# Boosting mind-body mechanisms for mitigating neuroinflammation in migraine

> **NIH NIH P01** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $677,876

## Abstract

Project Summary/Abstract 
Migraine headaches represent the third most prevalent medical disorder on the planet, yet many sufferers are 
not satisfactorily treated, and 3% of them suffer chronification of their migraine every year. Cortical spreading 
depression and hyperexcitability of the brain have been demonstrated in migraine, and migraine pain has been 
related to neuroinflammation. In this project, we propose to use PET/MRI using a translocator protein marker 
(TSPO), as well as a measure of the infra-slow oscillatory activity to assess neuroinflammation in migraine. 
Then, we will examine the effect of a mind-body therapy on neuroinflammation. Our design will combine a top- 
down approach, namely mindfulness mediation, with a bottom-up approach, i.e. non-invasive transcutaneous 
vagus nerve stimulation, and examine the synergistic effect of these therapies on both microglial/astrocytic 
activation as measured with PET and on the fluctuation of low-frequency oscillatory activity. Our results will 
indicate whether a coupling of a top-down with a bottom-up therapeutic approach can have measurable effects 
on neuroinflammation in migraine, and indicate whether glial activation may be a therapeutic target for 
migraine.

## Key facts

- **NIH application ID:** 10456011
- **Project number:** 5P01AT009965-04
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Marco Luciano Loggia
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $677,876
- **Award type:** 5
- **Project period:** 2018-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10456011

## Citation

> US National Institutes of Health, RePORTER application 10456011, Boosting mind-body mechanisms for mitigating neuroinflammation in migraine (5P01AT009965-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10456011. Licensed CC0.

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