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The effect of concurrent reward on aversive information processing in the brain

Neural networks for the processing of appetitive and aversive information, in isolation, have been well characterized. However, how the brain integrates competing signals associated with simultaneous appetitive and aversive information is less clear. In particular, it is unknown how the presence of...

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Detalles Bibliográficos
Autores principales: Kim, Andy J., Anderson, Brian A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474551/
https://www.ncbi.nlm.nih.gov/pubmed/32360930
http://dx.doi.org/10.1016/j.neuroimage.2020.116890
Descripción
Sumario:Neural networks for the processing of appetitive and aversive information, in isolation, have been well characterized. However, how the brain integrates competing signals associated with simultaneous appetitive and aversive information is less clear. In particular, it is unknown how the presence of concurrent reward modulates the processing of an aversive event throughout the brain. Here, we utilized a four-armed bandit task in an fMRI study to measure the representation of an aversive electric shock with and without the simultaneous receipt of monetary reward. Using a region of interest (ROI) approach, we first identified regions activated by the experience of aversive electric shock, and then measured how this shock-related activation is modulated by concurrent reward using independent data. Informed by prior literature and our own preliminary data, analyses focused on the dorsolateral prefrontal cortex, anterior and posterior insula, anterior cingulate cortex, and the thalamus and somatosensory cortex. We hypothesized that the neural response to punishment in these ROIs would be attenuated by the presence of concurrent reward. However, we found no evidence of concurrent reward attenuating the neural response to punishment in any ROI and also no evidence of concurrent punishment attenuating the neural response to reward in exploratory analyses. Altogether, our findings are consistent with the idea that neural networks responsible for the processing of reward and punishment signals are largely independent of one another, and that representations of overall value or utility are arrived at through the integration of separate reward and punishment signals at later stages of information processing.