Evidence map›Paper›PMID 42340106›Full record

SynthesisEuropean journal of pain (London, England)2026

The Human Dorsolateral Prefrontal Cortex in Pain and Pain Modulation: A Review and Activation-Likelihood Estimation Approach.

Lewis S Crawford, Damien C Boorman, James W M Kang, Allan Peng, Kevin A Keay, Luke A Henderson

Abstract readReviewMeta-Analysis
In one paragraph

Synthesis in European journal of pain (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lewis S CrawfordSchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.
Damien C BoormanSchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.
James W M KangSchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.
Allan PengSchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.
Kevin A KeaySchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.
Luke A HendersonSchool of Medical Sciences (Neuroscience), the Brain and Mind Centre, University of Sydney, Camperdown, Australia.ORCID https://orcid.org/0000-0002-1026-0151

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe dorsolateral prefrontal cortex (dlPFC) has become a cornerstone of pain neuroscience, believed critically involved in processing acute and chronic pain, as well as in pain modulation. The dlPFC is thought to balance sensory perception with the cognitive appraisal of noxious stimuli. In humans however, the dlPFC spans several cortical nodes, and little attention has been given to precisely which subareas are tethered to these delineable processes. The primary goal of this review and co-ordinate based meta-analysis was to precisely map dlPFC areas engaged under varied effects on overall pain perception.

methodsHere, we combined a stringent meta-analytic approach of neuroimaging studies reporting dlPFC activation as a core finding (i.e., within title, abstract, or keywords of each manuscript), with activation likelihood estimation to determine dlPFC engagement across experimental acute pain (combined n = 814), chronic pain (combined n = 2467), and the pain modulatory phenomenon of placebo analgesia (combined n = 791), conditioned pain modulation (combined n = 184), and offset analgesia (combined n = 47). Through activation likelihood estimate and foci analysis, we produced schema of the similar and disparate locations of dlPFC activity within and between pain perceptual and modulatory effects.

resultsDuring both acute and chronic pain and in placebo analgesia, we identified remarkably similar activation patterns predominantly within Brodmann areas 8, 9, and 46-with no clear laterality effect and the left and right cortical hemispheres engaged regardless of the site of experimentally applied or conditionally-present pain. Offset analgesia and conditioned pain modulation appeared to preferentially engage Brodmann areas 8 and 45, and 9 and 46, respectively.

conclusionsDespite the dlPFC large cortical surface area, these findings suggest that both the percept and inhibition of pain by placebo engage a similar focussed area of this region. Better understanding of exactly which cortical components of the extensive cortical pain system are involved in pain perception and modulation is critical for refining novel treatments such as non-invasive brain stimulation which seek to target and modulate specific sites of cortical processing to alleviate pain. SIGNIFICANCE STATEMENT: This meta-analysis precisely maps the dorsolateral prefrontal cortex (dlPFC) subregions engaged across acute pain, chronic pain and major endogenous pain-modulation paradigms. By integrating data from more than 4000 participants, it provides the most anatomically resolved evidence to date that dlPFC engagement is a shared feature of pain perception and modulation. These findings refine the cortical targets most relevant for therapeutic neuromodulation and strengthen the rationale for dlPFC-focused interventions in pain treatment.

Indexed as

Acute PainChronic PainDorsolateral Prefrontal CortexPainPain PerceptionPrefrontal CortexBrain MappingHumansLikelihood Functionsdorsolateral prefrontal cortexendogenous analgesiamagnetic resonance imagingpainplacebo analgesia

Identifiers

PMID42340106
PMCPMC13292397

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.