# Testing a theory of avoidance learning & overgeneralization in chronic pain

> **NIH NIH P20** · BROWN UNIVERSITY · 2022 · $393,149

## Abstract

When we touch a hot stove or bang our foot against the living room table, it hurts. While irritating in the 
moment, acute pain serves an important purpose. First, it triggers an immediate defensive response to 
prevent or avoid further tissue damage. Second, it serves as a potent teaching signal to make sure we 
avoid making the same mistake in the future. This is an adaptive response if pain perception subsides 
when the tissue heals. However, when pain persists longer than 3 months, maladaptive learning processes 
in the brain that misinterpret these teaching signals may contribute to pain chronification. Analogous to a 
fire alarm that continues to ring even after the fire has been extinguished, the brain is thought to continue 
to predict that it is in a context of harm and engages in avoidance behavior even after the tissue has 
healed. Importantly these harm beliefs are thought to translate to other non-harm contexts, leading to an 
over-generalization of harm avoidance. 
This harm-avoidance model of pain ties in nicely with recent neuroimaging findings showing alterations in 
the fronto-striatal circuitry involved in the representation of context values and reinforcement learning in 
chronic pain Patients. However, the mechanism by which these interacting brain systems contribute to 
chronic pain or amelioration thereof is unknown. 
Here we expand a learning task and computational models in combination with EEG to differentiate 
between (PFC-driven) estimates of context values and (BG-driven) learning in chronic pain patients. 
Specifically, we test the hypothesis that avoidance learning in chronic pain patients may be driven by an 
overemphasis on learning from negative outcomes and an overgeneralization from one context of harm 
avoidance to other contexts. We hypothesize that this can be additionally observed in increased EEG 
frontal theta-band power in chronic patients during harm avoidance learning. Theta-band power has been 
previously shown to covary with the representation of context values and learning and thus provides an 
important read-out of biased learning throughout the task. This work will provide the basis for a future 
longitudinal research study where this task will be used to predict the risk of developing chronic pain after 
an acute pain state.

## Key facts

- **NIH application ID:** 10763110
- **Project number:** 5P20GM103645-10
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Frederike Hermi Petzschner
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $393,149
- **Award type:** 5
- **Project period:** 2022-08-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10763110

## Citation

> US National Institutes of Health, RePORTER application 10763110, Testing a theory of avoidance learning & overgeneralization in chronic pain (5P20GM103645-10). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10763110. Licensed CC0.

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