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Aberrant neural computation of social controllability in nicotine-dependent humans

Medicine and Health

Aberrant neural computation of social controllability in nicotine-dependent humans

C. Mclaughlin, Q. X. Fu, et al.

This fascinating study by Caroline McLaughlin, Qi Xiu Fu, Soojung Na, Matthew Heflin, Dongil Chung, Vincenzo G. Fiore, and Xiaosi Gu uncovers the social controllability deficits in nicotine-dependent individuals. Using advanced fMRI techniques, the researchers highlight how smokers perceive less control and struggle with social influence, revealing crucial insights into addiction and social cognition.... show more
Abstract
Social controllability, or the ability to exert control during social interactions, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as smoking, which often takes place in social settings. Here, we examined social controllability in nicotine-dependent humans as they performed an fMRI task where they could influence the offers made by simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.
Publisher
Communications Biology
Published On
Aug 14, 2024
Authors
Caroline McLaughlin, Qi Xiu Fu, Soojung Na, Matthew Heflin, Dongil Chung, Vincenzo G. Fiore, Xiaosi Gu
Tags
nicotine dependence
social controllability
fMRI
smokers
social prediction errors
vmPFC
computational modeling
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