Somatic Marker Hypothesis

The Basic Idea

Have you ever asked for advice on a nerve-racking, high-stakes decision and received vague advice to “follow your heart” or “go with your gut”? Although you may have wanted more concrete suggestions, according to neuroscientist Antonio Damasio, those clichés may have a point. Damasio’s somatic marker hypothesis (SMH) states that by creating physiological responses, emotions can influence future decision-making processes. This influence can occur both consciously and unconsciously and helps us make difficult decisions quickly.

I continue to be fascinated by the fact that feelings are not just the shady side of reason but that they help us to reach decisions as well.

– Neurologist, Dr. Antonio R. Damasio, in an interview with Scientific American

Key Terms

The somatic marker hypothesis (SMH): A theory suggesting that emotional processes can consciously or unconsciously impact decision-making by creating biomarkers, also known as somatic markers.1

Somatic markers: Changes in the body and brain, which together make up an emotion. They are triggered by one’s perception of external or imagined events and can include both perceptible changes (posture, facial expression) and imperceptible changes (endocrine release, heart rate).1

Iowa gambling task (IGT): A psychological task, created by Antoine Bechara and his colleagues to study decision-making, which asks participants to pick from advantageous and disadvantageous card decks.2

Skin conductance response (SCR): Also referred to as a galvanic skin response or an electrodermal response, is a change in skin conductance, which occurs because of physiological arousal. It is used as a measure of somatic marker activation.1

History

In the late 1980s, researchers Antione Bechara and Antonio Damasio became interested in patients with ventromedial prefrontal (vmPFC) cortex damage. While these patients performed well on intelligence tests, they showed poor personal and social decision-making, repeating mistakes that previously led them to poor outcomes, such as financial and social losses.1,3 They also demonstrated issues in their emotional reactions. The patients experienced difficulties expressing emotions and experiencing emotions appropriate for a given situation. 1 These findings led Damasio to develop the somatic marker hypothesis, which states that patients with vmPFC damage make poorer life decisions and decide more slowly because they don’t have emotional signals to aid the decision-making process.1

To test the somatic marker hypothesis, Damasio, Bechara, and their colleagues created the Iowa gambling task (GT).1,2 This task contains four decks of cards, two of which are disadvantageous (immediate gain, but overall future loss) and two which are advantageous (low immediate gain, but high long-term gain). Their studies found that healthy controls come to prefer the good decks and avoid the bad decks. Patients with vmPFC damage or amygdala damage tended to prefer the bad decks. The researchers also noted that control subjects generated somatic signals, measured by skin conductance responses (SCRs), when they pull an advantageous or disadvantageous card and soon begin to exhibit SCRs before picking up a card. The vmPFC and amygdala patients, however, could not generate these anticipatory SCRs. Importantly, 30% of controls couldn’t consciously verbalize the rules of the game, but still performed well. On the other hand, 50% of vmPFC patients were able to explain which decks are good and bad, yet still performed worse than healthy participants.4 This research suggests that somatic markers encoded during past experiences can later bias our behavior, even at the unconscious level. The absence of this invisible somatic support also explains why patients with vmPFC damage can know what is right, but do what is wrong.

Consequences

Since Damasio first articulated the somatic marker hypothesis, many fields have explored the implications of emotions in decision-making including economics, health, aging, politics, and the study of individual differences in decision-making. The theory is often used to explain risky behaviors such as gambling, unsafe sex, and drug use. SMH proposes that drug-addicted persons may be more likely to use drugs because they aren’t able to use emotional signals to compare short-term gains and long-term losses5. This research can help reduce the stigma surrounding drug use and other choices of risky behavior as it explains that some populations may lack an unconscious advantage.

SMH also influenced economic theory and helped catalyze the field of neuroeconomics, which attempts to explain both rational and irrational choices. Previous economic models proposed that humans are rational agents, which constantly have the mental capacity and information to maximize gains and minimize losses.6 Building on their SMH research, Bechara and Damasio proposed a neural model for economic decisions, which explains that emotions are highly important in making fast and favorable decisions.1

The hypothesis also has important implications for learning, both of humans and autonomous agents. Researchers Sid Carter and Marcia Smith Pasqualini performed the gambling task and saw varying levels of somatic marker responses in their participants.7 They found a strong correlation between the level of SCR before poor choices and successful performance in the task. Their findings suggest the SMH can predict learning in healthy populations. Some researchers believe that AI can also benefit from emotional knowledge, and are proposing methods for incorporating artificial somatic markers into autonomous agents.8

Controversies

Although many researchers agree the SMH explains how emotions guide decision-making, some critics demand more empirical evidence. They state that by selecting patients with both vmPFC damage and impaired social decision-making, the original studies supporting the SMH created a selection bias9. Additionally, some researchers believe that more general learning impairments rather than a lack of somatic markers caused patients with vmPFC to perform poorly on the gambling task. Fellows and Farah believe that vmPFC damaged patients may perform worse because they can’t engage in reversal learning (learning a rule and then unlearning it), which is necessary to perform well in the gambling task as decks which at first seem profitable turn out to be disadvantageous9.

Other researchers, including Maia and McClelland, take issue with the level of awareness participants had in the gambling task10. They state that participants in the task had much more conscious knowledge of the correct decks than previously thought and therefore participants had no need for accessing unconscious markers.

In 2005, Bechara, Damasio, and other supporters of SMH wrote a response to the aforementioned criticisms11. They responded that conscious awareness in the gambling task in no way disproves the hypothesis, as patients with an understanding of which decks will be advantageous in the long term can still perform poorly on the task. The researchers also wrote that reversal learning requires a “stop” signal to reverse a previously learned contingency, and this signal may very well be a somatic marker. In other words, inhibiting previous learning is just another decision somatic markers influence. Years since its inception, the original supporters of the SMH continue to stand their ground that emotions guide decision-making, and so the debate on somatic markers rages on.

Case Studies

Somatic markers and The Ultimatum Game

The field of neuroeconomics studies economic decision-making by taking into consideration neuroscience tools and methods.12 This field attempts to fill in the gaps left by traditional economic theories, which considered humans rational and logical decision-makers. Mascha van ’t Wout and her colleagues contributed to this field by studying how somatic markers affect decision-making in the Ultimatum Game.13 In this game, one of the participants, the proposer, splits a sum of money between themselves and a responder. If the responder accepts their offer, both parties walk away with the agreed-upon amount. If the responder rejects the offer, neither player receives any money. Classical game theory would recommend proposers offer the least amount possible and that the responder accepts regardless of what sum they are offered. In practice, proposers tend to offer approximately half of the sum to the other participant and responders tend to reject offers they deem unfair. Wout and her team wanted to test whether emotional arousal was related to the irrational rejection of smaller offers and used SCRs to reflect emotional responses. Responders exhibited significantly higher SCRs for unfair offers coming from fellow participants compared to fair offers. Greater SCRs in responders also corresponded to a greater amount of offer rejections. The researchers concluded that emotional states play an important role in strategic decision-making and those future economic models take this into consideration.

Interoceptive ability and trading success

Narayanan Kandasamy and his colleagues wanted to see whether results supporting the SMH would hold up outside the lab.14 His team conducted a field experiment on a mid-sized hedge fund in the City of London to test whether the perception of somatic markers assisted traders in making more money. The participants all engaged in high-frequency trading, which often required making important and high-risk decisions very quickly. The researchers quantified the heartbeat detection skills of the traders to determine how advanced they are in perceiving their own physiological signals. Compared to their non-trading controls, traders exhibited a better ability to perceive their own heartbeat. Furthermore, the ability to perceive somatic markers predicted the profitability of the traders and the amount of time they survived in the financial markets. These results provide some initial support for the SMH outside of the lab and can explain why traders often attribute successful decisions to a gut feeling. It is important to note that because this experiment wasn’t a randomized control trial and involved correlations, we can’t make causal claims about interoceptive wisdom and trader success. However, the study does provide more evidence that classical economics can’t account for, suggesting risky decision-making such as trading may best be explained by the emerging field of neuroeconomics.

Related TDL Content

Amygdala

Bechara and Damasio found that in addition to the vmPFC, the amygdala plays an important role in guiding decision-making with the assistance of emotions1. Read this TDL article to learn more about the amygdala, how it guides decision-making, and why awareness of this brain structure can help achieve success in negotiations.

The Empathy Gap

Although the SMH popularized the idea that emotions can influence decision-making, many people still underestimate the effects of emotion on decision-making. This tendency creates an empathy gap, where predictions of one’s future behavior are incorrect due to the assumption that a current mood state will remain unchanged. Read this TDL article to learn more about the empathy gap and how it can help us understand addiction and emotional projection onto others.

Sources

  1. Bechara, A., & Damasio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic Behavior, 52(2), 336–372. https://doi.org/10.1016/j.geb.2004.06.010
  2. Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7–15. https://doi.org/10.1016/0010-0277(94)90018-3
  3. Bechara, A., Damasio, H., Tranel, D., & Anderson, S. W. (1998). Dissociation Of Working Memory from Decision Making within the Human Prefrontal Cortex. The Journal of Neuroscience, 18(1), 428–437. https://doi.org/10.1523/jneurosci.18-01-00428.1998
  4. Bechara, A. (1997). Deciding Advantageously Before Knowing the Advantageous Strategy. Science, 275(5304), 1293–1295. https://doi.org/10.1126/science.275.5304.1293
  5. Miller, P. M., & Bechara, A. (2013). In Biological research on addiction (Vol. 2). essay, Elsevier Academic Press.
  6. Naqvi, N., Shiv, B., & Bechara, A. (2006). The Role of Emotion in Decision Making. Current Directions in Psychological Science, 15(5), 260–264. https://doi.org/10.1111/j.1467-8721.2006.00448.x
  7. Carter, S., & Smith Pasqualini, M. (2004). Stronger autonomic response accompanies better learning: A test of Damasio’s somatic marker hypothesis. Cognition and Emotion, 18(7), 901–911. https://doi.org/10.1080/02699930341000338
  8. Cabrera, D., Cubillos, C., Urra, E., & Mellado, R. (2020). Framework for Incorporating Artificial Somatic Markers in the Decision-Making of Autonomous Agents. Applied Sciences, 10(20), 7361. https://doi.org/10.3390/app10207361
  9. Fellows, L. K., & Farah, M. J. (2004). Different Underlying Impairments in Decision-making Following Ventromedial and Dorsolateral Frontal Lobe Damage in Humans. Cerebral Cortex, 15(1), 58–63. https://doi.org/10.1093/cercor/bhh108
  10. Maia, T. V., & McClelland, J. L. (2004). A reexamination of the evidence for the somatic marker hypothesis: What participants really know in the Iowa gambling task. Proceedings of the National Academy of Sciences, 101(45), 16075–16080. https://doi.org/10.1073/pnas.0406666101
  11. Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (2005). The Iowa Gambling Task and the somatic marker hypothesis: some questions and answers. Trends in Cognitive Sciences, 9(4). https://doi.org/10.1016/j.tics.2005.02.002
  12. Chen, J. (n.d.). What Is Neuroeconomics? Investopedia. https://www.investopedia.com/terms/n/neuroeconomics.asp.
  13. van ’t Wout, M., Kahn, R. S., Sanfey, A. G., & Aleman, A. (2006). Affective state and decision-making in the Ultimatum Game. Experimental Brain Research, 169(4), 564–568. https://doi.org/10.1007/s00221-006-0346-5
  14. Kandasamy, N., Garfinkel, S. N., Page, L., Hardy, B., Critchley, H. D., Gurnell, M., & Coates, J. M. (2016). Interoceptive Ability Predicts Survival on a London Trading Floor. Scientific Reports, 6(1). https://doi.org/10.1038/srep32986

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