Odor modulates the temporal dynamics of fear memory consolidation.

Learn Mem

Psychological and Brain Sciences, Boston University, Boston, Massachusetts 02215, USA.

Published: April 2020

Systems consolidation (SC) theory proposes that recent, contextually rich memories are stored in the hippocampus (HPC). As these memories become remote, they are believed to rely more heavily on cortical structures within the prefrontal cortex (PFC), where they lose much of their contextual detail and become schematized. Odor is a particularly evocative cue for intense remote memory recall and despite these memories being remote, they are highly contextual. In instances such as posttraumatic stress disorder (PTSD), intense remote memory recall can occur years after trauma, which seemingly contradicts SC. We hypothesized that odor may shift the organization of salient or fearful memories such that when paired with an odor at the time of encoding, they are delayed in the de-contextualization process that occurs across time, and retrieval may still rely on the HPC, where memories are imbued with contextually rich information, even at remote time points. We investigated this by tagging odor- and non-odor-associated fear memories in male c57BL/6 mice and assessed recall and expression in the dorsal CA1 (dCA1) and prelimbic cortex (PL) 1 or 21 d later. In support of SC, our data showed that recent memories were more dCA1-dependent whereas remote memories were more PL-dependent. However, we also found that odor influenced this temporal dynamic, biasing the memory system from the PL to the dCA1 when odor cues were present. Behaviorally, inhibiting the dCA1 with activity-dependent DREADDs had no effect on recall at 1 d and unexpectedly caused an increase in freezing at 21 d. Together, these findings demonstrate that odor can shift the organization of fear memories at the systems level.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079569PMC
http://dx.doi.org/10.1101/lm.050690.119DOI Listing

Publication Analysis

Top Keywords

memories
9
contextually rich
8
hpc memories
8
memories remote
8
intense remote
8
remote memory
8
memory recall
8
odor shift
8
shift organization
8
fear memories
8

Similar Publications

Script training is a speech-language intervention designed to promote fluent connected speech via repeated rehearsal of functional content. This type of treatment has proven beneficial for individuals with aphasia and apraxia of speech caused by stroke and, more recently, for individuals with primary progressive aphasia (PPA). In the largest study to-date evaluating the efficacy of script training in individuals with nonfluent/agrammatic primary progressive aphasia (nfvPPA; Henry et al.

View Article and Find Full Text PDF

Cortical lesions impact cognitive decline in multiple sclerosis via volume loss of nonlesional cortex.

Ann Clin Transl Neurol

December 2024

MS Center Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Objective: To assess the interrelationship between cortical lesions and cortical thinning and volume loss in people with multiple sclerosis within cortical networks, and how this relates to future cognition.

Methods: In this longitudinal study, 230 people with multiple sclerosis and 60 healthy controls underwent 3 Tesla MRI at baseline and neuropsychological assessment at baseline and 5-year follow-up. Cortical regions (N = 212) were divided into seven functional networks.

View Article and Find Full Text PDF

Objective: Functional MRI (fMRI) helps with the identification of eloquent cortex to assist with function preservation in patients who undergo epilepsy surgery. Language and memory tasks can even be used effectively in clinically involved pediatric patients. Most pediatric studies report on English speaking-only cohorts from English-dominant countries, yet languages other than English (LOEs) are increasingly prevalent in countries such as the US.

View Article and Find Full Text PDF

Memristive Ion Dynamics to Enable Biorealistic Computing.

Chem Rev

December 2024

Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089, United States.

Conventional artificial intelligence (AI) systems are facing bottlenecks due to the fundamental mismatches between AI models, which rely on parallel, in-memory, and dynamic computation, and traditional transistors, which have been designed and optimized for sequential logic operations. This calls for the development of novel computing units beyond transistors. Inspired by the high efficiency and adaptability of biological neural networks, computing systems mimicking the capabilities of biological structures are gaining more attention.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!