Finance - Research Publications
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ItemThe effect of action contingency on social perception is independent of person-like appearance and is related to deactivation of the frontal component of the self-agency network.(Springer Science and Business Media LLC, 2022-10-15)The detection of object movement that is contingent on one's own actions (i.e., movements with action contingency) influences social perception of the object; such interactive objects tend to create a good impression. However, it remains unclear whether neural representation of action contingency is associated with subsequent socio-cognitive evaluation of "contacting agents", or whether the appearance of agents (e.g., face- or non-face-like avatars) is essential for this effect. In this study, we conducted a functional magnetic resonance imaging (fMRI) task with two phases: contact (contact with face- or non-face-like avatars moving contingently or non-contingently) and recognition (rating a static image of each avatar). Deactivation of the frontoparietal self-agency network and activation of the reward network were the main effects of action contingency during the contact phase, consistent with previous findings. During the recognition phase, static avatars that had previously moved in a contingent manner deactivated the frontal component of the frontoparietal network (bilateral insula and inferior-middle frontal gyri), regardless of person-like appearance. Our results imply that frontal deactivation may underlie the effect of action contingency on subsequent social perception, independent of person-like appearance.
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ItemInferences regarding oneself and others in the human brain.(Public Library of Science (PLoS), 2022-05)The human brain can infer one's own and other individuals' mental states through metacognition and mentalizing, respectively. A new study in PLOS Biology has implicated distinct brain regions of the medial prefrontal cortex (PFC) in metacognition and mentalizing.
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ItemTwo components of body-image disturbance are differentially associated with distinct eating disorder characteristics in healthy young women(PUBLIC LIBRARY SCIENCE, 2022-01-12)Body-image disturbance comprises two components. The first is perceptual in nature, and is measured by a discrepancy between one’s actual body and perceived self-image (“per ceived–actual discrepancy”). The other component is affective, and is measured by a dis crepancy between one’s perceived self-image and ideal body image (“perceived–ideal discrepancy”). The present study evaluated the relationships between body-image distur bance and characteristics of eating disorders such as symptoms and related personality traits. In a psychophysiological experiment, female university students (mean ± SD age = 21.0 ± 1.38 years) were presented with silhouette images of their own bodies that were dis torted in terms of width. The participants were asked whether each silhouette image was more overweight than their actual or ideal body images. Eating-disorder characteristics were assessed using six factors from the Japanese version of the Eating Disorder Inventory 2 (EDI2). We found that perceived–actual discrepancies correlated with negative self-evalu ation (i.e., factor 3 of the EDI2), whereas perceived–ideal discrepancies correlated with dis satisfaction with one’s own body (i.e., factor 2 of EDI2). These results imply that distinct psychological mechanisms underlie the two components of body-image disturbance.
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ItemPsychiatric symptoms influence reward-seeking and loss-avoidance decision-making through common and distinct computational processes(WILEY, 2021-09)AIM: Psychiatric symptoms are often accompanied by impairments in decision-making to attain rewards and avoid losses. However, due to the complex nature of mental disorders (e.g., high comorbidity), symptoms that are specifically associated with deficits in decision-making remain unidentified. Furthermore, the influence of psychiatric symptoms on computations underpinning reward-seeking and loss-avoidance decision-making remains elusive. Here, we aim to address these issues by leveraging a large-scale online experiment and computational modeling. METHODS: In the online experiment, we recruited 1900 non-diagnostic participants from the general population. They performed either a reward-seeking or loss-avoidance decision-making task, and subsequently completed questionnaires about psychiatric symptoms. RESULTS: We found that one trans-diagnostic dimension of psychiatric symptoms related to compulsive behavior and intrusive thought (CIT) was negatively correlated with overall decision-making performance in both the reward-seeking and loss-avoidance tasks. A deeper analysis further revealed that, in both tasks, the CIT psychiatric dimension was associated with lower preference for the options that recently led to better outcomes (i.e. reward or no-loss). On the other hand, in the reward-seeking task only, the CIT dimension was associated with lower preference for recently unchosen options. CONCLUSION: These findings suggest that psychiatric symptoms influence the two types of decision-making, reward-seeking and loss-avoidance, through both common and distinct computational processes.
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ItemVentral–Dorsal Subregions in the Posterior Cingulate Cortex Represent Pay and Interest, Two Key Attributes of Job Value(Oxford University Press, 2021-04-01)Career choices affect not only our financial status but also our future well-being. When making these choices, individuals evaluate their willingness to obtain a job (i.e., job values), primarily driven by simulation of future pay and interest. Despite the importance of these decisions, their underlying neural mechanisms remain unclear. In this study, we examined the neural representation of pay and interest. Forty students were presented with 80 job names and asked to evaluate their job values while undergoing functional magnetic resonance imaging (fMRI). Following fMRI, participants rated the jobs in terms of pay and interest. The fMRI data revealed that the ventromedial prefrontal cortex (vmPFC) was associated with job value representation, and the ventral and dorsal regions of the posterior cingulate cortex (PCC) were associated with pay and interest representations, respectively. These findings suggest that the neural computations underlying job valuation conform to a multi-attribute decision-making framework, with overall value signals represented in the vmPFC and the attribute values (i.e., pay and interest) represented in specific regions outside the vmPFC, in the PCC. Furthermore, anatomically distinct representations of pay and interest in the PCC may reflect the differing roles of the two subregions in future simulations.
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ItemTesting the reinforcement learning hypothesis of social conformity(Wiley Open Access, 2021-04-01)Our preferences are influenced by the opinions of others. The past human neuroimaging studies on social conformity have identified a network of brain regions related to social conformity that includes the posterior medial frontal cortex (pMFC), anterior insula, and striatum. Since these brain regions are also known to play important roles in reinforcement learning (i.e., processing prediction error), it was previously hypothesized that social conformity and reinforcement learning have a common neural mechanism. However, although this view is currently widely accepted, these two processes have never been directly compared; therefore, the extent to which they shared a common neural mechanism had remained unclear. This study aimed to formally test the hypothesis. The same group of participants (n = 25) performed social conformity and reinforcement learning tasks inside a functional magnetic resonance imaging (fMRI) scanner. Univariate fMRI data analyses revealed activation overlaps in the pMFC and bilateral insula between social conflict and unsigned prediction error and in the striatum between social conflict and signed prediction error. We further conducted multivoxel pattern analysis (MVPA) for more direct evidence of a shared neural mechanism. MVPA did not reveal any evidence to support the hypothesis in any of these regions but found that activation patterns between social conflict and prediction error in these regions were largely distinct. Taken together, the present study provides no clear evidence of a common neural mechanism between social conformity and reinforcement learning.
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ItemCommentary: A robust data-driven approach identifies four personality types across four large data sets(Frontiers Media SA, 2020)What kinds of personalities do humans have? Can these personalities be classified into several discrete types? These issues have been of considerable concern as they could potentially provide deeper understanding of the nature of human individuality and mental disorders. Recently, Gerlach et al. (2018) addressed these issues by applying established machine-learning techniques to big data (more than 1.5 million respondents in total). They found four “meaningful clusters” in personality dimensions, suggesting the existence of at least four personality types. Here, we propose an alternative interpretation of their result: a skewed distribution with no cluster structures in personality space can erroneously lead to the seemingly meaningful clusters.
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ItemExtrinsic Factors Underlying Food Valuation in the Human Brain(Frontiers Media SA, 2020)Subjective values for food rewards guide our dietary choices. There is growing evidence that value signals are constructed in the brain by integrating multiple types of information about flavor, taste, and nutritional attributes of the foods. However, much less is known about the influence of food-extrinsic factors such as labels, brands, prices, and packaging designs. In this mini-review article, we outline recent findings in decision neuroscience, consumer psychology, and food science about the effect of extrinsic factors on food value computations in the human brain. To date, studies have demonstrated that, while the integrated value signal is encoded in the ventromedial prefrontal cortex, information on the extrinsic factors of the food is encoded in diverse brain regions previously implicated in a wide range of functions: cognitive control, memory, emotion and reward processing. We suggest that a comprehensive understanding of food valuation requires elucidation of the mechanisms behind integrating extrinsic factors in the brain to compute an overall subjective value signal.