People’s Brain Patterns When Making Decisions
By Chenyu Wang
Neuroeconomics, an interdisciplinary field that seeks to explain human decision-making, is the study of how economic behavior can influence human interpretations of the brain, and how neuroscientific findings can shed light on economic models (Loewenstein et al., 2008). Combining neuroscience, economics, and psychology with a focus on the interplay between economic behavior and neural mechanisms, neuroeconomics has become a growing and popular field in recent years. Several highly studied topics are decision-making under risky and ambiguous situations, brain patterns when receiving awards and avoiding losses, and sexual decision-making (Loewenstein et al., 2008).
Research on action-based award-related approaches indicated that the ventromedial prefrontal cortex (vmPFC), located in the frontal lobe at the bottom of the cerebral hemispheres and implicated in the processing of risk and fear, and intraparietal sulcus, one of the two main sulci of the parietal lobe, were precursors of action-based decisions in humans (Wunderlich et al., 2009; Motzkin et al., 2015; Colby & Goldberg, 1999). A more in-depth study on reward-related decision-making was conducted on both human and macaque subjects, with the conclusion that the brain regions in charge of these kinds of choices were relatively similar in human and macaque brains. However, the finer analysis showed that human brains had more active areas than monkeys (Neubert et al., 2015). In a study on people’s reactions to economic fallacies (Martino et al., 2006), scholars used neuroscientific methods to study human brain patterns under the influence of the framing effect, a type of heuristics where participants’ selected choices are impacted by how the options were presented (Martino et al., 2006). Their findings reinforced the crucial role of the amygdala, the region that is highly associated with emotions, in human decision-making.
Behavioral economics divides human decision-making into two categories: The gain and the loss frame, in which the former emphasizes benefits and the latter stresses costs (Wunderlich et al., 2009). These frameworks are defined by values, which refer to the tokens assigned to each action by the brain. Previous research has shown that when evaluating values to make decisions, signals have been found in the orbital and medial prefrontal cortex and amygdala. However, these values were measured after the decision was made and did not show how the decision had been formed. Wunderlich et al. sought to address this knowledge gap. They studied the neural computations embedded in action-based decision-making, focusing on how choices were made between different physical actions to obtain awards and human brain patterns in this process. By using fMRI, they found that action-values for different physical actions arise in the supplementary motor area, and are present regardless of whether the action was chosen or not (Wunderlich et al., 2009). They concluded that the generation of output was directly connected to the action-value signals encoded by certain brain regions. To be specific, the brain areas that were in charge of choosing actions were the vmPFC and intraparietal sulcus, which helped to facilitate the computation prediction error in the brain rather than directly guiding choices. Highlighting an interesting feature in their experiment, the researchers found that there were various kinds of chosen value signals within the vmPFC. For example, the mid-vmPFC region was responsible for hand values when hand movements were selected, and the more posterior part of vmPFC was associated with the value of eye movements when they were selected (Wunderlich et al., 2009). This study revealed that precursors of human decision-making in the brain are different from the outcomes of these choice-making patterns by identifying mechanisms of action-based decision-making.
One prominent scenario of decision-making is reward-guided learning, which depends on a network of brain areas. Experimenters used humans and macaques as subjects to study the brain regions that were active in making reward-related decisions (Neubert et al., 2015). They found that, in general, medial and orbital frontal cortical circuits were responsible for reward-guided decision-making in both humans and macaques. This analysis on the patterns of cross-sectional interactions between multiple brain areas disclosed a finer division between various regions in the anterior cingulate cortex (ACC), vmPFC, and orbitofrontal cortex (OFC) (Neubert et al., 2015). When macaques were making reward-related decisions, their hypothalamus, ventral striatum, and amygdala were active, with lesions in these areas affecting their abilities to make decisions. However, humans and macaques varied in more delicate parcellations between brain components (Neubert et al., 2015).
In contrast, this pattern only resembled a part of human central OFC activity, as the more medial vmPFC serves as the center to investigate value representations. Researchers found that when humans had to make highly ambiguous decisions, their anterior OFC region tended to be active, leading them to believe that the region also tracked values of alternative choices (Neubert et al., 2015). This pattern was unique among humans, as it was not detected in macaques’ brains. The associated fMRI data demonstrated how humans and macaques showed similar activity levels in the medial and orbital frontal cortex area when making value-related decisions, revealing that the nature of decision-making could be universal across species. However, several cortical areas may only be active in humans, indicating the complexity of human decision-making processes.
Though the field of neuroeconomics seeks to study how the human brain functions when processing biased information, most studies focus on activity in the brain when making general decisions. There are a limited number of experiments that explore human brain patterns when undergoing specific behavioral economic heuristics (e.g., availability heuristic).
In conclusion, the study of neuroeconomics shows that humans do not make entirely rational decisions as predicted by machines. Currently, many enterprises have taken advantage of the scientific results yielded in the neuroeconomic domain to leverage attractive commercials. The advanced understanding of neuroeconomics also raises an ethical question on whether these findings will help consumers better identify marketing traps or assist corporations with increasing sales revenue. With the knowledge of neural-level brain patterns, scientists can better interpret the activity of brain regions involved in human decision-making processes, analyze the human brain’s relations with psychological factors, and alert people about potential emotional biases.
About the Author
Chenyu Wang is a visiting undergraduate student at Harvard College (home institution: University of California, Berkeley).
References
Colby, C. L., & Goldberg, M. E. (1999). Space and attention in parietal cortex. Annual Review of Neuroscience, 22(1), 319-349.
De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684-687.
Loewenstein, G., Rick, S., & Cohen, J. D. (2008). Neuroeconomics. Annual Review of Psychology, 59, 647–672.
Motzkin, J. C., Philippi, C. L., Wolf, R. C., Baskaya, M. K., & Koenigs, M. (2015). Ventromedial prefrontal cortex is critical for the regulation of amygdala activity in humans. Biological psychiatry, 77(3), 276-284.
Neubert, F. X., Mars, R. B., Sallet, J., & Rushworth, M. F. (2015). Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex. PNAS Proceedings of the National Academy of Sciences of the United States of America, 112(20), E2695-E2704.
Wunderlich, K., Rangel, A., & O’Doherty, J. P. (2009). Neural computations underlying action-based decision making in the human brain. PNAS Proceedings of the National Academy of Sciences of the United States of America, 106(40), 17199–17204.
Research on action-based award-related approaches indicated that the ventromedial prefrontal cortex (vmPFC), located in the frontal lobe at the bottom of the cerebral hemispheres and implicated in the processing of risk and fear, and intraparietal sulcus, one of the two main sulci of the parietal lobe, were precursors of action-based decisions in humans (Wunderlich et al., 2009; Motzkin et al., 2015; Colby & Goldberg, 1999). A more in-depth study on reward-related decision-making was conducted on both human and macaque subjects, with the conclusion that the brain regions in charge of these kinds of choices were relatively similar in human and macaque brains. However, the finer analysis showed that human brains had more active areas than monkeys (Neubert et al., 2015). In a study on people’s reactions to economic fallacies (Martino et al., 2006), scholars used neuroscientific methods to study human brain patterns under the influence of the framing effect, a type of heuristics where participants’ selected choices are impacted by how the options were presented (Martino et al., 2006). Their findings reinforced the crucial role of the amygdala, the region that is highly associated with emotions, in human decision-making.
Behavioral economics divides human decision-making into two categories: The gain and the loss frame, in which the former emphasizes benefits and the latter stresses costs (Wunderlich et al., 2009). These frameworks are defined by values, which refer to the tokens assigned to each action by the brain. Previous research has shown that when evaluating values to make decisions, signals have been found in the orbital and medial prefrontal cortex and amygdala. However, these values were measured after the decision was made and did not show how the decision had been formed. Wunderlich et al. sought to address this knowledge gap. They studied the neural computations embedded in action-based decision-making, focusing on how choices were made between different physical actions to obtain awards and human brain patterns in this process. By using fMRI, they found that action-values for different physical actions arise in the supplementary motor area, and are present regardless of whether the action was chosen or not (Wunderlich et al., 2009). They concluded that the generation of output was directly connected to the action-value signals encoded by certain brain regions. To be specific, the brain areas that were in charge of choosing actions were the vmPFC and intraparietal sulcus, which helped to facilitate the computation prediction error in the brain rather than directly guiding choices. Highlighting an interesting feature in their experiment, the researchers found that there were various kinds of chosen value signals within the vmPFC. For example, the mid-vmPFC region was responsible for hand values when hand movements were selected, and the more posterior part of vmPFC was associated with the value of eye movements when they were selected (Wunderlich et al., 2009). This study revealed that precursors of human decision-making in the brain are different from the outcomes of these choice-making patterns by identifying mechanisms of action-based decision-making.
One prominent scenario of decision-making is reward-guided learning, which depends on a network of brain areas. Experimenters used humans and macaques as subjects to study the brain regions that were active in making reward-related decisions (Neubert et al., 2015). They found that, in general, medial and orbital frontal cortical circuits were responsible for reward-guided decision-making in both humans and macaques. This analysis on the patterns of cross-sectional interactions between multiple brain areas disclosed a finer division between various regions in the anterior cingulate cortex (ACC), vmPFC, and orbitofrontal cortex (OFC) (Neubert et al., 2015). When macaques were making reward-related decisions, their hypothalamus, ventral striatum, and amygdala were active, with lesions in these areas affecting their abilities to make decisions. However, humans and macaques varied in more delicate parcellations between brain components (Neubert et al., 2015).
In contrast, this pattern only resembled a part of human central OFC activity, as the more medial vmPFC serves as the center to investigate value representations. Researchers found that when humans had to make highly ambiguous decisions, their anterior OFC region tended to be active, leading them to believe that the region also tracked values of alternative choices (Neubert et al., 2015). This pattern was unique among humans, as it was not detected in macaques’ brains. The associated fMRI data demonstrated how humans and macaques showed similar activity levels in the medial and orbital frontal cortex area when making value-related decisions, revealing that the nature of decision-making could be universal across species. However, several cortical areas may only be active in humans, indicating the complexity of human decision-making processes.
Though the field of neuroeconomics seeks to study how the human brain functions when processing biased information, most studies focus on activity in the brain when making general decisions. There are a limited number of experiments that explore human brain patterns when undergoing specific behavioral economic heuristics (e.g., availability heuristic).
In conclusion, the study of neuroeconomics shows that humans do not make entirely rational decisions as predicted by machines. Currently, many enterprises have taken advantage of the scientific results yielded in the neuroeconomic domain to leverage attractive commercials. The advanced understanding of neuroeconomics also raises an ethical question on whether these findings will help consumers better identify marketing traps or assist corporations with increasing sales revenue. With the knowledge of neural-level brain patterns, scientists can better interpret the activity of brain regions involved in human decision-making processes, analyze the human brain’s relations with psychological factors, and alert people about potential emotional biases.
About the Author
Chenyu Wang is a visiting undergraduate student at Harvard College (home institution: University of California, Berkeley).
References
Colby, C. L., & Goldberg, M. E. (1999). Space and attention in parietal cortex. Annual Review of Neuroscience, 22(1), 319-349.
De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684-687.
Loewenstein, G., Rick, S., & Cohen, J. D. (2008). Neuroeconomics. Annual Review of Psychology, 59, 647–672.
Motzkin, J. C., Philippi, C. L., Wolf, R. C., Baskaya, M. K., & Koenigs, M. (2015). Ventromedial prefrontal cortex is critical for the regulation of amygdala activity in humans. Biological psychiatry, 77(3), 276-284.
Neubert, F. X., Mars, R. B., Sallet, J., & Rushworth, M. F. (2015). Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex. PNAS Proceedings of the National Academy of Sciences of the United States of America, 112(20), E2695-E2704.
Wunderlich, K., Rangel, A., & O’Doherty, J. P. (2009). Neural computations underlying action-based decision making in the human brain. PNAS Proceedings of the National Academy of Sciences of the United States of America, 106(40), 17199–17204.