Professor in the Department of Psychology and Neuroscience
Research in my laboratory investigates the brain mechanisms underlying economic and social decision making; collectively, this research falls into the field of “decision neuroscience” or "neuroeconomics". My laboratory uses fMRI to probe brain function, behavioral assays to characterize individual differences, and other physiological methods (e.g., eye tracking, pharmacological manipulation, genetics) to link brain and behavior. Concurrent with research on basic processes, my laboratory has also investigated the application of new analysis methods for fMRI data, including functional connectivity analyses, pattern classification analyses, and combinatoric multivariate approaches. We have also been applying computational methods to problems in behavioral economics and consumer decision making.
I have also been very active in outreach, mentorship, and educational activities; as examples, I am lead author on the textbook Functional Magnetic Resonance Imaging (Sinauer Associates; 3rd edition in 2014), I teach Fundamentals of Decision Science, Decision Neuroscience and Neuroethics, and many of my postdoctoral and graduate trainees now lead research laboratories of their own.
Behavior and Physiology in Aging awarded by National Institutes of Health (Mentor). 2015 to 2025
Rapid measurement of prefrontal cortical activity using parallelized diffuse correlation spectroscopy awarded by Air Force Office of Scientific Research (Co-Principal Investigator). 2021 to 2024
Neurobiology Training Program awarded by National Institutes of Health (Mentor). 2019 to 2024
Duke Creating ADRD Researchers for the Next Generation - Stimulating Access to Research in Residency Program (CARiNG-StARR)" awarded by National Institutes of Health (Preceptor). 2020 to 2023
Improving Adherence to Adjuvant Endocrine Therapy in Breast Cancer Patients awarded by National Institutes of Health (Co Investigator). 2016 to 2022
A High-Performance 3T MRI for Brain Imaging awarded by National Institutes of Health (Minor User). 2021 to 2022
Targeting reward dysfunction as a mechanism to improve smoking cessation awarded by National Institutes of Health (Co-Mentor). 2016 to 2022
Nicotine Withdrawal and Reward Processing: Connecting Neurobiology to Real-World Behavior awarded by National Institutes of Health (Co-Mentor). 2017 to 2022
PFI:BIC - A Smart, Flexible, Large-Scale Sensing and Response Service System (LASSaRESS) for Monitoring and Management of Ground, Air and Waterborne Contaminants awarded by National Science Foundation (Investigator). 2016 to 2021
Mechanisms Regulating Complex Social Behavior awarded by University of Pennsylvania (Principal Investigator). 2016 to 2021
Massar, Stijn A. A., et al. Sleep deprivation, effort allocation and performance. Vol. 246, 2019, pp. 1–26. Epmc, doi:10.1016/bs.pbr.2019.03.007. Full Text
Jack, J., et al. “Mapping rhetorical topologies in cognitive neuroscience.” Topologies as Techniques for a Post-Critical Rhetoric, 2017, pp. 125–50. Scopus, doi:10.1007/978-3-319-51268-6_7. Full Text
Martin, R. S., and S. A. Huettel. “Cognitive functions as revealed by imaging of the human brain.” Neuroscience in the 21st Century: From Basic to Clinical, Second Edition, 2016, pp. 2727–53. Scopus, doi:10.1007/978-1-4939-3474-4_82. Full Text
Coutlee, C. G., and S. A. Huettel. “Rules, rewards, and responsibility: A reinforcement learning approach to action control.” Moral Psychology, Volume 4: Free Will And Moral Responsibility, 2014, pp. 327–34.
San Martin, R., and S. A. Huettel. “Cognitive functions as revealed by imaging of the human brain.” Neuroscience in the 21st Century: From Basic to Clinical, 2013, pp. 2213–38. Scopus, doi:10.1007/978-1-4614-1997-6_82. Full Text
Venkatraman, V., et al. “Neuroeconomics of risky decisions: From variables to strategies.” Decision Making, Affect, and Learning: Attention and Performance XXIII, 2011. Scopus, doi:10.1093/acprof:oso/9780199600434.003.0007. Full Text
Venkatraman, V., et al. “Economic decision-making and the sleep-deprived brain.” Neuroimaging of Sleep and Sleep Disorders, 2010, pp. 145–53. Scopus, doi:10.1017/CBO9781139088268. Full Text
Jenke, L., and S. A. Huettel. “Voter Preferences Reflect a Competition Between Policy and Identity.” Frontiers in Psychology, vol. 11, Oct. 2020. Scopus, doi:10.3389/fpsyg.2020.566020. Full Text
Kranton, Rachel, et al. “Deconstructing bias in social preferences reveals groupy and not-groupy behavior.” Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 35, Sept. 2020, pp. 21185–93. Epmc, doi:10.1073/pnas.1918952117. Full Text
Bell, Ryan P., et al. “Neural sensitivity to risk in adults with co-occurring HIV infection and cocaine use disorder.” Cogn Affect Behav Neurosci, vol. 20, no. 4, Aug. 2020, pp. 859–72. Pubmed, doi:10.3758/s13415-020-00806-4. Full Text
McDonald, Kelsey R., et al. “Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior.” Soc Cogn Affect Neurosci, vol. 15, no. 4, June 2020, pp. 383–93. Pubmed, doi:10.1093/scan/nsaa053. Full Text
Botvinik-Nezer, Rotem, et al. “Variability in the analysis of a single neuroimaging dataset by many teams.” Nature, vol. 582, no. 7810, June 2020, pp. 84–88. Pubmed, doi:10.1038/s41586-020-2314-9. Full Text
Bachman, Matthew D., and Scott A. Huettel. “Motivated control as a bridge between neuroeconomics and cognitive neuroscience.” Nature Human Behaviour, vol. 4, no. 4, Apr. 2020, pp. 332–33. Epmc, doi:10.1038/s41562-019-0794-0. Full Text
Meade, Christina S., et al. “Synergistic effects of marijuana abuse and HIV infection on neural activation during a cognitive interference task.” Addict Biol, vol. 24, no. 6, Nov. 2019, pp. 1235–44. Pubmed, doi:10.1111/adb.12678. Full Text
Li, Rosa, et al. “Developmental Maturation of the Precuneus as a Functional Core of the Default Mode Network.” Journal of Cognitive Neuroscience, vol. 31, no. 10, Oct. 2019, pp. 1506–19. Epmc, doi:10.1162/jocn_a_01426. Full Text
Warwick, Hunter, et al. “Small Social Incentives Did Not Improve the Survey Response Rate of Patients Who Underwent Orthopaedic Surgery: A Randomized Trial.” Clin Orthop Relat Res, vol. 477, no. 7, July 2019, pp. 1648–56. Pubmed, doi:10.1097/CORR.0000000000000732. Full Text
Zhang, Xue, et al. “Exploring common changes after acute mental stress and acute tryptophan depletion: Resting-state fMRI studies.” J Psychiatr Res, vol. 113, June 2019, pp. 172–80. Pubmed, doi:10.1016/j.jpsychires.2019.03.025. Full Text
“THE IMPACT OF FEEDBACK TIMING ON VALUE LEARNING IN AGING.” The Gerontologist, vol. 55, no. Suppl_2, Oxford University Press (OUP), 2015, pp. 140–140. Crossref, doi:10.1093/geront/gnv513.03. Full Text
Martin, Rene San, et al. “NEURAL SIGNATURES OF VALUE-DRIVEN ATTENTIONAL CAPTURE PREDICT INDIVIDUAL DIFFERENCES IN ECONOMIC CHOICE.” Journal of Cognitive Neuroscience, MIT PRESS, 2013, pp. 208–208.
Appelbaum, Lawrence, et al. “NEURORHETORIC: MAPPING THE SEMANTIC STRUCTURE OF COGNITIVE NEUROSCIENCE.” Journal of Cognitive Neuroscience, MIT PRESS, 2013, pp. 260–61.
Libedinsky, C., et al. “REWARD VALUATION IN SLEEP-DEPRIVED INDIVIDUALS.” Sleep, vol. 34, OXFORD UNIV PRESS INC, 2011, pp. A78–A78.
Wang, Lihong, et al. “Modulation Effect of Rumination Trait and Low Tryptophan on Default-Mode Network Connectivity.” Biological Psychiatry, vol. 67, no. 9, ELSEVIER SCIENCE INC, 2010, pp. 224S-224S.
Yaxley, Richard H., et al. “Brain activation during decisions involving behavioral risk: Adolescents v. adults.” Biological Psychiatry, vol. 63, no. 7, ELSEVIER SCIENCE INC, 2008, pp. 79S-79S.
Madden, D., et al. “Adult age differences and similarities in the functional neuroanatomy of visual attention: Evidence from FMRI.” Journal of Cognitive Neuroscience, M I T PRESS, 2005, pp. 154–154.
Bucur, B., et al. “Age-related decreases in cerebral white matter integrity: Implications for episodic and semantic retrieval processes.” Journal of Cognitive Neuroscience, M I T PRESS, 2005, pp. 234–234.
Huettel, S., et al. “Choices between gambles: Effects of certainty, risk, and ambiguity upon brain systems for decision making and reward evaluation.” Journal of Cognitive Neuroscience, M I T PRESS, 2005, pp. 221–221.