recording and stimulation. To improve the information transfer between the neural tissue and electronic devices, a comprehensive understanding of the biological activities around the neural electrode is critical. In vivo fluorescent microscopy technologies are rapidly developing and have revolutionized our understanding of cellular dynamics in response to neural interfacing materials. Here, we will provide an overview of the in vivo fluorescence microscopy systems and imaging configurations for studying the neural electronic interface, as well as recent findings in biological mechanisms learned using these advanced optical imaging modalities. Finally, we will discuss the current challenges and future directions. Graphical abstract

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Nella, Kevin T., Benjamin M. Norton, Hsiang-Tsun Chang, Rachel A. Heuer, Christian B. Roque, and Akihiro J. Matsuoka. "Bridging the electrode–neuron gap: finite element modeling of in vitro neurotrophin gradients to optimize neuroelectronic interfaces in the inner ear." Acta Biomaterialia, August 2022. http://dx.doi.org/10.1016/j.actbio.2022.08.035.

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