# Understanding overlap in resting state fMRI networks at the single cell level: a cross-species approach

> **NIH NIH R34** · WASHINGTON UNIVERSITY · 2020 · $708,750

## Abstract

Understanding overlap in resting state fMRI networks at the single cell level: a cross-species
approach
Abstract
Resting state functional connectivity MRI (rsfcMRI) is a popular tool to investigate the intrinsic
functional organization of the brain into large scale networks. Multiple different lines of
investigation have pointed to the importance of densely interconnected `hub' regions for
cognition and behavior. However, the functional architecture of cellular circuits in these hub
regions is unknown. To study the cellular underpinnings of hub regions, we bring together an
interdisciplinary research team to bridge across species and across scales. We start by
generalizing recent advances in human fcMRI analyses across species to characterize
individualized patterns of network overlap in rsfcMRI data from awake macaque monkeys (Aim
1). This allows us to identify regions of interest for recordings in this same animals from a hub
region where two (or more) networks spatially overlap, and from two non-hub regions that
strongly contribute to only one of the networks respectively. We then ask whether, at a finer
cellular scale, there is true neural coupling between both networks in hub regions, or whether
networks that appear spatially overlapping at the resolution of rsfcMRI data are in fact spatially
interdigitated rather than overlapping at a finer scale (Aim 2). Lastly, we use electrophysiological
recordings to determine whether individual neurons in hub regions integrate information from
both overlapping networks (i.e. coupling), or whether neurons dynamically switch their network
allegiance from one network to another over time (Aim 3). The outcomes of this proposal have
important implications for the modeling and interpretation of human rsfcMRI data. This R34
proposal provides the opportunity to establish a new collaboration and validate our methodology
across species. These factors are essential for the next stage of our project, a Targeted Brain
Circuits Project R01 proposal, in which we will build on this line of investigation by bridging into
behavior to study how fundamental principles of the brain circuits in hub regions form the
biological basis of mental processes.

## Key facts

- **NIH application ID:** 10059107
- **Project number:** 1R34NS118618-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Janine Diane Bijsterbosch
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $708,750
- **Award type:** 1
- **Project period:** 2020-08-15 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10059107

## Citation

> US National Institutes of Health, RePORTER application 10059107, Understanding overlap in resting state fMRI networks at the single cell level: a cross-species approach (1R34NS118618-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10059107. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*