Understanding and promoting subjective wellbeing (SWB) has been the topic of increasing research, due in part to its potential contributions to health and productivity. To date, the conceptualization of SWB has been grounded within social psychology and largely focused on self-report measures. In this paper, we explore the potentially complementary tools and theoretical perspectives offered by computational neuroscience, with a focus on the active inference (AI) framework. This framework is motivated by the fact that the brain does not have direct access to the world; to select actions, it must instead infer the most likely external causes of the sensory input it receives from both the body and the external world. Because sensory input is always consistent with multiple interpretations, the brain’s internal model must use background knowledge, in the form of prior expectations, to make a “best guess” about the situation it is in and how it will change by taking one action or another. This best guess arises by minimizing an error signal representing the deviation between predicted and observed sensations given a chosen action—quantified mathematically by a variable called free energy (FE). Crucially, recent proposals have illustrated how emotional experience may emerge within AI as a natural consequence of the brain keeping track of the success of its model in selecting actions to minimize FE. In this paper, we draw on the concepts and mathematics in AI to highlight how different computational strategies can be used to minimize FE—some more successfully than others. This affords a characterization of how diverse individuals may adopt unique strategies for achieving high SWB. It also highlights novel ways in which SWB could be effectively improved. These considerations lead us to propose a novel computational framework for understanding SWB. We highlight several parameters in these models that could explain individual and cultural differences in SWB, and how they might inspire novel interventions. We conclude by proposing a line of future empirical research based on computational modelling that could complement current approaches to the study of wellbeing and its improvement.
Magnetic alumite discs were obtained using anodic oxidation method. An additional chemical texture process was effective in improving tribological and magnetic recording characteristics. These discs were confirmed to exhibit a large Kerr rotation as well as a refractance with an angle as large as one degree
This study proposes the notion of “root concepts” in cultural production, defined as a novel style and mode that a creator expresses at the initial field development phase, and that has a great influence on subsequent creators. We explore the role of root concepts in cultural evolution by focusing on their capacity to generate new combinations with other elements and examine how creators use root concepts jointly with other elements. Using data on artists and albums in the rap genre from the online database Allmusic, we view music moods as a type of experience that music generates and focus on music moods as a phenotype in studying styles and modes. We constructed a dataset of recombinatory patterns in the subsequent cultural production and identified two types of root concepts: implosive concepts, which artists use jointly with similar elements; and explosive concepts, which artists use in conjunction with highly diversified elements. Implosive concepts are exclusive because they require creators to have network contagions with those familiar with the root concepts and have strong and specific socio-economic identities. Previous research has suggested that finding a new combination is challenging owing to creators’ limited cognitive capacities and the resulting local search. Our finding presents an alternative explanation: some root concepts (i.e., implosive ones) possess innate characteristics that limit creators from experimentally integrating diversified elements. This study develops new opportunities for future research on the evolutionary growth of cultural production and knowledge fields.
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