The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Pain sensitivity is inversely related to regional grey matter density in the brain
Open accessAbstract
Pain is a highly personal experience that varies substantially among individuals. In search of an anatomical correlate of pain sensitivity, we used voxel-based morphometry to investigate the relationship between grey matter density across the whole brain and interindividual differences in pain sensitivity in 116 healthy volunteers (62 women, 54 men). Structural magnetic resonance imaging (MRI) and psychophysical data from 10 previous functional MRI studies were used. Age, sex, unpleasantness ratings, scanner sequence, and sensory testing location were added to the model as covariates. Regression analysis of grey matter density across the whole brain and thermal pain intensity ratings at 49°C revealed a significant inverse relationship between pain sensitivity and grey matter density in bilateral regions of the posterior cingulate cortex, precuneus, intraparietal sulcus, and inferior parietal lobule. Unilateral regions of the left primary somatosensory cortex also exhibited this inverse relationship. No regions showed a positive relationship to pain sensitivity. These structural variations occurred in areas associated with the default mode network, attentional direction and shifting, as well as somatosensory processing. These findings underscore the potential importance of processes related to default mode thought and attention in shaping individual differences in pain sensitivity and indicate that pain sensitivity can potentially be predicted on the basis of brain structure.
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“exhibit significantly lower activation in the precuneus/dPCC, central nodes of self–referential [12; 61] and nociceptive processing [17; 64]”
From Neural mechanisms supporting the relationship between dispositional mindfulness and pain (2018) · cites this paper as [17]
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Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 7,018
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
The validation of visual analogue scales as ratio scale measures for chronic and experimental pain
Price, D. D., McGrath, P. A., Rafii, A., & Buckingham, B. (1983) · Pain · doi:10.1016/0304-3959(83)90126-4 · Cited by 3,921
Research works printed but not linked: 2
- Hadsel, 2006, FMRI studies of pain: not all baseline periods are equal., Soc Neurosci Abstr, 32, 14
- Martucci, 2006, A new spin on chronic pain imaging: quantitative perfusion imaging using arterial spin labeling MRI., Soc Neurosci Abstr, 32, 22
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Assessment of Chronic Pain: Domains, Methods, and Mechanisms
Fillingim, R. B., Loeser, J. D., Baron, R., & Edwards, R. R. (2016) · Journal of Pain · doi:10.1016/j.jpain.2015.08.010 · Cited by 422
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McFarlin, B. K., Venable, A. S., Henning, A. L., Sampson, J. N. B., Pennel, K. A. F., Vingren, J. L., & Hill, D. W. (2016) · BBA Clinical · doi:10.1016/j.bbacli.2016.02.003 · Cited by 165
Metadata
- Authors
- Emerson, N. M., Zeidan, F., Lobanov, O. V., Hadsel, M. S., Martucci, K. T., Quevedo, A. S., Starr, C. J., Nahman-Averbuch, H., Weissman-Fogel, I., Granovsky, Y., Yarnitsky, D., & Coghill, R. C.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- Wake Forest University Health Sciences (US)
- Corresponding author
- Coghill, Robert C.
- ORCID
- Venue
- Pain
- Published
- 2014-03
- Volume
- 155
- Issue
- 3
- Pages
- 566-573
- ISSN
- 0304-3959 (ISSN-L)
- PMC
- PMC3944887
- OpenAlex
- W2039104311
- Cited by
- 121
- References
- 66
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 5 · 2023: 13 · 2022: 13 · 2021: 11 · 2020: 14 · 2019: 13 · 2018: 7 · 2017: 4 · 2016: 10 · 2015: 8 · 2014: 10
- FWCI
- 6.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Pain (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Israel Science Foundation
- National Institutes of Health
- National Institute on Drug Abuse (R01DA020168, DA020168)
- National Institute of Neurological Disorders and Stroke (NS039426, R01NS039426)
- Topics
- Health Sciences › Medicine › Physiology (medical) › Pain Mechanisms and Treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Pain Management and Placebo Effect
- Health Sciences › Medicine › Anesthesiology and Pain Medicine › Pain Management and Treatment
- Keywords
- pain sensitivity, individual differences, gray matter density, thermal pain, posterior cingulate cortex, precuneus, intraparietal sulcus, inferior parietal lobule, primary somatosensory cortex, default mode network, attention, somatosensory processing, brain structure
- MeSH terms
- Adult, Aged, Cerebral Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Pain, Retrospective Studies, Databases, Factual, Pain Threshold, Young Adult
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