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Campbell, Angus Gordon

University of British Columbia

The physical substrate of memory in the brain is still a subject of debate. It is thought that strongly connected networks of neurons, called engrams, can reproduce the original activity pattern from partial cues. Synapses between engram neurons are thus the most likely candidate for memory storage; but questions remain over their long-term stability. Some groups have proposed activity related transcription, while normally considered transient, could be the beginning of a transition to a more permanent cell type that stores long term memory. Persistent chromatin conformation changes and resulting transcription changes, triggered by reactivation, could be a stable long-lasting storage mechanism which enables remembering at remote time points. Some groups have reported transcription predicted by this model. We trained classifiers using single-cell RNA (scRNA-seq) sequencing from the earlier transient signature (Jaeger et al., 2018; Lacar et al., 2016) and the long term engram neuron signature (Chen et al., 2020). The transient early signature was readily identifiable but when trying to identify engram cells exhibiting the long-term memory signature we found a significant decrease in classifier performance. The important features of the classifier were not genes reported as deferentially expressed in the original publication. Reproducing the original author’s results using their data proved challenging, suggesting the persistent long-term memory signature was not detected or does not exist. Reactivation did not appear to elicit a strong transcriptional response either, which contradicts models of transcriptomic engram cell formation. Unfortunately, the design of the original experiment does not allow for the falsification of the supposed persistent transcriptional program induced by reactivation. My research suggests future directions to take in evaluating transcription’s contribution to synaptic plasticity and memory.

Text

2023-09-26

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/86020

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/