Current Biology
Volume 32, Issue 2, 24 January 2022, Pages 304-314.e5
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Article
Neural reinstatement reveals divided organization of fear and extinction memories in the human brain

https://doi.org/10.1016/j.cub.2021.11.004Get rights and content
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Highlights

  • MVPA of fMRI dissociates competing memories of fear and extinction in humans

  • Memories of fear/extinction coded in dorsal/ventral prefrontal cortex, respectively

  • Medial temporal lobe activity predicts locus of reinstatement in prefrontal cortex

  • In a PTSD group, extinction memory misallocated to dorsal region coding for fear

Summary

Neurobiological research in rodents has revealed that competing experiences of fear and extinction are stored as distinct memory traces in the brain. This divided organization is adaptive for mitigating overgeneralization of fear to related stimuli that are learned to be safe while also maintaining threat associations for unsafe stimuli. The mechanisms involved in organizing these competing memories in the human brain remain unclear. Here, we used a hybrid form of Pavlovian conditioning with an episodic memory component to identify overlapping multivariate patterns of fMRI activity associated with the formation and retrieval of fear versus extinction. In healthy adults, distinct regions of the medial prefrontal cortex (PFC) and hippocampus showed selective reactivation of fear versus extinction memories based on the temporal context in which these memories were encoded. This dissociation was absent in participants with posttraumatic stress disorder (PTSD) symptoms. The divided neural organization of fear and extinction may support flexible retrieval of context-appropriate emotional memories, while their disorganization may promote overgeneralization and increased fear relapse in affective disorders.

Keywords

threat
inhibition
associative learning
declarative memory
MVPA
reactivation
representational similarity
Pavlovian conditioning

Data and code availability

  • All deidentified neuroimaging and behavioral data have been deposited at OSF and are publicly available as of the date of the publication. The DOI is listed in the Key resources table.

  • All custom python and R code used for analysis has been deposited at OSF and is publicly available as of the date of publication. The DOI is listed in the Key resources table.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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Twitter: @joeydunsmoor

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Lead contact