bmrk3_6levels_pain_dataset.mat

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Courier; color: #b245f3} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Courier; min-height: 12.0px} p.p3 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Courier; color: #b245f3; min-height: 12.0px} p.p4 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Courier} p.p5 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Courier; min-height: 14.0px} span.s1 {color: #000000} span.s2 {color: #b245f3} This dataset includes 33 participants, with brain responses to six levels of heat (non-painful and painful). The file format is an fmri_data object from the CANlab Core Tools repository for neuroimaging data analysis. See https://canlab.github.io/ Aspects of this data appear in these papers: Wager, T.D., Atlas, L.T., Lindquist, M.A., Roy, M., Choong-Wan, W., Kross, E. (2013). An fMRI-Based Neurologic Signature of Physical Pain. The New England Journal of Medicine. 368:1388-1397 (Study 2) Woo, C. -W., Roy, M., Buhle, J. T. &amp; Wager, T. D. (2015). Distinct brain systems mediate the effects of nociceptive input and self-regulation on pain. PLOS Biology. 13(1): e1002036. doi:10.1371/journal.pbio.1002036 Lindquist, Martin A., Anjali Krishnan, Marina López-Solà, Marieke Jepma, Choong-Wan Woo, Leonie Koban, Mathieu Roy, et al. 2015. ?Group-Regularized Individual Prediction: Theory and Application to Pain.? NeuroImage. http://www.sciencedirect.com/science/article/pii/S1053811915009982. <br>