# Distinct Mechanisms of Cognitive Behavioral Therapy Effects in Youth with Migraine: Insights from Neuroimaging and Quantitative Sensory Testing (The How and Why Youth with Headaches Get Better Study)

> **NIH NIH R01** · CINCINNATI CHILDRENS HOSP MED CTR · 2022 · $603,127

## Abstract

Project Summary:
The Federal Pain Research Strategy highlights the need for investigation of biological mechanisms that
underlie the treatment effects of non-pharmacological interventions in pediatric chronic pain patients.
Understanding biological mechanisms can advance the use of effective treatments such as cognitive
behavioral therapy (CBT) by providing patients and families with a stronger rationale for treatment, thereby
decreasing stigma and increasing confidence in and commitment to the care plan. In addition, mechanstic
insights foster patients' ability to effectively participate in shared decision-making and self-management, may
provide for more individualized and precise care, and will increase uptake by health care providers, patients,
and payors. Neuroimaging and quantitative sensory testing (QST) are techniques that can provide insight into
the biological basis for pain treatment effects. This project will study migraine, which affects > 6 million youth in
the U.S. Cochrane reviews show that psychological therapies for pediatric headache result in better outcomes
than control conditions (56% improved vs. 22% in 714 participants), and our CBT+Amitriptyline Study found
that 66% of youth with chronic migraine had a ≥ 50% reduction in headache days compared to 36% in an
education control+Amitriptyline (AMI) group. Despite this evidence base, the neural mechanisms supporting
the efficacy of CBT for pain remain poorly understood. The lack of mechanistic understanding is a barrier to
treatment utilization, particularly given the time, effort, and expense for pediatric migraine patients to receive
CBT vs. conventional pharmacological therapy (which in a national trial reduced headache days similar to
placebo pill: AMI 52% of participants improved; Placebo 61%). Pilot data from our group demonstrate that:
CBT induces changes in brain connectivity/activation, and QST at baseline predicts reduced migraines at 8
weeks. These findings show proof of concept specific to pediatric migraine patients and refined the design of
this project, which will recruit 240 youth ages 10 to 17 with migraine to undergo functional MRI and QST before
and after 8 weeks of either CBT, placebo, or AMI to address these aims: Aim 1: Does CBT engage brain
mechanisms which are distinct from those engaged by pill-based therapy (placebo & AMI)? Aim 2: Are poorer
baseline pain modulatory mechanisms measured by QST predictive of greater headache day reduction from
CBT vs. pill-based therapy? Exploratory Aims: a. Assess whether brain changes at 8 weeks in those who
receive CBT play a mediational role when outcomes are assessed at a 3 month follow-up; b. Test if the
findings from Aims 1 and 2 are supported when other pain contextual variables (anxiety, depression, sleep) are
included in the statistical models; c. Compare neuroimaging between placebo and AMI; d. All analyses will
include age, sex, pubertal status, and brain structural connectivity in the statistical models to as...

## Key facts

- **NIH application ID:** 10395448
- **Project number:** 5R01NS101321-05
- **Recipient organization:** CINCINNATI CHILDRENS HOSP MED CTR
- **Principal Investigator:** Robert C Coghill
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $603,127
- **Award type:** 5
- **Project period:** 2018-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10395448

## Citation

> US National Institutes of Health, RePORTER application 10395448, Distinct Mechanisms of Cognitive Behavioral Therapy Effects in Youth with Migraine: Insights from Neuroimaging and Quantitative Sensory Testing (The How and Why Youth with Headaches Get Better Study) (5R01NS101321-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10395448. Licensed CC0.

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