1
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van Brussel LD, Boksem MAS, Dietvorst RC, Smidts A. Brain activity of professional investors signals future stock performance. Proc Natl Acad Sci U S A 2024; 121:e2307982121. [PMID: 38593084 PMCID: PMC11032448 DOI: 10.1073/pnas.2307982121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 01/12/2024] [Indexed: 04/11/2024] Open
Abstract
A major aspiration of investors is to better forecast stock performance. Interestingly, emerging "neuroforecasting" research suggests that brain activity associated with anticipatory reward relates to market behavior and population-wide preferences, including stock price dynamics. In this study, we extend these findings to professional investors processing comprehensive real-world information on stock investment options while making predictions of long-term stock performance. Using functional MRI, we sampled investors' neural responses to investment cases and assessed whether these responses relate to future performance on the stock market. We found that our sample of investors could not successfully predict future market performance of the investment cases, confirming that stated preferences do not predict the market. Stock metrics of the investment cases were not predictive of future stock performance either. However, as investors processed case information, nucleus accumbens (NAcc) activity was higher for investment cases that ended up overperforming in the market. These findings remained robust, even when controlling for stock metrics and investors' predictions made in the scanner. Cross-validated prediction analysis indicated that NAcc activity could significantly predict future stock performance out-of-sample above chance. Our findings resonate with recent neuroforecasting studies and suggest that brain activity of professional investors may help in forecasting future stock performance.
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Affiliation(s)
- Leonard D. van Brussel
- Rotterdam School of Management, Department of Marketing Management, Erasmus University, Rotterdam3062PA, The Netherlands
| | - Maarten A. S. Boksem
- Rotterdam School of Management, Department of Marketing Management, Erasmus University, Rotterdam3062PA, The Netherlands
| | | | - Ale Smidts
- Rotterdam School of Management, Department of Marketing Management, Erasmus University, Rotterdam3062PA, The Netherlands
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2
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Lussange J, Vrizzi S, Palminteri S, Gutkin B. Mesoscale effects of trader learning behaviors in financial markets: A multi-agent reinforcement learning study. PLoS One 2024; 19:e0301141. [PMID: 38557590 PMCID: PMC10984546 DOI: 10.1371/journal.pone.0301141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/08/2024] [Indexed: 04/04/2024] Open
Abstract
Recent advances in the field of machine learning have yielded novel research perspectives in behavioural economics and financial markets microstructure studies. In this paper we study the impact of individual trader leaning characteristics on markets using a stock market simulator designed with a multi-agent architecture. Each agent, representing an autonomous investor, trades stocks through reinforcement learning, using a centralized double-auction limit order book. This approach allows us to study the impact of individual trader traits on the whole stock market at the mesoscale in a bottom-up approach. We chose to test three trader trait aspects: agent learning rate increases, herding behaviour and random trading. As hypothesized, we find that larger learning rates significantly increase the number of crashes. We also find that herding behaviour undermines market stability, while random trading tends to preserve it.
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Affiliation(s)
- Johann Lussange
- Laboratoire des Neurosciences Cognitives, Département des Études Cognitives, INSERM U960, Paris, France
| | - Stefano Vrizzi
- Laboratoire des Neurosciences Cognitives, Département des Études Cognitives, INSERM U960, Paris, France
| | - Stefano Palminteri
- Laboratoire des Neurosciences Cognitives, Département des Études Cognitives, INSERM U960, Paris, France
- Center for Cognition and Decision Making, Department of Psychology, NU University Higher School of Economics, Moscow, Russia
| | - Boris Gutkin
- Laboratoire des Neurosciences Cognitives, Département des Études Cognitives, INSERM U960, Paris, France
- Center for Cognition and Decision Making, Department of Psychology, NU University Higher School of Economics, Moscow, Russia
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3
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Fränken JP, Valentin S, Lucas CG, Bramley NR. Naïve information aggregation in human social learning. Cognition 2024; 242:105633. [PMID: 37897881 DOI: 10.1016/j.cognition.2023.105633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/30/2023]
Abstract
To glean accurate information from social networks, people should distinguish evidence from hearsay. For example, when testimony depends on others' beliefs as much as on first-hand information, there is a danger of evidence becoming inflated or ignored as it passes from person to person. We compare human inferences with an idealized rational account that anticipates and adjusts for these dependencies by evaluating peers' communications with respect to the underlying communication pathways. We report on three multi-player experiments examining the dynamics of both mixed human-artificial and all-human social networks. Our analyses suggest that most human inferences are best described by a naïve learning account that is insensitive to known or inferred dependencies between network peers. Consequently, we find that simulated social learners that assume their peers behave rationally make systematic judgment errors when reasoning on the basis of actual human communications. We suggest human groups learn collectively through naïve signaling and aggregation that is computationally efficient and surprisingly robust. Overall, our results challenge the idea that everyday social inference is well captured by idealized rational accounts and provide insight into the conditions under which collective wisdom can emerge from social interactions.
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Affiliation(s)
- J-Philipp Fränken
- Stanford University, United States of America; The University of Edinburgh, United Kingdom.
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4
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Park B, Smith VR. Blame and Praise cross-culturally: An fMRI investigation into causal attribution and moral judgment. Biol Psychol 2023; 184:108713. [PMID: 37839520 DOI: 10.1016/j.biopsycho.2023.108713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 10/11/2023] [Accepted: 10/11/2023] [Indexed: 10/17/2023]
Abstract
People from independent cultures are more likely to causally explain others' behaviors by their disposition [vs. situation] compared to those from interdependent cultures. However, few studies have directly examined how these differences in attribution shape individuals' moral judgment, nor the underlying neural mechanisms of this process. Aiming to address these questions, in the scanner, participants rated the blameworthiness or praiseworthiness of protagonists who did either a negative or positive behavior, respectively. These behaviors were pretested and found to be perceived as dispositionally or situationally caused to different extents on average. Regardless of their self-construal, participants showed enhanced dorsomedial prefrontal cortex (dmPFC) activity in response to the behaviors that were evaluated as more situationally caused on average. Importantly, relatively independent participants reduced their blame for the behaviors that they showed greater dmPFC activity to. Relatively interdependent participants reduced blame for the behaviors that they themselves inferred more situational causes for, but dmPFC activity did not explain their blame. These findings suggest that while dmPFC might support relatively independent participants' effortful consideration of situational contributors to a behavior to make moral judgments, relatively interdependent participants might engage in this process automatically and relied less on dmPFC recruitment.
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5
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Alon N, Schulz L, Rosenschein JS, Dayan P. A (Dis-)information Theory of Revealed and Unrevealed Preferences: Emerging Deception and Skepticism via Theory of Mind. Open Mind (Camb) 2023; 7:608-624. [PMID: 37840764 PMCID: PMC10575559 DOI: 10.1162/opmi_a_00097] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 07/19/2023] [Indexed: 10/17/2023] Open
Abstract
In complex situations involving communication, agents might attempt to mask their intentions, exploiting Shannon's theory of information as a theory of misinformation. Here, we introduce and analyze a simple multiagent reinforcement learning task where a buyer sends signals to a seller via its actions, and in which both agents are endowed with a recursive theory of mind. We show that this theory of mind, coupled with pure reward-maximization, gives rise to agents that selectively distort messages and become skeptical towards one another. Using information theory to analyze these interactions, we show how savvy buyers reduce mutual information between their preferences and actions, and how suspicious sellers learn to reinterpret or discard buyers' signals in a strategic manner.
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Affiliation(s)
- Nitay Alon
- Department of Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Lion Schulz
- Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | | | - Peter Dayan
- Department of Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Computer Science, University of Tübingen, Tübingen, Germany
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6
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Chen X, Liu J, Luo YJ, Feng C. Brain Systems Underlying Fundamental Motivations of Human Social Conformity. Neurosci Bull 2023; 39:328-342. [PMID: 36287291 PMCID: PMC9905476 DOI: 10.1007/s12264-022-00960-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 07/11/2022] [Indexed: 01/10/2023] Open
Abstract
From birth to adulthood, we often align our behaviors, attitudes, and opinions with a majority, a phenomenon known as social conformity. A seminal framework has proposed that conformity behaviors are mainly driven by three fundamental motives: a desire to gain more information to be accurate, to obtain social approval from others, and to maintain a favorable self-concept. Despite extensive interest in neuroimaging investigation of social conformity, the relationship between brain systems and these fundamental motivations has yet to be established. Here, we reviewed brain imaging findings of social conformity with a componential framework, aiming to reveal the neuropsychological substrates underlying different conformity motivations. First, information-seeking engages the evaluation of social information, information integration, and modification of task-related activity, corresponding to brain networks implicated in reward, cognitive control, and tasks at hand. Second, social acceptance involves the anticipation of social acceptance or rejection and mental state attribution, mediated by networks of reward, punishment, and mentalizing. Third, self-enhancement entails the excessive representation of positive self-related information and suppression of negative self-related information, ingroup favoritism and/or outgroup derogation, and elaborated mentalizing processes to the ingroup, supported by brain systems of reward, punishment, and mentalizing. Therefore, recent brain imaging studies have provided important insights into the fundamental motivations of social conformity in terms of component processes and brain mechanisms.
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Affiliation(s)
- Xinling Chen
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Jiaxi Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China
- School of Psychology, South China Normal University, Guangzhou, 510631, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Yue-Jia Luo
- Department of Applied Psychology, University of Health and Rehabilitation Sciences, Qingdao, 266113, China.
- The State Key Lab of Cognitive and Learning, Faculty of Psychology, Beijing Normal University, Beijing, 100875, China.
- The Research Center of Brain Science and Visual Cognition, Kunming University of Science and Technology, Kunming, 650506, China.
- College of Teacher Education, Qilu Normal University, Jinan, 250200, China.
| | - Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou, 510631, China.
- School of Psychology, South China Normal University, Guangzhou, 510631, China.
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.
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7
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Culture, theory-of-mind, and morality: How independent and interdependent minds make moral judgments. Biol Psychol 2022; 174:108423. [PMID: 36075489 DOI: 10.1016/j.biopsycho.2022.108423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 08/30/2022] [Accepted: 09/01/2022] [Indexed: 11/23/2022]
Abstract
Although the investigation of the neural mechanisms of morality has increased in recent years, the neural underpinnings of cultural variations in judgments of morality is understudied. In this paper, we propose that the well-established cultural differences in two cognitive processes, consideration of mental state and causal attribution, would lead to differences in moral judgment. Specifically, North Americans rely heavily on the mental state of a protagonist and dispositional attributions, whereas East Asians focus more on situational attributions and place less emphasis on the mental state of a protagonist. These differences would be accounted for by activity in brain regions implicated in thinking about others' minds, or theory-of-mind (ToM), which would underlie the cultural shaping of moral judgment. This proposed cultural neuroscience approach may broaden the scope of morality research, better predict moral behavior, and reduce disparities in diverse groups' moral judgment.
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8
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Singh M, Xu Q, Wang SJ, Hong T, Ghassemi MM, Lo AW. Real-time extended psychophysiological analysis of financial risk processing. PLoS One 2022; 17:e0269752. [PMID: 35877608 PMCID: PMC9312384 DOI: 10.1371/journal.pone.0269752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/27/2022] [Indexed: 11/19/2022] Open
Abstract
We study the relationships between the real-time psychophysiological activity of professional traders, their financial transactions, and market fluctuations. We collected multiple physiological signals such as heart rate, blood volume pulse, and electrodermal activity of 55 traders at a leading global financial institution during their normal working hours over a five-day period. Using their physiological measurements, we implemented a novel metric of trader’s “psychophysiological activation” to capture affect such as excitement, stress and irritation. We find statistically significant relations between traders’ psychophysiological activation levels and such as their financial transactions, market fluctuations, the type of financial products they traded, and their trading experience. We conducted post-measurement interviews with traders who participated in this study to obtain additional insights in the key factors driving their psychophysiological activation during financial risk processing. Our work illustrates that psychophysiological activation plays a prominent role in financial risk processing for professional traders.
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Affiliation(s)
- Manish Singh
- MIT Laboratory for Financial Engineering, Cambridge, Massachusetts, United States of America
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Qingyang Xu
- MIT Laboratory for Financial Engineering, Cambridge, Massachusetts, United States of America
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Sarah J. Wang
- MIT Laboratory for Financial Engineering, Cambridge, Massachusetts, United States of America
| | - Tinah Hong
- MIT Laboratory for Financial Engineering, Cambridge, Massachusetts, United States of America
| | - Mohammad M. Ghassemi
- Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, United States of America
- Ghamut Corporation, East Lansing, MI, United States of America
| | - Andrew W. Lo
- MIT Laboratory for Financial Engineering, Cambridge, Massachusetts, United States of America
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- MIT Sloan School of Management, Cambridge, Massachusetts, United States of America
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- * E-mail:
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9
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Transferring cognitive talent across domains to reduce the disposition effect in investment. Sci Rep 2021; 11:23068. [PMID: 34845327 PMCID: PMC8630220 DOI: 10.1038/s41598-021-02596-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 11/11/2021] [Indexed: 11/22/2022] Open
Abstract
We consider Theory of Mind (ToM), the ability to correctly predict the intentions of others. To an important degree, good ToM function requires abstraction from one’s own particular circumstances. Here, we posit that such abstraction can be transferred successfully to other, non-social contexts. We consider the disposition effect, which is a pervasive cognitive bias whereby investors, including professionals, improperly take their personal trading history into account when deciding on investments. We design an intervention policy whereby we attempt to transfer good ToM function, subconsciously, to personal investment decisions. In a within-subject repeated-intervention laboratory experiment, we record how the disposition effect is reduced by a very significant 85%, but only for those with high scores on the social-cognitive dimension of ToM function. No such transfer is observed in subjects who score well only on the social-perceptual dimension of ToM function. Our findings open up a promising way to exploit cognitive talent in one domain in order to alleviate cognitive deficiencies elsewhere.
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10
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Functional Connectivity Basis and Underlying Cognitive Mechanisms for Gender Differences in Guilt Aversion. eNeuro 2021; 8:ENEURO.0226-21.2021. [PMID: 34819311 PMCID: PMC8675089 DOI: 10.1523/eneuro.0226-21.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 11/05/2021] [Accepted: 11/18/2021] [Indexed: 11/21/2022] Open
Abstract
Prosocial behavior is pivotal to our society. Guilt aversion, which describes the tendency to reduce the discrepancy between a partner's expectation and his/her actual outcome, drives human prosocial behavior as does well-known inequity aversion. Although women are reported to be more inequity averse than men, gender differences in guilt aversion remain unexplored. Here, we conducted a functional magnetic resonance imaging (fMRI) study (n = 52) and a large-scale online behavioral study (n = 4723) of a trust game designed to investigate guilt and inequity aversions. The fMRI study demonstrated that men exhibited stronger guilt aversion and recruited right dorsolateral prefrontal cortex (DLPFC)-ventromedial PFC (VMPFC) connectivity more for guilt aversion than women, while VMPFC-dorsal medial PFC (DMPFC) connectivity was commonly used in both genders. Furthermore, our regression analysis of the online behavioral data collected with Big Five and demographic factors replicated the gender differences and revealed that Big Five Conscientiousness (rule-based decision) correlated with guilt aversion only in men, but Agreeableness (empathetic consideration) correlated with guilt aversion in both genders. Thus, this study suggests that gender differences in prosocial behavior are heterogeneous depending on underlying motives in the brain and that the consideration of social norms plays a key role in the stronger guilt aversion in men.
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11
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Konovalov A, Hill C, Daunizeau J, Ruff CC. Dissecting functional contributions of the social brain to strategic behavior. Neuron 2021; 109:3323-3337.e5. [PMID: 34407389 DOI: 10.1016/j.neuron.2021.07.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 06/21/2021] [Accepted: 07/27/2021] [Indexed: 10/20/2022]
Abstract
Social interactions routinely lead to neural activity in a "social brain network" comprising, among other regions, the temporoparietal junction (TPJ) and the dorsomedial prefrontal cortex (dmPFC). But what is the function of these areas? Are they specialized for behavior in social contexts or do they implement computations required for dealing with any reactive process, even non-living entities? Here, we use fMRI and a game paradigm separating the need for these two aspects of cognition. We find that most social-brain areas respond to both social and non-social reactivity rather than just to human opponents. However, the TPJ shows a dissociation from the dmPFC: its activity and connectivity primarily reflect context-dependent outcome processing and reactivity detection, while dmPFC engagement is linked to implementation of a behavioral strategy. Our results characterize an overarching computational property of the social brain but also suggest specialized roles for subregions of this network.
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Affiliation(s)
- Arkady Konovalov
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich 8006, Switzerland.
| | - Christopher Hill
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich 8006, Switzerland
| | - Jean Daunizeau
- Université Pierre et Marie Curie, Paris, France; Institut du Cerveau et de la Moelle épinière, Paris, France; INSERM UMR S975, Paris, France
| | - Christian C Ruff
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich 8006, Switzerland.
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12
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Connectivity adaptations in dopaminergic systems define the brain maturity of investors. Sci Rep 2021; 11:11671. [PMID: 34083626 PMCID: PMC8175592 DOI: 10.1038/s41598-021-91227-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 05/21/2021] [Indexed: 11/09/2022] Open
Abstract
Investment decisions rely on perceptions from external stimuli along with the integration of inner brain-body signals, all of which are shaped by experience. As experience is capable of molding both the structure and function of the human brain, we have used a novel neuroimaging connectomic-genetic approach to investigate the influence of investment work experience on brain anatomy. We found that senior investors display higher gray matter volume and increased structural brain connectivity in dopamine-related pathways, as well as a set of genes functionally associated with adrenaline and noradrenaline biosynthesis (SLC6A3, TH and SLC18A2), which is seemingly involved in reward processing and bodily stress responses during financial trading. These results suggest the key role of catecholamines in the way senior investors harness their emotions while raising bodily awareness as they grow in investment maturity.
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Toma FM, Miyakoshi M. Left Frontal EEG Power Responds to Stock Price Changes in a Simulated Asset Bubble Market. Brain Sci 2021; 11:brainsci11060670. [PMID: 34063778 PMCID: PMC8223788 DOI: 10.3390/brainsci11060670] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 11/16/2022] Open
Abstract
Financial bubbles are a result of aggregate irrational behavior and cannot be explained by standard economic pricing theory. Research in neuroeconomics can improve our understanding of their causes. We conducted an experiment in which 28 healthy subjects traded in a simulated market bubble, while scalp EEG was recorded using a low-cost, BCI-friendly desktop device with 14 electrodes. Independent component (IC) analysis was performed to decompose brain signals and the obtained scalp topography was used to cluster the ICs. We computed single-trial time-frequency power relative to the onset of stock price display and estimated the correlation between EEG power and stock price across trials using a general linear model. We found that delta band (1-4 Hz) EEG power within the left frontal region negatively correlated with the trial-by-trial stock prices including the financial bubble. We interpreted the result as stimulus-preceding negativity (SPN) occurring as a dis-inhibition of the resting state network. We conclude that the combination between the desktop-BCI-friendly EEG, the simulated financial bubble and advanced signal processing and statistical approaches could successfully identify the neural correlate of the financial bubble. We add to the neuroeconomics literature a complementary EEG neurometric as a bubble predictor, which can further be explored in future decision-making experiments.
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Affiliation(s)
| | - Makoto Miyakoshi
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0559, USA
- Correspondence:
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14
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Brain Activity Foreshadows Stock Price Dynamics. J Neurosci 2021; 41:3266-3274. [PMID: 33685944 PMCID: PMC8026346 DOI: 10.1523/jneurosci.1727-20.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 02/11/2021] [Accepted: 02/13/2021] [Indexed: 11/21/2022] Open
Abstract
Successful investing is challenging since stock prices are difficult to consistently forecast. Recent neuroimaging evidence suggests, however, that activity in brain regions associated with anticipatory affect may not only predict individual choice, but also forecast aggregate behavior out-of-sample. Thus, in two experiments, we specifically tested whether anticipatory affective brain activity in healthy humans could forecast aggregate changes in stock prices. Using functional magnetic resonance imaging, we found in a first experiment (n = 34, 6 females; 140 trials/subject) that nucleus accumbens activity forecast stock price direction, whereas anterior insula (AIns) activity forecast stock price inflections. In a second preregistered replication experiment (n = 39, 7 females) that included different subjects and stocks, AIns activity still forecast stock price inflections. Importantly, AIns activity forecast stock price movement even when choice behavior and conventional stock indicators did not (e.g., previous stock price movements), and classifier analysis indicated that forecasts based on brain activity should generalize to other markets. By demonstrating that AIns activity might serve as a leading indicator of stock price inflections, these findings imply that neural activity associated with anticipatory affect may extend to forecasting aggregate choice in dynamic and competitive environments such as stock markets.SIGNIFICANCE STATEMENT Many try but fail to consistently forecast changes in stock prices. New evidence, however, suggests that anticipatory affective brain activity may not only predict individual choice, but also may forecast aggregate choice. Assuming that stock prices index collective choice, we tested whether brain activity sampled during the assessment of stock prices could forecast subsequent changes in the prices of those stocks. In two neuroimaging experiments, a combination of previous stock price movements and brain activity in a region implicated in processing uncertainty and arousal forecast next-day stock price changes-even when behavior did not. These findings challenge traditional assumptions of market efficiency by implying that neuroimaging data might reveal "hidden information" capable of foreshadowing stock price dynamics.
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15
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An ALE Meta-Analysis on Investment Decision-Making. Brain Sci 2021; 11:brainsci11030399. [PMID: 33801075 PMCID: PMC8003996 DOI: 10.3390/brainsci11030399] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 11/16/2022] Open
Abstract
It is claimed that investment decision-making should rely on rational analyses based on facts and not emotions. However, trying to make money out of market forecasts can trigger all types of emotional responses. As the question on how investors decide remains controversial, we carried out an activation likelihood estimation (ALE) meta-analysis using functional magnetic resonance imaging (fMRI) studies that have reported whole-brain analyses on subjects performing an investment task. We identified the ventral striatum, anterior insula, amygdala and anterior cingulate cortex as being involved in this decision-making process. These regions are limbic-related structures which respond to reward, risk and emotional conflict. Our findings support the notion that investment choices are emotional decisions that take into account market information, individual preferences and beliefs.
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16
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Abstract
This paper examines the idea that adherence to social rules is in part driven by moral emotions and the ability to recognize the emotions of others. Moral emotions like shame and guilt produce negative feelings when social rules are transgressed. The ability to recognize and understand the emotions of others is known as affective theory of mind (ToM). ToM is necessary for people to understand how others are affected by the violations of social rules. Using a laboratory experiment, individuals participated in a rule-following task designed to capture the propensity to follow costly social rules and completed psychometric measures of guilt, shame, and ToM. The results show that individuals who feel more shame and have higher ToM are more likely to follow the rules. The results from this experiment suggest that both shame and ToM are important in understanding rule-following.
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17
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Pescetelli N, Yeung N. The effects of recursive communication dynamics on belief updating. Proc Biol Sci 2020; 287:20200025. [PMID: 32693730 PMCID: PMC7423656 DOI: 10.1098/rspb.2020.0025] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 07/01/2020] [Indexed: 11/12/2022] Open
Abstract
Many social interactions are characterized by dynamic interplay, such that individuals exert reciprocal influence over each other's behaviours and beliefs. The present study investigated how the dynamics of reciprocal influence affect individual beliefs in a social context, over and above the information communicated in an interaction. To this end, we developed a simple social decision-making paradigm in which two people are asked to make perceptual judgments while receiving information about each other's decisions. In a Static condition, information about the partner only conveyed their initial, independent judgment. However, in a Dynamic condition, each individual saw the evolving belief of their partner as they learnt about and responded to the individual's own judgment. The results indicated that in both conditions, the majority of confidence adjustments were characterized by an abrupt change followed by smaller adjustments around an equilibrium, and that participants' confidence was used to arbitrate conflict (although deviating from Bayesian norm). Crucially, recursive interaction had systematic effects on belief change relative to the static baseline, magnifying confidence change when partners agreed and reducing confidence change when they disagreed. These findings indicate that during dynamic interactions-often a characteristic of real-life and online social contexts-information is collectively transformed rather than acted upon by individuals in isolation. Consequently, the output of social events is not only influenced by what the dyad knows but also by predictable recursive and self-reinforcing dynamics.
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Affiliation(s)
- Niccolò Pescetelli
- Max Planck Institute for Human Development, 94 Lentzeallee, Berlin 14195, Germany
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Nick Yeung
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
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18
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Ito A, Yoshida K, Takeda K, Sawamura D, Murakami Y, Hasegawa A, Sakai S, Izuma K. The role of the ventromedial prefrontal cortex in automatic formation of impression and reflected impression. Hum Brain Mapp 2020; 41:3045-3058. [PMID: 32301546 PMCID: PMC7336154 DOI: 10.1002/hbm.24996] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 03/12/2020] [Accepted: 03/12/2020] [Indexed: 01/02/2023] Open
Abstract
Previous neuroimaging studies demonstrated that ventromedial prefrontal cortex (vmPFC) activity reflects how much an individual positively views each person (impression). Here, we investigated whether the degree to which individuals think others positively view them (reflected impression) is similarly tracked by activity in the vmPFC by using fMRI and speed-dating events. We also examined whether activity of the vmPFC in response to the faces of others would predict the impression formed through direct interactions with them. The task consisted of three sessions: pre-speed-dating fMRI, speed-dating events, and post-speed-dating fMRI (not reported here). During the pre-speed-dating fMRI, each participant passively viewed the faces of others whom they would meet in the subsequent speed-dating events. After the fMRI, they rated the impression and reflected impression of each face. During the speed-dating events, the participants had 3-min conversations with partners whose faces were presented during the fMRI task, and they were asked to choose the partners whom they preferred at the end of the events. The results revealed that the value of both the impression and reflected impression were automatically represented in the vmPFC. However, the impression fully mediated the link between the reflected impression and vmPFC activity. These results highlight a close link between reflected appraisal and impression formation and provide important insights into neural and psychological models of how the reflected impression is formed in the human brain.
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Affiliation(s)
- Ayahito Ito
- Department of Psychology, University of Southampton, Southampton, United Kingdom.,Japan Society for the Promotion of Science, Tokyo, Japan.,Faculty of Health Sciences, Hokkaido University, Sapporo, Japan.,Research Institute for Future Design, Kochi University of Technology, Kochi, Japan
| | - Kazuki Yoshida
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan
| | - Kenta Takeda
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan.,Department of Rehabilitation for the Movement Functions, National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Japan
| | | | - Yui Murakami
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan.,Department of Occupational Therapy, Hokkaido Bunkyo University, Hokkaido, Japan
| | - Ai Hasegawa
- Graduate School of Health Sciences, Hokkaido University, Hokkaido, Japan
| | - Shinya Sakai
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan
| | - Keise Izuma
- Department of Psychology, University of Southampton, Southampton, United Kingdom.,School of Economics and Management, Kochi University of Technology, Kochi, Japan
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19
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Computing Social Value Conversion in the Human Brain. J Neurosci 2019; 39:5153-5172. [PMID: 31000587 DOI: 10.1523/jneurosci.3117-18.2019] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 03/30/2019] [Accepted: 04/14/2019] [Indexed: 01/27/2023] Open
Abstract
Social signals play powerful roles in shaping self-oriented reward valuation and decision making. These signals activate social and valuation/decision areas, but the core computation for their integration into the self-oriented decision machinery remains unclear. Here, we study how a fundamental social signal, social value (others' reward value), is converted into self-oriented decision making in the human brain. Using behavioral analysis, modeling, and neuroimaging, we show three-stage processing of social value conversion from the offer to the effective value and then to the final decision value. First, a value of others' bonus on offer, called offered value, was encoded uniquely in the right temporoparietal junction (rTPJ) and also in the left dorsolateral prefrontal cortex (ldlPFC), which is commonly activated by offered self-bonus value. The effective value, an intermediate value representing the effective influence of the offer on the decision, was represented in the right anterior insula (rAI), and the final decision value was encoded in the medial prefrontal cortex (mPFC). Second, using psychophysiological interaction and dynamic causal modeling analyses, we demonstrated three-stage feedforward processing from the rTPJ and ldPFC to the rAI and then from rAI to the mPFC. Further, we showed that these characteristics of social conversion underlie distinct sociobehavioral phenotypes. We demonstrate that the variability in the conversion underlies the difference between prosocial and selfish subjects, as seen from the differential strength of the rAI and ldlPFC coupling to the mPFC responses, respectively. Together, these findings identified fundamental neural computation processes for social value conversion underlying complex social decision making behaviors.SIGNIFICANCE STATEMENT In daily life, we make decisions based on self-interest, but also in consideration for others' status. These social influences modulate valuation and decision signals in the brain, suggesting a fundamental process called value conversion that translates social information into self-referenced decisions. However, little is known about the conversion process and its underlying brain mechanisms. We investigated value conversion using human fMRI with computational modeling and found three essential stages in a progressive brain circuit from social to empathic and decision areas. Interestingly, the brain mechanism of conversion differed between prosocial and individualistic subjects. These findings reveal how the brain processes and merges social information into the elemental flow of self-interested decision making.
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20
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Statistical analysis of bitcoin during explosive behavior periods. PLoS One 2019; 14:e0213919. [PMID: 30901371 PMCID: PMC6430404 DOI: 10.1371/journal.pone.0213919] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 03/04/2019] [Indexed: 11/23/2022] Open
Abstract
This paper develops the ability of the normal inverse Gaussian distribution (NIG) to fit the returns of bitcoin (BTC). As the first cryptocurrency created, the behavior of this new asset is characterized by great volatility. The lack of a proper definition or classification under existing theory exacerbates this property in such a way that explosive periods followed by a rapid decline have been observed along the series, meaning bubble episodes. By detecting the periods in which a bubble rises and collapses, it is possible to study the statistical properties of such segments. In particular, adjusting a theoretical distribution may help to determine better strategies to hedge against these episodes. The NIG is an appropriate candidate not only because of its heavy-tailed property but also because it has been proven to be closed under convolution, a characteristic that can be implemented to measure multivariate value at risk. Using data on the price of BTC with respect to seven of the main global currencies, the NIG was able to fit every time segment despite the bubble behavior. In the out-of-sample tests, the NIG was proven to have an adjustment similar to that of a generalized hyperbolic (GH) distribution. This result could serve as a starting point for future studies regarding the statistical properties of cryptocurrencies as well as their multivariate distributions.
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21
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Deconstructing Theory-of-Mind Impairment in High-Functioning Adults with Autism. Curr Biol 2019; 29:513-519.e6. [DOI: 10.1016/j.cub.2018.12.039] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 11/22/2018] [Accepted: 12/20/2018] [Indexed: 12/22/2022]
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22
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Hackel LM, Amodio DM. Computational neuroscience approaches to social cognition. Curr Opin Psychol 2018; 24:92-97. [PMID: 30388495 DOI: 10.1016/j.copsyc.2018.09.001] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 08/06/2018] [Accepted: 09/06/2018] [Indexed: 01/25/2023]
Abstract
How do we form impressions of people and groups and use these representations to guide our actions? From its inception, social neuroscience has sought to illuminate such complex forms of social cognition, and recently these efforts have been invigorated by the use of computational modeling. Computational modeling provides a framework for delineating specific processes underlying social cognition and relating them to neural activity and behavior. We provide a primer on the computational modeling approach and describe how it has been used to elucidate psychological and neural mechanisms of impression formation, social learning, moral decision making, and intergroup bias.
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Affiliation(s)
- Leor M Hackel
- Department of Psychology, Stanford University, Jordan Hall, 450 Serra Mall, Stanford, CA 94305, USA.
| | - David M Amodio
- Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA; Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129, REC G, 1001 NK Amsterdam, NL.
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23
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Häusler AN, Kuhnen CM, Rudorf S, Weber B. Preferences and beliefs about financial risk taking mediate the association between anterior insula activation and self-reported real-life stock trading. Sci Rep 2018; 8:11207. [PMID: 30046095 PMCID: PMC6060130 DOI: 10.1038/s41598-018-29670-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 07/17/2018] [Indexed: 11/18/2022] Open
Abstract
People differ greatly in their financial risk taking behaviour. This heterogeneity has been associated with differences in brain activity, but only in laboratory settings using constrained behaviours. However, it is important to understand how these measures transfer to real life conditions, because the willingness to invest in riskier assets has a direct and considerable effect on long-term wealth accumulation. In a large fMRI study of 157 working age men (39.0 ± 6.4 SD years), we first show that activity in the anterior insula during the assessment of risky vs. safe choices in an investing task is associated with self-reported real-life active stock trading. We then show that this association remains intact when we control for financial constraints, education, the understanding of financial matters, and cognitive abilities. Finally, we use comprehensive measures of preferences and beliefs about risk taking to show that these two channels mediate the association between brain activation in the anterior insula and real-life active stock trading.
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Affiliation(s)
- Alexander N Häusler
- Center for Economics and Neuroscience, University of Bonn, Nachtigallenweg 86, 53127, Bonn, Germany.
- Department of Epileptology, University Hospital Bonn, Sigmund-Freud-Strasse 25, 53127, Bonn, Germany.
- Department of NeuroCognition/Imaging, Life&Brain Research Center, Sigmund-Freud-Strasse 25, 53127, Bonn, Germany.
| | - Camelia M Kuhnen
- Kenan-Flagler Business School, University of North Carolina, 300 Kenan Center Drive, Chapel Hill, NC, 27599, USA
| | - Sarah Rudorf
- Department of Social Psychology and Social Neuroscience, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012, Bern, Switzerland
| | - Bernd Weber
- Center for Economics and Neuroscience, University of Bonn, Nachtigallenweg 86, 53127, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Sigmund-Freud-Strasse 25, 53127, Bonn, Germany
- Department of NeuroCognition/Imaging, Life&Brain Research Center, Sigmund-Freud-Strasse 25, 53127, Bonn, Germany
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24
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Chib VS, Adachi R, O'Doherty JP. Neural substrates of social facilitation effects on incentive-based performance. Soc Cogn Affect Neurosci 2018; 13:391-403. [PMID: 29648653 PMCID: PMC5928408 DOI: 10.1093/scan/nsy024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 02/22/2018] [Accepted: 03/19/2018] [Indexed: 11/13/2022] Open
Abstract
Throughout our lives we must perform tasks while being observed by others. Previous studies have shown that the presence of an audience can cause increases in an individual’s performance as compared to when they are not being observed—a phenomenon called ‘social facilitation’. However, the neural mechanisms underlying this effect, in the context of skilled-task performance for monetary incentives, are not well understood. We used functional magnetic resonance imaging to monitor brain activity while healthy human participants performed a skilled-task during conditions in which they were paid based on their performance and observed and not observed by an audience. We found that during social facilitation, social signals represented in the dorsomedial prefrontal cortex (dmPFC) enhanced reward value computations in ventromedial prefrontal cortex (vmPFC). We also found that functional connectivity between dmPFC and ventral striatum was enhanced when participants exhibited social facilitation effects, indicative of a means by which social signals serve to modulate brain regions involved in regulating behavioral motivation. These findings illustrate how neural processing of social judgments gives rise to the enhanced motivational state that results in social facilitation of incentive-based performance.
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Affiliation(s)
- Vikram S Chib
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.,Kennedy Krieger Institute, Baltimore, MD, USA.,Division of Biology and Biological Engineering
| | - Ryo Adachi
- Division of Humanities and Social Sciences
| | - John P O'Doherty
- Division of Humanities and Social Sciences.,Computation and Neural Systems, California Institute of Technology, Pasadena, CA 91125, USA
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25
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Raggetti G, Ceravolo MG, Fattobene L, Di Dio C. Neural Correlates of Direct Access Trading in a Real Stock Market: An fMRI Investigation. Front Neurosci 2017; 11:536. [PMID: 29033782 PMCID: PMC5626870 DOI: 10.3389/fnins.2017.00536] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Accepted: 09/14/2017] [Indexed: 11/13/2022] Open
Abstract
Background: While financial decision making has been barely explored, no study has previously investigated the neural correlates of individual decisions made by professional traders involved in real stock market negotiations, using their own financial resources. Aim: We sought to detect how different brain areas are modulated by factors like age, expertise, psychological profile (speculative risk seeking or aversion) and, eventually, size and type (Buy/Sell) of stock negotiations, made through Direct Access Trading (DAT) platforms. Subjects and methods: Twenty male traders underwent fMRI while negotiating in the Italian stock market using their own preferred trading platform. Results: At least 20 decision events were collected during each fMRI session. Risk averse traders performed a lower number of financial transactions with respect to risk seekers, with a lower average economic value, but with a higher rate of filled proposals. Activations were observed in cortical and subcortical areas traditionally involved in decision processes, including the ventrolateral and dorsolateral prefrontal cortex (vlPFC, dlPFC), the posterior parietal cortex (PPC), the nucleus accumbens (NAcc), and dorsal striatum. Regression analysis indicated an important role of age in modulating activation of left NAcc, while traders' expertise was negatively related to activation of vlPFC. High value transactions were associated with a stronger activation of the right PPC when subjects' buy rather than sell. The success of the trading activity, based on a large number of filled transactions, was related with higher activation of vlPFC and dlPFC. Independent of chronological and professional age, traders differed in their attitude to DAT, with distinct brain activity profiles being detectable during fMRI sessions. Those subjects who described themselves as very self-confident, showed a lower or absent activation of both the caudate nucleus and the dlPFC, while more reflexive traders showed greater activation of areas involved in strategic decision making. Discussion: The neural correlates in DAT are similar to those observed in other decision making contexts. Trading is handled as a well-learned automatic behavior by expert traders; for those who mostly rely on heuristics, cognitive effort decreases, and transaction speed increases, but decision efficiency lowers following a poor involvement of the dlPFC.
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Affiliation(s)
- GianMario Raggetti
- Centre for Health Care Management, School of Medicine, Università Politecnica delle Marche, Ancona, Italy.,Department of Management, School of Economics, Università Politecnica delle Marche, Ancona, Italy
| | - Maria G Ceravolo
- Centre for Health Care Management, School of Medicine, Università Politecnica delle Marche, Ancona, Italy.,Department of Experimental and Clinical Medicine, School of Medicine, Università Politecnica delle Marche, Ancona, Italy
| | - Lucrezia Fattobene
- Department of Management, School of Economics, Università Politecnica delle Marche, Ancona, Italy.,Department of Experimental and Clinical Medicine, School of Medicine, Università Politecnica delle Marche, Ancona, Italy
| | - Cinzia Di Dio
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
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26
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Independent Neural Computation of Value from Other People's Confidence. J Neurosci 2017; 37:673-684. [PMID: 28100748 DOI: 10.1523/jneurosci.4490-15.2016] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 11/04/2016] [Accepted: 12/01/2016] [Indexed: 11/21/2022] Open
Abstract
Expectation of reward can be shaped by the observation of actions and expressions of other people in one's environment. A person's apparent confidence in the likely reward of an action, for instance, makes qualities of their evidence, not observed directly, socially accessible. This strategy is computationally distinguished from associative learning methods that rely on direct observation, by its use of inference from indirect evidence. In twenty-three healthy human subjects, we isolated effects of first-hand experience, other people's choices, and the mediating effect of their confidence, on decision-making and neural correlates of value within ventromedial prefrontal cortex (vmPFC). Value derived from first-hand experience and other people's choices (regardless of confidence) were indiscriminately represented across vmPFC. However, value computed from agent choices weighted by their associated confidence was represented with specificity for ventromedial area 10. This pattern corresponds to shifts of connectivity and overlapping cognitive processes along a posterior-anterior vmPFC axis. Task behavior and self-reported self-reliance for decision-making in other social contexts correlated. The tendency to conform in other social contexts corresponded to increased activation in cortical regions previously shown to respond to social conflict in proportion to subsequent conformity (Campbell-Meiklejohn et al., 2010). The tendency to self-monitor predicted a selectively enhanced response to accordance with others in the right temporoparietal junction (rTPJ). The findings anatomically decompose vmPFC value representations according to computational requirements and provide biological insight into the social transmission of preference and reassurance gained from the confidence of others. SIGNIFICANCE STATEMENT Decades of research have provided evidence that the ventromedial prefrontal cortex (vmPFC) signals the satisfaction we expect from imminent actions. However, we have a surprisingly modest understanding of the organization of value across this substantial and varied region. This study finds that using cues of the reliability of other peoples' knowledge to enhance expectation of personal success generates value correlates that are anatomically distinct from those concurrently computed from direct, personal experience. This suggests that representation of decision values in vmPFC is suborganized according to the underlying computation, consistent with what we know about the anatomical heterogeneity of the region. These results also provide insight into the observational learning process by which someone else's confidence can sway and reassure our choices.
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27
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Bang D, Frith CD. Making better decisions in groups. ROYAL SOCIETY OPEN SCIENCE 2017; 4:170193. [PMID: 28878973 PMCID: PMC5579088 DOI: 10.1098/rsos.170193] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Accepted: 07/10/2017] [Indexed: 06/07/2023]
Abstract
We review the literature to identify common problems of decision-making in individuals and groups. We are guided by a Bayesian framework to explain the interplay between past experience and new evidence, and the problem of exploring the space of hypotheses about all the possible states that the world could be in and all the possible actions that one could take. There are strong biases, hidden from awareness, that enter into these psychological processes. While biases increase the efficiency of information processing, they often do not lead to the most appropriate action. We highlight the advantages of group decision-making in overcoming biases and searching the hypothesis space for good models of the world and good solutions to problems. Diversity of group members can facilitate these achievements, but diverse groups also face their own problems. We discuss means of managing these pitfalls and make some recommendations on how to make better group decisions.
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Affiliation(s)
- Dan Bang
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK
- Interacting Minds Centre, Aarhus University, 8000 Aarhus, Denmark
| | - Chris D. Frith
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK
- Institute of Philosophy, University of London, London WC1E 7HU, UK
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28
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Hill CA, Suzuki S, Polania R, Moisa M, O'Doherty JP, Ruff CC. A causal account of the brain network computations underlying strategic social behavior. Nat Neurosci 2017; 20:1142-1149. [PMID: 28692061 DOI: 10.1038/nn.4602] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 06/07/2017] [Indexed: 12/12/2022]
Abstract
During competitive interactions, humans have to estimate the impact of their own actions on their opponent's strategy. Here we provide evidence that neural computations in the right temporoparietal junction (rTPJ) and interconnected structures are causally involved in this process. By combining inhibitory continuous theta-burst transcranial magnetic stimulation with model-based functional MRI, we show that disrupting neural excitability in the rTPJ reduces behavioral and neural indices of mentalizing-related computations, as well as functional connectivity of the rTPJ with ventral and dorsal parts of the medial prefrontal cortex. These results provide a causal demonstration that neural computations instantiated in the rTPJ are neurobiological prerequisites for the ability to integrate opponent beliefs into strategic choice, through system-level interaction within the valuation and mentalizing networks.
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Affiliation(s)
- Christopher A Hill
- Laboratory for Social and Neural Systems Research (SNS-Lab), Department of Economics, University of Zurich, Zurich, Switzerland
| | - Shinsuke Suzuki
- Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai, Miyagi, Japan.,Institute of Development, Aging and Cancer, Tohoku University, Sendai, Miyagi, Japan
| | - Rafael Polania
- Laboratory for Social and Neural Systems Research (SNS-Lab), Department of Economics, University of Zurich, Zurich, Switzerland
| | - Marius Moisa
- Laboratory for Social and Neural Systems Research (SNS-Lab), Department of Economics, University of Zurich, Zurich, Switzerland.,Biomedical Engineering, University and ETH of Zurich, Zurich, Switzerland
| | - John P O'Doherty
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California, USA.,Computation and Neural Systems, California Institute of Technology, Pasadena, California, USA
| | - Christian C Ruff
- Laboratory for Social and Neural Systems Research (SNS-Lab), Department of Economics, University of Zurich, Zurich, Switzerland
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29
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Social Information Is Integrated into Value and Confidence Judgments According to Its Reliability. J Neurosci 2017; 37:6066-6074. [PMID: 28566360 PMCID: PMC5481942 DOI: 10.1523/jneurosci.3880-16.2017] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 03/07/2017] [Accepted: 04/01/2017] [Indexed: 11/21/2022] Open
Abstract
How much we like something, whether it be a bottle of wine or a new film, is affected by the opinions of others. However, the social information that we receive can be contradictory and vary in its reliability. Here, we tested whether the brain incorporates these statistics when judging value and confidence. Participants provided value judgments about consumer goods in the presence of online reviews. We found that participants updated their initial value and confidence judgments in a Bayesian fashion, taking into account both the uncertainty of their initial beliefs and the reliability of the social information. Activity in dorsomedial prefrontal cortex tracked the degree of belief update. Analogous to how lower-level perceptual information is integrated, we found that the human brain integrates social information according to its reliability when judging value and confidence. SIGNIFICANCE STATEMENT The field of perceptual decision making has shown that the sensory system integrates different sources of information according to their respective reliability, as predicted by a Bayesian inference scheme. In this work, we hypothesized that a similar coding scheme is implemented by the human brain to process social signals and guide complex, value-based decisions. We provide experimental evidence that the human prefrontal cortex's activity is consistent with a Bayesian computation that integrates social information that differs in reliability and that this integration affects the neural representation of value and confidence.
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30
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Gutiérrez-Roig M, Segura C, Duch J, Perelló J. Market Imitation and Win-Stay Lose-Shift Strategies Emerge as Unintended Patterns in Market Direction Guesses. PLoS One 2016; 11:e0159078. [PMID: 27532219 PMCID: PMC4988703 DOI: 10.1371/journal.pone.0159078] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 06/27/2016] [Indexed: 11/19/2022] Open
Abstract
Decisions made in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market provides a rich environment to study how people make decisions since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go "up" or "down" in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions, which can be interpreted as Market Imitation and Win-Stay Lose-Shift emerging strategies, with Market Imitation being the most dominant. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to make a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, to avoid behavioural anomalies in financial analysts decisions and to improve not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops.
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Affiliation(s)
- Mario Gutiérrez-Roig
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain
| | - Carlota Segura
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain
| | - Jordi Duch
- Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Spain
| | - Josep Perelló
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain
- Universitat de Barcelona Institute of Complex Systems UBICS, Barcelona, Spain
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31
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Frydman C, Camerer CF. The Psychology and Neuroscience of Financial Decision Making. Trends Cogn Sci 2016; 20:661-675. [PMID: 27499348 DOI: 10.1016/j.tics.2016.07.003] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Revised: 07/06/2016] [Accepted: 07/07/2016] [Indexed: 10/21/2022]
Abstract
Financial decisions are among the most important life-shaping decisions that people make. We review facts about financial decisions and what cognitive and neural processes influence them. Because of cognitive constraints and a low average level of financial literacy, many household decisions violate sound financial principles. Households typically have underdiversified stock holdings and low retirement savings rates. Investors overextrapolate from past returns and trade too often. Even top corporate managers, who are typically highly educated, make decisions that are affected by overconfidence and personal history. Many of these behaviors can be explained by well-known principles from cognitive science. A boom in high-quality accumulated evidence-especially how practical, low-cost 'nudges' can improve financial decisions-is already giving clear guidance for balanced government regulation.
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Affiliation(s)
- Cary Frydman
- USC Marshall School of Business, Los Angeles, CA, USA.
| | - Colin F Camerer
- Division of the Humanities and Social Sciences, Caltech, Pasadena, CA, USA.
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Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex. Nat Commun 2016; 7:12327. [PMID: 27477632 PMCID: PMC4974652 DOI: 10.1038/ncomms12327] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 06/23/2016] [Indexed: 12/31/2022] Open
Abstract
In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. Past experiences and future predictions both shape our decisions. Here, the authors trained participants in a foraging task in which reward rates varied systematically over time and find the dACC tracks both recent and past reward rates, leading to opposing effects on decisions about whether to stay or leave a reward environment.
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Konovalov A, Krajbich I. Over a Decade of Neuroeconomics: What Have We Learned? ORGANIZATIONAL RESEARCH METHODS 2016. [DOI: 10.1177/1094428116644502] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
At its inception, neuroeconomics promised to revolutionize economics. That promise has not yet been realized, and neuroeconomics has seen limited penetration into mainstream economics. Nevertheless, it would be a mistake to declare that neuroeconomics has failed. Quite to the contrary, the yearly rate of neuroeconomics papers has roughly doubled since 2005. While the number of direct applications to economics remains limited, due to the infancy of the field, we have learned an amazing amount about how the brain makes decisions. In this article, we review some of the major topics that have emerged in neuroeconomics and highlight findings that we believe will form the basis for future applications to economics. When possible, we focus on existing applications to economics and future directions for that research.
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Affiliation(s)
- Arkady Konovalov
- Department of Economics, The Ohio State University, Columbus, OH, USA
| | - Ian Krajbich
- Department of Economics, The Ohio State University, Columbus, OH, USA
- Department of Psychology, The Ohio State University, Columbus, OH, USA
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Abstract
Prior studies have shown that traders quickly converge to the price-quantity equilibrium in markets for goods that are immediately consumed, but they produce speculative price bubbles in resalable asset markets. We present a stock-flow model of durable assets in which the existing stock of assets is subject to depreciation and producers may produce additional units of the asset. In our laboratory experiments inexperienced consumers who can resell their units disregard the consumption value of the assets and compete vigorously with producers, depressing prices and production. Consumers who have first participated in experiments without resale learn to heed their consumption values and, when they are given the option to resell, trade at equilibrium prices. Reproducibility is therefore the most natural and most effective treatment for suppression of bubbles in asset market experiments.
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Parkinson C, Wheatley T. The repurposed social brain. Trends Cogn Sci 2015; 19:133-41. [PMID: 25732617 DOI: 10.1016/j.tics.2015.01.003] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 12/08/2014] [Accepted: 01/10/2015] [Indexed: 11/29/2022]
Abstract
Human social intelligence depends on a diverse array of perceptual, cognitive, and motivational capacities. Some of these capacities depend on neural systems that may have evolved through modification of ancestral systems with non-social or more limited social functions (evolutionary repurposing). Social intelligence, in turn, enables new forms of repurposing within the lifetime of an individual (cultural and instrumental repurposing), which entail innovating over and exploiting pre-existing circuitry to meet problems our brains did not evolve to solve. Considering these repurposing processes can provide insight into the computations that brain regions contribute to social information processing, generate testable predictions that usefully constrain social neuroscience theory, and reveal biologically imposed constraints on cultural inventions and our ability to respond beneficially to contemporary challenges.
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Affiliation(s)
- Carolyn Parkinson
- Department of Psychological and Brain Sciences, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755, USA
| | - Thalia Wheatley
- Department of Psychological and Brain Sciences, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755, USA.
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Bossaerts P, Murawski C. From behavioural economics to neuroeconomics to decision neuroscience: the ascent of biology in research on human decision making. Curr Opin Behav Sci 2015. [DOI: 10.1016/j.cobeha.2015.07.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Toelch U, Dolan RJ. Informational and Normative Influences in Conformity from a Neurocomputational Perspective. Trends Cogn Sci 2015; 19:579-589. [DOI: 10.1016/j.tics.2015.07.007] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 07/09/2015] [Accepted: 07/23/2015] [Indexed: 10/23/2022]
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Cueva C, Roberts RE, Spencer T, Rani N, Tempest M, Tobler PN, Herbert J, Rustichini A. Cortisol and testosterone increase financial risk taking and may destabilize markets. Sci Rep 2015; 5:11206. [PMID: 26135946 PMCID: PMC4489095 DOI: 10.1038/srep11206] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 04/10/2015] [Indexed: 11/14/2022] Open
Abstract
It is widely known that financial markets can become dangerously unstable, yet it is unclear why. Recent research has highlighted the possibility that endogenous hormones, in particular testosterone and cortisol, may critically influence traders’ financial decision making. Here we show that cortisol, a hormone that modulates the response to physical or psychological stress, predicts instability in financial markets. Specifically, we recorded salivary levels of cortisol and testosterone in people participating in an experimental asset market (N = 142) and found that individual and aggregate levels of endogenous cortisol predict subsequent risk-taking and price instability. We then administered either cortisol (single oral dose of 100 mg hydrocortisone, N = 34) or testosterone (three doses of 10 g transdermal 1% testosterone gel over 48 hours, N = 41) to young males before they played an asset trading game. We found that both cortisol and testosterone shifted investment towards riskier assets. Cortisol appears to affect risk preferences directly, whereas testosterone operates by inducing increased optimism about future price changes. Our results suggest that changes in both cortisol and testosterone could play a destabilizing role in financial markets through increased risk taking behaviour, acting via different behavioural pathways.
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Affiliation(s)
- Carlos Cueva
- Departamento de Fundamentos del Análisis Económico, Universidad de Alicante, Spain
| | - R Edward Roberts
- Division of Brain Sciences, Department of Medicine, Imperial College London, UK
| | - Tom Spencer
- 1] Department of Psychiatry, University of Cambridge, UK [2] Cambridgeshire and Peterborough NHS Foundation Trust, Elizabeth House, Fulbourn Hospital, Cambridge, UK
| | - Nisha Rani
- Cambridgeshire and Peterborough NHS Foundation Trust, Elizabeth House, Fulbourn Hospital, Cambridge, UK
| | | | - Philippe N Tobler
- Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Switzerland
| | - Joe Herbert
- John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, UK
| | - Aldo Rustichini
- 1] Department of Economics, University of Minnesota, USA [2] Department of Physiology, Development and Neuroscience, University of Cambridge, UK
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Chater N. Can cognitive science create a cognitive economics? Cognition 2015; 135:52-5. [DOI: 10.1016/j.cognition.2014.10.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 10/24/2014] [Accepted: 10/27/2014] [Indexed: 11/30/2022]
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Jenkins AC, Dodell-Feder D, Saxe R, Knobe J. The neural bases of directed and spontaneous mental state attributions to group agents. PLoS One 2014; 9:e105341. [PMID: 25140705 PMCID: PMC4139375 DOI: 10.1371/journal.pone.0105341] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2014] [Accepted: 07/17/2014] [Indexed: 11/19/2022] Open
Abstract
In daily life, perceivers often need to predict and interpret the behavior of group agents, such as corporations and governments. Although research has investigated how perceivers reason about individual members of particular groups, less is known about how perceivers reason about group agents themselves. The present studies investigate how perceivers understand group agents by investigating the extent to which understanding the 'mind' of the group as a whole shares important properties and processes with understanding the minds of individuals. Experiment 1 demonstrates that perceivers are sometimes willing to attribute a mental state to a group as a whole even when they are not willing to attribute that mental state to any of the individual members of the group, suggesting that perceivers can reason about the beliefs and desires of group agents over and above those of their individual members. Experiment 2 demonstrates that the degree of activation in brain regions associated with attributing mental states to individuals--i.e., brain regions associated with mentalizing or theory-of-mind, including the medial prefrontal cortex (MPFC), temporo-parietal junction (TPJ), and precuneus--does not distinguish individual from group targets, either when reading statements about those targets' mental states (directed) or when attributing mental states implicitly in order to predict their behavior (spontaneous). Together, these results help to illuminate the processes that support understanding group agents themselves.
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Affiliation(s)
- Adrianna C. Jenkins
- Helen Wills Neuroscience Institute and Haas School of Business, University of California, Berkeley, California, United States of America
| | - David Dodell-Feder
- Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Rebecca Saxe
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Joshua Knobe
- Program in Cognitive Science, Yale University, New Haven, Connecticut, United States of America
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Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles. Proc Natl Acad Sci U S A 2014; 111:10503-8. [PMID: 25002476 DOI: 10.1073/pnas.1318416111] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.
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Ruff CC, Fehr E. The neurobiology of rewards and values in social decision making. Nat Rev Neurosci 2014; 15:549-62. [DOI: 10.1038/nrn3776] [Citation(s) in RCA: 439] [Impact Index Per Article: 43.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Frydman C, Barberis N, Camerer C, Bossaerts P, Rangel A. Using Neural Data to Test A Theory of Investor Behavior: An Application to Realization Utility. THE JOURNAL OF FINANCE 2014; 69:907-946. [PMID: 25774065 PMCID: PMC4357577 DOI: 10.1111/jofi.12126] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the "realization utility" theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market while we measured their brain activity. We find that all subjects exhibit a strong disposition effect in their trading, even though it is suboptimal. Consistent with the realization utility explanation for this behavior, we find that activity in the ventromedial prefrontal cortex, an area known to encode the value of options during choices, correlates with the capital gains of potential trades; that the neural measures of realization utility correlate across subjects with their individual tendency to exhibit a disposition effect; and that activity in the ventral striatum, an area known to encode information about changes in the present value of experienced utility, exhibits a positive response when subjects realize capital gains. These results provide support for the realization utility model and, more generally, demonstrate how neural data can be helpful in testing models of investor behavior.
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Affiliation(s)
- Cary Frydman
- Marshall School of Business, University of Southern California
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