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Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state functional connectivity (rsFC) of the default mode, salience, central executive, and sensorimotor networks in chronic pain patients, but their role as predictors of treatment responsiveness has not yet been explored. In this study, we used machine learning approaches to test if pre-treatment rsFC can predict responses to both real and sham acupuncture treatments in cLBP patients. Fifty cLBP patients participated in 4 weeks of either real (N = 24, age = 39.0 ± 12.6, 16 females) or sham acupuncture (N = 26, age = 40.0 ± 13.7, 15 females) treatment in a single-blinded trial, and a resting-state fMRI scan prior to treatment was used in data analysis. Both real and sham acupuncture can produce significant pain reduction, with those receiving real treatment experiencing greater pain relief than those receiving sham treatment. We found that pre-treatment rsFC could predict symptom changes with up to 34% and 29% variances for real and sham treatment, respectively, and the rsFC characteristics that were significantly predictive for real and sham treatment differed. These results suggest a potential way to predict treatment responses and may facilitate the development of treatment plans that optimize time, cost, and available resources., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Expectation can shape the perception of pain within a fraction of time, but little is known about how perceived expectation unfolds over time and modulates pain perception. Here, we combine magnetoencephalography (MEG) and machine learning approaches to track the neural dynamics of expectations of pain in healthy participants with both sexes. We found that the expectation of pain, as conditioned by facial cues, can be decoded from MEG as early as 150 ms and up to 1100 ms after cue onset, but decoding expectation elicited by unconsciously perceived cues requires more time and decays faster compared to consciously perceived ones. Also, results from temporal generalization suggest that neural dynamics of decoding cue-based expectation were predominately sustained during cue presentation but transient after cue presentation. Finally, although decoding expectation elicited by consciously perceived cues were based on a series of time-restricted brain regions during cue presentation, decoding relied on the medial prefrontal cortex and anterior cingulate cortex after cue presentation for both consciously and unconsciously perceived cues. These findings reveal the conscious and unconscious processing of expectation during pain anticipation and may shed light on enhancing clinical care by demonstrating the impact of expectation cues. [ABSTRACT FROM AUTHOR]