Graphene neuroscience literature

Lin, H. Y., Nurunnabi, M., Chen, W. H., & Huang, C. H.. (2019). Graphene in neuroscience. In Biomedical Applications of Graphene and 2D Nanomaterials

Plain numerical DOI: 10.1016/B978-0-12-815889-0.00016-7
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Perini, G., Palmieri, V., Ciasca, G., De Spirito, M., & Papi, M.. (2020). Unravelling the potential of graphene quantum dots in biomedicine and neuroscience. International Journal of Molecular Sciences

Plain numerical DOI: 10.3390/ijms21103712
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Orecchioni, M., Bordoni, V., Fuoco, C., Reina, G., Lin, H., Zoccheddu, M., … Delogu, L. G.. (2020). Toward High-Dimensional Single-Cell Analysis of Graphene Oxide Biological Impact: Tracking on Immune Cells by Single-Cell Mass Cytometry. Small

Plain numerical DOI: 10.1002/smll.202000123
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Song, Q., Jiang, Z., Li, N., Liu, P., Liu, L., Tang, M., & Cheng, G.. (2014). Anti-inflammatory effects of three-dimensional graphene foams cultured with microglial cells. Biomaterials

Plain numerical DOI: 10.1016/j.biomaterials.2014.05.002
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Kitko, K. E., & Zhang, Q.. (2019). Graphene-based nanomaterials: From production to integration with modern tools in neuroscience. Frontiers in Systems Neuroscience

Plain numerical DOI: 10.3389/fnsys.2019.00026
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Garcia-Cortadella, R., Schwesig, G., Jeschke, C., Illa, X., Gray, A. L., Savage, S., … Garrido, J. A.. (2021). Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. Nature Communications

Plain numerical DOI: 10.1038/s41467-020-20546-w
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Cherian, R. S., Sandeman, S., Ray, S., Savina, I. N., Ashtami, J., & Mohanan, P. V.. (2019). Green synthesis of Pluronic stabilized reduced graphene oxide: Chemical and biological characterization. Colloids and Surfaces B: Biointerfaces

Plain numerical DOI: 10.1016/j.colsurfb.2019.03.043
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Bramini, M., Alberini, G., Colombo, E., Chiacchiaretta, M., DiFrancesco, M. L., Maya-Vetencourt, J. F., … Cesca, F.. (2018). Interfacing graphene-based materials with neural cells. Frontiers in Systems Neuroscience

Plain numerical DOI: 10.3389/fnsys.2018.00012
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Capasso, A., Rodrigues, J., Moschetta, M., Buonocore, F., Faggio, G., Messina, G., … Lisi, N.. (2021). Interactions between Primary Neurons and Graphene Films with Different Structure and Electrical Conductivity. Advanced Functional Materials

Plain numerical DOI: 10.1002/adfm.202005300
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Rauti, R., Secomandi, N., Martín, C., Bosi, S., Severino, F. P. U., Scaini, D., … Ballerini, L.. (2020). Tuning Neuronal Circuit Formation in 3D Polymeric Scaffolds by Introducing Graphene at the Bio/Material Interface. Advanced Biosystems

Plain numerical DOI: 10.1002/adbi.201900233
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Thunemann, M., Lu, Y., Liu, X., Klllç, K., Desjardins, M., Vandenberghe, M., … Kuzum, D.. (2018). Deep 2-photon imaging and artifact-free optogenetics through transparent graphene microelectrode arrays. Nature Communications

Plain numerical DOI: 10.1038/s41467-018-04457-5
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Garcia-Cortadella, R., Schäfer, N., Cisneros-Fernandez, J., Ré, L., Illa, X., Schwesig, G., … Guimerà-Brunet, A.. (2020). Switchless multiplexing of graphene active sensor arrays for brain mapping. Nano Letters

Plain numerical DOI: 10.1021/acs.nanolett.0c00467
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Liu, X., Lu, Y., Iseri, E., Shi, Y., & Kuzum, D.. (2018). A compact closed-loop optogenetics system based on artifact-free transparent graphene electrodes. Frontiers in Neuroscience

Plain numerical DOI: 10.3389/fnins.2018.00132
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Lu, Y., Lyu, H., Richardson, A. G., Lucas, T. H., & Kuzum, D.. (2016). Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing. Scientific Reports

Plain numerical DOI: 10.1038/srep33526
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Chen, J., Yu, Q., Fu, W., Chen, X., Zhang, Q., Dong, S., … Zhang, S.. (2020). A highly sensitive amperometric glutamate oxidase microbiosensor based on a reduced graphene oxide/prussian blue nanocube/gold nanoparticle composite film-modified pt electrode. Sensors (Switzerland)

Plain numerical DOI: 10.3390/s20102924
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Park, D. W., Ness, J. P., Brodnick, S. K., Esquibel, C., Novello, J., Atry, F., … Ma, Z.. (2018). Electrical Neural Stimulation and Simultaneous in Vivo Monitoring with Transparent Graphene Electrode Arrays Implanted in GCaMP6f Mice. ACS Nano

Plain numerical DOI: 10.1021/acsnano.7b04321
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John, A. A., Subramanian, A. P., Vellayappan, M. V., Balaji, A., Mohandas, H., & Jaganathan, S. K.. (2015). Carbon nanotubes and graphene as emerging candidates in neuroregeneration and neurodrug delivery. International Journal of Nanomedicine

Plain numerical DOI: 10.2147/IJN.S83777
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Rauti, R., Musto, M., Bosi, S., Prato, M., & Ballerini, L.. (2019). Properties and behavior of carbon nanomaterials when interfacing neuronal cells: How far have we come?. Carbon

Plain numerical DOI: 10.1016/j.carbon.2018.11.026
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Zheng, Z., Huang, L., Yan, L., Yuan, F., Wang, L., Wang, K., … Liu, Y.. (2019). Polyaniline functionalized graphene nanoelectrodes for the regeneration of PC12 cells via electrical stimulation. International Journal of Molecular Sciences

Plain numerical DOI: 10.3390/ijms20082013
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Guan, S., Wang, J., & Fang, Y.. (2019). Transparent graphene bioelectronics as a new tool for multimodal neural interfaces. Nano Today

Plain numerical DOI: 10.1016/j.nantod.2019.01.003
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Lu, Y., Liu, X., & Kuzum, D.. (2018). Graphene-based neurotechnologies for advanced neural interfaces. Current Opinion in Biomedical Engineering

Plain numerical DOI: 10.1016/j.cobme.2018.06.001
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Fischer, R. A., Zhang, Y., Risner, M. L., Li, D., Xu, Y., & Sappington, R. M.. (2018). Impact of Graphene on the Efficacy of Neuron Culture Substrates. Advanced Healthcare Materials

Plain numerical DOI: 10.1002/adhm.201701290
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Wang, R., Shi, M., Brewer, B., Yang, L., Zhang, Y., Webb, D. J., … Xu, Y. Q.. (2018). Ultrasensitive Graphene Optoelectronic Probes for Recording Electrical Activities of Individual Synapses. Nano Letters

Plain numerical DOI: 10.1021/acs.nanolett.8b02298
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Bourrier, A., Shkorbatova, P., Bonizzato, M., Rey, E., Barraud, Q., Courtine, G., … Delacour, C.. (2019). Monolayer Graphene Coating of Intracortical Probes for Long-Lasting Neural Activity Monitoring. Advanced Healthcare Materials

Plain numerical DOI: 10.1002/adhm.201801331
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Moschetta, M., Lee, J. Y., Rodrigues, J., Podestà, A., Varvicchio, O., Son, J., … Capasso, A.. (2021). Hydrogenated Graphene Improves Neuronal Network Maturation and Excitatory Transmission. Advanced Biology

Plain numerical DOI: 10.1002/adbi.202000177
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Liu, X., Lu, Y., & Kuzum, D.. (2018). High-Density Porous Graphene Arrays Enable Detection and Analysis of Propagating Cortical Waves and Spirals. Scientific Reports

Plain numerical DOI: 10.1038/s41598-018-35613-y
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Ye, S., Yang, P., Cheng, K., Zhou, T., Wang, Y., Hou, Z., … Ren, L.. (2016). Drp1-Dependent Mitochondrial Fission Mediates Toxicity of Positively Charged Graphene in Microglia. ACS Biomaterials Science and Engineering

Plain numerical DOI: 10.1021/acsbiomaterials.5b00465
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Balch, H. B., McGuire, A. F., Horng, J., Tsai, H. Z., Qi, K. K., Duh, Y. S., … Wang, F.. (2021). Graphene Electric Field Sensor Enables Single Shot Label-Free Imaging of Bioelectric Potentials. Nano Letters

Plain numerical DOI: 10.1021/acs.nanolett.1c00543
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Shokoueinejad, M., Park, D. W., Jung, Y. H., Brodnick, S. K., Novello, J., Dingle, A., … Williams, J.. (2019). Progress in the field of micro-electrocorticography. Micromachines

Plain numerical DOI: 10.3390/mi10010062
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Monaco, A. M., & Giugliano, M.. (2014). Carbon-based smart nanomaterials in biomedicine and neuroengineering. Beilstein Journal of Nanotechnology

Plain numerical DOI: 10.3762/bjnano.5.196
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Zhao, S., Liu, X., Xu, Z., Ren, H., Deng, B., Tang, M., … Duan, X.. (2016). Graphene Encapsulated Copper Microwires as Highly MRI Compatible Neural Electrodes. Nano Letters

Plain numerical DOI: 10.1021/acs.nanolett.6b03829
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Li, G., Yang, J., Yang, W., Wang, F., Wang, Y., Wang, W., & Liu, L.. (2018). Label-free multidimensional information acquisition from optogenetically engineered cells using a graphene transistor. Nanoscale

Plain numerical DOI: 10.1039/c7nr07264c
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Liu, S., Zhao, Y., Hao, W., Zhang, X. D., & Ming, D.. (2020). Micro- and nanotechnology for neural electrode-tissue interfaces. Biosensors and Bioelectronics

Plain numerical DOI: 10.1016/j.bios.2020.112645
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Wu, T., Li, Y., Liang, X., Liu, X., & Tang, M.. (2021). Identification of potential circRNA-miRNA-mRNA regulatory networks in response to graphene quantum dots in microglia by microarray analysis. Ecotoxicology and Environmental Safety

Plain numerical DOI: 10.1016/j.ecoenv.2020.111672
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Guo, C. X., Ng, S. R., Khoo, S. Y., Zheng, X., Chen, P., & Li, C. M.. (2012). RGD-peptide functionalized graphene biomimetic live-cell sensor for real-time detection of nitric oxide molecules. ACS Nano

Plain numerical DOI: 10.1021/nn301974u
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Liu, & Speranza. (2019). Functionalization of Carbon Nanomaterials for Biomedical Applications. C — Journal of Carbon Research

Plain numerical DOI: 10.3390/c5040072
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Crowe, M., Lai, Y., Wang, Y., Lu, J., Zhao, M., Tian, Z., … Diao, J.. (2017). A Proteoliposome Method for Assessing Nanotoxicity on Synaptic Fusion and Membrane Integrity. Small Methods

Plain numerical DOI: 10.1002/smtd.201700207
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Liu, Y., & Duan, X.. (2020). Carbon-based nanomaterials for neural electrode technology. Wuli Huaxue Xuebao/ Acta Physico – Chimica Sinica

Plain numerical DOI: 10.3866/PKU.WHXB202007066
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Bramini, M., Rocchi, A., Benfenati, F., & Cesca, F.. (2019). Neuronal Cultures and Nanomaterials. In Advances in Neurobiology

Plain numerical DOI: 10.1007/978-3-030-11135-9_3
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Govindhan, M., Liu, Z., & Chen, A.. (2016). Design and electrochemical study of platinum-based nanomaterials for sensitive detection of nitric oxide in biomedical applications. Nanomaterials

Plain numerical DOI: 10.3390/nano6110211
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Kostarelos, K., Vincent, M., Hebert, C., & Garrido, J. A.. (2017). Graphene in the Design and Engineering of Next-Generation Neural Interfaces. Advanced Materials

Plain numerical DOI: 10.1002/adma.201700909
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Pampaloni, N. P., Giugliano, M., Scaini, D., Ballerini, L., & Rauti, R.. (2019). Advances in nano neuroscience: From nanomaterials to nanotools. Frontiers in Neuroscience

Plain numerical DOI: 10.3389/fnins.2018.00953
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Liu, X., Ren, C., Lu, Y., Hattori, R., Shi, Y., Zhao, R., … Kuzum, D.. (2019). Decoding ECoG High Gamma Power from Cellular Calcium Response using Transparent Graphene Microelectrodes. In International IEEE/EMBS Conference on Neural Engineering, NER

Plain numerical DOI: 10.1109/NER.2019.8717147
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Lee, J. H., Shin, Y. C., Jin, O. S., Han, D. W., Kang, S. H., Hong, S. W., & Kim, J. M.. (2012). Enhanced neurite outgrowth of PC-12 cells on graphene-monolayer-coated substrates as biomimetic cues. Journal of the Korean Physical Society

Plain numerical DOI: 10.3938/jkps.61.1696
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Gutruf, P., Good, C. H., & Rogers, J. A.. (2018). Perspective: Implantable optical systems for neuroscience research in behaving animal models—Current approaches and future directions. APL Photonics

Plain numerical DOI: 10.1063/1.5040256
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Geracitano, L. A., Fagan, S. B., & Monserrat, J. M.. (2021). Analysis of global and Latin-American trends in nanotoxicology with a focus on carbon nanomaterials: a scientometric approach. Journal of Chemical Technology and Biotechnology

Plain numerical DOI: 10.1002/jctb.6729
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Abbasi, R.. (2018). Interpretable Machine Learning with Applications in Neuroscience. UC Berkeley Electronic Theses and Dissertations
Wang, L., Jiang, T., Song, Y., Shi, W., & Cai, X.. (2014). Dopamine detection using a patch-clamp system on a planar microeletrode array electrodeposited by polypyrrole/graphene nanocomposites. Science China Technological Sciences

Plain numerical DOI: 10.1007/s11431-014-5465-9
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Golparvar, A. J., & Yapici, M. K.. (2018). Graphene-coated wearable textiles for EOG-based human-computer interaction. In 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2018

Plain numerical DOI: 10.1109/BSN.2018.8329690
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Govindhan, M., & Chen, A.. (2016). Enhanced electrochemical sensing of nitric oxide using a nanocomposite consisting of platinum-tungsten nanoparticles, reduced graphene oxide and an ionic liquid. Microchimica Acta

Plain numerical DOI: 10.1007/s00604-016-1936-y
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Monaco, A. M., & Giugliano, M.. (2015). Correction to Carbon-based smart nanomaterials in biomedicine and neuroengineering [Beilstein J. Nanotechnol. 5, (2014) 1849-1863] doi:10.3762/bjnano.5.196. Beilstein Journal of Nanotechnology

Plain numerical DOI: 10.3762/bjnano.6.51
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Vázquez-Guardado, A., Yang, Y., Bandodkar, A. J., & Rogers, J. A.. (2021). Author Correction: Recent advances in neurotechnologies with broad potential for neuroscience research (Nature Neuroscience, (2020), 23, 12, (1522-1536), 10.1038/s41593-020-00739-8). Nature Neuroscience

Plain numerical DOI: 10.1038/s41593-021-00813-9
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Nasri, B., Wu, T., Alharbi, A., Gupta, M., Ranjitkumar, R., Sebastian, S., … Shahrjerdi, D.. (2017). Heterogeneous integrated CMOS-graphene sensor array for dopamine detection. In Digest of Technical Papers – IEEE International Solid-State Circuits Conference

Plain numerical DOI: 10.1109/ISSCC.2017.7870364
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Tasnim, N.. (2018). An Integrated Study Towards Curing Neurodegenerative Disorders Using Materials Science and Stem Cell-based Tissue Engineering Approaches. ProQuest Dissertations and Theses
Rastogi, S. K., & Cohen-Karni, T.. (2019). Nanoelectronics for neuroscience. In Encyclopedia of Biomedical Engineering

Plain numerical DOI: 10.1016/B978-0-12-801238-3.99893-3
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Salazar, P., Martín, M., Ford, R., O’Neill, R. D., & González-Mora, J. L.. (2018). Neurotransmitter microsensors for neuroscience. In Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry

Plain numerical DOI: 10.1016/B978-0-12-409547-2.13917-4
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CHAPTER 4. Nanosensing the Brain. (2013)

Plain numerical DOI: 10.1039/9781849735414-00130
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Liu, X., Lu, Y., & Kuzum, D.. (2018). Investigation of Propagating Cortical Waves and Spirals Recorded by High Density Porous Graphene Arrays. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Plain numerical DOI: 10.1109/EMBC.2018.8512428
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Du, L., Hu, L., & Wu, C.. (2016). Micro/nano neuronal network cell biosensors. In Micro/Nano Cell and Molecular Sensors

Plain numerical DOI: 10.1007/978-981-10-1658-5_6
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