Uniqueness and Major Issues of Neuroethics

신경윤리의 독자성과 주요 쟁점들

  • Received : 2018.03.29
  • Accepted : 2018.03.30
  • Published : 2018.03.30


This paper aims to examine the philosophical significance of neuroethics and its unique position within the cognitive paradigm, and to discuss major issues of neuroethics. Recent advances in neuroscience enable more direct access and intervention to human mind, which reduces the distinction between matter and mind and brings up new philosophical questions on human nature. Neuroethics takes interdisciplinary and integrative approach, in order to deal with the ethical issues related to new findings and technology of neuroscience that cannot be covered by the traditional legal and social systems. Some of the ethical issues of neuroscience overlap with the classical bioethics problems but majority of major issues are unique to neuroethics. These issues are mainly related to mind reading through the observation and decoding of brain activities and to cognitive enhancement through directly manipulating brain functions. Considering the current status and trends of Korean neuroscientific research, it is necessary to begin in-depth discussion of neuroethical issues with the collaboration among experts in related fields.


Supported by : 한국뇌연구원 KBRI, 부산대학교


  1. 설선혜, 이춘길 (2008). 신경윤리학: 뇌과학의 윤리적, 철학적, 법적, 사회적 문제. 한국심리학회지: 일반, 27(1), 1-41.
  2. 이보배 (2015. 11. 16.). '토막살인' 박춘풍 사이코패스 감정 뇌영상 촬영. 연합뉴스,
  3. Aspinwall, L. G., Brown, T. R., & Tabery, J. (2012). The double-edged sword: Does biomechanism increase or decrease judges' sentencing of psychopaths? Science, 337(6096), 846-849.
  4. Bainbridge, W. S. (Ed.). (2013). Converging technologies for improving human performance: Nanotechnology, biotechnology, information technology and cognitive science. Springer Science & Business Media.
  5. Buckholtz, J. W., & Faigman, D. L. (2014). Promises, promises for neuroscience and law. Current Biology, 24(18), R861-R867.
  6. Dunlop, B. et al. (2017). Functional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder. The American Journal of Psychiatry, 174(6), 533-545.
  7. Elsey, J., & Kindt, M. (2016). Manipulating human memory through reconsolidation: Ethical implications of a new therapeutic approach. AJOB Neuroscience, 7(4), 225-236.
  8. Farah, M. J. (2005). Neuroethics: the practical and the philosophical. Trends in Cognitive Science, 9(1), 34-40.
  9. Farah, M. J. (2010). Neuroethics: An Introduction with Readings. MA: MIT Press.
  10. Farah, M. J., Hutchinson, J. B., Phelps, E. A., & Wagner, A. D. (2014). Functional MRI-based lie detection: scientific and societal challenges. Nature Reviews Neuroscience, 15(2), 123-131.
  11. Gazzaniga, M. S. (2006). 윤리적 뇌 (2009), 뇌는 윤리적인가.(2015) (김효은 역) 서울: 바다출판사.
  12. Giordano, J. J., & Gordijn, B. (Eds.). (2010). Scientific and philosophical perspectives in neuroethics. Cambridge University Press.
  13. Glannon, W. (2007). Defining right and wrong in brain science. IL: University of Chicago Press.
  14. Glannon, W. (2006). Psychopharmacology and memory. Journal of Medical Ethics, 32, 74-78.
  15. Goering, S., & Yuste, R. (2016). On the Necessity of Ethical Guidelines for Novel Neurotechnologies. Cell, 167(4), 882-885.
  16. Harmon-Jones, E., & Inzlicht, M. (2016). A brief overview of social neuroscience. Social Neuroscience: Biological Approaches to Social Psychology, 1.
  17. Haxby, J. V., Connolly, A. C., & Guntupalli, J. S. (2014). Decoding neural representational spaces using multivariate pattern analysis. Annual review of neuroscience, 37, 435-456.
  18. Hein, G., Morishima, Y., Leiberg, S., Sul, S., & Fehr, E. (2016). The brain's functional network architecture reveals human motives. Science, 351(6277), 1074-1078.
  19. Horikawa, T., & Kamitani, Y. (2017). Generic decoding of seen and imagined objects using hierarchical visual features. Nature communications, 8, 15037.
  20. Horikawa, T., Tamaki, M., Miyawaki, Y., & Kamitani, Y. (2013). Neural decoding of visual imagery during sleep. Science, 340(6132), 639-642.
  21. Hu, L., & Iannetti, G. D. (2016). Painful issues in pain prediction. Trends in neurosciences, 39(4), 212-220.
  22. Hyman, S. & Fenton, W. (2003). What are the right targets for psychopharmacolgy? Science, 299, 350-351.
  23. Illes, J., & Bird, S. J. (2006). Neuroethics: a modern context for ethics in neuroscience. Trends in neurosciences, 29(9), 511-517.
  24. Kadosh, R. C., Levy, N., O'Shea, J., Shea, N., & Savulescu, J. (2012). The neuroethics of non-invasive brain stimulation. Current Biology, 22(4), R108-R111.
  25. Kahnt, T. (2017). A decade of decoding reward-related fMRI signals and where we go from here. NeuroImage.
  26. Kragel, P. A., & LaBar, K. S. (2016). Decoding the Nature of Emotion in the Brain. Trends in cognitive sciences, 20(6), 444-455.
  27. Lombera, S., & Illes, J. (2009). The international dimensions of neuroethics. Developing world bioethics, 9(2), 57-64.
  28. Miller, G. (2010, May 13). fMRI lie detection gets its day in court. Science. Retrieved from
  29. Poldrack, R. A. (2011). Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding. Neuron, 72(5), 692-697.
  30. Poldrack, R. (2017). Neuroscience: The risks of reading the brain. Nature, 541(7636), 156-156.
  31. Racine, E., Bar-Ilan, O., & Illes, J. (2005). fMRI in the public eye. Nature Review Neuroscience, 6(2), 159-164.
  32. Racine, E., & Forlini, C. (2010). Cognitive enhancement, lifestyle choice or misuse of prescription drugs?. Neuroethics, 3(1), 1-4.
  33. Ritchie, J. B., Kaplan, D. M., & Klein, C. (2017). Decoding the brain: neural representation and the limits of multivariate pattern analysis in cognitive neuroscience. The British Journal for the Philosophy of Science.
  34. Sul, S., Güroğlu, B., Crone, E. A., & Chang, L. J. (2017). Medial prefrontal cortical thinning mediates shifts in other-regarding preferences during adolescence. Scientific reports, 7(1), 8510.
  35. Woo, C. W., Chang, L. J., Lindquist, M. A., & Wager, T. D. (2017). Building better biomarkers: brain models in translational neuroimaging. Nature neuroscience, 20(3), 365-377.
  36. Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nature methods, 8(8), 665-670.