Novel Contributions of Neuroergonomics and Cognitive Engineering to Population Health

  • Peter A. HallEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 953)


This chapter describes important ways in which brain imaging and brain stimulation technologies are poised to contribute to disease prevention at the level of whole populations, and how neuroergonomics and cognitive engineering have set the conditions for this to occur. The historically limited influence of neuroscience on population health is discussed with reference to logistics, conceptual barriers, and epistemic considerations. With respect to the latter, the brain is typically viewed as an outcome variable, rather than its more nuanced role as a predictor, mediator or moderator. Yet these later roles potentiate a number of important functions for neuroscience research within disease prevention with wide ranging implications. Using examples from multiple laboratories, I highlight several examples of how neuroimaging and neuromodulation technologies can be used to generate new knowledge to shape disease prevention programs and optimize health communication strategies.


Neuroergonomics rTMS fNIRS Brain Health Population 



This work was supported by an operating grant to P. Hall (435-2017-0027) from the Social Sciences and Humanities Research Council of Canada.


  1. 1.
    World Health Organization: Global status report on noncommunicable diseases (2014)Google Scholar
  2. 2.
    Erickson, K.I., Creswell, J.D., Verstynen, T.D., Gianaros, P.J.: Health neuroscience: defining a new field. Curr. Dir. Psychol. Sci. 23, 446–453 (2014)CrossRefGoogle Scholar
  3. 3.
    Hall, P.A.: Brain stimulation as a method for understanding, treating and preventing disorders of indulgent food consumption. Curr. Addict. Rep. (2019)Google Scholar
  4. 4.
    Hall, P.A.: Executive-control processes in high-calorie food consumption. Curr. Dir. Psych. Sci. 25, 91–98 (2016)CrossRefGoogle Scholar
  5. 5.
    Lowe, C.J., Staines, W.R., Manocchio, F., Hall, P.A.: The neurocognitive mechanisms underlying food cravings and snack food consumption. a combined continuous theta burst stimulation (cTBS) and EEG study. Neuroimage 177, 45–58 (2018)CrossRefGoogle Scholar
  6. 6.
    Hall, P.A., Lowe, C., Vincent, C.: Brain stimulation effects on food cravings and consumption: an update on Lowe et al. (2017) and a response to Generoso et al. (2017). Psychosom. Med. 79, 839–842 (2017)CrossRefGoogle Scholar
  7. 7.
    Safati, A.B., Hall, P.A.: Contextual cues as modifiers of cTBS effects on indulgent eating (Manuscript under review) Google Scholar
  8. 8.
    Suppa, A., Huang, Y.Z., Funke, K., Ridding, M.C., Cheeran, B., Di Lazzaro, V., Ziemann, U., Rothwell, J.C.: Ten years of theta burst stimulation in humans: established knowledge, unknowns and prospects. Brain. Stim. 9, 323–335 (2016)CrossRefGoogle Scholar
  9. 9.
    Erickson, K.I., Prakash, R.S., Voss, M.W., Chaddock, L., Hu, L., Morris, K.S., White, S.M., Wójcicki, T.R., McAuley, E., Kramer, A.F.: Aerobic fitness is associated with hippocampal volume in elderly humans. Hippocampus 19, 1030–1039 (2009)CrossRefGoogle Scholar
  10. 10.
    Erickson, K.I., Voss, M.W., Prakash, R.S., Basak, C., Szabo, A., Chaddock, L., Kim, J.S., Heo, S., Alves, H., White, S.M., Wojcicki, T.R.: Exercise training increases size of hippocampus and improves memory. P. Natl. Acad. Sci. USA 108, 3017–3022 (2011)CrossRefGoogle Scholar
  11. 11.
    Hillman, C.H., Erickson, K.I., Kramer, A.F.: Be smart, exercise your heart: exercise effects on brain and cognition. Nat. Rev. Neurosci. 9, 58 (2008)CrossRefGoogle Scholar
  12. 12.
    Stillman, C.M., Erickson, K.I.: Physical activity as a model for health neuroscience. Ann. NY. Acad. Sci. 1428, 103–111 (2018)CrossRefGoogle Scholar
  13. 13.
    Best, J.R., Chiu, B.K., Hall, P.A., Liu-Ambrose, T.: Larger lateral prefrontal cortex volume predicts better exercise adherence among older women: evidence from two exercise training studies. J. Gerontol. A-Bio. 72, 804–810 (2017)CrossRefGoogle Scholar
  14. 14.
    Gujral, S., McAuley, E., Oberlin, L.E., Kramer, A.F., Erickson, K.I.: Role of brain structure in predicting adherence to a physical activity regimen. Psychosom. Med. 80, 69–77 (2018)CrossRefGoogle Scholar
  15. 15.
    Hall, P.A., Fong, G.T.: Temporal self-regulation theory: a neurobiologically informed model for physical activity behavior. Front. Hum. Neurosci. 25, 117 (2015)Google Scholar
  16. 16.
    Falk, E., Scholz, C.: Persuasion, influence, and value: perspectives from communication and social neuroscience. Ann. Rev. Psychol. 4, 69 (2018)Google Scholar
  17. 17.
    Falk, E.B., Berkman, E.T., Lieberman, M.D.: From neural responses to population behavior: neural focus group predicts population-level media effects. Psychol. Sci. 23, 439–445 (2012)CrossRefGoogle Scholar
  18. 18.
    Falk, E.B., Morelli, S.A., Welborn, B.L., Dambacher, K., Lieberman, M.D.: Creating buzz: the neural correlates of effective message propagation. Psychol. Sci. 24, 1234–1242 (2013)CrossRefGoogle Scholar
  19. 19.
    Falk, E.B., Berkman, E.T., Whalen, D., Lieberman, M.D.: Neural activity during health messaging predicts reductions in smoking above and beyond self-report. Health Psychol. 30, 177 (2011)CrossRefGoogle Scholar
  20. 20.
    Burns, S.M., Barnes, L., Katzman, P.L., Ames, D.L., Falk, E.B., Lieberman, M.D.: A functional near infrared spectroscopy (fNIRS) replication of the sunscreen persuasion paradigm. Soc. Cogn. Affect. Neur. 1, 9 (2018)Google Scholar
  21. 21.
    Falk, E.B., O’Donnell, M.B., Tompson, S., Gonzalez, R., Dal Cin, S., Strecher, V., Cummings, K.M., An, L.: Functional brain imaging predicts public health campaign success. Soc. Cogn. Affect. Neur. 11, 204–214 (2015)CrossRefGoogle Scholar
  22. 22.
    Doré, B.P., Tompson, S.H., O’Donnell, M.B., An, L., Strecher, V., Falk, E.B.: Neural mechanisms of emotion regulation moderate the predictive value of affective and value-related brain responses to persuasive messages. J. Neurosci. 39, 1293–1300 (2019)CrossRefGoogle Scholar
  23. 23.
    Ayaz, H., Izzetoglu, M., Izzetoglu, K., Onaral, B.: The use of functional near-infrared spectroscopy in neuroergonomics. In: Neuroergonomics, pp. 17–25. Academic Press, London (2019)Google Scholar
  24. 24.
    Curtin, A., Ayaz, H.: The age of neuroergonomics: towards ubiquitous and continuous measurement of brain function with fNIRS. Jpn. Psychol. Res. 60(4), 374–386 (2018)CrossRefGoogle Scholar
  25. 25.
    Ferrari, M., Quaresima, V.: A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage 63, 921–935 (2012)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Public Health and Health SystemsUniversity of WaterlooWaterlooCanada

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