Understanding gratification delay from an evolutionary perspective helps to provide broader insights and opportunities to better understand the mechanism of self-control in humans. This study investigated delay of gratification, using accumulation and exchange tasks, in 8 non-human primate species at Nakhon Ratchasima Zoo, Thailand. The results agree with our hypothesis; the evolutionarily closer to humans the primates are, the more gratification delay ability they have. Comparative studies of primate cognition helped to deepen our understanding of human cognition and will lead to strategies to improve the capacity thereof.Reward plays a crucial role in supporting the selective processing of sensory information. Past studies in human adults have shown that rewarding stimuli could automatically capture attention even when they are behaviorally irrelevant and unactionable. While neural mechanisms underlying value-driven attention have been well understood in adulthood, it is still unclear how the human brain develops to support value-driven attention. Here, we measured EEG from typically developing early teens (13-15 years old), late teens (16-17 years old), and adults (19-31 years old) performing a value-driven attention task. Overall, we found that adults were generally faster and more accurate at selecting targets compared to early and late teens. Interestingly, we found that in late adolescence, selection history started to have robust impacts on behavioral performance and the amplitudes of the N2pc component a well-known neural index of target- related processing. However, reward did not modulate changes in behavioral performance or neural activity and it did not interact with selection history. In contrast, behavioral performance and the N2pc amplitudes were modulated by both selection and reward history. In particular, high-valued distractors worsen behavioral performance with a relatively higher degree compared to the low-valued-distractor and no-distractor conditions. Consistent with the behavioral results, this reward-based behavioral interference was accompanied by the reduction in the N2pc amplitude induced by distractors with higher value—a phenomenon that only occurred in adults. The comparable degrees of behavioral interference induced by the high-valued distractors and the corresponding reduction in the N2pc amplitude between late adolescents and adults. That said, low-valued distractors produced much higher attentional capture effects in late adolescents compared to early adolescents and adults at both behavioral and neural levels. Together, our findings suggest that value-driven attention emerges from the increase in the potentiation of the attentional network to both low- and high-valued stimuli during late adolescence, followed by the reduced distractibility of the attentional system to low-valued stimuli later in development. Taken together, the distinct impacts of selection and reward history on behavioral and neural results suggest that the interaction between attention and reward systems in human undergo significant changes much later in development to support value-driven attentional functions in early adulthood.In this project we have attempted to measure the experience users have while interacting with novel conversational AI devices like voice assistants (VAs) from a usability perspective. However, a basic challenge was to identify the relevant usability dimensions, due to which an extensive literature search was carried out. Anthropomorphism and personality of the AI agents were some of the new factors that emerged that had not been considered by previous research. Accordingly, we developed a usability as well as a personality scale for measuring these aspects. We also extended our model by considering Thai as the conversational medium between the humans and the VAs. We supplemented the developed usability scale by testing the acceptance of these devices in the mass consumer electronics (CE) market based on the attachment and love users develop for them and their humanness aspect. For greater societal impact, we segmented the users into early vs. late adopters of innovative technologies to check if any differences exist within the two groups.110Sirawaj ITTHIPURIPAT111Debajyoti PALThe Neurodevelopment of Value-driven Attention(Project 2020)Measuring the End-User Experience with Voice-Assistants: from Usability to Acceptance(Project 2021)79
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