Variables influencing the neural correlates of perceived risk of physical harm
Tóm tắt
Many human activities involve a risk of physical harm. However, not much is known about the specific brain regions involved in decision making regarding these risks. To explore the neural correlates of risk perception for physical harms, 19 participants took part in an event-related fMRI study while rating risky activities. The scenarios varied in level of potential harm (e.g., paralysis vs. stubbed toe), likelihood of injury (e.g., 1 chance in 100 vs. 1 chance in 1,000), and format (frequency vs. probability). Networks of brain regions were responsive to different aspects of risk information. Cortical language- processing areas, the middle temporal gyrus, and a region around the bed nucleus of stria terminalis responded more strongly to high- harm conditions. Prefrontal areas, along with subcortical ventral striatum, responded preferentially to high- likelihood conditions. Participants rated identical risks to be greater when information was presented in frequency format rather than probability format. These findings indicate that risk assessments for physical harm engage a broad network of brain regions that are sensitive to the severity of harm, the likelihood of risk, and the framing of risk information.
Tài liệu tham khảo
De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313, 684–687. doi:10.1126/science.1128356.
Diaz, M. T., & McCarthy, G. (2009). A comparison of brain activity evoked by single content and function words: An fMRI investigation of implicit word processing. Brain Research, 28, 38–49.
Ghashghaei, H. T., & Barbas, H. (2002). Pathways for emotion: Interactions of prefrontal and anterior temporal pathways in the amygdala of the rhesus monkey. Neuroscience, 115, 1261–1279.
Gigerenzer, G. (1998). Ecological intelligence: An adaptation for frequencies. In D. D. Cummins & C. Allen (Eds.), The evolution of mind (pp. 9–29). New York: Oxford University Press.
Groenewegen, H. J., Wright, C. I., & Uylings, H. B. (1997). The anatomical relationships of the prefrontal cortex with limbic structures and the basal ganglia. Journal of Psychopharmacology, 11, 99–106.
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005). Neural systems responding to degrees of uncertainty in human decision-making. Science, 310, 1680–1683. doi:10.1126/science.1115327.
Jones, O. D., & Goldsmith, T. H. (2005). Law and behavioral biology. Columbia Law Review, 105, 405–502.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.
Kelley, T. A., & Yantis, S. (2010). Neural correlates of learning to attend. Frontiers in Human Neuroscience, 4, 1–11.
Koehler, J. J. (2001). The psychology of numbers in the courtroom: How to make DNA match statistics seem impressive or insufficient. Southern California Law Review, 74, 1275–1306.
Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience, 21, RC159.
Krebs, R. M., Schott, B. H., & Düzel, E. (2009). Personality traits are differentially associated with patterns of reward and novelty processing in the human substantia nigra/ventral tegmental area. Biological Psychiatry, 65, 103–110. doi:10.1016/j.biopsych.2008.08.019.
Kuhnen, C. M., & Knutson, B. (2005). The neural basis of financial risk taking. Neuron, 47, 763–770.
Lieberman, M. D., Eisenberger, N. I., Crockett, M. J., Tom, S. M., Pfeifer, J. H., & Way, B. M. (2007). Putting feelings into words: Affect labeling disrupts amygdala activity in response to affective stimuli. Psychological Science, 18, 421–428. doi:10.1111/j.1467-9280.2007.01916.x.
Mason, R. A., & Just, M. A. (2011). Differentiable cortical networks for inferences concerning people’s intentions versus physical causality. Human Brain Mapping, 32, 313–329. doi:10.1002/hbm.21021.
McDonald, A. J., Mascagni, F., & Guo, L. (1996). Projections of the medial and lateral prefrontal cortices to the amygdala: A Phaseolus vulgaris leucoagglutinin study in the rat. Neuroscience, 71, 55–75. doi:10.1016/0306-4522(95)00417-3.
Muhammad, R., Wallis, J. D., & Miller, E. K. (2006). A comparison of abstract rules in the prefrontal cortex, premotor cortex, inferior temporal cortex, and striatum. Journal of Cognitive Neuroscience, 18, 974–989. doi:10.1162/jocn.2006.18.6.974.
Newman, R. L., & Joanisse, M. F. (2011). Modulation of brain regions involved in word recognition by homophonous stimuli: An fMRI study. Brain Research, 1367, 250–264.
Ochsner, K. N., Hughes, B., Robertson, E. R., Cooper, J. C., & Gabrieli, J. D. E. (2009). Neural systems supporting the control of affective and cognitive conflicts. Journal of Cognitive Neuroscience, 21, 1841–1854. doi:10.1162/jocn.2009.21129.
Phillips, R. G., & LeDoux, J. E. (1992). Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behavioral Neuroscience, 106, 274–285. doi:10.1037/0735-7044.106.2.274.
Preuschoff, K., Bossaerts, P., & Quartz, S. R. (2006). Neural differentiation of expected reward and risk in human subcortical structures. Neuron, 51, 381–390.
Quirk, G. J., Likhtik, E., Pelletier, J. G., & Paré, D. (2003). Stimulation of medial prefrontal cortex decreases the responsiveness of central amygdala output neurons. Journal of Neuroscience, 23, 8800–8807.
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, 902–910.
Seymour, B., Daw, N., Dayan, P., Singer, T., & Dolan, R. (2007). Differential encoding of losses and gains in the human striatum. Journal of Neuroscience, 27, 4826–4831. doi:10.1523/JNEUROSCI.0400-07.2007.
Siegrist, M. (1997). Communicating low risk magnitudes: Incidence rates expressed as frequency versus rates expressed as probability. Risk Analysis, 17, 507–510.
Slovic, P., Monahan, J., & MacGregor, D. G. (2000). Violence risk assessment and risk communication: The effects of using actual cases, providing instruction and employing probability verses frequency formats. Law and Human Behavior, 24, 271–296.
Straube, T., Mentzel, H. J., & Miltnera, W. H. R. (2007). Waiting for spiders: Brain activation during anticipatory anxiety in spider phobics. NeuroImage, 37, 1427–1436.
Taylor, S. F., Phan, K. L., Decker, L. R., & Liberzon, I. (2003). Subjective rating of emotionally salient stimuli modulates neural activity. NeuroImage, 18, 650–659.
Tobler, P. N., O’Doherty, J. P., Dolan, R. J., & Schultz, W. (2007). Reward value coding distinct from risk attitude-related uncertainty coding in human reward systems. Journal of Neurophysiology, 97, 1621–1632.
Viscusi, W. K., & Evans, W. (1990). Utility functions that depend on health status: Estimates and economic implications. American Economic Review, 80, 353–374.
Vorhold, V., Giessing, C., Wiedemann, P. M., Schütz, H., Gauggel, S., & Fink, G. R. (2007). The neural basis of risk ratings: Evidence from a functional magnetic resonance imaging (fMRI) study. Neuropsychologia, 45, 3242–3250. doi:10.1016/j.neuropsychologia.2007.06.023.
Walton, M. E., Croxson, P. L., Behrens, T. E. J., Kennerley, S. W., & Rushworth, M. F. S. (2007). Adaptive decision making and value in the anterior cingulate cortex. NeuroImage, 36, T142–T154.
Weber, E. U., Blais, A.-R., & Betz, N. E. (2002). A domain-specific risk-attitude scale: Measuring risk perceptions and risk behaviors. Journal of Behavioral Decision Making, 15, 263–290.
Wolfensteller, U., & von Cramon, D. Y. (2010). Bending the rules: Strategic behavioral differences are reflected in the brain. Journal of Cognitive Neuroscience, 22, 278–291.
Yamagishi, K. (1997). When a 12.86% mortality is more dangerous than 24.14%: Implications for risk communication. Applied Cognitive Psychology, 11, 495–506. doi:1.1002/(SICI)1099-0720(199712)11:6<495::AID-ACP481>3.CO;2-J.