Skip to main content
SpringerLink
Log in

Are there gender differences in young vs. aging brains under risk decision-making? An optical brain imaging study

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

Few research publications have reported on gender-dependent neural correlates of risk decision-making in older adults. In this study, we utilized functional near-infrared spectroscopy (fNIRS) to comprehensively investigate both age- and gender-dependent differences in neural correlates in response to a well-utilized risk decision-making protocol, the Balloon Analog Risk Task (BART). A newly-developed technique, atlas-guided diffuse optical tomography (atlas-DOT), was used to image the prefrontal cortices (PFC) of healthy subjects in two age groups (25–40 years; 60–92 years) using BART stimulation. The behavioral measures and brain activations imaged by atlas-DOT were recorded and compared for both age groups. Three-factor analysis of variance was conducted to include all effects of age (young, old), gender (male, female), case (win, lose) and their interactions for both behavioral and hemodynamic responses. The results indicated age differences in cortical activation patterns, activation amplitudes, and brain-behavior correlations. Larger areas of cortical activation with reduced amplitudes in the PFC were observed in older adults when they performed BART. Brain-behavior correlations indicated that young adults took more risks, whereas older adults were more risk-averse. Results also revealed a gender effect in young adults, but not in older adults. Both male and female older adults demonstrated strong PFC responses and the same risk-averse patterns under lose outcomes. This is the first study to examine the neural correlates of risk decisions in older adults by optical brain imaging.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Aklin, W. M., Lejuez, C. W., Zvolensky, M. J., Kahler, C. W. & Gwadz, M. (2005) Evaluation of behavioral measures of risk taking propensity with inner city adolescents. Behaviour Research and Therapy, 43(2), pp. 215–228.

  • Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N. & Golani, I. (2001) Controlling the false discovery rate in behavior genetics research, Behavioural Brain Research, 125(1-2), pp. 279–284.

  • Boas, D. A. & Dale, A. M. (2005) Simulation study of magnetic resonance imaging-guided cortically constrained diffuse optical tomography of human brain function, Applied Optics, 44(10), pp. 1957–1968.

  • Burgess, P. W., Dumontheil, I., & Gilbert, S. J. (2007). The gateway hypothesis of rostral prefrontal cortex (area 10) function. Trends in Cognitive Sciences, 11(7), 290–298.

    Article  PubMed  Google Scholar 

  • Cabeza, R. (2001) Cognitive neuroscience of aging: Contributions of functional neuroimaging. Scandinavian Journal of Psychology, 42(3), pp. 277–286.

  • Cabeza, R., Daselaar, S. M., Dolcos, F., Prince, S. E., Budde, M., & Nyberg, L. (2004). Task-independent and task-specific age effects on brain activity during working memory, Visual attention and episodic retrieval. Cerebral Cortex, 14(4), 364–375.

    Article  PubMed  Google Scholar 

  • Carstensen, L. L., Hartel, C. R. & Mather, M. (2006) A Review of Decision-Making Processes: Weighing the Risks and Benefits of Aging.

  • Cazzell, M., Li, L., Lin, Z. J., Patel, S. J., & Liu, H. (2012). Comparison of neural correlates of risk decision making between genders: An exploratory fNIRS study of the balloon analogue risk task (BART). NeuroImage, 62(3), 1896–1911.

    Article  PubMed  Google Scholar 

  • Coffey, C. E., Lucke, J. F., Saxton, J. A., Ratcliff, G., Unitas, L. J., Billig, B., & Bryan, R. N. (1998). Sex differences in brain aging: a quantitative magnetic resonance imaging study. Archives of Neurology, 55(2), 169–179.

    Article  CAS  PubMed  Google Scholar 

  • Crowley, T. J., Raymond, K. M., Mikulich-Gilbertson, S. K., Thompson, L. L. & Lejuez, C. W. (2006) A risk-taking “set” in a novel task among adolescents with serious conduct and substance problems. Journal of the American Academy of Child and Adolescent Psychiatry, 45(2), pp. 175–183.

  • Cui, X., Bray, S., Bryant, D. M., Glover, G. H. & Reiss, A. L. (2011) A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. NeuroImage, 54(4), pp. 2808–2821.

  • Deakin, J., Aitken, M., Robbins, T., & Sahakian, B. J. (2004). Risk taking during decision-making in normal volunteers changes with age. Journal of the International Neuropsychological Society, 10(4), 590–598.

    Article  PubMed  Google Scholar 

  • Dehghani, H., Eames, M. E., Yalavarthy, P. K., Davis, S. C., Srinivasan, S., Carpenter, C. M., Pogue, B. W., & Paulsen, K. D. (2008). Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction. Communications in Numerical Methods in Engineering, 25(6), 711–732.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dong, G., Lin, X., Zhou, H., & Du, X. (2014). Decision-making after continuous wins or losses in a randomized guessing task: Implications for how the prior selection results affect subsequent decision-making. Behavioral and Brain Functions, 10, 11.

    Article  PubMed  PubMed Central  Google Scholar 

  • Elliott, R. (2003). Executive functions and their disorders. British Medical Bulletin, 65, 49–59.

    Article  PubMed  Google Scholar 

  • Eppinger, B., Nystrom, L. E., & Cohen, J. D. (2012). Reduced sensitivity to immediate reward during decision-making in older than younger adults. PloS One, 7(5) p. e36953.

  • Ernst, M., Bolla, K., Mouratidis, M., Contoreggi, C., Matochik, J. A., Kurian, V., Cadet, J. L., Kimes, A. S., & London, E. D. (2002). Decision-making in a risk-taking task: a PET study. Neuropsychopharmacology, 26(5), 682–691.

    Article  PubMed  Google Scholar 

  • Eyler, L. T., Sherzai, A., Kaup, A. R., & Jeste, D. V. (2011). A review of functional brain imaging correlates of successful cognitive aging. Biological Psychiatry, 70(2), 115–122.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fellows, L. K. (2006). Deciding how to decide: Ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making. Brain, 129(Pt 4), 944–952.

    Article  PubMed  Google Scholar 

  • Fellows, L. K., & Farah, M. J. (2007). The role of ventromedial prefrontal cortex in decision making: Judgment under uncertainty or judgment per se? Cerebral Cortex, 17(11), 2669–2674.

    Article  PubMed  Google Scholar 

  • Folley, B. S., & Park, S. (2005). ‘Verbal creativity and schizotypal personality in relation to prefrontal hemispheric laterality: a behavioral and near-infrared optical imaging study’. Schizophrenia Research, 80(2–3), 271–282.

    Article  PubMed  PubMed Central  Google Scholar 

  • Franceschini, M. A., & Boas, D. A. (2004). Noninvasive measurement of neuronal activity with near-infrared optical imaging. NeuroImage, 21(1), 372–386.

    Article  PubMed  PubMed Central  Google Scholar 

  • Friedman, D. (2003). Cognition and aging: A highly selective overview of event-related potential (ERP) data. Journal of Clinical and Experimental Neuropsychology, 25(5), 702–720.

    Article  PubMed  Google Scholar 

  • Galvan, A., Schonberg, T., Mumford, J., Kohno, M., Poldrack, R. A., & London, E. D. (2013). Greater risk sensitivity of dorsolateral prefrontal cortex in young smokers than in nonsmokers. Psychopharmacology, 229(2), 345–355.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hansel, A. & von Kanel, R. (2008) ‘The ventro-medial prefrontal cortex: a major link between the autonomic nervous system, regulation of emotion, and stress reactivity?’, Biopsychosoc Med, 2, p. 21.

  • Harle, K. M., & Sanfey, A. G. (2012). Social economic decision-making across the lifespan: An fMRI investigation. Neuropsychologia,, 50(7), 1416–1424.

    Article  Google Scholar 

  • Harris, C. R., Jenkins, M., & Glaser, D. (2006). Gender differences in risk assessment: Why do women take fewer risks than men?. Judgment and Decision making, 1(1), 48–63.

    Google Scholar 

  • Knoch, D., Gianotti, L. R., Pascual-Leone, A., Treyer, V., Regard, M., Hohmann, M., & Brugger, P. (2006). Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior. The Journal of Neuroscience, 26(24), 6469–6472.

    Article  CAS  PubMed  Google Scholar 

  • Koechlin, E., & Hyafil, A. (2007). Anterior prefrontal function and the limits of human decision-making. Science, 318(5850), 594–598.

    Article  CAS  PubMed  Google Scholar 

  • Lee, T. M., Chan, C. C., Leung, A. W., Fox, P. T., & Gao, J. H. (2009). Sex-related differences in neural activity during risk taking: An fMRI study. Cerebral Cortex, 19(6), 1303–1312.

    Article  PubMed  Google Scholar 

  • Lee, T. M., Leung, A. W., Fox, P. T., Gao, J. H., & Chan, C. C. (2008). Age-related differences in neural activities during risk taking as revealed by functional MRI. Social Cognitive and Affective Neuroscience, 3(1), 7–15.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lejuez, C. W., Aklin, W., Bornovalova, M., & Moolchan, E. T. (2005). Differences in risk-taking propensity across inner-city adolescent ever- and never-smokers. Nicotine & Tobacco Research, 7(1), 71–79.

    Article  CAS  Google Scholar 

  • Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., Strong, D. R., & Brown, R. A. (2002). Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). Journal of Experimental Psychology. Applied, 8(2), 75–84.

    Article  CAS  PubMed  Google Scholar 

  • Lighthall, N. R., Mather, M., & Gorlick, M. A. (2009). Acute stress increases sex differences in risk seeking in the balloon analogue risk task. PloS One, 4(7) e6002.

  • Lighthall, N. R., Sakaki, M., Vasunilashorn, S., Nga, L., Somayajula, S., Chen, E. Y., Samii, N., & Mather, M. (2012). Gender differences in reward-related decision processing under stress. Social Cognitive and Affective Neuroscience, 7(4), 476–484.

    Article  PubMed  Google Scholar 

  • Lin, Z. J., Li, L., Cazzell, M., & Liu, H. (2014). Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults. Human Brain Mapping, 35(8), 4249–4266.

    Article  PubMed  PubMed Central  Google Scholar 

  • Mak, A. K., Hu, Z. G., Zhang, J. X., Xiao, Z., & Lee, T. M. (2009). Sex-related differences in neural activity during emotion regulation. Neuropsychologia, 47(13), 2900–2908.

    Article  PubMed  Google Scholar 

  • Marschner, A., Mell, T., Wartenburger, I., Villringer, A., Reischies, F. M., & Heekeren, H. R. (2005). Reward-based decision-making and aging. Brain Research Bulletin, 67(5), 382–390.

    Article  CAS  PubMed  Google Scholar 

  • McCarrey, A. C., Henry, J. D., von Hippel, W., Weidemann, G., Sachdev, P. S., Wohl, M. J., & Williams, M. (2012). Age differences in neural activity during slot machine gambling: An fMRI study. PloS One, 7(11) e49787.

  • McRae, K., Ochsner, K. N., Mauss, I. B., Gabrieli, J. J. D., & Gross, J. J. (2008). Gender Differences in Emotion Regulation: An fMRI Study of Cognitive Reappraisal. Group Processes & Intergroup Relations,, 11(2), 143–162.

    Article  Google Scholar 

  • Mohr, P. N., Li, S. C., & Heekeren, H. R. (2010). Neuroeconomics and aging: neuromodulation of economic decision making in old age. Neuroscience and Biobehavioral Reviews, 34(5), 678–688.

    Article  CAS  PubMed  Google Scholar 

  • Monti, M. M. (2011). Statistical Analysis of fMRI Time-Series: A critical review of the GLM approach. Frontiers in Human Neuroscience, 5, 28.

    Article  PubMed  PubMed Central  Google Scholar 

  • Nasreddine, Z. S., Phillips, N. A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699.

    Article  PubMed  Google Scholar 

  • Niu, H., Tian, F., Lin, Z. J., & Liu, H. (2010). Development of a compensation algorithm for accurate depth localization in diffuse optical tomography. Optics Letters, 35(3), 429–431.

    Article  PubMed  Google Scholar 

  • Pochon, J. B., Levy, R., Poline, J. B., Crozier, S., Lehericy, S., Pillon, B., Deweer, B., Le Bihan, D., & Dubois, B. (2001). The role of dorsolateral prefrontal cortex in the preparation of forthcoming actions: An fMRI study. Cerebral Cortex, 11(3), 260–266.

    Article  CAS  PubMed  Google Scholar 

  • Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605–628.

    Article  Google Scholar 

  • Rao, H., Korczykowski, M., Pluta, J., Hoang, A., & Detre, J. A. (2008). Neural correlates of voluntary and involuntary risk taking in the human brain: An fMRI study of the balloon analog risk task (BART). NeuroImage, 42(2), 902–910.

    Article  PubMed  Google Scholar 

  • Rogalsky, C., Vidal, C., Li, X., & Damasio, H. (2012). Risky decision-making in older adults without cognitive deficits: An fMRI study of VMPFC using the Iowa gambling task. Social Neuroscience, 7(2), 178–190.

    Article  PubMed  Google Scholar 

  • Rosen, A. C., Prull, M. W., O’Hara, R., Race, E. A., Desmond, J. E., Glover, G. H., Yesavage, J. A. & Gabrieli, J. D. (2002) Variable effects of aging on frontal lobe contributions to memory. Neuroreport, 13(18), pp. 2425–2428.

  • Samanez-Larkin, G. R., & Knutson, B. (2015). Decision making in the ageing brain: Changes in affective and motivational circuits. Nature Reviews. Neuroscience, 16(5), 278–289.

    Article  CAS  PubMed  Google Scholar 

  • Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003). Mapping cortical change across the human life span. Nature Neuroscience, 6(3), 309–315.

    Article  CAS  PubMed  Google Scholar 

  • Spreng, R. N., Wojtowicz, M., & Grady, C. L. (2010). Reliable differences in brain activity between young and old adults: A quantitative meta-analysis across multiple cognitive domains. Neuroscience and Biobehavioral Reviews, 34(8), 1178–1194.

    Article  PubMed  Google Scholar 

  • Strangman, G., Culver, J. P., Thompson, J. H. & Boas, D. A. (2002) A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. NeuroImage, 17(2), pp. 719–731.

  • Tanaka, S. C., Doya, K., Okada, G., Ueda, K., Okamoto, Y., & Yamawaki, S. (2004). Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops. Nature Neuroscience, 7(8), 887–893.

    Article  CAS  PubMed  Google Scholar 

  • van den Bos, R., Homberg, J., & de Visser, L. (2013). A critical review of sex differences in decision-making tasks: Focus on the Iowa gambling task. Behavioural Brain Research, 238, 95–108.

    Article  PubMed  Google Scholar 

  • Van Leijenhorst, L., Gunther Moor, B., Op de Macks, Z. A., Rombouts, S. A., Westenberg, P. M., & Crone, E. A. (2010). Adolescent risky decision-making: Neurocognitive development of reward and control regions. NeuroImage, 51(1), 345–355.

    Article  PubMed  Google Scholar 

  • Wager, T. D., Phan, K. L., Liberzon, I., & Taylor, S. F. (2003). Valence, Gender, and lateralization of functional brain anatomy in emotion: a meta-analysis of findings from neuroimaging. NeuroImage, 19(3), 513–531.

    Article  PubMed  Google Scholar 

  • Yurgelun-Todd, D. (2007) Emotional and cognitive changes during adolescence. Current Opinion in Neurobiology, 17(2), pp. 251–257.

  • Zhang, H., Duan, L., Zhang, Y. J., Lu, C. M., Liu, H., & Zhu, C. Z. (2011). Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy. NeuroImage, 55(2), 607–615.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the support in part from the 2012 Southern Nursing Research Society Research Award.

Author information

Author notes

  1. Lin Li

    Present address: Department of Neurology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA

Authors and Affiliations

  1. Department of Bioengineering, Joint Graduate Program between University of Texas at Arlington and University of Texas Southwestern Medical Center, University of Texas at Arlington, Arlington, TX, 76019, USA

    Lin Li & Hanli Liu

  2. Cook Children’s Medical Center, Fort Worth, TX, 76104, USA

    Mary Cazzell

  3. Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA

    Li Zeng

Authors
  1. Lin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mary Cazzell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hanli Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hanli Liu.

Ethics declarations

Conflict of interest

All of the authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, L., Cazzell, M., Zeng, L. et al. Are there gender differences in young vs. aging brains under risk decision-making? An optical brain imaging study . Brain Imaging and Behavior 11, 1085–1098 (2017). https://doi.org/10.1007/s11682-016-9580-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-016-9580-z

Keywords

Search

Navigation