We need to measure the "goodness" of each policy at the group and societal level to make our society free and fair. However, it is known that such an index cannot be successfully created without methods for comparing “happiness” (or utility) of different people (Arrow's impossibility theorem; Arrow, 1963). It is also known that it is impossible to compare utility across individuals using classical methods based solely on behavioral data. In our project, we propose methods to measure “happiness” in an interpersonally comparable manner by combining various physiological indices. Rich happiness (such as "pleasure" and "aspiration") arises from being guaranteed the freedom to move (mobility) and the freedom to choose. In such an environment, people feel a sense of "belonging" and achieve a good state of mental and social well-being. Therefore, in normative economics, the goal of society is to ensure that individuals can lead lives they have reason to value, that is, to guarantee substantial freedoms for each person (Sen, 1999).
We aim not only to improve "happiness" at the individual level but also to aggregate it at the societal level and achieve equality. We are developing innovative technology to measure indicators of "happiness" from brain activity, making it possible to compare happiness across individuals. By achieving the projects, we will bridge detailed neuroscientific findings on brain indicators of "pleasure" and "aspiration" as felt by individuals to real-world activities, such as evaluating mobility policies in smart cities. This will contribute to the creation of societal technologies that enhance "well-being" through brain indicators.

(2) Quantification of the “aspiration” using brain indices

• The relationship between the two concepts of utility (experiential utility and decision utility), which are considered to be the basis of “pleasure” and “aspiration”, was investigated, and we found decision utility is constructed by integrating the “pleasure” provided by rewards.
• We investigated the dynamic process underlying the sense of controlling one's actions and their outcomes ("sense of agency") using MEG (magnetoencephalography) with high temporal resolution. By employing Q-learning, a type of reinforcement learning, we calculated the prediction errors and the transitions of expectations for action outcomes, decoding these from brain activity data.
• To elucidate the neural circuitry underlying the "sense of agency," we conducted electrocorticogram (ECoG) in marmosets during self-initiated vocalization. We observed the functional connectivity between the frontal and temporal lobes, focusing on the causality in the top-down direction (from the frontal lobe to the temporal lobe) within specific frequency bands during vocalization.
• To study the dynamic process of "autobiographical memory" which drives "aspiration," we developed an experimental system using virtual reality (VR) for mobility virtual experiences and measured the brain activity through MEG.
• By recording single neurons from epileptic patients, we have found that abstract context information is represented by human hippocampus.

If we succeed in quantifying and socially aggregating the diverse "pleasure" and "aspiration" of people, it could become a significant well-being indicator that complements GDP, as envisioned by the OECD and the United Nations ("Beyond GDP"). Moving forward, we will scientifically identify what constitutes a "rich environment" and "freedom of action" crucial to "happiness" in modern society. Using VR technology and other methods to create controlled rich experimental environments, we will measure brain activity and validate our findings through various approaches to ensure the legitimacy of our developments. (MATSUMORI Kaosu: Tamagawa University, MATSUMOTO Madoka: Kyoto University, Ralph Adolphs: Caltech)