Brain Recording, Mind-Reading, and Neurotechnology



Further References

Magnetic control of the nervous system (vs. Optogenetics & Chemogenetics)

Christiansen, M. G., Senko, A. W., & Anikeeva, P.. (2019). Magnetic Strategies for Nervous System Control. Annual Review of Neuroscience

Plain numerical DOI: 10.1146/annurev-neuro-070918-050241
DOI URL
directSciHub download

Wheeler, M. A., Smith, C. J., Ottolini, M., Barker, B. S., Purohit, A. M., Grippo, R. M., … Güler, A. D.. (2016). Genetically targeted magnetic control of the nervous system. Nature Neuroscience

Plain numerical DOI: 10.1038/nn.4265
DOI URL
directSciHub download

Adamczyk, A. K., & Zawadzki, P.. (2020). The Memory-Modifying Potential of Optogenetics and the Need for Neuroethics. NanoEthics

Plain numerical DOI: 10.1007/s11569-020-00377-1
DOI URL
directSciHub download

Kole, K., Zhang, Y., Jansen, E. J. R., Brouns, T., Bijlsma, A., Calcini, N., … Celikel, T.. (2020). Assessing the utility of Magneto to control neuronal excitability in the somatosensory cortex. Nature Neuroscience

Plain numerical DOI: 10.1038/s41593-019-0474-4
DOI URL
directSciHub download


Keifer, O., Kambara, K., Lau, A., Makinson, S., & Bertrand, D.. (2020). Chemogenetics a robust approach to pharmacology and gene therapy. Biochemical Pharmacology

Plain numerical DOI: 10.1016/j.bcp.2020.113889
DOI URL
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Magnus, C. J., Lee, P. H., Bonaventura, J., Zemla, R., Gomez, J. L., Ramirez, M. H., … Sternson, S. M.. (2019). Ultrapotent chemogenetics for research and potential clinical applications. Science

Plain numerical DOI: 10.1126/science.aav5282
DOI URL
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Poth, K. M., Texakalidis, P., & Boulis, N. M.. (2021). Chemogenetics: Beyond Lesions and Electrodes. Neurosurgery

Plain numerical DOI: 10.1093/neuros/nyab147
DOI URL
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Vlasov, K., Van Dort, C. J., & Solt, K.. (2018). Optogenetics and Chemogenetics. In Methods in Enzymology

Plain numerical DOI: 10.1016/bs.mie.2018.01.022
DOI URL
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Aldous Huxley (Moksha, 1977): No more thinking – Everybody’s Happy Now

meditate, woman, yoga

No more thinking – just obey and conform


Everybody’s Happy Now
No more Mammy, no more Pappy:
Ain’t we lucky, ain’t we happy?
Everybody’s oh so happy,
Everybody’s happy now!
Sex galore, but no more marriages;
No more pushing baby carriages;
No one has to change a nappy
Ain’t we lucky, ain’t we happy:
Everybody’s happy now.
Dope for tea and dope for dinner,
Fun all night, and love and laughter;
No remorse, no morning after.
Where’s the sin, and who’s the sinner?
Everybody’s happy now!
Girls pneumatic, girls exotic,
Girls ecstatic, girls erotic
Hug me, Baby; make it snappy.
Everybody’s oh so happy,
Everybody’s happy now!
Lots to eat and hours for drinking
Soma cocktails–no more thinking.
NO MORE THINKING, NO MORE THINKING!
~ Aldous Huxley


Aldous Huxley – a Fabian socialist advocating mind-control (a wolf in sheep’s clothing)



Graphene and the “Human Brain Project”

ec.europa.eu/commission/presscorner/detail/en/IP_13_54
“Graphene” will investigate and exploit the unique properties of a revolutionary carbon-based material. Graphene is an extraordinary combination of physical and chemical properties: it is the thinnest material, it conducts electricity much better than copper, it is 100-300 times stronger than steel and it has unique optical properties. The use of graphene was made possible by European scientists in 2004, and the substance is set to become the wonder material of the 21st century, as plastics were to the 20th century, including by replacing silicon in ICT products.
Graphene_and_Human_Brain_Project_win_largest_research_excellence_award_in_history__as_battle_for_sustained_science_funding_continues

Further References

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
DOI URL
directSciHub download

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
DOI URL
directSciHub download

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
DOI URL
directSciHub download

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
DOI URL
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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
DOI URL
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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
DOI URL
directSciHub download

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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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Castagnola, E., Garg, R., Rastogi, S. K., Cohen-Karni, T., & Cui, X. T.. (2020). 3D Fuzzy Graphene Microelectrode Array for Neurotransmitter Sensing at Sub-cellular Spatial Resolution. ChemRxiv
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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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
DOI URL
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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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Nano Machines for Ultimate Control of False Memories

Nano Machines for Ultimate Control of False Memories

Further References

Liu, Q., Liu, Y., Lv, J., Chen, E., & Yu, Y.. (2019). Photocontrolled Liquid Transportation in Microtubes by Manipulating Mesogen Orientations in Liquid Crystal Polymers. Advanced Intelligent Systems

Plain numerical DOI: 10.1002/aisy.201900060
DOI URL
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Tian, K., Yang, S., Niu, J., & Wang, H.. (2021). Enhanced Thermal Conductivity and Mechanical Toughness of the Epoxy Resin by Incorporation of Mesogens without Nanofillers. IEEE Access

Plain numerical DOI: 10.1109/ACCESS.2021.3058612
DOI URL
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Wang, L., Zhang, Y., Zhan, C., You, Y., Zhang, H., Ma, J., … Wei, R.. (2019). Synthesis and photoinduced anisotropy of polymers containing nunchaku-like unit with an azobenzene and a mesogen. Polymers

Plain numerical DOI: 10.3390/polym11040600
DOI URL
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Liu, C., Ding, W., Liu, Y., Zhao, H., & Cheng, X.. (2020). Self-assembled star-shaped aza-BODIPY mesogen affords white-light emission. New Journal of Chemistry

Plain numerical DOI: 10.1039/c9nj04755g
DOI URL
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Kawano, S. I., Kato, M., Soumiya, S., Nakaya, M., Onoe, J., & Tanaka, K.. (2018). Columnar Liquid Crystals from a Giant Macrocycle Mesogen. Angewandte Chemie – International Edition

Plain numerical DOI: 10.1002/anie.201709542
DOI URL
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He, R., Wen, P., Ye, Y., Oh, E., Kang, S. W., Lee, S. H., & Lee, M. H.. (2020). Bulk-mediated in-situ homogeneous photoalignment induced by reactive mesogen containing diphenylacetylene moiety. Liquid Crystals

Plain numerical DOI: 10.1080/02678292.2019.1680759
DOI URL
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Kwok, M. H., Bohannon, C. A., Crooks, J. L., Li, R., Zhao, B., & Zhu, L.. (2020). Grafting density-induced smectic A to hexagonal columnar transition in mesogen-free isotactic liquid crystalline polyethers with n-dodecylsulfonyl side groups. Giant

Plain numerical DOI: 10.1016/j.giant.2020.100003
DOI URL
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Pan, H., Xiao, A., Zhang, W., Luo, L., Shen, Z., & Fan, X.. (2019). Hierarchical nanostructures of a liquid crystalline block copolymer with a hydrogen-bonded calamitic mesogen. Polymer

Plain numerical DOI: 10.1016/j.polymer.2019.121835
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Wang, M., Bao, W. W., Chang, W. Y., Chen, X. M., Lin, B. P., Yang, H., & Chen, E. Q.. (2019). Poly[(side-on mesogen)-Alt-(end-on mesogen)]: A compromised molecular arrangement. Macromolecules

Plain numerical DOI: 10.1021/acs.macromol.9b00607
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Keerthiga, R., Kaliyappan, T., & Kannan, P.. (2019). Studies on twist bent core zinc (II) methacrylate supramolecular columnar hexagonal phase mesogen derived from azobenzene moiety and its photo luminescent behaviours. Inorganic Chemistry Communications

Plain numerical DOI: 10.1016/j.inoche.2018.11.002
DOI URL
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He, R., Oh, E., Ye, Y., Wen, P., Jeong, K. U., Lee, S. H., … Lee, M. H.. (2019). Fabrication of highly efficient coatable polarizer from tolane-based smectic reactive mesogen. Polymer

Plain numerical DOI: 10.1016/j.polymer.2019.05.032
DOI URL
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Lyu, X. L., Pan, H. B., Shen, Z. H., & Fan, X. H.. (2018). Self-assembly and Properties of Block Copolymers Containing Mesogen-Jacketed Liquid Crystalline Polymers as Rod Blocks. Chinese Journal of Polymer Science (English Edition)

Plain numerical DOI: 10.1007/s10118-018-2115-x
DOI URL
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Lee, M., Bae, J. W., Kim, A., Yun, H. S., & Song, K.. (2015). Alignments of reactive mesogen using rubbed glass substrates. Polymer (Korea)

Plain numerical DOI: 10.7317/pk.2015.39.1.174
DOI URL
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Kamarudin, M. A., Khan, A. A., Williams, C., Rughoobur, G., Said, S. M., Nosheen, S., … Wilkinson, T. D.. (2016). Self-assembled liquid crystalline nanotemplates and their incorporation in dye-sensitised solar cells. Electrochimica Acta

Plain numerical DOI: 10.1016/j.electacta.2016.11.021
DOI URL
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Yeom, Y. S., Cho, K. Y., Seo, H. Y., Lee, J. S., Im, D. H., Nam, C. Y., & Yoon, H. G.. (2020). Unprecedentedly high thermal conductivity of carbon/epoxy composites derived from parameter optimization studies. Composites Science and Technology

Plain numerical DOI: 10.1016/j.compscitech.2019.107915
DOI URL
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Palani, T., Saravanan, C., & Kannan, P.. (2011). Pendant triazole ring assisted mesogen containing side chain liquid crystalline polymethacrylates: Synthesis and characterization. Journal of Chemical Sciences

Plain numerical DOI: 10.1007/s12039-011-0061-z
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Ishinabe, T., Isa, H., Shibata, Y., & Fujikake, H.. (2021). Flexible polymer network liquid crystals using imprinted spacers bonded by UV-curable reactive mesogen for smart window applications. Journal of Information Display

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Battle For The Mind – The Mechanics of Indoctrination, Brainwashing and Thought Control – by William Sargant (1957)

ia801300.us.archive.org/27/items/BattleForTheMind-Sargant/Battle-For-The-Mind_William-Sargant.pdf

Battle-For-The-Mind_William-Sargant