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Abstract
'Neuroeconomics' can be broadly defined as the research of how the brain interacts with the environment to make decisions that are functional given individual and contextual constraints. Deciphering such brain-environment transactions requires mechanistic understandings of the neurobiological processes that implement value-dependent decision making. To this end, a common empirical approach is to investigate neural mechanisms of reward-based decision making. Flexible updating of choices and associated expected outcomes in ways that are adaptive for a given task (or a given set of tasks) at hand relies on dynamic neurochemical tuning of the brain's functional circuitries involved in the representation of tasks, goals and reward prediction. Empirical evidence as well as computational theories indicate that various neurotransmitter systems (e.g., dopamine, norepinephrine, and serotonin) play important roles in reward-based decision making. In light of the apparent aging-related decline in various aspects of the dopaminergic system as well as the effects of neuromodulation on reward-related processes, this article focuses selectively on the literature that highlights the triadic relations between dopaminergic modulation, reward-based decision making, and aging. Directions for future research on aging and neuroeconomoics are discussed.

The Oxford Handbook of Cultural Neuroscience and Global Mental Health is the first ever comprehensive overview of this field. It explores how culture influences and affects the neurobiological mechanisms underlying mental health, and the disparities that exist in the treatment of mental health across the world.

The 'Oxford Handbook of Cultural Neuroscience and Global Mental Health' is a comprehensive overview of this field. It explores how culture influences and affects the neurobiological mechanisms underlying mental health, and the disparities that exist in the treatment of mental health across the world.

AbstractObservational learning is an important mechanism for cognitive and social development. However, the neurophysiological mechanisms underlying observational learning in children are not well understood. In this study, we used a probabilistic reward‐based observational learning paradigm to compare behavioral and electrophysiological markers of individual and observational reinforcement learning in 8‐ to 10‐year‐old children. Specifically, we manipulated the amount of observable information as well as children's similarity in age to the observed person (same‐aged child vs. adult) to examine the effects of similarity in age on the integration of observed information in children. We show that the feedback‐related negativity (FRN) during individual reinforcement learning reflects the valence of outcomes of own actions. Furthermore, we found that the feedback‐related negativity during observational reinforcement learning (oFRN) showed a similar distinction between outcome valences of observed actions. This suggests that the oFRN can serve as a measure of observational learning in middle childhood. Moreover, during observational learning children profited from the additional social information and imitated the choices of their own peers more than those of adults, indicating that children have a tendency to conform more with similar others (e.g. their own peers) compared to dissimilar others (adults). Taken together, our results show that children can benefit from integrating observable information and that oFRN may serve as a measure of observational learning in children.

In the early 2020s, the coronavirus pandemic brought the notion of remotely connected care to the general population across the globe. Oftentimes, the timely provisioning of access to and the implementation of affordable care are drivers behind tele-healthcare initiatives. Tele-healthcare has already garnered significant momentum in research and implementations in the years preceding the worldwide challenge of 2020, supported by the emerging capabilities of communication networks. The Tactile Internet (TI) with human-in-the-loop is one of those developments, leading to the democratization of skills and expertise that will significantly impact the long-term developments of the provisioning of care. However, significant challenges remain that require today's communication networks to adapt to support the ultra-low latency required. The resulting latency challenge necessitates trans-disciplinary research efforts combining psychophysiological as well as technological solutions to achieve one millisecond and below round-trip times. The objective of this paper is to provide an overview of the benefits enabled by solving this network latency reduction challenge by employing state-of-the-art Time-Sensitive Networking (TSN) devices in a testbed, realizing the service differentiation required for the multi-modal human-machine interface. With completely new types of services and use cases resulting from the TI, we describe the potential impacts on remote surgery and remote rehabilitation as examples, with a focus on the future of tele-healthcare in rural settings.