To examine whether prescription opioid use in patients with chronic pain impacts brain activity patterns during emotion regulation.

As prescription opioids are increasingly used for treating chronic pain, there is a need to better characterize how opioid analgesics impact the brain function. Emerging research suggests that prescription opioids may actually increase pain (opioid-induced hyperalgesia) and cause deficits in emotion regulation. Here we report a pilot fMRI study of prescription opioid effects on brain activity associated with emotion regulation of painful stimuli, analyzed using Multivariate Pattern Analysis (MVPA), a machine-learning, pattern classification technique.

BOLD fMRI data were collected from ten chronic low back pain patients on opioid therapy (5 women, 5 men; age, 49 ± 13 years) and ten matched opioid-nai¨ve chronic low back pain patients (5 women, 5 men; age, 44 ± 13 years) during emotion regulation of evoked thermal pain. MVPA procedure was ran as implemented in the connectome-MVPA CONN toolbox. To get statistically significant effects with modest number of subjects, non-parametric statistics were performed with 1000 simulations at the voxel level of p < 0.001, uncorrected (two-tailed), and at the cluster level of p < 0.05, false discovery rate corrected.

Pilot findings suggest that certain features of BOLD fMRI response (i.e., fine-grained spatial patterns of brain activity distributed over multiple voxels) during emotion regulation is different between chronic pain patients on opioids and those not on opioids. These differential features can potentially be used as inputs to a classifier.