, Volume 9, Issue 3, pp 279–288 | Cite as

“A Light Switch in the #Brain”: Optogenetics on Social Media

  • Julie M. Robillard
  • Cody Lo
  • Tanya L. Feng
  • Craig A. Hennessey
Brief Communication


Neuroscience communication is increasingly taking place on multidirectional social media platforms, creating new opportunities but also calling for critical ethical considerations. Twitter, one of the most popular social media applications in the world, is a leading platform for the dissemination of all information types, including emerging areas of neuroscience such as optogenetics, a technique aimed at the control of specific neurons. Since its discovery in 2005, optogenetics has been featured in the public eye and discussed extensively on social media, but little is known about how this new technique is portrayed and who the users participating in the conversation are. To address this gap, we conducted content analysis of a sample of 1000 tweets mentioning “optogenetics” over a one-year period between 2014 and 2015. We found that academic researchers are the largest group contributing to the conversation, that the tweets often contain links to third-party websites from news organizations and peer-reviewed journals, and that common thematic motifs include the applications of optogenetics specifically for the control of brain activity and the treatment of disease. We also found that the majority of the tweets are neutral in their tone regarding optogenetics. As Twitter serves as a current and dynamic forum for exchange about advances in neuroscience, the conversation about optogenetics on this engaging platform can inform socially-responsive knowledge dissemination efforts in this area.


Optogenetics Social media Internet Neuroscience communication 


  1. 1.
    Robillard, Julie, Louise Whiteley, Thomas Johnson, Jonathan Lim, Wyeth Wasserman, and Judy Illes. 2013. Utilizing social media to study information-seeking and ethical issues in gene therapy. Journal of Medical Internet Research. doi:10.2196/jmir.2313.Google Scholar
  2. 2.
    Robillard, Julie, Emanuel Cabral, Craig Hennessey, Brian Kwon, and Judy Illes. 2015. Fueling hope: stem cells in social media. Stem Cell Reviews. doi:10.1007/s12015–015-9591-y.Google Scholar
  3. 3.
    Hawn, Carleen. 2009. Take two aspirin and tweet me in the morning: how Twitter, Facebook, and other social media are reshaping health care. Health Affairs. doi:10.1377/hlthaff.28.2.361.Google Scholar
  4. 4.
    Twitter Inc. 2016. Twitter. Accessed 8 May 2016
  5. 5.
    Acar, Adam, and Yuya Muraki. 2011. Twitter for crisis communication: lessons learned from Japan’s tsunami disaster. International Journal of Web Based Communities. doi:10.1504/IJWBC.2011.041206.Google Scholar
  6. 6.
    Conover, Michael, Jacob Ratkiewicz, Matthew R. Francisco, Bruno Gonçalves, Filippo Menczer, and Alessandro Flammini. 2011. Political polarization on Twitter. ICWSM 133: 89–96.Google Scholar
  7. 7.
    Chew, Cynthia, and Gunther Eysenbach. 2010. Pandemics in the age of Twitter: content analysis of tweets during the 2009 H1N1 outbreak. PloS ONE. doi:10.1371/journal.pone.0014118.Google Scholar
  8. 8.
    Rybalko, Svetlana, and Trent Seltzer. 2010. Dialogic communication in 140 characters or less: how Fortune 500 companies engage stakeholders using Twitter. Public Relations Review. doi:10.1016/j.pubrev.2010.08.004.Google Scholar
  9. 9.
    Bruns, Axel, and Stefan Stieglitz. 2012. Quantitative approaches to comparing communication patterns on Twitter. Journal of Technology in Human Services. doi:10.1080/15228835.2012.744249.Google Scholar
  10. 10.
    Grunig, James, and Todd Hunt. 1984. Managing public relations. New York: Holt, Rinehart and Winston.Google Scholar
  11. 11.
    Sha, Bey-Ling. 2007. Dimensions of public relations: moving beyond traditional public relations models. In New Media and Public Relations, ed. S.C. Duhe, 3–26. New York: Peter Lang.Google Scholar
  12. 12.
    Waters, Richard, and Jia Jamal. 2011. Tweet, tweet, tweet: a content analysis of nonprofit organizations’ Twitter updates. Public Relations Review. doi:10.1016/j.pubrev.2011.03.002.Google Scholar
  13. 13.
    Adams, Samantha. 2010. Revisiting the online health information reliability debate in the wake of “web 2.0”: an inter-disciplinary literature and website review. International Journal of Medical Informatics. doi:10.1016/j.ijmedinf.2010.01.006.Google Scholar
  14. 14.
    Boyden, Edward, Feng Zhang, Ernst Bamberg, Georg Nagel, and Karl Deisseroth. 2005. Millisecond-timescale, genetically targeted optical control of neural activity. Nature Neuroscience. doi:10.1038/nn1525.Google Scholar
  15. 15.
    Deisseroth, Karl. 2011. Optogenetics. Nature Methods. doi:10.1038/nmeth.f.324.Google Scholar
  16. 16.
    Deisseroth, Karl. 2012. Optogenetics and psychiatry: applications, challenges, and opportunities. Biological Psychiatry. doi:10.1016/j.biopsych.2011.12.021.Google Scholar
  17. 17.
    Malpass, Katy. 2012. Epilepsy: shining a light on seizure control - optogenetic approach shows promise for treatment and prevention of epilepsies. Nature Reviews Neurology. doi:10.1038/nrneurol.2012.256.Google Scholar
  18. 18.
    Pascoli, Vincent, Marc Turiault, and Christian Lüscher. 2012. Reversal of cocaine-evoked synaptic potentiation resets drug-induced adaptive behavior. Nature. doi:10.1038/nature10709.Google Scholar
  19. 19.
    Racine, Eric, Ofek Bar-Ilan, and Judy Illes. 2005. fMRI in the public eye. Nature Reviews Neuroscience. doi:10.1038/nrn1609.Google Scholar
  20. 20.
    Illes, Judy, Mary Moser, Jennifer McCormick, Eric Racine, Sandra Blakeslee, Arthur Caplan, Erika Hayden, Jay Ingram, Tiffany Lohwater, Peter McKnight, Christie Nicholson, Anthony Phillips, Kevin Sauvé, Elaine Snell, and Samuel Weiss. 2010. Neurotalk: improving the communication of neuroscience research. Nature Reviews Neuroscience. doi:10.1038/nrn2773.Google Scholar
  21. 21.
    Deisseroth, Karl. 2010. Controlling the brain with light. Scientific American 5(3): 48–55.CrossRefGoogle Scholar
  22. 22.
    Gilbert, Frederic, Alexander Harris, and Robert Kapsa. 2014. Controlling brain cells with light: ethical considerations for optogenetic clinical trials. AJOB Neuroscience. doi:10.1080/21507740.2014.911213.Google Scholar
  23. 23.
    Scanfeld, Daniel, Vanessa Scanfeld, and Elaine Larson. 2010. Dissemination of health information through social networks: Twitter and antibiotics. American Journal of Infection Control. doi:10.1016/j.ajic.2009.11.004.Google Scholar
  24. 24.
    Robillard, Julie, Thomas Johnson, Craig Hennessey, Lynn Beattie, and Judy Illes. 2013. Aging 2.0: health information about dementia on Twitter. PLoS ONE. doi:10.1371/journal.pone.0069861.Google Scholar
  25. 25.
    Krippendorff, Klaus, 2007. Computing Krippendorff’s alpha reliability. Departmental Papers (ASC). Accessed 21 July 2016.
  26. 26.
    Keller, Brett, Alain Labrique, Kriti Jain, Andrew Pekosz, and Orin Levine. 2014. Mind the gap: social media engagement by public health researchers. Journal of Medical Internet Research. doi:10.2196/jmir.2982.Google Scholar
  27. 27.
    Purcell-Davis, Allyson. 2013. The representations of novel neurotechnologies in social media: five case studies. The New Bioethics: A Multidisciplinary Journal of Biotechnology and the Body 19: 30–45.CrossRefGoogle Scholar
  28. 28.
    Pearce, Warren, Kim Holmberg, Iina Hellsten, and Brigitte Nerlich. 2014. Climate change on Twitter: topics, communities and conversations about the 2013 IPCC Working Group 1 report. PLoS ONE. doi:10.1371/journal.pone.0094785.Google Scholar
  29. 29.
    Waters, Richard, and Jensen Williams. 2011. Squawking, tweeting, cooing, and hooting: analyzing the communication patterns of government agencies on Twitter. Journal of Public Affairs. doi:10.1002/pa.385.Google Scholar
  30. 30.
    Annice, Kim, Heather Hansen, Joe Murphy, Ashley Richards, Jennifer Duke, and Jane Allen. 2013. Methodological considerations in analyzing Twitter data. JNCI Monographs. doi:10.1093/jncimonographs/lgt026.Google Scholar
  31. 31.
    Mislove, Alan, Sune Lehmann, Yong-Yeol Ahn, Jukka-Pekka Onnela, and J. Niels Rosenquist. 2011. Understanding the demographics of Twitter users. In: Fifth International AAAI Conference on Weblogs and Social Media.Google Scholar
  32. 32.
    Sloan, Luke, Jeffrey Morgan, Peter Burnap, and Matthew Williams. 2015. Who tweets? Deriving the demographic characteristics of age, occupation and social class from Twitter user meta-data. PLOS ONE. doi:10.1371/journal.pone.0115545.Google Scholar
  33. 33.
    Smith, Joanna, and Smith, Aaron. 2012. Twitter use 2012. Pew Research Center. Accessed 3 August 2016.

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Julie M. Robillard
    • 1
  • Cody Lo
    • 1
  • Tanya L. Feng
    • 1
  • Craig A. Hennessey
    • 2
  1. 1.National Core for Neuroethics, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook MallUniversity of British ColumbiaVancouverCanada
  2. 2.Department of Energy, Electrical and Computer EngineeringBritish Columbia Institute of TechnologyBurnabyCanada

Personalised recommendations