Skip to content Skip to navigation

Transcriptomic analysis of neural circuits activated during encoding of long-term memory

Stanford Neurosciences Institute, Boxuan Zhao

Our ability to remember makes us human, and is essential for advanced cognition – for acquiring new skills, and for integrating previous experiences into future decision-making. While it is known that long-term memory (LTM) formation requires new gene expression, we lack a detailed and comprehensive understanding of which genes must be expressed to encode memories, and how these genes change over time during the consolidation of memories. The major objective of this proposal is to reach a comprehensive molecular and mechanistic understanding of LTM.

Here I propose to use fear conditioning in mice to uncover the molecular pathways underlying LTM formation; and at the same time, produce transformative technologies (“FLARE-omics”) to overcome the long tagging window limitation of current tools by selectively labeling functional circuits with high temporal resolution. Through the profiling of transcriptome and epitranscriptome dynamics of active neurons during fear memory formation, we  will identify differences in post-transcriptional regulation and gene expression dynamics over time, potentially revealing key factors in memory-encoding mechanisms and/or interesting targets for the manipulation of LTM for therapeutic benefit. 

My proposed study will provide a comprehensive molecular characterization of the RNA content of neurons activated specifically by fear conditioning, including RNA methylation patterns, and thereby gain unprecedented insight into basic mechanisms underlying LTM encoding. My proposed study also has broad significance beyond memory study, as we will develop and make widely available a family of new molecular technologies, which can be used by other neuroscientists to characterize transcriptomes of specific subsets of neurons that are activated during any behavior or cognitive process of interest with unprecedented speed and accuracy, and provide a means to interrogate the mechanisms by which these circuits encode function.


Lead Researcher(s): 


Alice Ting (Genetics & Biology) and Liqun Luo (Biology)

Funding Type: 
Postdoctoral Fellowship
Award Year: