# Understanding evoked and resting-state fMRI through multi scale imaging

> **NIH NIH R01** · YALE UNIVERSITY · 2020 · $933,301

## Abstract

Project Summary
This RFA is aimed at bringing together interdisciplinary teams to focus on novel, transformative and integrative
efforts that will revolutionize our understanding of the biological and bioinformatics content of the data collected
from non-invasive human functional brain imaging techniques. Our proposal does exactly this. We are a
multidisciplinary team of scientists with combined expertise in optogenetics, two photon Ca2+ imaging,
biomedical engineering, molecular biology, animal and human fMRI, network theory, data analysis and
modeling. In this work, we will use a novel imaging device that combines mesoscopic imaging of genetically
encoded Ca2+ indicators with very high (50m) spatial and high temporal (25ms) resolution across the entire
cortex and simultaneous fMRI in transgenic mouse models. These animal experiments are designed to
complement similar experiments in healthy human subjects. The results from the animal experiments will
answer several long-standing questions about the source of the fMRI signal. Specifically, using imaging, we
will quantify the contributions of different cell populations (excitatory neurons, inhibitory neurons, and glial cells)
to the fMRI signal observed. We will be able to test and validate, for the first time, the application of graph
theory approaches to the analysis of human fMRI data, and we will develop and test a new approach based on
control theory for extracting more information from the fMRI signal. A powerful set of carefully controlled
imaging experiments in mice will inform several aspects of analysis of human data. The human data will
contain a test/retest component to ensure replication of the results and to allow predictive models to be built in
one data set and tested in another. This work truly bridges scale and modalities and the simultaneous nature of
the animal experiments will allow unprecedented clarity on the underlying source of the signal changes
observed in fMRI. These animal studies are essential for providing new insights into the basis of human fMRI
signals and data of this nature has not previously been available. The work in this proposal is novel in that it
will directly inform measures of both evoked and spontaneous activity in terms of the underlying cell signal
sources revealing the relative contributions of excitatory, inhibitory and glial cells to the fMRI signal. The
implications of the work are multifaceted. This work will provide a platform for evaluating neurological models
of disease. For example, mouse models of disease can be used to link to human data in diseases such as
PTSD, depression, and autism, to name a few. It will also provide a firmer biological basis for understanding
the node and network measures used in assessing the functional organization of the brain and will have
important implications for the design of therapeutic interventions across a range of diseases.

## Key facts

- **NIH application ID:** 9986022
- **Project number:** 5R01MH111424-05
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** R Todd Constable
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $933,301
- **Award type:** 5
- **Project period:** 2016-09-16 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986022

## Citation

> US National Institutes of Health, RePORTER application 9986022, Understanding evoked and resting-state fMRI through multi scale imaging (5R01MH111424-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9986022. Licensed CC0.

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