EEG Community Framework

Framework References

The bibliography behind the EEG Community Framework

Every citation in the Community Framework links to its entry below. The resource catalogue in the Library offers another view on these works, alongside 311 readings, tools and recordings in total.

References

The online Community Framework Catalog offers another view on these references and an expanded list of additional resources.

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Altaheri, H., Muhammad, G., Alsulaiman, M., Amin, S. U., Altuwaijri, G. A., Abdul, W., Bencherif, M. A., & Faisal, M. (2023). Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review. Neural Computing and Applications, 35(20), 14681–14722.
Aron, A. R., Ivry, R. B., Jeffery, K. J., Poldrack, R. A., Schmidt, R., Summerfield, C., & Urai, A. E. (2020). How Can Neuroscientists Respond to the Climate Emergency? Neuron, 106(1), 17–20.
Bastos-Filho, T. (2020). Introduction to Non-Invasive EEG-Based Brain-Computer Interfaces for Assistive Technologies. CRC Press.
Becoming a Scientist: The Graphic Novel. (2024, July 31). Issuu.
Berlant, L. (2011). Cruel Optimism. Duke University Press.
Birhane, A., Dehdashtian, S., Prabhu, V., & Boddeti, V. (2024). The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models. Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 1229–1244.
Bolte, L., & van Wynsberghe, A. (2024). Sustainable AI and the third wave of AI ethics: A structural turn. AI and Ethics.
Borsboom, D., van der Maas, H. L. J., Dalege, J., Kievit, R. A., & Haig, B. D. (2021). Theory Construction Methodology: A Practical Framework for Building Theories in Psychology. Perspectives on Psychological Science, 16(4), 756–766.
Boto, E., Meyer, S. S., Shah, V., Alem, O., Knappe, S., Kruger, P., Fromhold, T. M., Lim, M., Glover, P. M., Morris, P. G., Bowtell, R., Barnes, G. R., & Brookes, M. J. (2017). A new generation of magnetoencephalography: Room temperature measurements using optically-pumped magnetometers. NeuroImage, 149, 404–414.
Burns, S. M., Barnes, L. N., McCulloh, I. A., Dagher, M. M., Falk, E. B., Storey, J. D., & Lieberman, M. D. (2019). Making social neuroscience less WEIRD: Using fNIRS to measure neural signatures of persuasive influence in a Middle East participant sample. Journal of Personality and Social Psychology, 116(3), e1–e11.
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience.
Carroll, S. R., Garba, I., Figueroa-Rodríguez, O. L., Holbrook, J., Lovett, R., Materechera, S., Parsons, M., Raseroka, K., Rodriguez-Lonebear, D., Rowe, R., Sara, R., Walker, J. D., Anderson, J., & Hudson, M. (2020). The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1).
Caspar, E. A. (2024). Guidelines for Inclusive and Diverse Human Neuroscience Research Practices. The Journal of Neuroscience, 44(48), e1971242024.
Choy, T., Baker, E., & Stavropoulos, K. (2022). Systemic Racism in EEG Research: Considerations and Potential Solutions. Affective Science, 3(1), 14–20.
Cichy, R. M., & Kaiser, D. (2019). Deep Neural Networks as Scientific Models. Trends in Cognitive Sciences, 23(4), 305–317.
Collaboration, O. S. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716.
Corneyllie, A., Walters, T., Dubarry, A. S., He, X., Hinault, T., Ković, V., Medani, T., Pascarella, A., Pinet, S., Ruzzoli, M., Schaworonkow, N., Šoškić, A., Stekić, K., Tsilimparis, K., Ulloa, J. L., Wang, R., & Chaumon, M. (2024). Doing conferences differently: Decentralising for ecological and social sustainability.
Del Giudice, M., & Gangestad, S. W. (2021). A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions. Advances in Methods and Practices in Psychological Science, 4(1), 2515245920954925.
Dotson, V. M., & Duarte, A. (2020). The importance of diversity in cognitive neuroscience. Annals of the New York Academy of Sciences, 1464(1), 181–191.
DuPre, E., & Poldrack, R. A. (2024). The future of data analysis is now: Integrating generative AI in neuroimaging methods development. Imaging Neuroscience, 2, 1–8.
Eronen, M. I., & Bringmann, L. F. (2021). The Theory Crisis in Psychology: How to Move Forward. Perspectives on Psychological Science, 16(4), 779–788.
Es, M. W. j van, Spaak, E., Schoffelen, J.-M., & Oostenveld, R. (2024). Reducing the efforts to create reproducible analysis code with FieldTrip. Journal of Open Source Software, 9(94), 5566.
Fairclough, S. H. (2017). Physiological computing and intelligent adaptation. In Emotions and affect in human factors and human-computer interaction (pp. 539–556). Elsevier Academic Press.
Farwell, L. A. (2012). Brain fingerprinting: A comprehensive tutorial review of detection of concealed information with event-related brain potentials. Cognitive Neurodynamics, 6(2), 115–154.
Forest, D. (2013). Neuroscepticisme. Ithaque.
Forest, D. (2022). Neuropromesses. Ithaque.
Frégnac, Y. (2017). Big data and the industrialization of neuroscience: A safe roadmap for understanding the brain? Science, 358(6362), 470–477.
Gerstner, W., Sprekeler, H., & Deco, G. (2012). Theory and Simulation in Neuroscience. Science, 338(6103), 60–65.
Girolamo, T., Parker, T. C., & Eigsti, I.-M. (2022). Incorporating Dis/ability Studies and Critical Race Theory to combat systematic exclusion of Black, Indigenous, and People of Color in clinical neuroscience. Frontiers in Neuroscience, 16, 988092.
Govaart, G. H., Schettino, A., Helbling, S., Mehler, D. M. A., Ngiam, W. X. Q., Moreau, D., Chiossi, F., Zanesco, A. P., Yang, Y.-F., Gau, R., Bartlett, J. E., Alanis, J. C. G., Gutsell, J., Çetinçelik, M., Pavlov, Y. G., Šoškić, A., Ehinger, B. V., Mouseli, P., Algermissen, J., … Paul, M. (2022). EEG ERP Preregistration Template. OSF.
Hari, R., & Puce, A. (2023). MEG-EEG Primer. Oxford University Press.
Henrich, J. (2020). The WEIRDest People In The World: How The West Became Psychologically Peculiar And Particularly Prosperous.
Hinrichs, H., Scholz, M., Baum, A. K., Kam, J. W. Y., Knight, R. T., & Heinze, H.-J. (2020). Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications. Scientific Reports, 10(1), 5218.
Hinrichs, N., Albarracin, M., Bolis, D., Jiang, Y., Christov-Moore, L., & Schilbach, L. (manuscript). Geometric Hyperscanning of Affect under Active Inference.
Höller, Y., Uhl, A., Bathke, A., Thomschewski, A., Butz, K., Nardone, R., Fell, J., & Trinka, E. (2017). Reliability of EEG Measures of Interaction: A Paradigm Shift Is Needed to Fight the Reproducibility Crisis. Frontiers in Human Neuroscience, 11.
Holzinger, A., Goebel, R., Fong, R., Moon, T., Müller, K.-R., & Samek, W. (2022). xxAI - Beyond Explainable Artificial Intelligence. In A. Holzinger, R. Goebel, R. Fong, T. Moon, K.-R. Müller, & W. Samek (Eds.), xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers (pp. 3–10). Springer International Publishing.
Hyman, S. E. (2011). Cognitive Enhancement: Promises and Perils. Neuron, 69(4), 595–598.
Ienca, M., & Andorno, R. (2017). Towards new human rights in the age of neuroscience and neurotechnology. Life Sciences, Society and Policy, 13(1), 5.
Ioannidis, J. P. A. (2005). Why Most Published Research Findings Are False. PLOS Medicine, 2(8), e124.
Ishaq, S. L., Parada, F. J., Wolf, P. G., Bonilla, C. Y., Carney, M. A., Benezra, A., Wissel, E., Friedman, M., DeAngelis, K. M., Robinson, J. M., Fahimipour, A. K., Manus, M. B., Grieneisen, L., Dietz, L. G., Pathak, A., Chauhan, A., Kuthyar, S., Stewart, J. D., Dasari, M. R., … Morar, N. (2021). Introducing the Microbes and Social Equity Working Group: Considering the Microbial Components of Social, Environmental, and Health Justice. mSystems, 6(4), e0047121.
Knoechel, T.-D., Schweizer, K., Acar, O. A., Akil, A. M., Al-Hoorie, A. H., Buehler, F., Elsherif, M., Giannini, A., Heyselaar, E., Hosseini, M., Ilangovan, V., Kovacs, M., Lin, Z., Liu, M., Peeters, A., Ravenzwaaij, D. van, Vranka, M. A., Yamada, Y., Yang, Y.-F., & Aczel, B. (2024). Principles for Responsible AI Usage in Research. OSF.
Koile, E., & Cristia, A. (2021) Toward Cumulative Cognitive Science: A Comparison of Meta-Analysis, Mega-Analysis, and Hybrid Approaches. Open Mind; 5 154–173.
Krol, L. R., Haselager, P., & Zander, T. O. (2020). Cognitive and affective probing: A tutorial and review of active learning for neuroadaptive technology. Journal of Neural Engineering, 17(1), 012001.
La Scala, S., Mullins, J. L., Firat, R. B., Emotional Learning Research Community Advisory Board, & Michalska, K. J. (2022). Equity, diversity, and inclusion in developmental neuroscience: Practical lessons from community-based participatory research. Frontiers in Integrative Neuroscience, 16, 1007249.
Lakens, D., Mesquida, C., Rasti, S., & Ditroilo, M. (2024). The benefits of preregistration and Registered Reports. Evidence-Based Toxicology, 2(1), 2376046.
Lange, J., Massart, C., Mouraux, A., & Standaert, F.-X. (2018). Side-channel attacks against the human brain: The PIN code case study (extended version). Brain Informatics, 5(2), 12.
Lannelongue, L., Grealey, J., & Inouye, M. (2021). Green Algorithms: Quantifying the Carbon Footprint of Computation. Advanced Science, 8(12), 2100707.
Mariette, J., Blanchard, O., Berné, O., Aumont, O., Carrey, J., Ligozat, A., Lellouch, E., Roche, P.-E., Guennebaud, G., Thanwerdas, J., Bardou, P., Salin, G., Maigne, E., Servan, S., & Ben-Ari, T. (2022). An open-source tool to assess the carbon footprint of research. Environmental Research: Infrastructure and Sustainability, 2(3), 035008.
Marini, F., Lee, C., Wagner, J., Makeig, S., & Gola, M. (2019). A comparative evaluation of signal quality between a research-grade and a wireless dry-electrode mobile EEG system. Journal of Neural Engineering, 16(5), 054001.
Marques, C. T., & Fritzen Gomes, B. M. (2020). Reuse, Reduce, Recycle. In W. Leal Filho, A. M. Azul, L. Brandli, P. G. özuyar, & T. Wall (Eds.), Responsible Consumption and Production (pp. 626–634). Springer International Publishing.
McCabe, D. P., & Castel, A. D. (2008). Seeing is believing: The effect of brain images on judgments of scientific reasoning. Cognition, 107(1), 343–352.
Mecacci, G., & Haselager, P. (2019). Identifying Criteria for the Evaluation of the Implications of Brain Reading for Mental Privacy. Science and Engineering Ethics, 25(2), 443–461.
Moor, J. H. (2005). Why We Need Better Ethics for Emerging Technologies. Ethics and Information Technology, 7(3), 111–119.
Muhl, E. (2024). The challenge of wearable neurodevices for workplace monitoring: An EU legal perspective. Frontiers in Human Dynamics, 6.
Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., Simonsohn, U., Wagenmakers, E.-J., Ware, J. J., & Ioannidis, J. P. A. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1(1), 1–9.
Mushtaq, F., Welke, D., Gallagher, A., Pavlov, Y. G., Kouara, L., Bosch-Bayard, J., van den Bosch, J. J. F., Arvaneh, M., Bland, A. R., Chaumon, M., Borck, C., He, X., Luck, S. J., Machizawa, M. G., Pernet, C., Puce, A., Segalowitz, S. J., Rogers, C., Awais, M., … Valdes-Sosa, P. (2024). One hundred years of EEG for brain and behaviour research. Nature Human Behaviour, 8(8), 1437–1443.
Muthukrishna, M., Bell, A. V., Henrich, J., Curtin, C. M., Gedranovich, A., McInerney, J., & Thue, B. (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance. Psychological Science, 31(6), 678–701.
Newen, A., Gallagher, S., & De Bruin, L. (2018). 4E Cognition: Historical Roots, Key Concepts, and Central Issues. In A. Newen, L. De Bruin, & S. Gallagher (Eds.), The Oxford Handbook of 4E Cognition (p. 0). Oxford University Press.
Nielsen, E.B. and Andersen, G. (2022), The Cruel Optimism of Anthropocene Technologies: Suspicion and Fascination of Technology in Okja, What Happened to Monday, and Geostorm. J Pop Cult, 55: 735-754.
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Niso, G., Romero, E., Moreau, J. T., Araujo, A., & Krol, L. R. (2023). Wireless EEG: A survey of systems and studies. NeuroImage, 269, 119774.
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Parada, F. J., Grasso-Cladera, A., Rossi, A., Soto-Icaza, P., Arenas-Pérez, M., & Errázuriz, M. C. (2024). Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective. The European Journal of Neuroscience, 60(3), 4148–4168.
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Zander, T. O., Krol, L. R., Birbaumer, N. P., & Gramann, K. (2016). Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity. Proceedings of the National Academy of Sciences, 113(52), 14898–14903.