Ambiguity aversion in schizophrenia: An fMRI study of decision-making under risk and ambiguity
Introduction
Making decisions under uncertainty is an integral part of everyday life. Recently, altered decision-making under uncertainty has been reported in various psychiatric disorders (Krug et al., 2014, Pushkarskaya et al., 2015), particularly schizophrenia, wherein patients frequently exhibit behavioral symptoms such as financial problems and interpersonal conflicts (Koelkebeck et al., 2010, Kurtz et al., 2009).
In recent years, the fields of behavioral economics and neuroeconomics have been expanding rapidly. In line with their advancements, some efforts using these disciplines have been made to assess behavioral problems observed in psychiatric disorders. Findings from these interdisciplinary studies have begun to lay the groundwork needed to improve the diagnostics and treatments for various psychiatric disorders (Lee, 2013, Sharp et al., 2012, Takahashi, 2013). Decision-making under uncertainty is one of the most studied areas in decision theory (Hasler, 2012). Therefore, applying neuroeconomics tools can help elucidate the mechanisms underlying altered decision-making under uncertainty in schizophrenia.
In economics, researchers distinguish two types of uncertainty: risk and ambiguity (Camerer and Weber, 1992). Under “risk,” the precise probabilities of outcomes can be estimated (e.g., a 50% chance of $10). In contrast, “ambiguity” refers to situations in which the probabilities of outcomes are unknown (e.g., an unknown chance of winning $10).
Although healthy people are averse to both risk and ambiguity, they tend to prefer risk over ambiguity, which is referred to as “ambiguity aversion” (Camerer and Weber, 1992, Ellsberg, 1961). Suppose there are two bowls each filled with a mix of 24 red and blue chips. One bowl has 12 red and 12 blue chips (the risky bowl), but the composition of the other bowl is unknown to the participants (the ambiguous bowl). Participants are asked to select one bowl and told that if a red chip is drawn, they qualify for a predefined payoff. For the risky bowl, the probability of drawing a red chip is 0.5. For the ambiguous bowl, the probability of drawing a red chip is unknown, but the winning probability is also 0.5 (see Supplementary materials for details regarding risk/ambiguity aversion). Nevertheless, most individuals choose the risky bowl, even if its payoff is lower than that of the ambiguous one, and the degree of ambiguity aversion is reportedly linked with various types of behavior, such as self-insurance (Alary et al., 2013) and risk-taking behavior (Tymula et al., 2012).
Several studies have investigated attitudes toward risk in schizophrenia to elucidate altered decision-making under uncertainty in this illness (Cheng et al., 2012, Lee et al., 2007; these studies are described in the Discussion section). However, in real life, the probabilities of outcomes can rarely be estimated (e.g., the likelihood of being complimented by co-workers), and clinical findings show that patients with schizophrenia often feel strong discomfort in such ambiguous situations (Combs et al., 2007). It is known that patients with schizophrenia display a strong desire to obtain a specific answer on a topic, rather than dealing with ambiguity (Couture et al., 2006). Furthermore, previous studies reported that this tendency was improved by social cognitive interventions (Combs et al., 2007). Accordingly, clarifying attitudes under ambiguity is a key to understanding and preventing real-life maladaptive behavior in schizophrenia.
To date, many studies have used the Iowa gambling task (IGT) with the purpose of investigating decision-making under ambiguity in schizophrenia (Bechara et al., 1994, Sevy et al., 2007). However, in the IGT, the probability distribution is not known to the participants at the beginning of the test, and they gradually learn this from feedbacks during the task. Therefore, the IGT is a complex measure with elements of decision-making under both risk and ambiguity, and poor performance in the task partially reflects dysfunctional learning abilities (Buckert et al., 2014). Thus, it remains unclear how attitudes toward ambiguity can be compared between patients with schizophrenia and healthy subjects.
A number of previous studies using functional magnetic resonance imaging (fMRI) have compared neural correlates of decision-making under risk and ambiguity among healthy subjects. These studies showed that several brain areas, such as the prefrontal cortex, including orbitofrontal cortex (OFC), insula, and posterior parietal cortex, were more activated during ambiguous decision-making relative to risky decision-making (Bach et al., 2009, Bach et al., 2011, Hsu et al., 2005, Huettel et al., 2006, Levy et al., 2010), suggesting that these areas are crucial for decision-making under ambiguity. However, to the best of our knowledge, no study has directly compared neural correlates of decision-making under risk and those under ambiguity in schizophrenia. Elucidating this issue along with attitudes under risk/ambiguity should help us gain a better understanding of the mechanisms of altered decision-making in schizophrenia.
Here, we modified the fMRI task which clearly distinguished risk and ambiguity containing no feedback learning (Levy et al., 2010). Clinically, patients with schizophrenia often feel strong discomfort in socially ambiguous situations. Accordingly, one may intuitively predict that ambiguity aversion would be increased in schizophrenia. On the contrary, if patients with schizophrenia have difficulty in processing ambiguity, they may exhibit diminished ambiguity aversion together with reduced brain activation in the areas (e.g., OFC, insula, posterior parietal cortex) that have been implicated in decision-making under ambiguity in healthy volunteers.
Section snippets
Participants
Twenty-one out-patients with schizophrenia, diagnosed based on the patient edition of the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID), participated in this study. None of the patients had current comorbid psychiatric disorders. Thirty-three healthy controls who did not meet the criteria for any psychiatric disorders according to the non-patient edition of SCID were enrolled. The control group was matched with the patient group in terms of age, gender, handedness, current
Behavioral data
Overall, the participants performed the task well and only missed an average of 1.1 ± 1.4 (S.D.) trials. Concerning the reaction time, there was a significant main effect of condition (F1, 49 = 38.78, p < 0.01), with the response time under ambiguity being longer than that under risk, but neither the main effect of group nor interaction between group and condition was significant (Table S3).
Fig. 2A and B depict the rates of choosing the variable bowl across the winning amount under risk and
Discussion
We found that ambiguity aversion was attenuated in schizophrenia. Furthermore, the left lateral OFC activation, which was seen in healthy controls, was not increased during decision-making under ambiguity compared to under risk in the schizophrenia group. These findings add to our understanding of the mechanisms underlying altered decision-making in schizophrenia.
The healthy controls in our research exhibited typical ambiguity aversion (see Supplementary Materials). There was no difference in
Conflict of interest
All authors declare that they have no conflicts of interest.
Contributors
Junya Fujino, Kimito Hirose, Shisei Tei, Ryosaku Kawada, Yujiro Yoshihara, Toshiya Murai and Hidehiko Takahashi designed the study and wrote the protocol. Junya Fujino managed the literature searches and wrote the first draft of the manuscript. Junya Fujino performed data processing and statistical analyses under technical supervision by Jun Miyata, Genichi Sugihara and Hidehiko Takahashi. Takashi Ideno and Kazuhisa Takemura contributed new analytic tools. Kosuke Tsurumi, Noriko Matsukawa,
Role of the funding source
This work was supported by the Japan Society for the Promotion of Science (Young Scientists A 23680045, Scientific Research A 24243061, 15H01690, B 15H04893, C 26461767, and S 22220003) and Grant-in-Aid for challenging Exploratory Research (16K13106); the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) (on innovative areas 23118004, 23120009, 16H06572, 16H01504); the Uehara Memorial Foundation; the Smoking Research Foundation; the Takeda Science Foundation;
Acknowledgments
The authors wish to extend their gratitude to the research team of the Department of Psychiatry at Kyoto University for their assistance in data acquisition.
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