# Interrogation of network-wide neuronal dynamics during fear memory in mouse default mode network

> **NIH NIH K08** · STANFORD UNIVERSITY · 2020 · $187,057

## Abstract

Project Abstract
 Cognitive symptoms are a clinically important component of many psychiatric disorders,
affecting complex domains, like long-term memory, mediated by coordinated interaction of
activity across brain-wide networks. Importantly, the specific neuronal dynamics and
mechanisms underlying integrated network function are incompletely understood, even in
health. The objective of this proposal is to understand how correlated neuronal dynamics in a
clinically important memory-related network, the default mode network (DMN), contribute to
memory processing using a mouse model. The central hypothesis is that correlated low-
frequency activity across the DMN occurs in short periods of time associated with
propagation of memory-related activity between network structures. The proposal probes
DMN function by combining optogenetics with a novel optical technique, multifiber
photometry (MFP), which directly measures neuronal dynamics simultaneously across DMN
areas. My preliminary studies using MFP show slow correlated dynamics in excitatory neuron
populations across DMN (but not a control area) in mouse. I can now directly probe the real-
time network-wide neuronal activity and interactions associated with correlated DMN
dynamics during memory. Aim 1 will determine how reliably theta, 3-10Hz activity classically
associated with memory, propagates through the DMN in its correlated state. Aim 2 will
examine DMN dynamics induced by memory (fear conditioning), and their relationship to recall
(context recall). Aim 3 will demonstrate DMN interactions during memory by optogenetically
inhibiting individual areas during memory processing and measuring resulting network
dynamics. These aims represent the first in-depth dissection of neuronal dynamics across the
DMN during memory. They utilize an innovative approach, leveraging novel and generalizable
methods in a mouse model to generate fundamental insight into DMN function during long-
term memory, with relevance to human neuroimaging findings and clinical symptoms. In the
process, I will become proficient in all-optical approaches to probing distributed networks,
analysis of network-wide activity, and integrated behavioral testing. I will work with an expert
advisory committee (Dr. Deisseroth, Dr. Blair, Dr. Wiltgen, Dr. Etkin, Dr. O’Hara) with pioneering
experience mentoring trainees in these methods. This training in cutting-edge systems
neuroscience, will critically supplement my molecular and cellular neuroscience background,
allowing me to launch a career as an independent investigator examining how distributed
neural circuits integrate and regulate their function to generate cognition in health and disease.

## Key facts

- **NIH application ID:** 9764515
- **Project number:** 5K08MH117350-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Carrie Shilyansky
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $187,057
- **Award type:** 5
- **Project period:** 2018-08-15 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9764515

## Citation

> US National Institutes of Health, RePORTER application 9764515, Interrogation of network-wide neuronal dynamics during fear memory in mouse default mode network (5K08MH117350-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9764515. Licensed CC0.

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