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Dean Mobbs

Researcher at California Institute of Technology

Publications -  93
Citations -  10464

Dean Mobbs is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Anxiety & Ventromedial prefrontal cortex. The author has an hindex of 40, co-authored 84 publications receiving 7729 citations. Previous affiliations of Dean Mobbs include Cognition and Brain Sciences Unit & Stanford University.

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Reduced parietal and visual cortical activation during global processing in Williams syndrome

TL;DR: Preliminary results largely confirm previous research findings and neural models implicating neurodevelopmental abnormalities in extended subcortical and cortical visual systems in WS, most notably dorsal‐stream pathways.
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The ethological deconstruction of fear(s)

TL;DR: This work attempts to clarify semantic issues by describing the link between ethologically defined defensive strategies and fear and provides a clearer differentiation between fears, the contexts that evoke them and how they are organized within defensive survival circuits.
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The role of empathy in experiencing vicarious anxiety.

TL;DR: The results highlight the impact of one’s social environment on experiencing anxiety, particularly for those who are highly empathic, and have implications for extending basic models of anxiety to incorporate interpersonal processes, understanding the role of empathy in social learning, and potential applications for therapeutic contexts.

Using social and behavioural science to support COVID-19 pandemic response

Jay J. Van Bavel, +42 more
TL;DR: In this paper, the authors discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping.
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Mentalizing during social InterAction: A four component model

TL;DR: The interactive mentalizing theory (IMT) is proposed -to emphasize the role of metacognition in different mentalizing components and to advance knowledge on mentalizing during live social interaction by identifying how these subprocesses can be organized by different target agents and facilitated by combining computational modeling and interactive brain approaches.