The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Brain Morphological Signatures for Chronic Pain
Open accessAbstract
Chronic pain can be understood not only as an altered functional state, but also as a consequence of neuronal plasticity. Here we use in vivo structural MRI to compare global, local, and architectural changes in gray matter properties in patients suffering from chronic back pain (CBP), complex regional pain syndrome (CRPS) and knee osteoarthritis (OA), relative to healthy controls. We find that different chronic pain types exhibit unique anatomical 'brain signatures'. Only the CBP group showed altered whole-brain gray matter volume, while regional gray matter density was distinct for each group. Voxel-wise comparison of gray matter density showed that the impact on the extent of chronicity of pain was localized to a common set of regions across all conditions. When gray matter density was examined for large regions approximating Brodmann areas, it exhibited unique large-scale distributed networks for each group. We derived a barcode, summarized by a single index of within-subject co-variation of gray matter density, which enabled classification of individual brains to their conditions with high accuracy. This index also enabled calculating time constants and asymptotic amplitudes for an exponential increase in brain re-organization with pain chronicity, and showed that brain reorganization with pain chronicity was 6 times slower and twice as large in CBP in comparison to CRPS. The results show an exuberance of brain anatomical reorganization peculiar to each condition and as such reflecting the unique maladaptive physiology of different types of chronic pain.
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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
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. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 6,982
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
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
Human brain mechanisms of pain perception and regulation in health and disease
Apkarian, A. V., Bushnell, M. C., Treede, R., & Zubieta, J. (2005) · European Journal of Pain · doi:10.1016/j.ejpain.2004.11.001 · Cited by 3,126
Self-citationMolecular mechanisms of nociception
Julius, D., & Basbaum, A. I. (2001) · Nature · doi:10.1038/35093019 · Cited by 2,685 · cited 2×
“Thus, we can conclude that living with distinct chronic pain conditions confers a brain anatomical network reorganization, reflecting at least in part a physiological reorganization, that must be the result of the sum total of experiential changes (coping and suffering that result in novel associations and deficits in…”
BackgroundNeurodegenerative Diseases Target Large-Scale Human Brain Networks
Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.024 · Cited by 2,350
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Alexander-Bloch, A., Giedd, J. N., & Bullmore, E. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3465 · Cited by 1,064
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Baliki, M. N., Petre, B., Torbey, S., Herrmann, K. M., Huang, L., Schnitzer, T. J., Fields, H. L., & Apkarian, A. V. (2012) · Nature Neuroscience · doi:10.1038/nn.3153 · Cited by 1,050
Self-citationDeconstructing the Neuropathic Pain Phenotype to Reveal Neural Mechanisms
von Hehn, C. A., Baron, R., & Woolf, C. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.02.008 · Cited by 800
Hashmi, J. A., Baliki, M. N., Huang, L., Baria, A. T., Torbey, S., Hermann, K. M., Schnitzer, T. J., & Apkarian, A. V. (2013) · Brain · doi:10.1093/brain/awt211 · Cited by 762
Self-citationNociception, pain, negative moods, and behavior selection
Baliki, M. N., & Apkarian, A. V. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.005 · Cited by 731
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Metadata
- Authors
- Baliki, M. N., Schnitzer, T. J., Bauer, W. R., & Apkarian, A. V.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-10-13
- Volume
- 6
- Issue
- 10
- Pages
- e26010
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2168733416
- Cited by
- 371
- References
- 57
- FWCI
- 13.68
- Type
- journal article
- Language
- en
- Open access
- gold
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