scholarly journals Putting the Nonsocial Into Social Neuroscience: A Role for Domain-General Priority Maps During Social Interactions

2020 ◽  
Vol 15 (4) ◽  
pp. 1076-1094 ◽  
Author(s):  
Richard Ramsey ◽  
Rob Ward

Whether on a first date or during a team briefing at work, people’s daily lives are inundated with social information, and in recent years, researchers have begun studying the neural mechanisms that support social-information processing. We argue that the focus of social neuroscience research to date has been skewed toward specialized processes at the expense of general processing mechanisms with a consequence that unrealistic expectations have been set for what specialized processes alone can achieve. We propose that for social neuroscience to develop into a more mature research program, it needs to embrace hybrid models that integrate specialized person representations with domain-general solutions, such as prioritization and selection, which operate across all classes of information (both social and nonsocial). To illustrate our central arguments, we first describe and then evaluate a hybrid model of information processing during social interactions that (a) generates novel and falsifiable predictions compared with existing models; (b) is predicated on a wealth of neurobiological evidence spanning many decades, methods, and species; (c) requires a superior standard of evidence to substantiate domain-specific mechanisms of social behavior; and (d) transforms expectations of what types of neural mechanisms may contribute to social-information processing in both typical and atypical populations.

2019 ◽  
Author(s):  
Richard Ramsey ◽  
Robert Ward

Whether on a first-date or during a team briefing at work, our daily lives are inundated with social information and in recent years research has begun studying the neural mechanisms that support social information processing. We argue that the focus of social neuroscience research to date has been skewed towards specialised processes at the expense of general processing mechanisms with a consequence that unrealistic expectations have been set for what specialised processes alone can achieve. We propose that for social neuroscience to develop into a more mature research programme, it needs to embrace hybrid models that integrate specialised person representations with domain-general solutions, such as prioritisation and selection, which operate across all classes of information (both social and non-social). To illustrate our central arguments, we first describe then evaluate a hybrid model of information processing during social interactions that: 1) generates novel and falsifiable predictions compared to existing models; 2) is predicated on a wealth of neurobiological evidence spanning many decades, methods and species; 3) requires a superior standard of evidence to substantiate domain-specific mechanisms of social behaviour, and; 4) transforms expectations of what types of neural mechanisms may contribute to social information processing in both typical and atypical populations.


2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.


2008 ◽  
Author(s):  
Jonathan M. Kurss ◽  
Anna E. Craig ◽  
Jennifer Reiter-Purtill ◽  
Kathryn Vannatta ◽  
Cynthia Gerhardt

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