@article {834, title = {Separate neural representations for physical pain and social rejection.}, journal = {Nat Commun}, volume = {5}, year = {2014}, month = {2014}, pages = {5380}, abstract = {

Current theories suggest that physical pain and social rejection share common neural mechanisms, largely by virtue of overlapping functional magnetic resonance imaging (fMRI) activity. Here we challenge this notion by identifying distinct multivariate fMRI patterns unique to pain and rejection. Sixty participants experience painful heat and warmth and view photos of ex-partners and friends on separate trials. FMRI pattern classifiers discriminate pain and rejection from their respective control conditions in out-of-sample individuals with 92\% and 80\% accuracy. The rejection classifier performs at chance on pain, and vice versa. Pain- and rejection-related representations are uncorrelated within regions thought to encode pain affect (for example, dorsal anterior cingulate) and show distinct functional connectivity with other regions in a separate resting-state data set (N=91). These findings demonstrate that separate representations underlie pain and rejection despite common fMRI activity at the gross anatomical level. Rather than co-opting pain circuitry, rejection involves distinct affective representations in humans.

}, issn = {2041-1723}, doi = {10.1038/ncomms6380}, author = {Woo, Choong-Wan and Koban, Leonie and Kross, Ethan and Lindquist, Martin A and Banich, Marie T and Ruzic, Luka and Andrews-Hanna, Jessica R and Wager, Tor D} } @article {839, title = {An fMRI-based neurologic signature of physical pain.}, journal = {N Engl J Med}, volume = {368}, year = {2013}, month = {2013 Apr 11}, pages = {1388-97}, abstract = {

BACKGROUND: Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified.

METHODS: In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions--a neurologic signature--that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil.

RESULTS: In study 1, the neurologic signature showed sensitivity and specificity of 94\% or more (95\% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93\% sensitivity and specificity (95\% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85\% sensitivity (95\% CI, 76 to 94) and 73\% specificity (95\% CI, 61 to 84) and with 95\% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered.

CONCLUSIONS: It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.).

}, keywords = {Adult, Analgesics, Opioid, Artificial Intelligence, Brain, brain mapping, Female, Hot Temperature, Humans, Magnetic Resonance Imaging, Male, Pain, Pain Measurement, Piperidines, ROC Curve, Sensitivity and Specificity, Young Adult}, issn = {1533-4406}, doi = {10.1056/NEJMoa1204471}, author = {Wager, Tor D and Atlas, Lauren Y and Lindquist, Martin A and Roy, Mathieu and Woo, Choong-Wan and Kross, Ethan} }