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Journal articles on the topic 'Interface neuronale'

Author: Grafiati

Published: 26 October 2024

Last updated: 5 July 2025

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Goto, Toichiro, Nahoko Kasai, Rick Lu, Roxana Filip, and Koji Sumitomo. "Scanning Electron Microscopy Observation of Interface Between Single Neurons and Conductive Surfaces." Journal of Nanoscience and Nanotechnology 16, no. 4 (2016): 3383–87. http://dx.doi.org/10.1166/jnn.2016.12311.

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Interfaces between single neurons and conductive substrates were investigated using focused ion beam (FIB) milling and subsequent scanning electron microscopy (SEM) observation. The interfaces play an important role in controlling neuronal growth when we fabricate neuron-nanostructure integrated devices. Cross sectional images of cultivated neurons obtained with an FIB/SEM dual system show the clear affinity of the neurons for the substrates. Very few neurons attached themselves to indium tin oxide (ITO) and this repulsion yielded a wide interspace at the neuron-ITO interface. A neuron-gold interface exhibited partial adhesion. On the other hand, a neuron-titanium interface showed good adhesion and small interspaces were observed. These results are consistent with an assessment made using fluorescence microscopy. We expect the much higher spatial resolution of SEM images to provide us with more detailed information. Our study shows that the interface between a single neuron and a substrate offers useful information as regards improving surface properties and establishing neuron-nanostructure integrated devices.

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Wang, Xinyuan. "Intracortical Brain-machine Interface for Restoring Sensory Motor Function: Progress and Challenges." International Journal of Biology and Life Sciences 3, no. 2 (2023): 31–38. http://dx.doi.org/10.54097/ijbls.v3i2.10514.

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Limb loss or paralysis due to spinal cord injury has a devastating impact on quality of life. One way to restore the sensory and motor abilities lost by amputees and quadriplegics is to provide them with implants that interface directly with the central nervous system. Such Brain-machine interfaces could enable patients to exert active control over the electrical contractions of prosthetic limbs or paralysed muscles. The parallel interface can transmit sensory information about these motor outcomes back to the patient. Recent developments in algorithms for decoding motor intention from neuronal activity, using biomimetic and adaptation-based approaches and methods for delivering sensory feedback through electrical stimulation of neurons have shown promise for invasive interfaces with sensorimotor cortex, although significant challenges remain.

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Bernardin, Evans, Christopher L. Frewin, Abhishek Dey, et al. "Development of an all-SiC neuronal interface device." MRS Advances 1, no. 55 (2016): 3679–84. http://dx.doi.org/10.1557/adv.2016.360.

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ABSTRACTThe intracortical neural interface (INI) is a key component of brain machine interfaces (BMI) which offer the possibility to restore functions lost by patients due to severe trauma to the central or peripheral nervous system. Unfortunately today’s neural electrodes suffer from a variety of design flaws, mainly the use of non-biocompatible materials based on Si or W with polymer coatings to mask the underlying material. Silicon carbide (SiC) is a semiconductor that has been proven to be highly biocompatible, and this chemically inert, physically robust material system may provide the longevity and reliability needed for the INI community. The design, fabrication, and preliminary testing of a prototype all-SiC planar microelectrode array based on 4H-SiC with an amorphous silicon carbide (a-SiC) insulator is described. The fabrication of the planar microelectrode was performed utilizing a series of conventional micromachining steps. Preliminary data is presented which shows a proof of concept for an all-SiC microelectrode device.

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Sahni, Deshdeepak, Andrew Jea, Javier A. Mata, et al. "Biocompatibility of pristine graphene for neuronal interface." Journal of Neurosurgery: Pediatrics 11, no. 5 (2013): 575–83. http://dx.doi.org/10.3171/2013.1.peds12374.

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Object Graphene possesses unique electrical, physical, and chemical properties that may offer significant potential as a bioscaffold for neuronal regeneration after spinal cord injury. The purpose of this investigation was to establish the in vitro biocompatibility of pristine graphene for interface with primary rat cortical neurons. Methods Graphene films were prepared by chemical vapor deposition on a copper foil catalytic substrate and subsequent apposition on bare Permanox plastic polymer dishes. Rat neuronal cell culture was grown on graphene-coated surfaces, and cell growth and attachment were compared with those on uncoated and poly-d-lysine (PDL)-coated controls; the latter surface is highly favorable for neuronal attachment and growth. Live/dead cell analysis was conducted with flow cytometry using ethidium homodimer-1 and calcein AM dyes. Lactate dehydrogenase (LDH) levels—indicative of cytotoxicity—were measured as markers of cell death. Phase contrast microscopy of active cell culture was conducted to assess neuronal attachment and morphology. Results Statistically significant differences in the percentage of live or dead neurons were noted between graphene and PDL surfaces, as well as between the PDL-coated and bare surfaces, but there was little difference in cell viability between graphene-coated and bare surfaces. There were significantly lower LDH levels in the graphene-coated samples compared with the uncoated ones, indicating that graphene was not more cytotoxic than the bare control surface. According to phase contrast microscopy, neurons attached to the graphene-coated surface and were able to elaborate long, neuritic processes suggestive of normal neuronal metabolism and morphology. Conclusions Further use of graphene as a bioscaffold will require surface modification that enhances hydrophilicity to increase cellular attachment and growth. Graphene is a nanomaterial that is biocompatible with neurons and may have significant biomedical applications.

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Cao, Jiong, Jenni I. Viholainen, Caroline Dart, Helen K. Warwick, Mark L. Leyland, and Michael J. Courtney. "The PSD95–nNOS interface." Journal of Cell Biology 168, no. 1 (2005): 117–26. http://dx.doi.org/10.1083/jcb.200407024.

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The stress-activated protein kinase p38 and nitric oxide (NO) are proposed downstream effectors of excitotoxic cell death. Although the postsynaptic density protein PSD95 can recruit the calcium-dependent neuronal NO synthase (nNOS) to the mouth of the calcium-permeable NMDA receptor, and depletion of PSD95 inhibits excitotoxicity, the possibility that selective uncoupling of nNOS from PSD95 might be neuroprotective is unexplored. The relationship between excitotoxic stress–generated NO and activation of p38, and the significance of the PSD95–nNOS interaction to p38 activation also remain unclear. We find that NOS inhibitors reduce both glutamate-induced p38 activation and the resulting neuronal death, whereas NO donor has effects consistent with NO as an upstream regulator of p38 in glutamate-induced cell death. Experiments using a panel of decoy constructs targeting the PSD95–nNOS interaction suggest that this interaction and subsequent NO production are critical for glutamate-induced p38 activation and the ensuing cell death, and demonstrate that the PSD95–nNOS interface provides a genuine possibility for design of neuroprotective drugs with increased selectivity.

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Macías Macías, José Manuel, Juan Alberto Ramírez Quintana, José Salvador Antonio Méndez Aguirre, Mario Ignacio Chacón Murguía, and Alma Delia Corral Sáenz. "Procesamiento embebido de p300 basado en red neuronal convolucional para interfaz cerebro-computadora ubicua." RECIBE, Revista ELECTRÓNICA DE COMPUTACIÓN, INFORMÁTICA, BIOMÉDICA Y ELECTRÓNICA 9, no. 2 (2021): B1—B24. http://dx.doi.org/10.32870/recibe.v9i2.153.

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Se propone un método de bajo costo computacional para detectar el potencial evocado P300 en aplicaciones ubicuas de comunicación y control, el cual se denomina Procesamiento Embebido P300 (EP-300). La entrada de EP-300 es una señal electroencefalografía (EEG) de un canal y la arquitectura de este método se basa en los algoritmos que utilizan redes neuronales convolucionales. Para implementar el método EP-300, también se presenta una interfaz cerebro-computadora embebida que utiliza cuatro estímulos para evocar el P300 y tiene conectividad con una red de Internet de las cosas. Con esta interfaz, se generó una base de datos para los experimentos y contiene las señales EEG de ocho sujetos. De acuerdo con los resultados, EP-300 se adapta a las señales EEG que genera cada sujeto, tiene un desempeño de 96% utilizando un electrodo y se procesa en tiempo real por su baja complejidad. Sin embargo, para evitar errores en la detección, los sujetos deben mantenerse concentrados y seguir el protocolo de adquisición. Como conclusiones, EP-300 es uno de los métodos más competitivo en la literatura debido a su desempeño, baja cantidad de electrodos y a que extiende el procesamiento de la onda P300 a sistemas ubicuos utilizados en aplicaciones cotidianas.

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Liang, Elaine, Jiuyun Shi, and Bozhi Tian. "Freestanding nanomaterials for subcellular neuronal interfaces." iScience 25, no. 1 (2022): 103534. http://dx.doi.org/10.1016/j.isci.2021.103534.

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Keskinbora, Kadircan H., and Kader Keskinbora. "Ethical considerations on novel neuronal interfaces." Neurological Sciences 39, no. 4 (2017): 607–13. http://dx.doi.org/10.1007/s10072-017-3209-x.

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Pronker, Matti F., Roderick P. Tas, Hedwich C. Vlieg, and Bert J. C. Janssen. "Nogo Receptor crystal structures with a native disulfide pattern suggest a novel mode of self-interaction." Acta Crystallographica Section D Structural Biology 73, no. 11 (2017): 860–76. http://dx.doi.org/10.1107/s2059798317013791.

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The Nogo Receptor (NgR) is a glycophosphatidylinositol-anchored cell-surface protein and is a receptor for three myelin-associated inhibitors of regeneration: myelin-associated glycoprotein, Nogo66 and oligodendrocyte myelin glycoprotein. In combination with different co-receptors, NgR mediates signalling that reduces neuronal plasticity. The available structures of the NgR ligand-binding leucine-rich repeat (LRR) domain have an artificial disulfide pattern owing to truncated C-terminal construct boundaries. NgR has previously been shown to self-associateviaits LRR domain, but the structural basis of this interaction remains elusive. Here, crystal structures of the NgR LRR with a longer C-terminal segment and a native disulfide pattern are presented. An additional C-terminal loop proximal to the C-terminal LRR cap is stabilized by two newly formed disulfide bonds, but is otherwise mostly unstructured in the absence of any stabilizing interactions. NgR crystallized in six unique crystal forms, three of which share a crystal-packing interface. NgR crystal-packing interfaces from all eight unique crystal forms are compared in order to explore how NgR could self-interact on the neuronal plasma membrane.

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Milekovic, Tomislav, Anish A. Sarma, Daniel Bacher, et al. "Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals." Journal of Neurophysiology 120, no. 1 (2018): 343–60. http://dx.doi.org/10.1152/jn.00493.2017.

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Restoring communication for people with locked-in syndrome remains a challenging clinical problem without a reliable solution. Recent studies have shown that people with paralysis can use brain-computer interfaces (BCIs) based on intracortical spiking activity to efficiently type messages. However, due to neuronal signal instability, most intracortical BCIs have required frequent calibration and continuous assistance of skilled engineers to maintain performance. Here, an individual with locked-in syndrome due to brain stem stroke and an individual with tetraplegia secondary to amyotrophic lateral sclerosis (ALS) used a simple communication BCI based on intracortical local field potentials (LFPs) for 76 and 138 days, respectively, without recalibration and without significant loss of performance. BCI spelling rates of 3.07 and 6.88 correct characters/minute allowed the participants to type messages and write emails. Our results indicate that people with locked-in syndrome could soon use a slow but reliable LFP-based BCI for everyday communication without ongoing intervention from a technician or caregiver. NEW & NOTEWORTHY This study demonstrates, for the first time, stable repeated use of an intracortical brain-computer interface by people with tetraplegia over up to four and a half months. The approach uses local field potentials (LFPs), signals that may be more stable than neuronal action potentials, to decode participants’ commands. Throughout the several months of evaluation, the decoder remained unchanged; thus no technical interventions were required to maintain consistent brain-computer interface operation.

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SAKURAI, Yoshio. "Multi-neuronal activity-cell assembly-brain-machine interface." Japanese Journal of Physiological Psychology and Psychophysiology 24, no. 1 (2006): 57–67. http://dx.doi.org/10.5674/jjppp1983.24.57.

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Maksimenko, V. A., A. A. Harchenko, and A. Lüttjohann. "Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity." Information and Control Systems, no. 4 (September 23, 2018): 115–22. http://dx.doi.org/10.31799/1684-8853-2018-4-115-122.

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Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans.

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Fadeeva, Elena, Andrea Deiwick, Boris Chichkov, and Sabrina Schlie-Wolter. "Impact of laser-structured biomaterial interfaces on guided cell responses." Interface Focus 4, no. 1 (2014): 20130048. http://dx.doi.org/10.1098/rsfs.2013.0048.

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To achieve a perfect integration of biomaterials into the body, tissue formation in contact with the interface has to be controlled. In this connection, a selective cell control is required: fibrotic encapsulation has to be inhibited, while tissue guidance has to be stimulated. As conventional biomaterials do not fulfil this specification, functionalization of the biointerface is under development to mimic the natural environment of the cells. One approach focuses on the fabrication of defined surface topographies. Thereby, ultrashort pulse laser ablation is very beneficial, owing to a large variety of fabricated structures, reduced heat-affected zones, high precision and reproducibility. We demonstrate that nanostructures in platinum and microstructures in silicon selectively control cell behaviour: inhibiting fibroblasts, while stimulating neuronal attachment and differentiation. However, the control of fibroblasts strongly correlates with the created size dimensions of the surface structures. These findings suggest favourable biomaterial interfaces for electronic devices. The mechanisms which are responsible for selective cell control are poorly understood. To give an insight, cell behaviour in dependence of biomaterial interfaces is discussed—including basic research on the role of the extracellular matrix. This knowledge is essential to understand such specific cell responses and to optimize biomaterial interfaces for future biomedical applications.

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Patolsky, Fernando, Brian P. Timko, Gengfeng Zheng, and Charles M. Lieber. "Nanowire-Based Nanoelectronic Devices in the Life Sciences." MRS Bulletin 32, no. 2 (2007): 142–49. http://dx.doi.org/10.1557/mrs2007.47.

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AbstractThe interface between nanosystems and biosystems is emerging as one of the broadest and most dynamic areas of science and technology, bringing together biology, chemistry, physics, biotechnology, medicine, and many areas of engineering. The combination of these diverse areas of research promises to yield revolutionary advances in healthcare, medicine, and the life sciences through the creation of new and powerful tools that enable direct, sensitive, and rapid analysis of biological and chemical species. Devices based on nanowires have emerged as one of the most powerful and general platforms for ultrasensitive, direct electrical detection of biological and chemical species and for building functional interfaces to biological systems, including neurons. Here, we discuss representative ex amples of nanowire nanosensors for ultrasensitive detection of proteins and individual virus particles as well as recording, stimulation, and inhibition of neuronal signals in nanowire-neuron hybrid structures.

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Hinterberger, Thilo, Ralf Veit, Barbara Wilhelm, Nikolaus Weiskopf, Jean-Jacques Vatine, and Niels Birbaumer. "Neuronal mechanisms underlying control of a brain-computer interface." European Journal of Neuroscience 21, no. 11 (2005): 3169–81. http://dx.doi.org/10.1111/j.1460-9568.2005.04092.x.

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Fisher, Robert S. "12. Neuronal damage and epilepsy: basic and clinical interface." Epilepsy Research 10, no. 1 (1991): 80–89. http://dx.doi.org/10.1016/0920-1211(91)90098-z.

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Giuffrè, Mauro, Rita Moretti, Giuseppina Campisciano, et al. "You Talking to Me? Says the Enteric Nervous System (ENS) to the Microbe. How Intestinal Microbes Interact with the ENS." Journal of Clinical Medicine 9, no. 11 (2020): 3705. http://dx.doi.org/10.3390/jcm9113705.

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Mammalian organisms form intimate interfaces with commensal and pathogenic gut microorganisms. Increasing evidence suggests a close interaction between gut microorganisms and the enteric nervous system (ENS), as the first interface to the central nervous system. Each microorganism can exert a different effect on the ENS, including phenotypical neuronal changes or the induction of chemical transmitters that interact with ENS neurons. Some pathogenic bacteria take advantage of the ENS to create a more suitable environment for their growth or to promote the effects of their toxins. In addition, some commensal bacteria can affect the central nervous system (CNS) by locally interacting with the ENS. From the current knowledge emerges an interesting field that may shape future concepts on the pathogen–host synergic interaction. The aim of this narrative review is to report the current findings regarding the inter-relationships between bacteria, viruses, and parasites and the ENS.

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Dillon, Aiden P., Saba Moslehi, Bret Brouse, et al. "Evolution of Retinal Neuron Fractality When Interfacing with Carbon Nanotube Electrodes." Bioengineering 11, no. 8 (2024): 823. http://dx.doi.org/10.3390/bioengineering11080823.

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Exploring how neurons in the mammalian body interact with the artificial interface of implants can be used to learn about fundamental cell behavior and to refine medical applications. For fundamental and applied research, it is crucial to determine the conditions that encourage neurons to maintain their natural behavior during interactions with non-natural interfaces. Our previous investigations quantified the deterioration of neuronal connectivity when their dendrites deviate from their natural fractal geometry. Fractal resonance proposes that neurons will exhibit enhanced connectivity if an implant’s electrode geometry is matched to the fractal geometry of the neurons. Here, we use in vitro imaging to quantify the fractal geometry of mouse retinal neurons and show that they change during interaction with the electrode. Our results demonstrate that it is crucial to understand these changes in the fractal properties of neurons for fractal resonance to be effective in the in vivo mammalian system.

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Seyock, Silke, Vanessa Maybeck, Emmanuel Scorsone, et al. "Interfacing neurons on carbon nanotubes covered with diamond." RSC Advances 7, no. 1 (2017): 153–60. http://dx.doi.org/10.1039/c6ra20207a.

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Tamura, H., T. Kawashima, S. Suzuki, I. Fujita, and H. Kaneko. "Efficient Signal Processing of Multineuronal Activities for Neural Interface and Prosthesis." Methods of Information in Medicine 46, no. 02 (2007): 147–50. http://dx.doi.org/10.1055/s-0038-1625396.

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Summary Objectives : Multineuronal spike trains must be efficiently decoded in order to utilize them for controlling artificial limbs and organs. Here we evaluated the efficiency of pooling (averaging) and combining (vectorizing) activities of multiple neurons for decoding neuronal information. Methods : Multineuronal activities in the monkey inferior temporal (IT) cortex were obtained by classifying spikes of constituent neurons from multichannel data recorded with a multisite microelectrode. We compared pooling and combining procedures for the amount of visual information transferred by neurons, and for the success rate of stimulus estimation based on neuronal activities in each trial. Results : Both pooling and combining activities of multiple neurons increased the amount of information and the success rate with the number of neurons. However, the degree of improvement obtained by increasing the number of neurons was higher when combining activities as opposed to pooling them. Conclusion: Combining the activities of multiple neurons is more efficient than pooling them for obtaining a precise interpretation of neuronal signals.

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Taskin, Mehmet Berat, Ruodan Xu, Huiling Zhao, et al. "Poly(norepinephrine) as a functional bio-interface for neuronal differentiation on electrospun fibers." Physical Chemistry Chemical Physics 17, no. 14 (2015): 9446–53. http://dx.doi.org/10.1039/c5cp00413f.

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Tay, Andy, Felix E. Schweizer, and Dino Di Carlo. "Micro- and nano-technologies to probe the mechano-biology of the brain." Lab on a Chip 16, no. 11 (2016): 1962–77. http://dx.doi.org/10.1039/c6lc00349d.

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Wu, Xiaosa, David J. Craik та Quentin Kaas. "Interactions of Globular and Ribbon [γ4E]GID with α4β2 Neuronal Nicotinic Acetylcholine Receptor". Marine Drugs 19, № 9 (2021): 482. http://dx.doi.org/10.3390/md19090482.

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The α4β2 nAChR is implicated in a range of diseases and disorders including nicotine addiction, epilepsy and Parkinson’s and Alzheimer’s diseases. Designing α4β2 nAChR selective inhibitors could help define the role of the α4β2 nAChR in such disease states. In this study, we aimed to modify globular and ribbon α-conotoxin GID to selectively target the α4β2 nAChR through competitive inhibition of the α4(+)β2(−) or α4(+)α4(−) interfaces. The binding modes of the globular α-conotoxin [γ4E]GID with rat α3β2, α4β2 and α7 nAChRs were deduced using computational methods and were validated using published experimental data. The binding mode of globular [γ4E]GID at α4β2 nAChR can explain the experimental mutagenesis data, suggesting that it could be used to design GID variants. The predicted mutational energy results showed that globular [γ4E]GID is optimal for binding to α4β2 nAChR and its activity could not likely be further improved through amino-acid substitutions. The binding mode of ribbon GID with the (α4)3(β2)2 nAChR was deduced using the information from the cryo-electron structure of (α4)3(β2)2 nAChR and the binding mode of ribbon AuIB. The program FoldX predicted the mutational energies of ribbon [γ4E]GID at the α4(+)α4(−) interface, and several ribbon[γ4E]GID mutants were suggested to have desirable properties to inhibit (α4)3(β2)2 nAChR.

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Lin, Yue-Xian, Shu-Han Li, and Wei-Chen Huang. "Fabrication of Soft Tissue Scaffold-Mimicked Microelectrode Arrays Using Enzyme-Mediated Transfer Printing." Micromachines 12, no. 9 (2021): 1057. http://dx.doi.org/10.3390/mi12091057.

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Hydrogels are the ideal materials in the development of implanted bioactive neural interfaces because of the nerve tissue-mimicked physical and biological properties that can enhance neural interfacing compatibility. However, the integration of hydrogels and rigid/dehydrated electronic microstructure is challenging due to the non-reliable interfacial bonding, whereas hydrogels are not compatible with most conditions required for the micromachined fabrication process. Herein, we propose a new enzyme-mediated transfer printing process to design an adhesive biological hydrogel neural interface. The donor substrate was fabricated via photo-crosslinking of gelatin methacryloyl (GelMA) containing various conductive nanoparticles (NPs), including Ag nanowires (NWs), Pt NWs, and PEDOT:PSS, to form a stretchable conductive bioelectrode, called NP-doped GelMA. On the other hand, a receiver substrate composed of microbial transglutaminase-incorporated gelatin (mTG-Gln) enabled simultaneous temporally controlled gelation and covalent bond-enhanced adhesion to achieve one-step transfer printing of the prefabricated NP-doped GelMA features. The integrated hydrogel microelectrode arrays (MEA) were adhesive, and mechanically/structurally bio-compliant with stable conductivity. The devices were structurally stable in moisture to support the growth of neuronal cells. Despite that the introduction of AgNW and PEDOT:PSS NPs in the hydrogels needed further study to avoid cell toxicity, the PtNW-doped GelMA exhibited a comparable live cell density. This Gln-based MEA is expected to be the next-generation bioactive neural interface.

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Ochoa, Vanessa, Annalee J. Loeffler, and Christie D. Fowler. "Emerging Role of the Cerebrospinal Fluid – Neuronal Interface in Neuropathology." Neuro - Open Journal 2, no. 2 (2015): 92–98. http://dx.doi.org/10.17140/noj-2-118.

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Barnes, Peter J. "Neuroeffector mechanisms: The interface between inflammation and neuronal responses☆☆☆★." Journal of Allergy and Clinical Immunology 98, no. 5 (1996): S73—S83. http://dx.doi.org/10.1016/s0091-6749(96)70020-9.

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Cortés-Llanos, Belén, Rossana Rauti, Ángel Ayuso-Sacido, Lucas Pérez, and Laura Ballerini. "Impact of Magnetite Nanowires on In Vitro Hippocampal Neural Networks." Biomolecules 13, no. 5 (2023): 783. http://dx.doi.org/10.3390/biom13050783.

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Nanomaterials design, synthesis, and characterization are ever-expanding approaches toward developing biodevices or neural interfaces to treat neurological diseases. The ability of nanomaterials features to tune neuronal networks’ morphology or functionality is still under study. In this work, we unveil how interfacing mammalian brain cultured neurons and iron oxide nanowires’ (NWs) orientation affect neuronal and glial densities and network activity. Iron oxide NWs were synthesized by electrodeposition, fixing the diameter to 100 nm and the length to 1 µm. Scanning electron microscopy, Raman, and contact angle measurements were performed to characterize the NWs’ morphology, chemical composition, and hydrophilicity. Hippocampal cultures were seeded on NWs devices, and after 14 days, the cell morphology was studied by immunocytochemistry and confocal microscopy. Live calcium imaging was performed to study neuronal activity. Using random nanowires (R-NWs), higher neuronal and glial cell densities were obtained compared with the control and vertical nanowires (V-NWs), while using V-NWs, more stellate glial cells were found. R-NWs produced a reduction in neuronal activity, while V-NWs increased the neuronal network activity, possibly due to a higher neuronal maturity and a lower number of GABAergic neurons, respectively. These results highlight the potential of NWs manipulations to design ad hoc regenerative interfaces.

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Deriabin, Konstantin V., Sergey O. Kirichenko, Alexander V. Lopachev, Yuriy Sysoev, Pavel E. Musienko, and Regina M. Islamova. "Ferrocenyl-containing silicone nanocomposites as materials for neuronal interfaces." Composites Part B: Engineering 236 (May 2022): 109838. http://dx.doi.org/10.1016/j.compositesb.2022.109838.

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Wolfrum, Bernhard, Yulia Mourzina, Frank Sommerhage, and Andreas Offenhäusser. "Suspended Nanoporous Membranes as Interfaces for Neuronal Biohybrid Systems." Nano Letters 6, no. 3 (2006): 453–57. http://dx.doi.org/10.1021/nl052370x.

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Coyle, Damien, Jose Principe, Fabien Lotte, and Anton Nijholt. "Guest Editorial: Brain/neuronal - Computer game interfaces and interaction." IEEE Transactions on Computational Intelligence and AI in Games 5, no. 2 (2013): 77–81. http://dx.doi.org/10.1109/tciaig.2013.2264736.

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Münzberg, Heike, Elizabeth Floyd, and Ji Suk Chang. "Sympathetic Innervation of White Adipose Tissue: to Beige or Not to Beige?" Physiology 36, no. 4 (2021): 246–55. http://dx.doi.org/10.1152/physiol.00038.2020.

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Obesity research progresses in understanding neuronal circuits and adipocyte biology to regulate metabolism. However, the interface of neuro-adipocyte interaction is less studied. We summarize the current knowledge of adipose tissue innervation and interaction with adipocytes and emphasize adipocyte transitions from white to brown adipocytes and vice versa. We further highlight emerging concepts for the differential neuronal regulation of brown/beige versus white adipocyte and the interdependence of both for metabolic regulation.

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Vomero, Maria, Elisa Castagnola, Emma Maggiolini, et al. "A Direct Comparison of Glassy Carbon and PEDOT-PSS Electrodes for High Charge Injection and Low Impedance Neural Interfaces." Advances in Science and Technology 102 (October 2016): 68–76. http://dx.doi.org/10.4028/www.scientific.net/ast.102.68.

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For neural applications, materials able to interface with the brain without harming it while recording high-fidelity signals over long-term implants are still sought after. Glassy Carbon (GC) and Poly (3,4-ethylenedioxythiophene)-poly (styrenesulfonate) (PEDOT-PSS) have proved to be promising materials for neural interfaces as they show – compared to conventional metal electrodes - higher conductivity, better electrochemical stability, very good mechanical properties and therefore seem to be very promising for in vivo applications. We present here, for the first time, a direct comparison between GC and PEDOT-PSS microelectrodes in terms of biocompatibility, electrical and electrochemical properties as well as in vivo recording capabilities, using electrocorticography microelectrode arrays located on flexible polyimide substrate. The GC microelectrodes were fabricated using a traditional negative lithography processes followed by pyrolysis. PEDOT-PSS was selectively electrodeposited on the desired electrodes. Electrochemical performance of the two materials was evaluated through electrochemical impedance spectroscopy and cyclic voltammetry. Biocompatibility was assessed through in-vitro studies evaluating cultured cells viability. The in vivo performance of the GC and PEDOT-PSS electrodes was directly compared by simultaneously recording neuronal activity during somatosensory stimulation in Long-Evans rats. We found that both GC and PEDOT-PSS electrodes outperform metals in terms of electrochemical performance and allow to obtain excellent recordings of somatosensory evoked potentials from the rat brain surface. Furthermore, we found that both GC and PEDOT-PSS substrates are highly biocompatible, confirming that they are safe for neural interface applications.

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Weigel, Tobias, Julian Brennecke, and Jan Hansmann. "Improvement of the Electronic—Neuronal Interface by Natural Deposition of ECM." Materials 14, no. 6 (2021): 1378. http://dx.doi.org/10.3390/ma14061378.

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The foreign body reaction to neuronal electrode implants limits potential applications as well as the therapeutic period. Developments in the basic electrode design might improve the tissue compatibility and thereby reduce the foreign body reaction. In this work, the approach of embedding 3D carbon nanofiber electrodes in extracellular matrix (ECM) synthesized by human fibroblasts for a compatible connection to neuronal cells was investigated. Porous electrode material was manufactured by solution coelectrospinning of polyacrylonitrile and polyamide as a fibrous porogen. Moreover, NaCl represented an additional particulate porogen. To achieve the required conductivity for an electrical interface, meshes were carbonized. Through the application of two different porogens, the electrodes’ flexibility and porosity was improved. Human dermal fibroblasts were cultured on the electrode surface for ECM generation and removed afterwards. Scanning electron microscopy imaging revealed a nano fibrous ECM network covering the carbon fibers. The collagen amount of the ECM coating was quantified by hydroxyproline-assays. The modification with the natural protein coating on the electrode functionality resulted in a minor increase of the electrical capacity, which slightly improved the already outstanding electrical interface properties. Increased cell numbers of SH-SY5Y cell line on ECM-modified electrodes demonstrated an improved cell adhesion. During cell differentiation, the natural ECM enhanced the formation of neurites regarding length and branching. The conducted experiments indicated the prevention of direct cell-electrode contacts by the modification, which might help to shield temporary the electrode from immunological cells to reduce the foreign body reaction and improve the electrodes’ tissue integration.

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Abdullaeva, Oliya S., Matthias Schulz, Frank Balzer, et al. "Photoelectrical Stimulation of Neuronal Cells by an Organic Semiconductor–Electrolyte Interface." Langmuir 32, no. 33 (2016): 8533–42. http://dx.doi.org/10.1021/acs.langmuir.6b02085.

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Vermaas, M., M. C. Piastra, T. F. Oostendorp, N. F. Ramsey, and P. H. E. Tiesinga. "FEMfuns: A Volume Conduction Modeling Pipeline that Includes Resistive, Capacitive or Dispersive Tissue and Electrodes." Neuroinformatics 18, no. 4 (2020): 569–80. http://dx.doi.org/10.1007/s12021-020-09458-8.

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Abstract Applications such as brain computer interfaces require recordings of relevant neuronal population activity with high precision, for example, with electrocorticography (ECoG) grids. In order to achieve this, both the placement of the electrode grid on the cortex and the electrode properties, such as the electrode size and material, need to be optimized. For this purpose, it is essential to have a reliable tool that is able to simulate the extracellular potential, i.e., to solve the so-called ECoG forward problem, and to incorporate the properties of the electrodes explicitly in the model. In this study, this need is addressed by introducing the first open-source pipeline, FEMfuns (finite element method for useful neuroscience simulations), that allows neuroscientists to solve the forward problem in a variety of different geometrical domains, including different types of source models and electrode properties, such as resistive and capacitive materials. FEMfuns is based on the finite element method (FEM) implemented in FEniCS and includes the geometry tessellation, several electrode-electrolyte implementations and adaptive refinement options. The code of the pipeline is available under the GNU General Public License version 3 at https://github.com/meronvermaas/FEMfuns. We tested our pipeline with several geometries and source configurations such as a dipolar source in a multi-layer sphere model and a five-compartment realistically-shaped head model. Furthermore, we describe the main scripts in the pipeline, illustrating its flexible and versatile use. Provided with a sufficiently fine tessellation, the numerical solution of the forward problem approximates the analytical solution. Furthermore, we show dispersive material and interface effects in line with previous literature. Our results indicate substantial capacitive and dispersive effects due to the electrode-electrolyte interface when using stimulating electrodes. The results demonstrate that the pipeline presented in this paper is an accurate and flexible tool to simulate signals generated on electrode grids by the spatiotemporal electrical activity patterns produced by sources and thereby allows the user to optimize grids for brain computer interfaces including exploration of alternative electrode materials/properties.

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Sarmiento-Ramos, José Luis. "Aplicaciones de las redes neuronales y el deep learning a la ingeniería biomédica." Revista UIS Ingenierías 19, no. 4 (2020): 1–18. http://dx.doi.org/10.18273/revuin.v19n4-2020001.

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Hoy en día, las redes neuronales artificiales y el deep learning, son dos de las herramientas más poderosas del aprendizaje de máquina, que tienen por objetivo desarrollar sistemas que aprenden automáticamente, reconocen patrones, predicen comportamientos y generalizan información a partir de conjuntos de datos. Estasdos herramientas se han convertido en un potencial campo de investigación con aplicaciones a la ingeniería, no siendo la ingeniería biomédica la excepción. En este artículo se presenta una revisión actualizada de las principales aplicaciones de las redes neuronales y el deep learning a la ingeniería biomédica en las ramas de la ómica, la imagenología, las interfaces cerebro-máquina y hombre-máquina, y la gestión y administración de la salud pública; ramas que se extienden desde el estudio de procesos a nivel molecular, hasta procesos que involucran grandes poblaciones.Palabras clave:aprendizaje de máquina; inteligencia artificial; reconocimiento de patrones; ómica; bioinformática; biomedicina; imagenología; interfaces cerebro-máquina; interfaces hombre-máquina;salud pública.

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Gáspár, Szilveszter, Tiziana Ravasenga, Raluca-Elena Munteanu, Sorin David, Fabio Benfenati, and Elisabetta Colombo. "Electrochemically Synthesized Poly(3-hexylthiophene) Nanowires as Photosensitive Neuronal Interfaces." Materials 14, no. 16 (2021): 4761. http://dx.doi.org/10.3390/ma14164761.

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Poly(3-hexylthiophene) (P3HT) is a hole-conducting polymer that has been intensively used to develop organic optoelectronic devices (e.g., organic solar cells). Recently, P3HT films and nanoparticles have also been used to restore the photosensitivity of retinal neurons. The template-assisted electrochemical synthesis of polymer nanowires advantageously combines polymerization and polymer nanostructuring into one, relatively simple, procedure. However, obtaining P3HT nanowires through this procedure was rarely investigated. Therefore, this study aimed to investigate the template-assisted electrochemical synthesis of P3HT nanowires doped with tetrabutylammonium hexafluorophosphate (TBAHFP) and their biocompatibility with primary neurons. We show that template-assisted electrochemical synthesis can relatively easily turn 3-hexylthiophene (3HT) into longer (e.g., 17 ± 3 µm) or shorter (e.g., 1.5 ± 0.4 µm) P3HT nanowires with an average diameter of 196 ± 55 nm (determined by the used template). The nanowires produce measurable photocurrents following illumination. Finally, we show that primary cortical neurons can be grown onto P3HT nanowires drop-casted on a glass substrate without relevant changes in their viability and electrophysiological properties, indicating that P3HT nanowires obtained by template-assisted electrochemical synthesis represent a promising neuronal interface for photostimulation.

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Mesiti, Fabio, and Ilangko Balasingham. "Nanomachine-to-Neuron Communication Interfaces for Neuronal Stimulation at Nanoscale." IEEE Journal on Selected Areas in Communications 31, no. 12 (2013): 695–704. http://dx.doi.org/10.1109/jsac.2013.sup2.1213002.

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Kudoh, Suguru N., Chie Hosokawa, Ai Kiyohara, Takahisa Taguchi, and Isao Hayashi. "Biomodeling System - Interaction Between Living Neuronal Networks and the Outer World." Journal of Robotics and Mechatronics 19, no. 5 (2007): 592–600. http://dx.doi.org/10.20965/jrm.2007.p0592.

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Rat hippocampal neurons reorganized into complex networks in a culture dish with 64 planar microelectrodes and the electrical activity of neurons were recorded from individual sites. Multi-site recording system for extracellular action potentials was used for recording the activity of living neuronal networks and for applying input from the outer world to the network. The living neuronal network was able to distinguish among patterns of evoked action potentials based on different input, suggesting that the living neuronal network can express several pattern independently, meaning that it has fundamental mechanisms for intelligent information processing. We are developing a “biomodeling system,” in which a living neuronal network is connected to a moving robot with premised control rules corresponding to a genetically provided interface of neuronal networks to peripheral systems. Premised rules are described in fuzzy logic and the robot can generate instinctive behavior, avoiding collision. Sensor input from the robot body was sent to a neuronal network, and the robot moved based on commands from the living neuronal network. This is a good modeling system to analyze interaction between biological information processing and electrical devices.

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Eggers, M. D. "Electronically wired petri dish: A microfabricated interface to the biological neuronal network." Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 8, no. 6 (1990): 1392. http://dx.doi.org/10.1116/1.585084.

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Liopo, Anton V., Michael P. Stewart, Jared Hudson, James M. Tour, and Todd C. Pappas. "Biocompatibility of Native and Functionalized Single-Walled Carbon Nanotubes for Neuronal Interface." Journal of Nanoscience and Nanotechnology 6, no. 5 (2006): 1365–74. http://dx.doi.org/10.1166/jnn.2006.155.

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Wang, Sheng, Stephanie Szobota, Yuan Wang, et al. "All Optical Interface for Parallel, Remote, and Spatiotemporal Control of Neuronal Activity." Nano Letters 7, no. 12 (2007): 3859–63. http://dx.doi.org/10.1021/nl072783t.

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DiCaprio, R. A., and C. Schmidtmann. "A Multichannel Counter/Timer Interface for the Acquisition of Neuronal Spike Trains." IEEE Transactions on Biomedical Engineering BME-32, no. 5 (1985): 345–47. http://dx.doi.org/10.1109/tbme.1985.325553.

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Reul, J. M. H. M. "S.05.02 Neuronal signaling and epigenetic mechanisms at the cognition-emotion interface." European Neuropsychopharmacology 20 (August 2010): S168—S169. http://dx.doi.org/10.1016/s0924-977x(10)70138-3.

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Islam, Asiful, and Latika Menon. "Interactions between E18 Rat Hippocampal Neurons and Au-Nanowire Arrays." Advanced Materials Research 383-390 (November 2011): 3863–68. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.3863.

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The anodization of aluminum templates created nanoporous alumina tubes arranged parallel to each other and electrodeposition using gold solution (AuHCl4) resulted in arrays of gold nanowires (GNWs) inside the pores. For investigation of Au-nano-neuronal interactions, we have cultured embryonic day 18 rat hippocampal neurons on the surface of nanowires. For preliminary understanding of the neuronal growth and connectivity, we studied the images of nano-neuronal interactions by using optical, fluorescence and scanning electron microscopy (SEM). For adhesion of neurons to nanoarrays surfaces, we used bioconjugating protein coating Poly-D-Lysine (PDL). The embryonic hippocampal tissues were dissociated mechanically and cultured on Au-nano templates. We demonstrated well-defined neuronal networks on Au-nanowire (GNW) arrays and on standard glass coverslips. The neurons attached with the nanowires surfaces by an interface of PDL, which is a positively charged poly-peptide and plays a vital role in neurites growth on the nanowire arrays. The pre- and post-synaptic affects of neuronal interactions on the surfaces of nanowires were measured by Ca+ imaging in Keck microscope.

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Alghazali, Karrer M., Rabab N. Hamzah, Zeid A. Nima, et al. "Plasmonic Nanofactors as Switchable Devices to Promote or Inhibit Neuronal Activity and Function." Nanomaterials 9, no. 7 (2019): 1029. http://dx.doi.org/10.3390/nano9071029.

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Gold nanosystems have been investigated extensively for a variety of applications, from specific cancer cell targeting to tissue regeneration. Specifically, a recent and exciting focus has been the gold nanosystems’ interface with neuronal biology. Researchers are investigating the ability to use these systems neuronal applications ranging from the enhancement of stem cell differentiation and therapy to stimulation or inhibition of neuronal activity. Most of these new areas of research are based on the integration of the plasmonic properties of such nanosystems into complex synthetic extracellular matrices (ECM) that can interact and affect positively the activity of neuronal cells. Therefore, the ability to integrate the plasmonic properties of these nanoparticles into multidimensional and morphological structures to support cellular proliferation and activity is potentially of great interest, particularly to address medical conditions that are currently not fully treatable. This review discusses some of the promising developments and unique capabilities offered by the integration of plasmonic nanosystems into morphologically complex ECM devices, designed to control and study the activity of neuronal cells.

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Zheng, Ke. "Neuromodulation Based on Brain-computer Interface Technology." Highlights in Science, Engineering and Technology 36 (March 21, 2023): 460–67. http://dx.doi.org/10.54097/hset.v36i.5716.

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Therapeutic brain-computer interface (BCI) is a fast-developing area with considerable potential in improving the life qualities of various patients. Although a complete mechanistic understanding is yet achieved, empirical explorations into neuromodulatory devices, including deep brain stimulation (DBS), transcranial magnetic and electrical stimulation (TMS, TES), and electroencephalography (EEG), have enriched the repertoire for treating many neurologic diseases. Four such diseases discussed are Parkinson's disease (PD), substance use disorder (SUD), epilepsy, and depression. BCI devices alleviate symptoms by modulating neuronal activities, for instance, via directly delivering electrical stimulation, but each disease poses challenges now. Currently, neuromodulation techniques for PD and epilepsy are relatively mature and require few more perfections, while the ones concerning SUD and depression are young and fledgling, but multiple studies have revealed preliminary success and therapeutic potential. This article aims to review four techniques’ applications in four common neurologic disorders, including current achievements, associated difficulties, and potential future directions.

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Welle, Theresa M., Kristen Alanis, Michelle L. Colombo, Jonathan V. Sweedler, and Mei Shen. "A high spatiotemporal study of somatic exocytosis with scanning electrochemical microscopy and nanoITIES electrodes." Chemical Science 9, no. 22 (2018): 4937–41. http://dx.doi.org/10.1039/c8sc01131a.

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Extra-synaptic exocytosis is an essential component of cellular communication. A knowledge gap exists in the exocytosis of the non-redox active transmitter acetylcholine. Using the nano-interface between two immiscible electrolyte solutions and scanning electrochemical microscopy, a high resolution spatiotemporal study of acetylcholine exocytosis is shown from individual neuronal soma.

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Lebedev, M. A. "BRAIN-COMPUTER INTERFACE FOR THE AUGMENTATION OF BRAIN FUNCTIONS." Science and Innovations in Medicine 1, no. 3 (2016): 11–27. http://dx.doi.org/10.35693/2500-1388-2016-0-3-11-27.

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Brain-computer interface (BCI) connects the nervous system departments with external devices for the purpose of recovery of motor and sensory functions of patients with neurological lesions. Over the past half-century BCI have gone from initial ideas to the high-tech modern incarnations. This development contributed significantly to the invasive techniques of multichannel registration activity of neuronal ensembles. Modern BCI are able to manage mechanical prosthetic arms and legs. Furthermore, BCI can provide sensory feedback, allowing the user to feel the movement of the prosthesis and its interaction with external objects. Latest BCI connect multiple users to the brain network. In this review, these achievements are dealt with a focus on invasive BCI.

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Li, Zheng, Joseph E. O'Doherty, Mikhail A. Lebedev, and Miguel A. L. Nicolelis. "Adaptive Decoding for Brain-Machine Interfaces Through Bayesian Parameter Updates." Neural Computation 23, no. 12 (2011): 3162–204. http://dx.doi.org/10.1162/neco_a_00207.

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Brain-machine interfaces (BMIs) transform the activity of neurons recorded in motor areas of the brain into movements of external actuators. Representation of movements by neuronal populations varies over time, during both voluntary limb movements and movements controlled through BMIs, due to motor learning, neuronal plasticity, and instability in recordings. To ensure accurate BMI performance over long time spans, BMI decoders must adapt to these changes. We propose the Bayesian regression self-training method for updating the parameters of an unscented Kalman filter decoder. This novel paradigm uses the decoder's output to periodically update its neuronal tuning model in a Bayesian linear regression. We use two previously known statistical formulations of Bayesian linear regression: a joint formulation, which allows fast and exact inference, and a factorized formulation, which allows the addition and temporary omission of neurons from updates but requires approximate variational inference. To evaluate these methods, we performed offline reconstructions and closed-loop experiments with rhesus monkeys implanted cortically with microwire electrodes. Offline reconstructions used data recorded in areas M1, S1, PMd, SMA, and PP of three monkeys while they controlled a cursor using a handheld joystick. The Bayesian regression self-training updates significantly improved the accuracy of offline reconstructions compared to the same decoder without updates. We performed 11 sessions of real-time, closed-loop experiments with a monkey implanted in areas M1 and S1. These sessions spanned 29 days. The monkey controlled the cursor using the decoder with and without updates. The updates maintained control accuracy and did not require information about monkey hand movements, assumptions about desired movements, or knowledge of the intended movement goals as training signals. These results indicate that Bayesian regression self-training can maintain BMI control accuracy over long periods, making clinical neuroprosthetics more viable.

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