# Circuit Mechanisms Governing the Default Mode Network

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $732,894

## Abstract

PROJECT SUMMARY
 Non-invasive functional magnetic resonance imaging (fMRI) has revolutionized our
understanding of macroscopic functional brain networks. However, inherent constraints of current fMRI
methodologies in humans limit our ability to probe the mechanisms underlying these networks. The
overarching goal of this project is to shed light on cellular and circuit mechanisms underlying the
functional organization of the default-mode network (DMN) – a large-scale brain network that is crucial
for a wide range of behaviors. While the new technologies in rodents allows us to experimentally reveal
causal control of DMN, rodent DMN topology has only been defined using resting-state fMRI, but not
functionally in terms of activation or suppression of brain activity in response to behaviorally relevant
salient stimuli. This represents a critical barrier preventing any straightforward translation between
rodent and human DMN research findings. To address this, we developed a novel silent zero-echo-
time (ZTE) fMRI technique, enabling awake rodent imaging and the use of an auditory oddball
paradigm, wherein deviant oddball stimuli presented amongst a sequence of repetitive control stimuli
can drive attention and suppress DMN. We also developed an MR-compatible, four-channel,
spectrally-resolved fiber-photometry system, allowing concurrent recording of ground-truth neuronal
activities during fMRI. To shed light on the circuit mechanisms governing the DMN, we proposed
two complementary research Aims building on our rigorous prior research. In Aim 1, we will determine
how attention to salient stimuli alters DMN activity and connectivity using the novel ZTE-photometry
platform. In Aim 2, we will introduce time-locked optogenetics on defined cell types to causally
manipulate the activity of anterior insula – the brain region assumed to be responsible for DMN dynamic
switching in numerous fMRI causal modeling studies. Functionally dissecting the rodent DMN
architecture is critical to the understanding of DMN transition mechanisms, which will enable us to
causally model, and make predictions about brain states, bringing insight into the network basis of
human behavior and neuropsychiatric/neurological disorders.
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## Key facts

- **NIH application ID:** 10380898
- **Project number:** 5R01MH126518-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Vinod Menon
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $732,894
- **Award type:** 5
- **Project period:** 2021-04-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10380898

## Citation

> US National Institutes of Health, RePORTER application 10380898, Circuit Mechanisms Governing the Default Mode Network (5R01MH126518-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10380898. Licensed CC0.

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